ipl-men-cricket-2008-2023-data-analysis.ipynb

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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/input/ipl-mens-cricket-matches-data-2008-2023/match_data.csv\n",
      "/kaggle/input/ipl-mens-cricket-matches-data-2008-2023/match_info_data.csv\n"
     ]
    }
   ],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fe117ea",
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    "tags": []
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   "source": [
    "Let's see the data."
   ]
  },
  {
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   "id": "cc29b8f0",
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       "      <th>season</th>\n",
       "      <th>start_date</th>\n",
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       "      <th>other_player_dismissed</th>\n",
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       "      <td>2007/08</td>\n",
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       "      <td>M Chinnaswamy Stadium</td>\n",
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       "      <td>14.6</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
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       "      <td>2007/08</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
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       "      <td>15.1</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
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       "      <td>335982</td>\n",
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       "    <tr>\n",
       "      <th>243816</th>\n",
       "      <td>335982</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>2008-04-18</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>2</td>\n",
       "      <td>15.2</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
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      ],
      "text/plain": [
       "        match_id   season  start_date                             venue  \\\n",
       "0        1370353     2023  2023-05-29  Narendra Modi Stadium, Ahmedabad   \n",
       "1        1370353     2023  2023-05-29  Narendra Modi Stadium, Ahmedabad   \n",
       "2        1370353     2023  2023-05-29  Narendra Modi Stadium, Ahmedabad   \n",
       "3        1370353     2023  2023-05-29  Narendra Modi Stadium, Ahmedabad   \n",
       "4        1370353     2023  2023-05-29  Narendra Modi Stadium, Ahmedabad   \n",
       "...          ...      ...         ...                               ...   \n",
       "243812    335982  2007/08  2008-04-18             M Chinnaswamy Stadium   \n",
       "243813    335982  2007/08  2008-04-18             M Chinnaswamy Stadium   \n",
       "243814    335982  2007/08  2008-04-18             M Chinnaswamy Stadium   \n",
       "243815    335982  2007/08  2008-04-18             M Chinnaswamy Stadium   \n",
       "243816    335982  2007/08  2008-04-18             M Chinnaswamy Stadium   \n",
       "\n",
       "        innings  ball                 batting_team           bowling_team  \\\n",
       "0             1   0.1               Gujarat Titans    Chennai Super Kings   \n",
       "1             1   0.2               Gujarat Titans    Chennai Super Kings   \n",
       "2             1   0.3               Gujarat Titans    Chennai Super Kings   \n",
       "3             1   0.4               Gujarat Titans    Chennai Super Kings   \n",
       "4             1   0.5               Gujarat Titans    Chennai Super Kings   \n",
       "...         ...   ...                          ...                    ...   \n",
       "243812        2  14.5  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "243813        2  14.6  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "243814        2  14.7  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "243815        2  15.1  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "243816        2  15.2  Royal Challengers Bangalore  Kolkata Knight Riders   \n",
       "\n",
       "             striker   non_striker  ... wides  noballs  byes  legbyes  \\\n",
       "0            WP Saha  Shubman Gill  ...   NaN      NaN   NaN      NaN   \n",
       "1            WP Saha  Shubman Gill  ...   NaN      NaN   NaN      NaN   \n",
       "2            WP Saha  Shubman Gill  ...   NaN      NaN   NaN      NaN   \n",
       "3       Shubman Gill       WP Saha  ...   NaN      NaN   NaN      NaN   \n",
       "4            WP Saha  Shubman Gill  ...   NaN      NaN   NaN      NaN   \n",
       "...              ...           ...  ...   ...      ...   ...      ...   \n",
       "243812       P Kumar      SB Joshi  ...   NaN      NaN   NaN      1.0   \n",
       "243813      SB Joshi       P Kumar  ...   NaN      NaN   NaN      NaN   \n",
       "243814       P Kumar      SB Joshi  ...   NaN      NaN   NaN      NaN   \n",
       "243815      SB Joshi       P Kumar  ...   1.0      NaN   NaN      NaN   \n",
       "243816      SB Joshi       P Kumar  ...   NaN      NaN   NaN      NaN   \n",
       "\n",
       "        penalty  wicket_type  player_dismissed  other_wicket_type  \\\n",
       "0           NaN          NaN               NaN                NaN   \n",
       "1           NaN          NaN               NaN                NaN   \n",
       "2           NaN          NaN               NaN                NaN   \n",
       "3           NaN          NaN               NaN                NaN   \n",
       "4           NaN          NaN               NaN                NaN   \n",
       "...         ...          ...               ...                ...   \n",
       "243812      NaN          NaN               NaN                NaN   \n",
       "243813      NaN          NaN               NaN                NaN   \n",
       "243814      NaN          NaN               NaN                NaN   \n",
       "243815      NaN          NaN               NaN                NaN   \n",
       "243816      NaN       caught          SB Joshi                NaN   \n",
       "\n",
       "       other_player_dismissed cricsheet_id  \n",
       "0                         NaN      1370353  \n",
       "1                         NaN      1370353  \n",
       "2                         NaN      1370353  \n",
       "3                         NaN      1370353  \n",
       "4                         NaN      1370353  \n",
       "...                       ...          ...  \n",
       "243812                    NaN       335982  \n",
       "243813                    NaN       335982  \n",
       "243814                    NaN       335982  \n",
       "243815                    NaN       335982  \n",
       "243816                    NaN       335982  \n",
       "\n",
       "[243817 rows x 23 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
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   ],
   "source": [
    "match_data_df = pd.read_csv(\"/kaggle/input/ipl-mens-cricket-matches-data-2008-2023/match_data.csv\",low_memory=False)\n",
    "match_data_df"
   ]
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
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       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1370353</td>\n",
       "      <td>2023</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2023/05/29</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>D/L</td>\n",
       "      <td>1</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>DP Conway</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1370352</td>\n",
       "      <td>2023</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2023/05/26</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>Shubman Gill</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>J Madanagopal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1370351</td>\n",
       "      <td>2023</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2023/05/24</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "      <td>Akash Madhwal</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>VK Sharma</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1370350</td>\n",
       "      <td>2023</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2023/05/23</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>RD Gaikwad</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1359543</td>\n",
       "      <td>2023</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2023/05/21</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>C Green</td>\n",
       "      <td>Wankhede Stadium, Mumbai</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>R Pandit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1019</th>\n",
       "      <td>335986</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2008/04/20</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>DJ Hussey</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>BF Bowden</td>\n",
       "      <td>K Hariharan</td>\n",
       "      <td>Asad Rauf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1020</th>\n",
       "      <td>335985</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2008/04/20</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>MV Boucher</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>SJ Davis</td>\n",
       "      <td>DJ Harper</td>\n",
       "      <td>AV Jayaprakash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1021</th>\n",
       "      <td>335984</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2008/04/19</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>MF Maharoof</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>Aleem Dar</td>\n",
       "      <td>GA Pratapkumar</td>\n",
       "      <td>IL Howell</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1022</th>\n",
       "      <td>335983</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>2008/04/19</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>MEK Hussey</td>\n",
       "      <td>Punjab Cricket Association Stadium, Mohali</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>SL Shastri</td>\n",
       "      <td>RB Tiffin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1023</th>\n",
       "      <td>335982</td>\n",
       "      <td>2007/08</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2008/04/18</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>140</td>\n",
       "      <td>0</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>Asad Rauf</td>\n",
       "      <td>RE Koertzen</td>\n",
       "      <td>AM Saheba</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1024 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           id   season        city        date                        team1  \\\n",
       "0     1370353     2023   Ahmedabad  2023/05/29               Gujarat Titans   \n",
       "1     1370352     2023   Ahmedabad  2023/05/26               Gujarat Titans   \n",
       "2     1370351     2023     Chennai  2023/05/24               Mumbai Indians   \n",
       "3     1370350     2023     Chennai  2023/05/23          Chennai Super Kings   \n",
       "4     1359543     2023      Mumbai  2023/05/21          Sunrisers Hyderabad   \n",
       "...       ...      ...         ...         ...                          ...   \n",
       "1019   335986  2007/08     Kolkata  2008/04/20        Kolkata Knight Riders   \n",
       "1020   335985  2007/08      Mumbai  2008/04/20               Mumbai Indians   \n",
       "1021   335984  2007/08       Delhi  2008/04/19             Delhi Daredevils   \n",
       "1022   335983  2007/08  Chandigarh  2008/04/19              Kings XI Punjab   \n",
       "1023   335982  2007/08   Bangalore  2008/04/18  Royal Challengers Bangalore   \n",
       "\n",
       "                            team2                  toss_winner toss_decision  \\\n",
       "0             Chennai Super Kings          Chennai Super Kings         field   \n",
       "1                  Mumbai Indians               Mumbai Indians         field   \n",
       "2            Lucknow Super Giants               Mumbai Indians           bat   \n",
       "3                  Gujarat Titans               Gujarat Titans         field   \n",
       "4                  Mumbai Indians               Mumbai Indians         field   \n",
       "...                           ...                          ...           ...   \n",
       "1019              Deccan Chargers              Deccan Chargers           bat   \n",
       "1020  Royal Challengers Bangalore               Mumbai Indians           bat   \n",
       "1021             Rajasthan Royals             Rajasthan Royals           bat   \n",
       "1022          Chennai Super Kings          Chennai Super Kings           bat   \n",
       "1023        Kolkata Knight Riders  Royal Challengers Bangalore         field   \n",
       "\n",
       "      result  dl_applied                       winner  win_by_runs  \\\n",
       "0        D/L           1          Chennai Super Kings            0   \n",
       "1     normal           0               Gujarat Titans           62   \n",
       "2     normal           0               Mumbai Indians           81   \n",
       "3     normal           0          Chennai Super Kings           15   \n",
       "4     normal           0               Mumbai Indians            0   \n",
       "...      ...         ...                          ...          ...   \n",
       "1019  normal           0        Kolkata Knight Riders            0   \n",
       "1020  normal           0  Royal Challengers Bangalore            0   \n",
       "1021  normal           0             Delhi Daredevils            0   \n",
       "1022  normal           0          Chennai Super Kings           33   \n",
       "1023  normal           0        Kolkata Knight Riders          140   \n",
       "\n",
       "      win_by_wickets player_of_match  \\\n",
       "0                  5       DP Conway   \n",
       "1                  0    Shubman Gill   \n",
       "2                  0   Akash Madhwal   \n",
       "3                  0      RD Gaikwad   \n",
       "4                  8         C Green   \n",
       "...              ...             ...   \n",
       "1019               5       DJ Hussey   \n",
       "1020               5      MV Boucher   \n",
       "1021               9     MF Maharoof   \n",
       "1022               0      MEK Hussey   \n",
       "1023               0     BB McCullum   \n",
       "\n",
       "                                           venue                umpire1  \\\n",
       "0               Narendra Modi Stadium, Ahmedabad            Nitin Menon   \n",
       "1               Narendra Modi Stadium, Ahmedabad            Nitin Menon   \n",
       "2       MA Chidambaram Stadium, Chepauk, Chennai           BNJ Oxenford   \n",
       "3       MA Chidambaram Stadium, Chepauk, Chennai           AK Chaudhary   \n",
       "4                       Wankhede Stadium, Mumbai  KN Ananthapadmanabhan   \n",
       "...                                          ...                    ...   \n",
       "1019                                Eden Gardens              BF Bowden   \n",
       "1020                            Wankhede Stadium               SJ Davis   \n",
       "1021                            Feroz Shah Kotla              Aleem Dar   \n",
       "1022  Punjab Cricket Association Stadium, Mohali              MR Benson   \n",
       "1023                       M Chinnaswamy Stadium              Asad Rauf   \n",
       "\n",
       "             umpire2                umpire3  \n",
       "0          RJ Tucker  KN Ananthapadmanabhan  \n",
       "1          RJ Tucker          J Madanagopal  \n",
       "2          VK Sharma            CB Gaffaney  \n",
       "3        CB Gaffaney           BNJ Oxenford  \n",
       "4          RJ Tucker               R Pandit  \n",
       "...              ...                    ...  \n",
       "1019     K Hariharan              Asad Rauf  \n",
       "1020       DJ Harper         AV Jayaprakash  \n",
       "1021  GA Pratapkumar              IL Howell  \n",
       "1022      SL Shastri              RB Tiffin  \n",
       "1023     RE Koertzen              AM Saheba  \n",
       "\n",
       "[1024 rows x 18 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_info_data = pd.read_csv(\"/kaggle/input/ipl-mens-cricket-matches-data-2008-2023/match_info_data.csv\")\n",
    "match_info_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "903b38ce",
   "metadata": {
    "papermill": {
     "duration": 0.022611,
     "end_time": "2024-04-05T18:34:52.324285",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.301674",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Here, we have two dataframes.\n",
    "\n",
    "First, we have the ball by ball data for every IPL match played between 2008-2023.\n",
    "\n",
    "Second, we have all the information about the IPL matches."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38ad4f2b",
   "metadata": {
    "papermill": {
     "duration": 0.022186,
     "end_time": "2024-04-05T18:34:52.368965",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.346779",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We will do the analysis on the \"match_info_data\" dataframe which contains the information about the IPL matches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cc76e282",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:52.416695Z",
     "iopub.status.busy": "2024-04-05T18:34:52.416081Z",
     "iopub.status.idle": "2024-04-05T18:34:52.436134Z",
     "shell.execute_reply": "2024-04-05T18:34:52.434786Z"
    },
    "papermill": {
     "duration": 0.047557,
     "end_time": "2024-04-05T18:34:52.439566",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.392009",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1370353</td>\n",
       "      <td>2023</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2023/05/29</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>D/L</td>\n",
       "      <td>1</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>DP Conway</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1370352</td>\n",
       "      <td>2023</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2023/05/26</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>Shubman Gill</td>\n",
       "      <td>Narendra Modi Stadium, Ahmedabad</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>J Madanagopal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1370351</td>\n",
       "      <td>2023</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2023/05/24</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "      <td>Akash Madhwal</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "      <td>VK Sharma</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1370350</td>\n",
       "      <td>2023</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2023/05/23</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>RD Gaikwad</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>BNJ Oxenford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1359543</td>\n",
       "      <td>2023</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2023/05/21</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>C Green</td>\n",
       "      <td>Wankhede Stadium, Mumbai</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>R Pandit</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id season       city        date                team1  \\\n",
       "0  1370353   2023  Ahmedabad  2023/05/29       Gujarat Titans   \n",
       "1  1370352   2023  Ahmedabad  2023/05/26       Gujarat Titans   \n",
       "2  1370351   2023    Chennai  2023/05/24       Mumbai Indians   \n",
       "3  1370350   2023    Chennai  2023/05/23  Chennai Super Kings   \n",
       "4  1359543   2023     Mumbai  2023/05/21  Sunrisers Hyderabad   \n",
       "\n",
       "                  team2          toss_winner toss_decision  result  \\\n",
       "0   Chennai Super Kings  Chennai Super Kings         field     D/L   \n",
       "1        Mumbai Indians       Mumbai Indians         field  normal   \n",
       "2  Lucknow Super Giants       Mumbai Indians           bat  normal   \n",
       "3        Gujarat Titans       Gujarat Titans         field  normal   \n",
       "4        Mumbai Indians       Mumbai Indians         field  normal   \n",
       "\n",
       "   dl_applied               winner  win_by_runs  win_by_wickets  \\\n",
       "0           1  Chennai Super Kings            0               5   \n",
       "1           0       Gujarat Titans           62               0   \n",
       "2           0       Mumbai Indians           81               0   \n",
       "3           0  Chennai Super Kings           15               0   \n",
       "4           0       Mumbai Indians            0               8   \n",
       "\n",
       "  player_of_match                                     venue  \\\n",
       "0       DP Conway          Narendra Modi Stadium, Ahmedabad   \n",
       "1    Shubman Gill          Narendra Modi Stadium, Ahmedabad   \n",
       "2   Akash Madhwal  MA Chidambaram Stadium, Chepauk, Chennai   \n",
       "3      RD Gaikwad  MA Chidambaram Stadium, Chepauk, Chennai   \n",
       "4         C Green                  Wankhede Stadium, Mumbai   \n",
       "\n",
       "                 umpire1      umpire2                umpire3  \n",
       "0            Nitin Menon    RJ Tucker  KN Ananthapadmanabhan  \n",
       "1            Nitin Menon    RJ Tucker          J Madanagopal  \n",
       "2           BNJ Oxenford    VK Sharma            CB Gaffaney  \n",
       "3           AK Chaudhary  CB Gaffaney           BNJ Oxenford  \n",
       "4  KN Ananthapadmanabhan    RJ Tucker               R Pandit  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_info_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b010ab0",
   "metadata": {
    "papermill": {
     "duration": 0.022632,
     "end_time": "2024-04-05T18:34:52.485551",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.462919",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Let's see the total number of matches played between 2008-2023."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e1e9f87f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:52.533295Z",
     "iopub.status.busy": "2024-04-05T18:34:52.532885Z",
     "iopub.status.idle": "2024-04-05T18:34:52.540100Z",
     "shell.execute_reply": "2024-04-05T18:34:52.539028Z"
    },
    "papermill": {
     "duration": 0.034076,
     "end_time": "2024-04-05T18:34:52.542640",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.508564",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1024"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(match_info_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a44a0df6",
   "metadata": {
    "papermill": {
     "duration": 0.023904,
     "end_time": "2024-04-05T18:34:52.590227",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.566323",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "There were 1024 IPL matches played between 2008 to 2023."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d290ccf",
   "metadata": {
    "papermill": {
     "duration": 0.022848,
     "end_time": "2024-04-05T18:34:52.637385",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.614537",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Let's see the seaseon wise matches played."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eb303dd2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:52.685309Z",
     "iopub.status.busy": "2024-04-05T18:34:52.684939Z",
     "iopub.status.idle": "2024-04-05T18:34:52.690248Z",
     "shell.execute_reply": "2024-04-05T18:34:52.689091Z"
    },
    "papermill": {
     "duration": 0.032618,
     "end_time": "2024-04-05T18:34:52.693119",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.660501",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Columns are : ['id', 'season', 'city', 'date', 'team1', 'team2', 'toss_winner', 'toss_decision', 'result', 'dl_applied', 'winner', 'win_by_runs', 'win_by_wickets', 'player_of_match', 'venue', 'umpire1', 'umpire2', 'umpire3']\n"
     ]
    }
   ],
   "source": [
    "print(\"Columns are :\",list(match_info_data.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d8e8820b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:52.741235Z",
     "iopub.status.busy": "2024-04-05T18:34:52.740836Z",
     "iopub.status.idle": "2024-04-05T18:34:52.761349Z",
     "shell.execute_reply": "2024-04-05T18:34:52.760475Z"
    },
    "papermill": {
     "duration": 0.047272,
     "end_time": "2024-04-05T18:34:52.763441",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.716169",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2007/08</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2009</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2009/10</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2015</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2016</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2017</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020/21</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     season  count\n",
       "14  2007/08     58\n",
       "15     2009     57\n",
       "11  2009/10     60\n",
       "4      2011     73\n",
       "3      2012     74\n",
       "0      2013     76\n",
       "10     2014     60\n",
       "13     2015     59\n",
       "9      2016     60\n",
       "12     2017     59\n",
       "8      2018     60\n",
       "7      2019     60\n",
       "6   2020/21     60\n",
       "5      2021     60\n",
       "2      2022     74\n",
       "1      2023     74"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Assuming match_info_data is your DataFrame\n",
    "sorted_season_counts = match_info_data[\"season\"].value_counts().reset_index().sort_values(by='season')\n",
    "\n",
    "sorted_season_counts\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03b61419",
   "metadata": {
    "papermill": {
     "duration": 0.023873,
     "end_time": "2024-04-05T18:34:52.810733",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.786860",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## (1) DATASET 1 ANALYSIS : IPL ALL MATCHES OVERVIEW"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "998aa668",
   "metadata": {
    "papermill": {
     "duration": 0.023458,
     "end_time": "2024-04-05T18:34:52.858283",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.834825",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### [A] General Overview:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be4144a8",
   "metadata": {
    "papermill": {
     "duration": 0.023325,
     "end_time": "2024-04-05T18:34:52.904905",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.881580",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "How many matches are there in the dataset?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f6b55a64",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:52.954230Z",
     "iopub.status.busy": "2024-04-05T18:34:52.953201Z",
     "iopub.status.idle": "2024-04-05T18:34:52.958381Z",
     "shell.execute_reply": "2024-04-05T18:34:52.957642Z"
    },
    "papermill": {
     "duration": 0.032667,
     "end_time": "2024-04-05T18:34:52.961202",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.928535",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Number of matches played are : 1024\n"
     ]
    }
   ],
   "source": [
    "print(\"Total Number of matches played are :\",len(match_info_data))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1113341b",
   "metadata": {
    "papermill": {
     "duration": 0.023541,
     "end_time": "2024-04-05T18:34:53.008236",
     "exception": false,
     "start_time": "2024-04-05T18:34:52.984695",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "How many unique seasons are represented in the dataset?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b65d9278",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:53.057690Z",
     "iopub.status.busy": "2024-04-05T18:34:53.056710Z",
     "iopub.status.idle": "2024-04-05T18:34:53.067043Z",
     "shell.execute_reply": "2024-04-05T18:34:53.065491Z"
    },
    "papermill": {
     "duration": 0.037523,
     "end_time": "2024-04-05T18:34:53.069342",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.031819",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of unique seasons are : 16\n"
     ]
    }
   ],
   "source": [
    "print(\"Total number of unique seasons are :\",len(list(match_info_data[\"season\"].unique())))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c070786",
   "metadata": {
    "papermill": {
     "duration": 0.023383,
     "end_time": "2024-04-05T18:34:53.116615",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.093232",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "What are the different cities where matches have been played?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "04457180",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:53.226924Z",
     "iopub.status.busy": "2024-04-05T18:34:53.226284Z",
     "iopub.status.idle": "2024-04-05T18:34:53.232537Z",
     "shell.execute_reply": "2024-04-05T18:34:53.231212Z"
    },
    "papermill": {
     "duration": 0.034218,
     "end_time": "2024-04-05T18:34:53.235118",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.200900",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Different cities where IPL matches were played : ['Ahmedabad', 'Chennai', 'Mumbai', 'Bengaluru', 'Kolkata', 'Delhi', 'Dharamsala', 'Hyderabad', 'Lucknow', 'Jaipur', 'Chandigarh', 'Guwahati', 'Navi Mumbai', 'Pune', 'Dubai', 'Sharjah', 'Abu Dhabi', nan, 'Visakhapatnam', 'Indore', 'Bangalore', 'Kanpur', 'Rajkot', 'Raipur', 'Ranchi', 'Cuttack', 'Kochi', 'Nagpur', 'Johannesburg', 'Centurion', 'Durban', 'Bloemfontein', 'Port Elizabeth', 'Kimberley', 'East London', 'Cape Town']\n"
     ]
    }
   ],
   "source": [
    "print(\"Different cities where IPL matches were played :\",list(match_info_data[\"city\"].unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9afdef88",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:53.285599Z",
     "iopub.status.busy": "2024-04-05T18:34:53.284833Z",
     "iopub.status.idle": "2024-04-05T18:34:53.291316Z",
     "shell.execute_reply": "2024-04-05T18:34:53.290145Z"
    },
    "papermill": {
     "duration": 0.034678,
     "end_time": "2024-04-05T18:34:53.293853",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.259175",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of cities where IPL matches were played : 36\n"
     ]
    }
   ],
   "source": [
    "print(\"Total number of cities where IPL matches were played :\",len(list(match_info_data[\"city\"].unique())))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd8e4317",
   "metadata": {
    "papermill": {
     "duration": 0.023824,
     "end_time": "2024-04-05T18:34:53.341767",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.317943",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "What are the unique venues where matches have taken place?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "98dd61ab",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:53.391747Z",
     "iopub.status.busy": "2024-04-05T18:34:53.391389Z",
     "iopub.status.idle": "2024-04-05T18:34:53.398610Z",
     "shell.execute_reply": "2024-04-05T18:34:53.397588Z"
    },
    "papermill": {
     "duration": 0.035427,
     "end_time": "2024-04-05T18:34:53.401357",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.365930",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Venues for IPL matches : \n",
      " \n",
      "----------------------------------------------------------------------------------------------------\n",
      "1. Narendra Modi Stadium, Ahmedabad\n",
      "2. MA Chidambaram Stadium, Chepauk, Chennai\n",
      "3. Wankhede Stadium, Mumbai\n",
      "4. M Chinnaswamy Stadium, Bengaluru\n",
      "5. Eden Gardens, Kolkata\n",
      "6. Arun Jaitley Stadium, Delhi\n",
      "7. Himachal Pradesh Cricket Association Stadium, Dharamsala\n",
      "8. Rajiv Gandhi International Stadium, Uppal, Hyderabad\n",
      "9. Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cricket Stadium, Lucknow\n",
      "10. Sawai Mansingh Stadium, Jaipur\n",
      "11. Punjab Cricket Association IS Bindra Stadium, Mohali, Chandigarh\n",
      "12. Barsapara Cricket Stadium, Guwahati\n",
      "13. Brabourne Stadium, Mumbai\n",
      "14. Dr DY Patil Sports Academy, Mumbai\n",
      "15. Maharashtra Cricket Association Stadium, Pune\n",
      "16. Dubai International Cricket Stadium\n",
      "17. Sharjah Cricket Stadium\n",
      "18. Zayed Cricket Stadium, Abu Dhabi\n",
      "19. Sheikh Zayed Stadium\n",
      "20. Rajiv Gandhi International Stadium\n",
      "21. Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium\n",
      "22. MA Chidambaram Stadium\n",
      "23. Punjab Cricket Association IS Bindra Stadium\n",
      "24. Wankhede Stadium\n",
      "25. M.Chinnaswamy Stadium\n",
      "26. Arun Jaitley Stadium\n",
      "27. Eden Gardens\n",
      "28. Sawai Mansingh Stadium\n",
      "29. Maharashtra Cricket Association Stadium\n",
      "30. Holkar Cricket Stadium\n",
      "31. Rajiv Gandhi International Stadium, Uppal\n",
      "32. M Chinnaswamy Stadium\n",
      "33. Feroz Shah Kotla\n",
      "34. Green Park\n",
      "35. Punjab Cricket Association IS Bindra Stadium, Mohali\n",
      "36. Saurashtra Cricket Association Stadium\n",
      "37. Shaheed Veer Narayan Singh International Stadium\n",
      "38. JSCA International Stadium Complex\n",
      "39. Brabourne Stadium\n",
      "40. Punjab Cricket Association Stadium, Mohali\n",
      "41. MA Chidambaram Stadium, Chepauk\n",
      "42. Sardar Patel Stadium, Motera\n",
      "43. Barabati Stadium\n",
      "44. Subrata Roy Sahara Stadium\n",
      "45. Himachal Pradesh Cricket Association Stadium\n",
      "46. Dr DY Patil Sports Academy\n",
      "47. Nehru Stadium\n",
      "48. Vidarbha Cricket Association Stadium, Jamtha\n",
      "49. New Wanderers Stadium\n",
      "50. SuperSport Park\n",
      "51. Kingsmead\n",
      "52. OUTsurance Oval\n",
      "53. St George's Park\n",
      "54. De Beers Diamond Oval\n",
      "55. Buffalo Park\n",
      "56. Newlands\n"
     ]
    }
   ],
   "source": [
    "print(\"Venues for IPL matches : \\n \")\n",
    "print(\"-\"*100)\n",
    "\n",
    "all_venues_with_serial = [print(f\"{i}. {venue}\") for i, venue in enumerate(match_info_data[\"venue\"].unique(),1)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd4d900a",
   "metadata": {
    "papermill": {
     "duration": 0.024178,
     "end_time": "2024-04-05T18:34:53.450421",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.426243",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "What are the total number of teams participating in the dataset?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c23b19dc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:53.502540Z",
     "iopub.status.busy": "2024-04-05T18:34:53.501464Z",
     "iopub.status.idle": "2024-04-05T18:34:53.507601Z",
     "shell.execute_reply": "2024-04-05T18:34:53.506339Z"
    },
    "papermill": {
     "duration": 0.03463,
     "end_time": "2024-04-05T18:34:53.510238",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.475608",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "all_teams = list(set(list(match_info_data[\"team1\"].unique()) + list(match_info_data[\"team2\"].unique())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c0abbf1b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:53.561061Z",
     "iopub.status.busy": "2024-04-05T18:34:53.559916Z",
     "iopub.status.idle": "2024-04-05T18:34:53.567308Z",
     "shell.execute_reply": "2024-04-05T18:34:53.566048Z"
    },
    "papermill": {
     "duration": 0.03557,
     "end_time": "2024-04-05T18:34:53.569983",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.534413",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All IPL Teams  : \n",
      " \n",
      "----------------------------------------------------------------------------------------------------\n",
      "1. Deccan Chargers\n",
      "2. Punjab Kings\n",
      "3. Rajasthan Royals\n",
      "4. Kolkata Knight Riders\n",
      "5. Lucknow Super Giants\n",
      "6. Kings XI Punjab\n",
      "7. Rising Pune Supergiant\n",
      "8. Delhi Capitals\n",
      "9. Sunrisers Hyderabad\n",
      "10. Royal Challengers Bangalore\n",
      "11. Gujarat Lions\n",
      "12. Pune Warriors\n",
      "13. Kochi Tuskers Kerala\n",
      "14. Delhi Daredevils\n",
      "15. Mumbai Indians\n",
      "16. Gujarat Titans\n",
      "17. Rising Pune Supergiants\n",
      "18. Chennai Super Kings\n"
     ]
    }
   ],
   "source": [
    "print(\"All IPL Teams  : \\n \")\n",
    "print(\"-\"*100)\n",
    "\n",
    "printing_ipl_teams = [print(f\"{i}. {team}\") for i, team in enumerate(all_teams,1)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b4049a0",
   "metadata": {
    "papermill": {
     "duration": 0.025024,
     "end_time": "2024-04-05T18:34:53.619992",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.594968",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "How many matches have resulted in a tie?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "859c9fa7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:53.671373Z",
     "iopub.status.busy": "2024-04-05T18:34:53.670337Z",
     "iopub.status.idle": "2024-04-05T18:34:53.700383Z",
     "shell.execute_reply": "2024-04-05T18:34:53.699314Z"
    },
    "papermill": {
     "duration": 0.059209,
     "end_time": "2024-04-05T18:34:53.703557",
     "exception": false,
     "start_time": "2024-04-05T18:34:53.644348",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of tied matches : 19\n",
      "----------------------------------------------------------------------------------------------------\n",
      "Matches where 'winner' column has NaN values:\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1359519</td>\n",
       "      <td>2023</td>\n",
       "      <td>Lucknow</td>\n",
       "      <td>2023/05/03</td>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Chennai Super Kings</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bharat Ratna Shri Atal Bihari Vajpayee Ekana C...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>NA Patwardhan</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>1254077</td>\n",
       "      <td>2021</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2021/04/25</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PP Shaw</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk, Chennai</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>KN Ananthapadmanabhan</td>\n",
       "      <td>Tapan Sharma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>1216517</td>\n",
       "      <td>2020/21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020/10/18</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>KL Rahul</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>PR Reiffel</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>1216512</td>\n",
       "      <td>2020/21</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>2020/10/18</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>LH Ferguson</td>\n",
       "      <td>Sheikh Zayed Stadium</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>VK Sharma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>1216547</td>\n",
       "      <td>2020/21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020/09/28</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>PR Reiffel</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266</th>\n",
       "      <td>1216493</td>\n",
       "      <td>2020/21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020/09/20</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>MP Stoinis</td>\n",
       "      <td>Dubai International Cricket Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>PR Reiffel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>1178426</td>\n",
       "      <td>2019</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2019/05/02</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>JJ Bumrah</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>279</th>\n",
       "      <td>1178424</td>\n",
       "      <td>2019</td>\n",
       "      <td>Bengaluru</td>\n",
       "      <td>2019/04/30</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M.Chinnaswamy Stadium</td>\n",
       "      <td>NJ Llong</td>\n",
       "      <td>UV Gandhe</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318</th>\n",
       "      <td>1175365</td>\n",
       "      <td>2019</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2019/03/30</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PP Shaw</td>\n",
       "      <td>Arun Jaitley Stadium</td>\n",
       "      <td>AY Dandekar</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>M Erasmus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>1082625</td>\n",
       "      <td>2017</td>\n",
       "      <td>Rajkot</td>\n",
       "      <td>2017/04/29</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>KH Pandya</td>\n",
       "      <td>Saurashtra Cricket Association Stadium</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>CB Gaffaney</td>\n",
       "      <td>A Nand Kishore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>829813</td>\n",
       "      <td>2015</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2015/05/17</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>K Srinivasan</td>\n",
       "      <td>PG Pathak</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>538</th>\n",
       "      <td>829763</td>\n",
       "      <td>2015</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2015/04/29</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>JD Cloete</td>\n",
       "      <td>PG Pathak</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>829741</td>\n",
       "      <td>2015</td>\n",
       "      <td>Ahmedabad</td>\n",
       "      <td>2015/04/21</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>SE Marsh</td>\n",
       "      <td>Sardar Patel Stadium, Motera</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>607</th>\n",
       "      <td>729315</td>\n",
       "      <td>2014</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>2014/04/29</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>JP Faulkner</td>\n",
       "      <td>Sheikh Zayed Stadium</td>\n",
       "      <td>Aleem Dar</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682</th>\n",
       "      <td>598017</td>\n",
       "      <td>2013</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2013/04/16</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>V Kohli</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>K Srinath</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>696</th>\n",
       "      <td>598004</td>\n",
       "      <td>2013</td>\n",
       "      <td>Hyderabad</td>\n",
       "      <td>2013/04/07</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>GH Vihari</td>\n",
       "      <td>Rajiv Gandhi International Stadium, Uppal</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>K Srinath</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>782</th>\n",
       "      <td>501265</td>\n",
       "      <td>2011</td>\n",
       "      <td>Delhi</td>\n",
       "      <td>2011/05/21</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Pune Warriors</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Feroz Shah Kotla</td>\n",
       "      <td>SS Hazare</td>\n",
       "      <td>RJ Tucker</td>\n",
       "      <td>RB Tiffin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>893</th>\n",
       "      <td>419121</td>\n",
       "      <td>2009/10</td>\n",
       "      <td>Chennai</td>\n",
       "      <td>2010/03/21</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>J Theron</td>\n",
       "      <td>MA Chidambaram Stadium, Chepauk</td>\n",
       "      <td>K Hariharan</td>\n",
       "      <td>DJ Harper</td>\n",
       "      <td>S Das</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>958</th>\n",
       "      <td>392190</td>\n",
       "      <td>2009</td>\n",
       "      <td>Cape Town</td>\n",
       "      <td>2009/04/23</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>YK Pathan</td>\n",
       "      <td>Newlands</td>\n",
       "      <td>MR Benson</td>\n",
       "      <td>M Erasmus</td>\n",
       "      <td>AM Saheba</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id   season       city        date                        team1  \\\n",
       "29   1359519     2023    Lucknow  2023/05/03         Lucknow Super Giants   \n",
       "189  1254077     2021    Chennai  2021/04/25               Delhi Capitals   \n",
       "232  1216517  2020/21        NaN  2020/10/18               Mumbai Indians   \n",
       "233  1216512  2020/21  Abu Dhabi  2020/10/18        Kolkata Knight Riders   \n",
       "258  1216547  2020/21        NaN  2020/09/28  Royal Challengers Bangalore   \n",
       "266  1216493  2020/21        NaN  2020/09/20               Delhi Capitals   \n",
       "277  1178426     2019     Mumbai  2019/05/02               Mumbai Indians   \n",
       "279  1178424     2019  Bengaluru  2019/04/30  Royal Challengers Bangalore   \n",
       "318  1175365     2019      Delhi  2019/03/30        Kolkata Knight Riders   \n",
       "413  1082625     2017     Rajkot  2017/04/29                Gujarat Lions   \n",
       "512   829813     2015  Bangalore  2015/05/17  Royal Challengers Bangalore   \n",
       "538   829763     2015  Bangalore  2015/04/29  Royal Challengers Bangalore   \n",
       "548   829741     2015  Ahmedabad  2015/04/21             Rajasthan Royals   \n",
       "607   729315     2014  Abu Dhabi  2014/04/29        Kolkata Knight Riders   \n",
       "682   598017     2013  Bangalore  2013/04/16  Royal Challengers Bangalore   \n",
       "696   598004     2013  Hyderabad  2013/04/07          Sunrisers Hyderabad   \n",
       "782   501265     2011      Delhi  2011/05/21             Delhi Daredevils   \n",
       "893   419121  2009/10    Chennai  2010/03/21          Chennai Super Kings   \n",
       "958   392190     2009  Cape Town  2009/04/23        Kolkata Knight Riders   \n",
       "\n",
       "                           team2                  toss_winner toss_decision  \\\n",
       "29           Chennai Super Kings          Chennai Super Kings         field   \n",
       "189          Sunrisers Hyderabad               Delhi Capitals           bat   \n",
       "232              Kings XI Punjab               Mumbai Indians           bat   \n",
       "233          Sunrisers Hyderabad          Sunrisers Hyderabad         field   \n",
       "258               Mumbai Indians               Mumbai Indians         field   \n",
       "266              Kings XI Punjab              Kings XI Punjab         field   \n",
       "277          Sunrisers Hyderabad               Mumbai Indians           bat   \n",
       "279             Rajasthan Royals             Rajasthan Royals         field   \n",
       "318               Delhi Capitals               Delhi Capitals         field   \n",
       "413               Mumbai Indians                Gujarat Lions           bat   \n",
       "512             Delhi Daredevils  Royal Challengers Bangalore         field   \n",
       "538             Rajasthan Royals             Rajasthan Royals         field   \n",
       "548              Kings XI Punjab              Kings XI Punjab         field   \n",
       "607             Rajasthan Royals             Rajasthan Royals           bat   \n",
       "682             Delhi Daredevils  Royal Challengers Bangalore         field   \n",
       "696  Royal Challengers Bangalore  Royal Challengers Bangalore           bat   \n",
       "782                Pune Warriors             Delhi Daredevils           bat   \n",
       "893              Kings XI Punjab          Chennai Super Kings         field   \n",
       "958             Rajasthan Royals        Kolkata Knight Riders         field   \n",
       "\n",
       "     result  dl_applied winner  win_by_runs  win_by_wickets player_of_match  \\\n",
       "29   normal           0    NaN            0               0             NaN   \n",
       "189  normal           0    NaN            0               0         PP Shaw   \n",
       "232  normal           0    NaN            0               0        KL Rahul   \n",
       "233  normal           0    NaN            0               0     LH Ferguson   \n",
       "258  normal           0    NaN            0               0  AB de Villiers   \n",
       "266  normal           0    NaN            0               0      MP Stoinis   \n",
       "277  normal           0    NaN            0               0       JJ Bumrah   \n",
       "279  normal           0    NaN            0               0             NaN   \n",
       "318  normal           0    NaN            0               0         PP Shaw   \n",
       "413  normal           0    NaN            0               0       KH Pandya   \n",
       "512  normal           0    NaN            0               0             NaN   \n",
       "538  normal           0    NaN            0               0             NaN   \n",
       "548  normal           0    NaN            0               0        SE Marsh   \n",
       "607  normal           0    NaN            0               0     JP Faulkner   \n",
       "682  normal           0    NaN            0               0         V Kohli   \n",
       "696  normal           0    NaN            0               0       GH Vihari   \n",
       "782  normal           0    NaN            0               0             NaN   \n",
       "893  normal           0    NaN            0               0        J Theron   \n",
       "958  normal           0    NaN            0               0       YK Pathan   \n",
       "\n",
       "                                                 venue          umpire1  \\\n",
       "29   Bharat Ratna Shri Atal Bihari Vajpayee Ekana C...     AK Chaudhary   \n",
       "189           MA Chidambaram Stadium, Chepauk, Chennai      CB Gaffaney   \n",
       "232                Dubai International Cricket Stadium      Nitin Menon   \n",
       "233                               Sheikh Zayed Stadium        PG Pathak   \n",
       "258                Dubai International Cricket Stadium      Nitin Menon   \n",
       "266                Dubai International Cricket Stadium     AK Chaudhary   \n",
       "277                                   Wankhede Stadium        CK Nandan   \n",
       "279                              M.Chinnaswamy Stadium         NJ Llong   \n",
       "318                               Arun Jaitley Stadium      AY Dandekar   \n",
       "413             Saurashtra Cricket Association Stadium     AK Chaudhary   \n",
       "512                              M Chinnaswamy Stadium  HDPK Dharmasena   \n",
       "538                              M Chinnaswamy Stadium        JD Cloete   \n",
       "548                       Sardar Patel Stadium, Motera        M Erasmus   \n",
       "607                               Sheikh Zayed Stadium        Aleem Dar   \n",
       "682                              M Chinnaswamy Stadium        M Erasmus   \n",
       "696          Rajiv Gandhi International Stadium, Uppal     AK Chaudhary   \n",
       "782                                   Feroz Shah Kotla        SS Hazare   \n",
       "893                    MA Chidambaram Stadium, Chepauk      K Hariharan   \n",
       "958                                           Newlands        MR Benson   \n",
       "\n",
       "                   umpire2         umpire3  \n",
       "29           NA Patwardhan     CB Gaffaney  \n",
       "189  KN Ananthapadmanabhan    Tapan Sharma  \n",
       "232             PR Reiffel    AK Chaudhary  \n",
       "233                 S Ravi       VK Sharma  \n",
       "258             PR Reiffel    AK Chaudhary  \n",
       "266            Nitin Menon      PR Reiffel  \n",
       "277                 S Ravi  A Nand Kishore  \n",
       "279              UV Gandhe    AK Chaudhary  \n",
       "318            Nitin Menon       M Erasmus  \n",
       "413            CB Gaffaney  A Nand Kishore  \n",
       "512           K Srinivasan       PG Pathak  \n",
       "538              PG Pathak   C Shamshuddin  \n",
       "548                 S Ravi    AK Chaudhary  \n",
       "607           AK Chaudhary     VA Kulkarni  \n",
       "682            VA Kulkarni       K Srinath  \n",
       "696                 S Ravi       K Srinath  \n",
       "782              RJ Tucker       RB Tiffin  \n",
       "893              DJ Harper           S Das  \n",
       "958              M Erasmus       AM Saheba  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nan_matches = match_info_data[match_info_data[\"winner\"].isna()]\n",
    "print(\"Total number of tied matches :\", len(nan_matches))\n",
    "print(\"-\"*100)\n",
    "print(\"Matches where 'winner' column has NaN values:\")\n",
    "nan_matches\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84f674d5",
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### [B] Team Performance:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d0a1a9a",
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    },
    "tags": []
   },
   "source": [
    "Which team has won the most matches overall?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cff7f6cf",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>winner</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Delhi Capitals</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Punjab Kings</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Lucknow Super Giants</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Pune Warriors</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Rising Pune Supergiant</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Kochi Tuskers Kerala</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         winner  count\n",
       "0                Mumbai Indians    138\n",
       "1           Chennai Super Kings    131\n",
       "2         Kolkata Knight Riders    119\n",
       "3   Royal Challengers Bangalore    114\n",
       "4              Rajasthan Royals    101\n",
       "5               Kings XI Punjab     85\n",
       "6           Sunrisers Hyderabad     78\n",
       "7              Delhi Daredevils     67\n",
       "8                Delhi Capitals     38\n",
       "9               Deccan Chargers     29\n",
       "10               Gujarat Titans     23\n",
       "11                 Punjab Kings     19\n",
       "12         Lucknow Super Giants     17\n",
       "13                Gujarat Lions     13\n",
       "14                Pune Warriors     12\n",
       "15       Rising Pune Supergiant     10\n",
       "16         Kochi Tuskers Kerala      6\n",
       "17      Rising Pune Supergiants      5"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match_info_data[\"winner\"].value_counts().reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f7d14e8",
   "metadata": {
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    "tags": []
   },
   "source": [
    "From above information, it can be said that Mumbai Indians have won most matches."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41e99e89",
   "metadata": {
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    },
    "tags": []
   },
   "source": [
    "Which team has won the most matches in each season?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "16d43b81",
   "metadata": {
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   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>winner</th>\n",
       "      <th>wins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007/08</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007/08</td>\n",
       "      <td>Deccan Chargers</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007/08</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007/08</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007/08</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>2023</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2023</td>\n",
       "      <td>Punjab Kings</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2023</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2023</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>2023</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      season                       winner  wins\n",
       "0    2007/08          Chennai Super Kings     9\n",
       "1    2007/08              Deccan Chargers     2\n",
       "2    2007/08             Delhi Daredevils     7\n",
       "3    2007/08              Kings XI Punjab    10\n",
       "4    2007/08        Kolkata Knight Riders     6\n",
       "..       ...                          ...   ...\n",
       "131     2023               Mumbai Indians     9\n",
       "132     2023                 Punjab Kings     6\n",
       "133     2023             Rajasthan Royals     7\n",
       "134     2023  Royal Challengers Bangalore     7\n",
       "135     2023          Sunrisers Hyderabad     4\n",
       "\n",
       "[136 rows x 3 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "season_winner_counts = match_info_data.groupby(['season', 'winner']).size().reset_index(name='wins')\n",
    "season_winner_counts\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
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      "/tmp/ipykernel_19/4253911799.py:2: FutureWarning: The provided callable <built-in function max> is currently using SeriesGroupBy.max. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"max\" instead.\n",
      "  idx = season_winner_counts.groupby('season')['wins'].transform(max) == season_winner_counts['wins']\n"
     ]
    }
   ],
   "source": [
    "# Find the index of the maximum wins for each season\n",
    "idx = season_winner_counts.groupby('season')['wins'].transform(max) == season_winner_counts['wins']\n"
   ]
  },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>winner</th>\n",
       "      <th>wins</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2007/08</td>\n",
       "      <td>Rajasthan Royals</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2009</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2009/10</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2011</td>\n",
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       "      <td>11</td>\n",
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       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2012</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2013</td>\n",
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       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2014</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2015</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2015</td>\n",
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       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>2016</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2017</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>2018</td>\n",
       "      <td>Chennai Super Kings</td>\n",
       "      <td>11</td>\n",
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       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>2019</td>\n",
       "      <td>Chennai Super Kings</td>\n",
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       "      <td>11</td>\n",
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       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>2022</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>2023</td>\n",
       "      <td>Gujarat Titans</td>\n",
       "      <td>11</td>\n",
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      ],
      "text/plain": [
       "      season                 winner  wins\n",
       "6    2007/08       Rajasthan Royals    13\n",
       "10      2009       Delhi Daredevils    10\n",
       "21   2009/10         Mumbai Indians    11\n",
       "24      2011    Chennai Super Kings    11\n",
       "38      2012  Kolkata Knight Riders    12\n",
       "47      2013         Mumbai Indians    13\n",
       "54      2014        Kings XI Punjab    12\n",
       "60      2015    Chennai Super Kings    10\n",
       "64      2015         Mumbai Indians    10\n",
       "75      2016    Sunrisers Hyderabad    11\n",
       "80      2017         Mumbai Indians    11\n",
       "84      2018    Chennai Super Kings    11\n",
       "92      2019    Chennai Super Kings    10\n",
       "96      2019         Mumbai Indians    10\n",
       "104  2020/21         Mumbai Indians    11\n",
       "108     2021    Chennai Super Kings    11\n",
       "118     2022         Gujarat Titans    12\n",
       "128     2023         Gujarat Titans    11"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter out the rows with maximum wins for each season\n",
    "most_wins_per_season = season_winner_counts[idx]\n",
    "most_wins_per_season"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d845f5f8",
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   "source": [
    "Which team has won the most matches when batting first/batting second?"
   ]
  },
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   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "Team with most wins when batting first:\n",
      "Mumbai Indians\n",
      "Team with most wins when batting second:\n",
      "Mumbai Indians\n"
     ]
    }
   ],
   "source": [
    "# Filter out matches where result is not 'normal' (i.e., disregard matches with no result)\n",
    "normal_matches = match_info_data[match_info_data['result'] == 'normal']\n",
    "\n",
    "# Count matches won by each team when batting first\n",
    "batting_first_wins = normal_matches[normal_matches['win_by_runs'] > 0]['winner'].value_counts()\n",
    "\n",
    "# Count matches won by each team when batting second\n",
    "batting_second_wins = normal_matches[normal_matches['win_by_wickets'] > 0]['winner'].value_counts()\n",
    "\n",
    "# Print the team that won the most matches when batting first\n",
    "print(\"Team with most wins when batting first:\")\n",
    "print(batting_first_wins.idxmax())\n",
    "\n",
    "# Print the team that won the most matches when batting second\n",
    "print(\"Team with most wins when batting second:\")\n",
    "print(batting_second_wins.idxmax())"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "Which team has won the most matches by runs/wickets?"
   ]
  },
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    {
     "name": "stdout",
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     "text": [
      "Team with most wins by runs:\n",
      "Mumbai Indians\n",
      "Team with most wins by wickets:\n",
      "Mumbai Indians\n"
     ]
    }
   ],
   "source": [
    "# Filter out matches where result is not 'normal' (i.e., disregard matches with no result)\n",
    "normal_matches = match_info_data[match_info_data['result'] == 'normal']\n",
    "\n",
    "# Count matches won by each team by runs\n",
    "runs_wins = normal_matches[normal_matches['win_by_runs'] > 0]['winner'].value_counts()\n",
    "\n",
    "# Count matches won by each team by wickets\n",
    "wickets_wins = normal_matches[normal_matches['win_by_wickets'] > 0]['winner'].value_counts()\n",
    "\n",
    "# Print the team that won the most matches by runs\n",
    "print(\"Team with most wins by runs:\")\n",
    "print(runs_wins.idxmax())\n",
    "\n",
    "# Print the team that won the most matches by wickets\n",
    "print(\"Team with most wins by wickets:\")\n",
    "print(wickets_wins.idxmax())"
   ]
  },
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   "source": [
    "How does the performance of each team vary across seasons?"
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>17.543860</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.771930</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.508772</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.280702</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.543860</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.280702</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.280702</td>\n",
       "      <td>10.526316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>16.071429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.142857</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.357143</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>19.642857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.344828</td>\n",
       "      <td>6.896552</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.068966</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.793103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.965517</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.241379</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.172414</td>\n",
       "      <td>13.793103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>19.298246</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.017544</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.771930</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.789474</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.526316</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.526316</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.526316</td>\n",
       "      <td>17.543860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>16.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020/21</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>13.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>18.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>5.405405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.459459</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.216216</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.108108</td>\n",
       "      <td>12.162162</td>\n",
       "      <td>5.405405</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.459459</td>\n",
       "      <td>13.513514</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.162162</td>\n",
       "      <td>8.108108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>12.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.944444</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.277778</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>11.111111</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.944444</td>\n",
       "      <td>9.722222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.722222</td>\n",
       "      <td>5.555556</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "winner   Chennai Super Kings  Deccan Chargers  Delhi Capitals  \\\n",
       "season                                                          \n",
       "2007/08            14.285714         3.571429             NaN   \n",
       "2009               12.962963        16.666667             NaN   \n",
       "2009/10            15.000000        13.333333             NaN   \n",
       "2011               15.714286         8.571429             NaN   \n",
       "2012               13.513514         5.405405             NaN   \n",
       "2013               15.789474              NaN             NaN   \n",
       "2014               16.949153              NaN             NaN   \n",
       "2015               17.543860              NaN             NaN   \n",
       "2016                     NaN              NaN             NaN   \n",
       "2017                     NaN              NaN             NaN   \n",
       "2018               19.298246              NaN             NaN   \n",
       "2019               16.666667              NaN       15.000000   \n",
       "2020/21            10.000000              NaN       13.333333   \n",
       "2021               18.333333              NaN       15.000000   \n",
       "2022                5.405405              NaN        9.459459   \n",
       "2023               12.500000              NaN        6.944444   \n",
       "\n",
       "winner   Delhi Daredevils  Gujarat Lions  Gujarat Titans  Kings XI Punjab  \\\n",
       "season                                                                      \n",
       "2007/08         12.500000            NaN             NaN        16.071429   \n",
       "2009            16.666667            NaN             NaN        12.962963   \n",
       "2009/10         11.666667            NaN             NaN         5.000000   \n",
       "2011             5.714286            NaN             NaN        10.000000   \n",
       "2012            14.864865            NaN             NaN        10.810811   \n",
       "2013             3.947368            NaN             NaN        10.526316   \n",
       "2014             3.389831            NaN             NaN        20.338983   \n",
       "2015             8.771930            NaN             NaN         3.508772   \n",
       "2016            12.500000      16.071429             NaN         7.142857   \n",
       "2017            10.344828       6.896552             NaN        12.068966   \n",
       "2018             7.017544            NaN             NaN         8.771930   \n",
       "2019                  NaN            NaN             NaN        10.000000   \n",
       "2020/21               NaN            NaN             NaN         8.333333   \n",
       "2021                  NaN            NaN             NaN              NaN   \n",
       "2022                  NaN            NaN       16.216216              NaN   \n",
       "2023                  NaN            NaN       15.277778              NaN   \n",
       "\n",
       "winner   Kochi Tuskers Kerala  Kolkata Knight Riders  Lucknow Super Giants  \\\n",
       "season                                                                       \n",
       "2007/08                   NaN              10.714286                   NaN   \n",
       "2009                      NaN               3.703704                   NaN   \n",
       "2009/10                   NaN              11.666667                   NaN   \n",
       "2011                 7.142857              10.000000                   NaN   \n",
       "2012                      NaN              16.216216                   NaN   \n",
       "2013                      NaN               7.894737                   NaN   \n",
       "2014                      NaN              18.644068                   NaN   \n",
       "2015                      NaN              12.280702                   NaN   \n",
       "2016                      NaN              12.500000                   NaN   \n",
       "2017                      NaN              13.793103                   NaN   \n",
       "2018                      NaN              15.789474                   NaN   \n",
       "2019                      NaN              10.000000                   NaN   \n",
       "2020/21                   NaN              10.000000                   NaN   \n",
       "2021                      NaN              15.000000                   NaN   \n",
       "2022                      NaN               8.108108             12.162162   \n",
       "2023                      NaN               8.333333             11.111111   \n",
       "\n",
       "winner   Mumbai Indians  Pune Warriors  Punjab Kings  Rajasthan Royals  \\\n",
       "season                                                                   \n",
       "2007/08       12.500000            NaN           NaN         23.214286   \n",
       "2009           9.259259            NaN           NaN          9.259259   \n",
       "2009/10       18.333333            NaN           NaN         10.000000   \n",
       "2011          14.285714       5.714286           NaN          8.571429   \n",
       "2012          13.513514       5.405405           NaN          9.459459   \n",
       "2013          17.105263       5.263158           NaN         14.473684   \n",
       "2014          11.864407            NaN           NaN         10.169492   \n",
       "2015          17.543860            NaN           NaN         12.280702   \n",
       "2016          12.500000            NaN           NaN               NaN   \n",
       "2017          18.965517            NaN           NaN               NaN   \n",
       "2018          10.526316            NaN           NaN         10.526316   \n",
       "2019          16.666667            NaN           NaN          8.333333   \n",
       "2020/21       18.333333            NaN           NaN         10.000000   \n",
       "2021          11.666667            NaN     10.000000          8.333333   \n",
       "2022           5.405405            NaN      9.459459         13.513514   \n",
       "2023          12.500000            NaN      6.944444          9.722222   \n",
       "\n",
       "winner   Rising Pune Supergiant  Rising Pune Supergiants  \\\n",
       "season                                                     \n",
       "2007/08                     NaN                      NaN   \n",
       "2009                        NaN                      NaN   \n",
       "2009/10                     NaN                      NaN   \n",
       "2011                        NaN                      NaN   \n",
       "2012                        NaN                      NaN   \n",
       "2013                        NaN                      NaN   \n",
       "2014                        NaN                      NaN   \n",
       "2015                        NaN                      NaN   \n",
       "2016                        NaN                 5.357143   \n",
       "2017                  17.241379                      NaN   \n",
       "2018                        NaN                      NaN   \n",
       "2019                        NaN                      NaN   \n",
       "2020/21                     NaN                      NaN   \n",
       "2021                        NaN                      NaN   \n",
       "2022                        NaN                      NaN   \n",
       "2023                        NaN                      NaN   \n",
       "\n",
       "winner   Royal Challengers Bangalore  Sunrisers Hyderabad  \n",
       "season                                                     \n",
       "2007/08                     7.142857                  NaN  \n",
       "2009                       16.666667                  NaN  \n",
       "2009/10                    13.333333                  NaN  \n",
       "2011                       12.857143                  NaN  \n",
       "2012                       10.810811                  NaN  \n",
       "2013                       10.526316            11.842105  \n",
       "2014                        8.474576             8.474576  \n",
       "2015                       12.280702            10.526316  \n",
       "2016                       14.285714            19.642857  \n",
       "2017                        5.172414            13.793103  \n",
       "2018                       10.526316            17.543860  \n",
       "2019                        8.333333            10.000000  \n",
       "2020/21                    10.000000            13.333333  \n",
       "2021                       15.000000             5.000000  \n",
       "2022                       12.162162             8.108108  \n",
       "2023                        9.722222             5.555556  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter out matches where result is not 'normal' (i.e., disregard matches with no result)\n",
    "normal_matches = match_info_data[match_info_data['result'] == 'normal']\n",
    "\n",
    "# Group by season and team, count the matches won by each team in each season\n",
    "season_team_wins = normal_matches.groupby(['season', 'winner']).size().reset_index(name='wins')\n",
    "\n",
    "# Group by season, count the total matches played in each season\n",
    "season_total_matches = normal_matches.groupby('season').size().reset_index(name='total_matches')\n",
    "\n",
    "# Merge the two DataFrames to calculate win percentage\n",
    "season_performance = pd.merge(season_team_wins, season_total_matches, on='season')\n",
    "\n",
    "# Calculate win percentage for each team in each season\n",
    "season_performance['win_percentage'] = (season_performance['wins'] / season_performance['total_matches']) * 100\n",
    "\n",
    "# Pivot the DataFrame to have teams as columns and seasons as rows\n",
    "season_performance_pivot = season_performance.pivot(index='season', columns='winner', values='win_percentage')\n",
    "\n",
    "season_performance_pivot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5529654",
   "metadata": {
    "papermill": {
     "duration": 0.027207,
     "end_time": "2024-04-05T18:34:54.676888",
     "exception": false,
     "start_time": "2024-04-05T18:34:54.649681",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "What is the win percentage of each team?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "136568a7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:54.736331Z",
     "iopub.status.busy": "2024-04-05T18:34:54.735435Z",
     "iopub.status.idle": "2024-04-05T18:34:54.752020Z",
     "shell.execute_reply": "2024-04-05T18:34:54.750812Z"
    },
    "papermill": {
     "duration": 0.049093,
     "end_time": "2024-04-05T18:34:54.754385",
     "exception": false,
     "start_time": "2024-04-05T18:34:54.705292",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gujarat Titans                 71.875000\n",
       "Rising Pune Supergiant         62.500000\n",
       "Chennai Super Kings            58.447489\n",
       "Lucknow Super Giants           56.666667\n",
       "Mumbai Indians                 55.870445\n",
       "Kolkata Knight Riders          50.438596\n",
       "Delhi Capitals                 49.350649\n",
       "Rajasthan Royals               49.019608\n",
       "Sunrisers Hyderabad            47.204969\n",
       "Royal Challengers Bangalore    46.835443\n",
       "Kings XI Punjab                45.108696\n",
       "Punjab Kings                   43.902439\n",
       "Gujarat Lions                  43.333333\n",
       "Delhi Daredevils               41.935484\n",
       "Deccan Chargers                38.666667\n",
       "Kochi Tuskers Kerala           38.461538\n",
       "Rising Pune Supergiants        27.272727\n",
       "Pune Warriors                  26.086957\n",
       "Name: count, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter out matches where result is not 'normal' (i.e., disregard matches with no result)\n",
    "normal_matches = match_info_data[match_info_data['result'] == 'normal']\n",
    "\n",
    "# Count matches won by each team\n",
    "team_wins = normal_matches['winner'].value_counts()\n",
    "\n",
    "# Count total matches played by each team\n",
    "total_matches = normal_matches['team1'].value_counts() + normal_matches['team2'].value_counts()\n",
    "\n",
    "# Calculate win percentage for each team\n",
    "win_percentage = (team_wins / total_matches) * 100\n",
    "\n",
    "# Sort win percentage from highest to lowest\n",
    "win_percentage_sorted = win_percentage.sort_values(ascending=False)\n",
    "\n",
    "win_percentage_sorted\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "517df500",
   "metadata": {
    "papermill": {
     "duration": 0.027527,
     "end_time": "2024-04-05T18:34:54.809677",
     "exception": false,
     "start_time": "2024-04-05T18:34:54.782150",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "069d8d9e",
   "metadata": {
    "papermill": {
     "duration": 0.027245,
     "end_time": "2024-04-05T18:34:54.864676",
     "exception": false,
     "start_time": "2024-04-05T18:34:54.837431",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### [C] Match Analysis:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dfa137dd",
   "metadata": {
    "papermill": {
     "duration": 0.027521,
     "end_time": "2024-04-05T18:34:54.920079",
     "exception": false,
     "start_time": "2024-04-05T18:34:54.892558",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "How many matches have been affected by the Duckworth-Lewis method?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "de07eadb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:54.977255Z",
     "iopub.status.busy": "2024-04-05T18:34:54.976820Z",
     "iopub.status.idle": "2024-04-05T18:34:54.985905Z",
     "shell.execute_reply": "2024-04-05T18:34:54.984754Z"
    },
    "papermill": {
     "duration": 0.040955,
     "end_time": "2024-04-05T18:34:54.988691",
     "exception": false,
     "start_time": "2024-04-05T18:34:54.947736",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total matches where DL method was applied : 21\n"
     ]
    }
   ],
   "source": [
    "print(\"Total matches where DL method was applied :\",match_info_data[\"dl_applied\"].value_counts()[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93ce5e83",
   "metadata": {
    "papermill": {
     "duration": 0.027771,
     "end_time": "2024-04-05T18:34:55.044526",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.016755",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "How many matches have been won by a margin of less than 10 runs/less than 3 wickets?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3f75c02a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:55.113560Z",
     "iopub.status.busy": "2024-04-05T18:34:55.112255Z",
     "iopub.status.idle": "2024-04-05T18:34:55.122284Z",
     "shell.execute_reply": "2024-04-05T18:34:55.120942Z"
    },
    "papermill": {
     "duration": 0.052623,
     "end_time": "2024-04-05T18:34:55.124770",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.072147",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total matches with the condition of - won by a margin of less than 10 runs/less than 3 wickets : 110\n"
     ]
    }
   ],
   "source": [
    "output_df = match_info_data[((match_info_data[\"win_by_runs\"] < 10) &  (match_info_data[\"win_by_runs\"] != 0)) | ((match_info_data[\"win_by_wickets\"] < 3) & (match_info_data[\"win_by_wickets\"] != 0))]\n",
    "\n",
    "print(\"Total matches with the condition of - won by a margin of less than 10 runs/less than 3 wickets :\", len(output_df))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2e2e109",
   "metadata": {
    "papermill": {
     "duration": 0.029601,
     "end_time": "2024-04-05T18:34:55.183421",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.153820",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Is there any correlation between winning the toss and winning the match?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "5768457b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:55.253710Z",
     "iopub.status.busy": "2024-04-05T18:34:55.252909Z",
     "iopub.status.idle": "2024-04-05T18:34:55.263262Z",
     "shell.execute_reply": "2024-04-05T18:34:55.261608Z"
    },
    "papermill": {
     "duration": 0.054059,
     "end_time": "2024-04-05T18:34:55.266283",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.212224",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Percentage of matches won by the toss winner: 50.48828125\n"
     ]
    }
   ],
   "source": [
    "toss_winner = match_info_data['toss_winner']\n",
    "winner = match_info_data['winner']\n",
    "\n",
    "# Count the number of times where the toss winner is the same as the match winner\n",
    "matches_won_by_toss_winner = (toss_winner == winner).sum()\n",
    "\n",
    "# Calculate the total number of matches\n",
    "total_matches = len(match_info_data)\n",
    "\n",
    "# Calculate the percentage of matches won by the toss winner\n",
    "percentage_won = (matches_won_by_toss_winner / total_matches) * 100\n",
    "\n",
    "print(\"Percentage of matches won by the toss winner:\", percentage_won)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2af0b74a",
   "metadata": {
    "papermill": {
     "duration": 0.029942,
     "end_time": "2024-04-05T18:34:55.336648",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.306706",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "How many matches have resulted in different types of results (normal, tie, no result)?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "97425097",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:55.397009Z",
     "iopub.status.busy": "2024-04-05T18:34:55.396027Z",
     "iopub.status.idle": "2024-04-05T18:34:55.409493Z",
     "shell.execute_reply": "2024-04-05T18:34:55.408184Z"
    },
    "papermill": {
     "duration": 0.047874,
     "end_time": "2024-04-05T18:34:55.413513",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.365639",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of matches with different types of results:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>result</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>normal</td>\n",
       "      <td>1003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D/L</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   result  count\n",
       "0  normal   1003\n",
       "1     D/L     21"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_counts = match_info_data['result'].value_counts().reset_index()\n",
    "\n",
    "print(\"Number of matches with different types of results:\")\n",
    "result_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6c75869b",
   "metadata": {
    "papermill": {
     "duration": 0.028436,
     "end_time": "2024-04-05T18:34:55.471079",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.442643",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ffb5ab33",
   "metadata": {
    "papermill": {
     "duration": 0.030536,
     "end_time": "2024-04-05T18:34:55.530599",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.500063",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### [D] Player Analysis:\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "948e27b1",
   "metadata": {
    "papermill": {
     "duration": 0.031865,
     "end_time": "2024-04-05T18:34:55.599037",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.567172",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Who are the top players with the most 'Player of the Match' awards?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f821fb26",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:55.663187Z",
     "iopub.status.busy": "2024-04-05T18:34:55.662406Z",
     "iopub.status.idle": "2024-04-05T18:34:56.037287Z",
     "shell.execute_reply": "2024-04-05T18:34:56.035825Z"
    },
    "papermill": {
     "duration": 0.407395,
     "end_time": "2024-04-05T18:34:56.040115",
     "exception": false,
     "start_time": "2024-04-05T18:34:55.632720",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "player_counts = match_info_data[\"player_of_match\"].value_counts().reset_index()\n",
    "\n",
    "# Plotting the graph\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.bar(player_counts['player_of_match'][:10], player_counts['count'][:10], color='skyblue')\n",
    "plt.xlabel('Player')\n",
    "plt.ylabel('Number of Times Player of the Match')\n",
    "plt.title('Top 10 Players of the Match')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92a93b28",
   "metadata": {
    "papermill": {
     "duration": 0.029331,
     "end_time": "2024-04-05T18:34:56.098830",
     "exception": false,
     "start_time": "2024-04-05T18:34:56.069499",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "AB de Villiers has the highest amount of man of the match awards."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef9df09e",
   "metadata": {
    "papermill": {
     "duration": 0.028589,
     "end_time": "2024-04-05T18:34:56.156828",
     "exception": false,
     "start_time": "2024-04-05T18:34:56.128239",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### [E] Venue Analysis:\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "292b15a4",
   "metadata": {
    "papermill": {
     "duration": 0.029029,
     "end_time": "2024-04-05T18:34:56.215223",
     "exception": false,
     "start_time": "2024-04-05T18:34:56.186194",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Which venue has hosted the most number of matches?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "07c5a3fc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:56.275162Z",
     "iopub.status.busy": "2024-04-05T18:34:56.274758Z",
     "iopub.status.idle": "2024-04-05T18:34:56.807070Z",
     "shell.execute_reply": "2024-04-05T18:34:56.805946Z"
    },
    "papermill": {
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   "source": [
    "import plotly.graph_objs as go\n",
    "import plotly.io as pio\n",
    "\n",
    "# Assuming match_info_data is your DataFrame containing the venue data\n",
    "venue_counts = match_info_data[\"venue\"].value_counts().reset_index()\n",
    "\n",
    "# Create a bar plot\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Bar(\n",
    "    x=venue_counts['venue'][:10],  # Venue names\n",
    "    y=venue_counts['count'][:10],  # Number of times each venue has hosted IPL matches\n",
    "    marker_color='red'  # Color of the bars\n",
    "))\n",
    "\n",
    "# Update layout\n",
    "fig.update_layout(\n",
    "    title='Top 10 Venues of IPL',\n",
    "    xaxis=dict(title='Venues'),\n",
    "    yaxis=dict(title='Hosted IPL Matches'),\n",
    "    xaxis_tickangle=-45  # Rotate x-axis labels for better readability\n",
    ")\n",
    "\n",
    "# Show the interactive plot\n",
    "pio.show(fig)\n"
   ]
  },
  {
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   "source": [
    "Are there any venues where teams tend to perform better/worse?"
   ]
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  {
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     "text": [
      "Win percentages at different venues:\n",
      "----------------------------------------------------------------------\n"
     ]
    },
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajiv Gandhi International Stadium, Uppal, Hyderabad</th>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cricket Stadium, Lucknow</th>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>42.857143</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sawai Mansingh Stadium, Jaipur</th>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association IS Bindra Stadium, Mohali, Chandigarh</th>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barsapara Cricket Stadium, Guwahati</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brabourne Stadium, Mumbai</th>\n",
       "      <td>11.764706</td>\n",
       "      <td>11.764706</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.764706</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.764706</td>\n",
       "      <td>11.764706</td>\n",
       "      <td>23.529412</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.647059</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr DY Patil Sports Academy, Mumbai</th>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maharashtra Cricket Association Stadium, Pune</th>\n",
       "      <td>23.076923</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.692308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.384615</td>\n",
       "      <td>15.384615</td>\n",
       "      <td>7.692308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.384615</td>\n",
       "      <td>15.384615</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dubai International Cricket Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>6.521739</td>\n",
       "      <td>19.565217</td>\n",
       "      <td>15.217391</td>\n",
       "      <td>15.217391</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.347826</td>\n",
       "      <td>10.869565</td>\n",
       "      <td>6.521739</td>\n",
       "      <td>4.347826</td>\n",
       "      <td>8.695652</td>\n",
       "      <td>2.173913</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sharjah Cricket Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>10.714286</td>\n",
       "      <td>10.714286</td>\n",
       "      <td>7.142857</td>\n",
       "      <td>10.714286</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.571429</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>17.857143</td>\n",
       "      <td>7.142857</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>3.571429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zayed Cricket Stadium, Abu Dhabi</th>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>12.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>25.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sheikh Zayed Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>20.689655</td>\n",
       "      <td>10.344828</td>\n",
       "      <td>6.896552</td>\n",
       "      <td>6.896552</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.896552</td>\n",
       "      <td>17.241379</td>\n",
       "      <td>17.241379</td>\n",
       "      <td>6.896552</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajiv Gandhi International Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>66.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>15.384615</td>\n",
       "      <td>15.384615</td>\n",
       "      <td>23.076923</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.692308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.692308</td>\n",
       "      <td>7.692308</td>\n",
       "      <td>7.692308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.384615</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA Chidambaram Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>22.222222</td>\n",
       "      <td>77.777778</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association IS Bindra Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wankhede Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>56.164384</td>\n",
       "      <td>9.589041</td>\n",
       "      <td>1.369863</td>\n",
       "      <td>4.109589</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.369863</td>\n",
       "      <td>1.369863</td>\n",
       "      <td>5.479452</td>\n",
       "      <td>6.849315</td>\n",
       "      <td>2.739726</td>\n",
       "      <td>2.739726</td>\n",
       "      <td>1.369863</td>\n",
       "      <td>1.369863</td>\n",
       "      <td>1.369863</td>\n",
       "      <td>1.369863</td>\n",
       "      <td>1.369863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M.Chinnaswamy Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>53.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arun Jaitley Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>7.142857</td>\n",
       "      <td>7.142857</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>7.142857</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.428571</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.142857</td>\n",
       "      <td>28.571429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eden Gardens</th>\n",
       "      <td>0.0</td>\n",
       "      <td>12.987013</td>\n",
       "      <td>6.493506</td>\n",
       "      <td>2.597403</td>\n",
       "      <td>5.194805</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.298701</td>\n",
       "      <td>58.441558</td>\n",
       "      <td>2.597403</td>\n",
       "      <td>3.896104</td>\n",
       "      <td>1.298701</td>\n",
       "      <td>1.298701</td>\n",
       "      <td>2.597403</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.298701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sawai Mansingh Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4.255319</td>\n",
       "      <td>6.382979</td>\n",
       "      <td>2.12766</td>\n",
       "      <td>6.382979</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.12766</td>\n",
       "      <td>6.382979</td>\n",
       "      <td>68.085106</td>\n",
       "      <td>2.12766</td>\n",
       "      <td>2.12766</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maharashtra Cricket Association Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>9.090909</td>\n",
       "      <td>22.727273</td>\n",
       "      <td>4.545455</td>\n",
       "      <td>9.090909</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.636364</td>\n",
       "      <td>4.545455</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.090909</td>\n",
       "      <td>22.727273</td>\n",
       "      <td>4.545455</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holkar Cricket Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>22.222222</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.111111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.111111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44.444444</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajiv Gandhi International Stadium, Uppal</th>\n",
       "      <td>0.0</td>\n",
       "      <td>10.204082</td>\n",
       "      <td>4.081633</td>\n",
       "      <td>38.77551</td>\n",
       "      <td>4.081633</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.163265</td>\n",
       "      <td>4.081633</td>\n",
       "      <td>8.163265</td>\n",
       "      <td>8.163265</td>\n",
       "      <td>2.040816</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.040816</td>\n",
       "      <td>2.040816</td>\n",
       "      <td>6.122449</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M Chinnaswamy Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>12.307692</td>\n",
       "      <td>6.153846</td>\n",
       "      <td>3.076923</td>\n",
       "      <td>43.076923</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.230769</td>\n",
       "      <td>4.615385</td>\n",
       "      <td>7.692308</td>\n",
       "      <td>4.615385</td>\n",
       "      <td>1.538462</td>\n",
       "      <td>1.538462</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.538462</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Feroz Shah Kotla</th>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>38.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>3.333333</td>\n",
       "      <td>1.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Green Park</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association IS Bindra Stadium, Mohali</th>\n",
       "      <td>0.0</td>\n",
       "      <td>9.090909</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.181818</td>\n",
       "      <td>9.090909</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.090909</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.363636</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.181818</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saurashtra Cricket Association Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shaheed Veer Narayan Singh International Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>66.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JSCA International Stadium Complex</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.857143</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brabourne Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association Stadium, Mohali</th>\n",
       "      <td>0.0</td>\n",
       "      <td>8.571429</td>\n",
       "      <td>8.571429</td>\n",
       "      <td>5.714286</td>\n",
       "      <td>5.714286</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.714286</td>\n",
       "      <td>8.571429</td>\n",
       "      <td>51.428571</td>\n",
       "      <td>2.857143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.857143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA Chidambaram Stadium, Chepauk</th>\n",
       "      <td>0.0</td>\n",
       "      <td>6.25</td>\n",
       "      <td>68.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.166667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.166667</td>\n",
       "      <td>2.083333</td>\n",
       "      <td>2.083333</td>\n",
       "      <td>4.166667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.083333</td>\n",
       "      <td>4.166667</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sardar Patel Stadium, Motera</th>\n",
       "      <td>0.0</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barabati Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.857143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.857143</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Subrata Roy Sahara Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>6.25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.75</td>\n",
       "      <td>6.25</td>\n",
       "      <td>6.25</td>\n",
       "      <td>6.25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>6.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Himachal Pradesh Cricket Association Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.111111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>55.555556</td>\n",
       "      <td>11.111111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.222222</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr DY Patil Sports Academy</th>\n",
       "      <td>0.0</td>\n",
       "      <td>29.411765</td>\n",
       "      <td>17.647059</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.882353</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.764706</td>\n",
       "      <td>5.882353</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.882353</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.764706</td>\n",
       "      <td>11.764706</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nehru Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vidarbha Cricket Association Stadium, Jamtha</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>66.666667</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Wanderers Stadium</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>12.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SuperSport Park</th>\n",
       "      <td>0.0</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.666667</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kingsmead</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OUTsurance Oval</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St George's Park</th>\n",
       "      <td>0.0</td>\n",
       "      <td>28.571429</td>\n",
       "      <td>28.571429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>De Beers Diamond Oval</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Buffalo Park</th>\n",
       "      <td>0.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Newlands</th>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>14.285714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.571429</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   Gujarat Titans  \\\n",
       "Narendra Modi Stadium, Ahmedabad                             37.5   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                      0.0   \n",
       "Wankhede Stadium, Mumbai                                 7.894737   \n",
       "M Chinnaswamy Stadium, Bengaluru                        14.285714   \n",
       "Eden Gardens, Kolkata                                   22.222222   \n",
       "Arun Jaitley Stadium, Delhi                              9.090909   \n",
       "Himachal Pradesh Cricket Association Stadium, D...            0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...            0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...      14.285714   \n",
       "Sawai Mansingh Stadium, Jaipur                               20.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...           20.0   \n",
       "Barsapara Cricket Stadium, Guwahati                           0.0   \n",
       "Brabourne Stadium, Mumbai                               11.764706   \n",
       "Dr DY Patil Sports Academy, Mumbai                           10.0   \n",
       "Maharashtra Cricket Association Stadium, Pune           23.076923   \n",
       "Dubai International Cricket Stadium                           0.0   \n",
       "Sharjah Cricket Stadium                                       0.0   \n",
       "Zayed Cricket Stadium, Abu Dhabi                              0.0   \n",
       "Sheikh Zayed Stadium                                          0.0   \n",
       "Rajiv Gandhi International Stadium                            0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...            0.0   \n",
       "MA Chidambaram Stadium                                        0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                  0.0   \n",
       "Wankhede Stadium                                              0.0   \n",
       "M.Chinnaswamy Stadium                                         0.0   \n",
       "Arun Jaitley Stadium                                          0.0   \n",
       "Eden Gardens                                                  0.0   \n",
       "Sawai Mansingh Stadium                                        0.0   \n",
       "Maharashtra Cricket Association Stadium                       0.0   \n",
       "Holkar Cricket Stadium                                        0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                     0.0   \n",
       "M Chinnaswamy Stadium                                         0.0   \n",
       "Feroz Shah Kotla                                              0.0   \n",
       "Green Park                                                    0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...            0.0   \n",
       "Saurashtra Cricket Association Stadium                        0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium              0.0   \n",
       "JSCA International Stadium Complex                            0.0   \n",
       "Brabourne Stadium                                             0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                    0.0   \n",
       "MA Chidambaram Stadium, Chepauk                               0.0   \n",
       "Sardar Patel Stadium, Motera                                  0.0   \n",
       "Barabati Stadium                                              0.0   \n",
       "Subrata Roy Sahara Stadium                                    0.0   \n",
       "Himachal Pradesh Cricket Association Stadium                  0.0   \n",
       "Dr DY Patil Sports Academy                                    0.0   \n",
       "Nehru Stadium                                                 0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                  0.0   \n",
       "New Wanderers Stadium                                         0.0   \n",
       "SuperSport Park                                               0.0   \n",
       "Kingsmead                                                     0.0   \n",
       "OUTsurance Oval                                               0.0   \n",
       "St George's Park                                              0.0   \n",
       "De Beers Diamond Oval                                         0.0   \n",
       "Buffalo Park                                                  0.0   \n",
       "Newlands                                                      0.0   \n",
       "\n",
       "                                                   Mumbai Indians  \\\n",
       "Narendra Modi Stadium, Ahmedabad                              0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                15.789474   \n",
       "Wankhede Stadium, Mumbai                                18.421053   \n",
       "M Chinnaswamy Stadium, Bengaluru                              0.0   \n",
       "Eden Gardens, Kolkata                                         0.0   \n",
       "Arun Jaitley Stadium, Delhi                             27.272727   \n",
       "Himachal Pradesh Cricket Association Stadium, D...            0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...      14.285714   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...            0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...           20.0   \n",
       "Barsapara Cricket Stadium, Guwahati                           0.0   \n",
       "Brabourne Stadium, Mumbai                               11.764706   \n",
       "Dr DY Patil Sports Academy, Mumbai                            5.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                 0.0   \n",
       "Dubai International Cricket Stadium                      6.521739   \n",
       "Sharjah Cricket Stadium                                 10.714286   \n",
       "Zayed Cricket Stadium, Abu Dhabi                             25.0   \n",
       "Sheikh Zayed Stadium                                    20.689655   \n",
       "Rajiv Gandhi International Stadium                      13.333333   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...      15.384615   \n",
       "MA Chidambaram Stadium                                  22.222222   \n",
       "Punjab Cricket Association IS Bindra Stadium                  0.0   \n",
       "Wankhede Stadium                                        56.164384   \n",
       "M.Chinnaswamy Stadium                                    6.666667   \n",
       "Arun Jaitley Stadium                                     7.142857   \n",
       "Eden Gardens                                            12.987013   \n",
       "Sawai Mansingh Stadium                                   4.255319   \n",
       "Maharashtra Cricket Association Stadium                  9.090909   \n",
       "Holkar Cricket Stadium                                  22.222222   \n",
       "Rajiv Gandhi International Stadium, Uppal               10.204082   \n",
       "M Chinnaswamy Stadium                                   12.307692   \n",
       "Feroz Shah Kotla                                              5.0   \n",
       "Green Park                                                    0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...       9.090909   \n",
       "Saurashtra Cricket Association Stadium                        0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium              0.0   \n",
       "JSCA International Stadium Complex                            0.0   \n",
       "Brabourne Stadium                                            50.0   \n",
       "Punjab Cricket Association Stadium, Mohali               8.571429   \n",
       "MA Chidambaram Stadium, Chepauk                              6.25   \n",
       "Sardar Patel Stadium, Motera                             8.333333   \n",
       "Barabati Stadium                                              0.0   \n",
       "Subrata Roy Sahara Stadium                                   12.5   \n",
       "Himachal Pradesh Cricket Association Stadium                  0.0   \n",
       "Dr DY Patil Sports Academy                              29.411765   \n",
       "Nehru Stadium                                                 0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                  0.0   \n",
       "New Wanderers Stadium                                         0.0   \n",
       "SuperSport Park                                          8.333333   \n",
       "Kingsmead                                                     0.0   \n",
       "OUTsurance Oval                                               0.0   \n",
       "St George's Park                                        28.571429   \n",
       "De Beers Diamond Oval                                         0.0   \n",
       "Buffalo Park                                            33.333333   \n",
       "Newlands                                                14.285714   \n",
       "\n",
       "                                                   Chennai Super Kings  \\\n",
       "Narendra Modi Stadium, Ahmedabad                                  6.25   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                     26.315789   \n",
       "Wankhede Stadium, Mumbai                                     13.157895   \n",
       "M Chinnaswamy Stadium, Bengaluru                             14.285714   \n",
       "Eden Gardens, Kolkata                                        11.111111   \n",
       "Arun Jaitley Stadium, Delhi                                  18.181818   \n",
       "Himachal Pradesh Cricket Association Stadium, D...                 0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...                 0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...                 0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                     0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                 0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                                0.0   \n",
       "Brabourne Stadium, Mumbai                                          0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                                15.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                 7.692308   \n",
       "Dubai International Cricket Stadium                          19.565217   \n",
       "Sharjah Cricket Stadium                                      10.714286   \n",
       "Zayed Cricket Stadium, Abu Dhabi                                  12.5   \n",
       "Sheikh Zayed Stadium                                         10.344828   \n",
       "Rajiv Gandhi International Stadium                            6.666667   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...           15.384615   \n",
       "MA Chidambaram Stadium                                       77.777778   \n",
       "Punjab Cricket Association IS Bindra Stadium                       0.0   \n",
       "Wankhede Stadium                                              9.589041   \n",
       "M.Chinnaswamy Stadium                                         6.666667   \n",
       "Arun Jaitley Stadium                                          7.142857   \n",
       "Eden Gardens                                                  6.493506   \n",
       "Sawai Mansingh Stadium                                        6.382979   \n",
       "Maharashtra Cricket Association Stadium                      22.727273   \n",
       "Holkar Cricket Stadium                                             0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                     4.081633   \n",
       "M Chinnaswamy Stadium                                         6.153846   \n",
       "Feroz Shah Kotla                                              8.333333   \n",
       "Green Park                                                         0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                 0.0   \n",
       "Saurashtra Cricket Association Stadium                             0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium                   0.0   \n",
       "JSCA International Stadium Complex                           42.857143   \n",
       "Brabourne Stadium                                                 10.0   \n",
       "Punjab Cricket Association Stadium, Mohali                    8.571429   \n",
       "MA Chidambaram Stadium, Chepauk                                  68.75   \n",
       "Sardar Patel Stadium, Motera                                       0.0   \n",
       "Barabati Stadium                                                   0.0   \n",
       "Subrata Roy Sahara Stadium                                        6.25   \n",
       "Himachal Pradesh Cricket Association Stadium                 11.111111   \n",
       "Dr DY Patil Sports Academy                                   17.647059   \n",
       "Nehru Stadium                                                      0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                       0.0   \n",
       "New Wanderers Stadium                                             12.5   \n",
       "SuperSport Park                                              16.666667   \n",
       "Kingsmead                                                     6.666667   \n",
       "OUTsurance Oval                                                    0.0   \n",
       "St George's Park                                             28.571429   \n",
       "De Beers Diamond Oval                                        33.333333   \n",
       "Buffalo Park                                                 33.333333   \n",
       "Newlands                                                           0.0   \n",
       "\n",
       "                                                   Sunrisers Hyderabad  \\\n",
       "Narendra Modi Stadium, Ahmedabad                                   0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                      5.263158   \n",
       "Wankhede Stadium, Mumbai                                      2.631579   \n",
       "M Chinnaswamy Stadium, Bengaluru                                   0.0   \n",
       "Eden Gardens, Kolkata                                        11.111111   \n",
       "Arun Jaitley Stadium, Delhi                                   9.090909   \n",
       "Himachal Pradesh Cricket Association Stadium, D...                 0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...           14.285714   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...                 0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                    20.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                 0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                                0.0   \n",
       "Brabourne Stadium, Mumbai                                    11.764706   \n",
       "Dr DY Patil Sports Academy, Mumbai                                15.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                      0.0   \n",
       "Dubai International Cricket Stadium                          15.217391   \n",
       "Sharjah Cricket Stadium                                       7.142857   \n",
       "Zayed Cricket Stadium, Abu Dhabi                                  12.5   \n",
       "Sheikh Zayed Stadium                                          6.896552   \n",
       "Rajiv Gandhi International Stadium                           66.666667   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...           23.076923   \n",
       "MA Chidambaram Stadium                                             0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                       0.0   \n",
       "Wankhede Stadium                                              1.369863   \n",
       "M.Chinnaswamy Stadium                                              0.0   \n",
       "Arun Jaitley Stadium                                         14.285714   \n",
       "Eden Gardens                                                  2.597403   \n",
       "Sawai Mansingh Stadium                                         2.12766   \n",
       "Maharashtra Cricket Association Stadium                       4.545455   \n",
       "Holkar Cricket Stadium                                             0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                     38.77551   \n",
       "M Chinnaswamy Stadium                                         3.076923   \n",
       "Feroz Shah Kotla                                              6.666667   \n",
       "Green Park                                                        25.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...           18.181818   \n",
       "Saurashtra Cricket Association Stadium                            10.0   \n",
       "Shaheed Veer Narayan Singh International Stadium             16.666667   \n",
       "JSCA International Stadium Complex                           14.285714   \n",
       "Brabourne Stadium                                                 10.0   \n",
       "Punjab Cricket Association Stadium, Mohali                    5.714286   \n",
       "MA Chidambaram Stadium, Chepauk                                    0.0   \n",
       "Sardar Patel Stadium, Motera                                  8.333333   \n",
       "Barabati Stadium                                                   0.0   \n",
       "Subrata Roy Sahara Stadium                                         0.0   \n",
       "Himachal Pradesh Cricket Association Stadium                       0.0   \n",
       "Dr DY Patil Sports Academy                                         0.0   \n",
       "Nehru Stadium                                                      0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                       0.0   \n",
       "New Wanderers Stadium                                              0.0   \n",
       "SuperSport Park                                                    0.0   \n",
       "Kingsmead                                                          0.0   \n",
       "OUTsurance Oval                                                    0.0   \n",
       "St George's Park                                                   0.0   \n",
       "De Beers Diamond Oval                                              0.0   \n",
       "Buffalo Park                                                       0.0   \n",
       "Newlands                                                           0.0   \n",
       "\n",
       "                                                   Royal Challengers Bangalore  \\\n",
       "Narendra Modi Stadium, Ahmedabad                                          6.25   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                             15.789474   \n",
       "Wankhede Stadium, Mumbai                                             13.157895   \n",
       "M Chinnaswamy Stadium, Bengaluru                                     42.857143   \n",
       "Eden Gardens, Kolkata                                                11.111111   \n",
       "Arun Jaitley Stadium, Delhi                                                0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...                         0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...                   14.285714   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...                   14.285714   \n",
       "Sawai Mansingh Stadium, Jaipur                                            20.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                        20.0   \n",
       "Barsapara Cricket Stadium, Guwahati                                        0.0   \n",
       "Brabourne Stadium, Mumbai                                                  0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                                        10.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                        15.384615   \n",
       "Dubai International Cricket Stadium                                  15.217391   \n",
       "Sharjah Cricket Stadium                                              10.714286   \n",
       "Zayed Cricket Stadium, Abu Dhabi                                           0.0   \n",
       "Sheikh Zayed Stadium                                                  6.896552   \n",
       "Rajiv Gandhi International Stadium                                         0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...                         0.0   \n",
       "MA Chidambaram Stadium                                                     0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                              10.0   \n",
       "Wankhede Stadium                                                      4.109589   \n",
       "M.Chinnaswamy Stadium                                                53.333333   \n",
       "Arun Jaitley Stadium                                                  7.142857   \n",
       "Eden Gardens                                                          5.194805   \n",
       "Sawai Mansingh Stadium                                                6.382979   \n",
       "Maharashtra Cricket Association Stadium                               9.090909   \n",
       "Holkar Cricket Stadium                                               11.111111   \n",
       "Rajiv Gandhi International Stadium, Uppal                             4.081633   \n",
       "M Chinnaswamy Stadium                                                43.076923   \n",
       "Feroz Shah Kotla                                                      8.333333   \n",
       "Green Park                                                                 0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                    9.090909   \n",
       "Saurashtra Cricket Association Stadium                                    10.0   \n",
       "Shaheed Veer Narayan Singh International Stadium                     16.666667   \n",
       "JSCA International Stadium Complex                                   14.285714   \n",
       "Brabourne Stadium                                                         10.0   \n",
       "Punjab Cricket Association Stadium, Mohali                            5.714286   \n",
       "MA Chidambaram Stadium, Chepauk                                       4.166667   \n",
       "Sardar Patel Stadium, Motera                                          8.333333   \n",
       "Barabati Stadium                                                           0.0   \n",
       "Subrata Roy Sahara Stadium                                                12.5   \n",
       "Himachal Pradesh Cricket Association Stadium                               0.0   \n",
       "Dr DY Patil Sports Academy                                            5.882353   \n",
       "Nehru Stadium                                                             20.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                               0.0   \n",
       "New Wanderers Stadium                                                     37.5   \n",
       "SuperSport Park                                                      16.666667   \n",
       "Kingsmead                                                                 20.0   \n",
       "OUTsurance Oval                                                            0.0   \n",
       "St George's Park                                                           0.0   \n",
       "De Beers Diamond Oval                                                      0.0   \n",
       "Buffalo Park                                                               0.0   \n",
       "Newlands                                                             14.285714   \n",
       "\n",
       "                                                   Lucknow Super Giants  \\\n",
       "Narendra Modi Stadium, Ahmedabad                                    0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                            0.0   \n",
       "Wankhede Stadium, Mumbai                                       5.263158   \n",
       "M Chinnaswamy Stadium, Bengaluru                              14.285714   \n",
       "Eden Gardens, Kolkata                                         11.111111   \n",
       "Arun Jaitley Stadium, Delhi                                         0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...                  0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...            14.285714   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...            42.857143   \n",
       "Sawai Mansingh Stadium, Jaipur                                     20.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                 20.0   \n",
       "Barsapara Cricket Stadium, Guwahati                                 0.0   \n",
       "Brabourne Stadium, Mumbai                                     11.764706   \n",
       "Dr DY Patil Sports Academy, Mumbai                                 15.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                 15.384615   \n",
       "Dubai International Cricket Stadium                                 0.0   \n",
       "Sharjah Cricket Stadium                                             0.0   \n",
       "Zayed Cricket Stadium, Abu Dhabi                                    0.0   \n",
       "Sheikh Zayed Stadium                                                0.0   \n",
       "Rajiv Gandhi International Stadium                                  0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...                  0.0   \n",
       "MA Chidambaram Stadium                                              0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                        0.0   \n",
       "Wankhede Stadium                                                    0.0   \n",
       "M.Chinnaswamy Stadium                                               0.0   \n",
       "Arun Jaitley Stadium                                                0.0   \n",
       "Eden Gardens                                                        0.0   \n",
       "Sawai Mansingh Stadium                                              0.0   \n",
       "Maharashtra Cricket Association Stadium                             0.0   \n",
       "Holkar Cricket Stadium                                              0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                           0.0   \n",
       "M Chinnaswamy Stadium                                               0.0   \n",
       "Feroz Shah Kotla                                                    0.0   \n",
       "Green Park                                                          0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                  0.0   \n",
       "Saurashtra Cricket Association Stadium                              0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium                    0.0   \n",
       "JSCA International Stadium Complex                                  0.0   \n",
       "Brabourne Stadium                                                   0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                          0.0   \n",
       "MA Chidambaram Stadium, Chepauk                                     0.0   \n",
       "Sardar Patel Stadium, Motera                                        0.0   \n",
       "Barabati Stadium                                                    0.0   \n",
       "Subrata Roy Sahara Stadium                                          0.0   \n",
       "Himachal Pradesh Cricket Association Stadium                        0.0   \n",
       "Dr DY Patil Sports Academy                                          0.0   \n",
       "Nehru Stadium                                                       0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                        0.0   \n",
       "New Wanderers Stadium                                               0.0   \n",
       "SuperSport Park                                                     0.0   \n",
       "Kingsmead                                                           0.0   \n",
       "OUTsurance Oval                                                     0.0   \n",
       "St George's Park                                                    0.0   \n",
       "De Beers Diamond Oval                                               0.0   \n",
       "Buffalo Park                                                        0.0   \n",
       "Newlands                                                            0.0   \n",
       "\n",
       "                                                   Punjab Kings  \\\n",
       "Narendra Modi Stadium, Ahmedabad                           6.25   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai              10.526316   \n",
       "Wankhede Stadium, Mumbai                              10.526316   \n",
       "M Chinnaswamy Stadium, Bengaluru                            0.0   \n",
       "Eden Gardens, Kolkata                                       0.0   \n",
       "Arun Jaitley Stadium, Delhi                            9.090909   \n",
       "Himachal Pradesh Cricket Association Stadium, D...          0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...          0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...    14.285714   \n",
       "Sawai Mansingh Stadium, Jaipur                              0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...         20.0   \n",
       "Barsapara Cricket Stadium, Guwahati                        50.0   \n",
       "Brabourne Stadium, Mumbai                             11.764706   \n",
       "Dr DY Patil Sports Academy, Mumbai                         10.0   \n",
       "Maharashtra Cricket Association Stadium, Pune          7.692308   \n",
       "Dubai International Cricket Stadium                    4.347826   \n",
       "Sharjah Cricket Stadium                                3.571429   \n",
       "Zayed Cricket Stadium, Abu Dhabi                            0.0   \n",
       "Sheikh Zayed Stadium                                        0.0   \n",
       "Rajiv Gandhi International Stadium                          0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...          0.0   \n",
       "MA Chidambaram Stadium                                      0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                0.0   \n",
       "Wankhede Stadium                                            0.0   \n",
       "M.Chinnaswamy Stadium                                       0.0   \n",
       "Arun Jaitley Stadium                                        0.0   \n",
       "Eden Gardens                                                0.0   \n",
       "Sawai Mansingh Stadium                                      0.0   \n",
       "Maharashtra Cricket Association Stadium                     0.0   \n",
       "Holkar Cricket Stadium                                      0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                   0.0   \n",
       "M Chinnaswamy Stadium                                       0.0   \n",
       "Feroz Shah Kotla                                            0.0   \n",
       "Green Park                                                  0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...          0.0   \n",
       "Saurashtra Cricket Association Stadium                      0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium            0.0   \n",
       "JSCA International Stadium Complex                          0.0   \n",
       "Brabourne Stadium                                           0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                  0.0   \n",
       "MA Chidambaram Stadium, Chepauk                             0.0   \n",
       "Sardar Patel Stadium, Motera                                0.0   \n",
       "Barabati Stadium                                            0.0   \n",
       "Subrata Roy Sahara Stadium                                  0.0   \n",
       "Himachal Pradesh Cricket Association Stadium                0.0   \n",
       "Dr DY Patil Sports Academy                                  0.0   \n",
       "Nehru Stadium                                               0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                0.0   \n",
       "New Wanderers Stadium                                       0.0   \n",
       "SuperSport Park                                             0.0   \n",
       "Kingsmead                                                   0.0   \n",
       "OUTsurance Oval                                             0.0   \n",
       "St George's Park                                            0.0   \n",
       "De Beers Diamond Oval                                       0.0   \n",
       "Buffalo Park                                                0.0   \n",
       "Newlands                                                    0.0   \n",
       "\n",
       "                                                   Delhi Capitals  \\\n",
       "Narendra Modi Stadium, Ahmedabad                            18.75   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                 5.263158   \n",
       "Wankhede Stadium, Mumbai                                 7.894737   \n",
       "M Chinnaswamy Stadium, Bengaluru                              0.0   \n",
       "Eden Gardens, Kolkata                                         0.0   \n",
       "Arun Jaitley Stadium, Delhi                             18.181818   \n",
       "Himachal Pradesh Cricket Association Stadium, D...           50.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...      14.285714   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...            0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...            0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                           0.0   \n",
       "Brabourne Stadium, Mumbai                               23.529412   \n",
       "Dr DY Patil Sports Academy, Mumbai                           10.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                 0.0   \n",
       "Dubai International Cricket Stadium                     10.869565   \n",
       "Sharjah Cricket Stadium                                 14.285714   \n",
       "Zayed Cricket Stadium, Abu Dhabi                             12.5   \n",
       "Sheikh Zayed Stadium                                     6.896552   \n",
       "Rajiv Gandhi International Stadium                       6.666667   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...       7.692308   \n",
       "MA Chidambaram Stadium                                        0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                  0.0   \n",
       "Wankhede Stadium                                         1.369863   \n",
       "M.Chinnaswamy Stadium                                    6.666667   \n",
       "Arun Jaitley Stadium                                    21.428571   \n",
       "Eden Gardens                                             1.298701   \n",
       "Sawai Mansingh Stadium                                    2.12766   \n",
       "Maharashtra Cricket Association Stadium                       0.0   \n",
       "Holkar Cricket Stadium                                        0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                     0.0   \n",
       "M Chinnaswamy Stadium                                         0.0   \n",
       "Feroz Shah Kotla                                              0.0   \n",
       "Green Park                                                    0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...            0.0   \n",
       "Saurashtra Cricket Association Stadium                        0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium              0.0   \n",
       "JSCA International Stadium Complex                            0.0   \n",
       "Brabourne Stadium                                             0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                    0.0   \n",
       "MA Chidambaram Stadium, Chepauk                               0.0   \n",
       "Sardar Patel Stadium, Motera                                  0.0   \n",
       "Barabati Stadium                                              0.0   \n",
       "Subrata Roy Sahara Stadium                                    0.0   \n",
       "Himachal Pradesh Cricket Association Stadium                  0.0   \n",
       "Dr DY Patil Sports Academy                                    0.0   \n",
       "Nehru Stadium                                                 0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                  0.0   \n",
       "New Wanderers Stadium                                         0.0   \n",
       "SuperSport Park                                               0.0   \n",
       "Kingsmead                                                     0.0   \n",
       "OUTsurance Oval                                               0.0   \n",
       "St George's Park                                              0.0   \n",
       "De Beers Diamond Oval                                         0.0   \n",
       "Buffalo Park                                                  0.0   \n",
       "Newlands                                                      0.0   \n",
       "\n",
       "                                                   Kolkata Knight Riders  \\\n",
       "Narendra Modi Stadium, Ahmedabad                                    12.5   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                       10.526316   \n",
       "Wankhede Stadium, Mumbai                                        7.894737   \n",
       "M Chinnaswamy Stadium, Bengaluru                               14.285714   \n",
       "Eden Gardens, Kolkata                                          22.222222   \n",
       "Arun Jaitley Stadium, Delhi                                          0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...                   0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...             14.285714   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...                   0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                       0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                   0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                                  0.0   \n",
       "Brabourne Stadium, Mumbai                                            0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                                   5.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                  15.384615   \n",
       "Dubai International Cricket Stadium                             6.521739   \n",
       "Sharjah Cricket Stadium                                        17.857143   \n",
       "Zayed Cricket Stadium, Abu Dhabi                                    25.0   \n",
       "Sheikh Zayed Stadium                                           17.241379   \n",
       "Rajiv Gandhi International Stadium                              6.666667   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...                   0.0   \n",
       "MA Chidambaram Stadium                                               0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                        10.0   \n",
       "Wankhede Stadium                                                1.369863   \n",
       "M.Chinnaswamy Stadium                                          13.333333   \n",
       "Arun Jaitley Stadium                                                 0.0   \n",
       "Eden Gardens                                                   58.441558   \n",
       "Sawai Mansingh Stadium                                          6.382979   \n",
       "Maharashtra Cricket Association Stadium                        13.636364   \n",
       "Holkar Cricket Stadium                                         11.111111   \n",
       "Rajiv Gandhi International Stadium, Uppal                       8.163265   \n",
       "M Chinnaswamy Stadium                                           9.230769   \n",
       "Feroz Shah Kotla                                                8.333333   \n",
       "Green Park                                                           0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...              9.090909   \n",
       "Saurashtra Cricket Association Stadium                              10.0   \n",
       "Shaheed Veer Narayan Singh International Stadium                     0.0   \n",
       "JSCA International Stadium Complex                             14.285714   \n",
       "Brabourne Stadium                                                    0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                      5.714286   \n",
       "MA Chidambaram Stadium, Chepauk                                 4.166667   \n",
       "Sardar Patel Stadium, Motera                                         0.0   \n",
       "Barabati Stadium                                               42.857143   \n",
       "Subrata Roy Sahara Stadium                                         18.75   \n",
       "Himachal Pradesh Cricket Association Stadium                         0.0   \n",
       "Dr DY Patil Sports Academy                                     11.764706   \n",
       "Nehru Stadium                                                        0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                         0.0   \n",
       "New Wanderers Stadium                                                0.0   \n",
       "SuperSport Park                                                 8.333333   \n",
       "Kingsmead                                                      13.333333   \n",
       "OUTsurance Oval                                                      0.0   \n",
       "St George's Park                                                     0.0   \n",
       "De Beers Diamond Oval                                                0.0   \n",
       "Buffalo Park                                                         0.0   \n",
       "Newlands                                                             0.0   \n",
       "\n",
       "                                                   Rajasthan Royals  \\\n",
       "Narendra Modi Stadium, Ahmedabad                               12.5   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                   5.263158   \n",
       "Wankhede Stadium, Mumbai                                  13.157895   \n",
       "M Chinnaswamy Stadium, Bengaluru                                0.0   \n",
       "Eden Gardens, Kolkata                                     11.111111   \n",
       "Arun Jaitley Stadium, Delhi                                9.090909   \n",
       "Himachal Pradesh Cricket Association Stadium, D...             50.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...        14.285714   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...              0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                 20.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...              0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                            50.0   \n",
       "Brabourne Stadium, Mumbai                                 17.647059   \n",
       "Dr DY Patil Sports Academy, Mumbai                              5.0   \n",
       "Maharashtra Cricket Association Stadium, Pune             15.384615   \n",
       "Dubai International Cricket Stadium                        4.347826   \n",
       "Sharjah Cricket Stadium                                    7.142857   \n",
       "Zayed Cricket Stadium, Abu Dhabi                               12.5   \n",
       "Sheikh Zayed Stadium                                      17.241379   \n",
       "Rajiv Gandhi International Stadium                              0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...         7.692308   \n",
       "MA Chidambaram Stadium                                          0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                    0.0   \n",
       "Wankhede Stadium                                           5.479452   \n",
       "M.Chinnaswamy Stadium                                      6.666667   \n",
       "Arun Jaitley Stadium                                            0.0   \n",
       "Eden Gardens                                               2.597403   \n",
       "Sawai Mansingh Stadium                                    68.085106   \n",
       "Maharashtra Cricket Association Stadium                    4.545455   \n",
       "Holkar Cricket Stadium                                          0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                  4.081633   \n",
       "M Chinnaswamy Stadium                                      4.615385   \n",
       "Feroz Shah Kotla                                           6.666667   \n",
       "Green Park                                                      0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...              0.0   \n",
       "Saurashtra Cricket Association Stadium                          0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium                0.0   \n",
       "JSCA International Stadium Complex                              0.0   \n",
       "Brabourne Stadium                                              20.0   \n",
       "Punjab Cricket Association Stadium, Mohali                 8.571429   \n",
       "MA Chidambaram Stadium, Chepauk                            2.083333   \n",
       "Sardar Patel Stadium, Motera                              58.333333   \n",
       "Barabati Stadium                                                0.0   \n",
       "Subrata Roy Sahara Stadium                                     6.25   \n",
       "Himachal Pradesh Cricket Association Stadium                    0.0   \n",
       "Dr DY Patil Sports Academy                                 5.882353   \n",
       "Nehru Stadium                                                   0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha              33.333333   \n",
       "New Wanderers Stadium                                           0.0   \n",
       "SuperSport Park                                           16.666667   \n",
       "Kingsmead                                                 13.333333   \n",
       "OUTsurance Oval                                                 0.0   \n",
       "St George's Park                                          14.285714   \n",
       "De Beers Diamond Oval                                           0.0   \n",
       "Buffalo Park                                                    0.0   \n",
       "Newlands                                                        0.0   \n",
       "\n",
       "                                                   Kings XI Punjab  \\\n",
       "Narendra Modi Stadium, Ahmedabad                               0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                       0.0   \n",
       "Wankhede Stadium, Mumbai                                       0.0   \n",
       "M Chinnaswamy Stadium, Bengaluru                               0.0   \n",
       "Eden Gardens, Kolkata                                          0.0   \n",
       "Arun Jaitley Stadium, Delhi                                    0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...             0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...             0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...             0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                 0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...             0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                            0.0   \n",
       "Brabourne Stadium, Mumbai                                      0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                             0.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                  0.0   \n",
       "Dubai International Cricket Stadium                       8.695652   \n",
       "Sharjah Cricket Stadium                                  14.285714   \n",
       "Zayed Cricket Stadium, Abu Dhabi                               0.0   \n",
       "Sheikh Zayed Stadium                                      6.896552   \n",
       "Rajiv Gandhi International Stadium                             0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...        7.692308   \n",
       "MA Chidambaram Stadium                                         0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                  80.0   \n",
       "Wankhede Stadium                                          6.849315   \n",
       "M.Chinnaswamy Stadium                                          0.0   \n",
       "Arun Jaitley Stadium                                      7.142857   \n",
       "Eden Gardens                                              3.896104   \n",
       "Sawai Mansingh Stadium                                     2.12766   \n",
       "Maharashtra Cricket Association Stadium                        0.0   \n",
       "Holkar Cricket Stadium                                   44.444444   \n",
       "Rajiv Gandhi International Stadium, Uppal                 8.163265   \n",
       "M Chinnaswamy Stadium                                     7.692308   \n",
       "Feroz Shah Kotla                                          6.666667   \n",
       "Green Park                                                     0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...       36.363636   \n",
       "Saurashtra Cricket Association Stadium                        20.0   \n",
       "Shaheed Veer Narayan Singh International Stadium               0.0   \n",
       "JSCA International Stadium Complex                             0.0   \n",
       "Brabourne Stadium                                              0.0   \n",
       "Punjab Cricket Association Stadium, Mohali               51.428571   \n",
       "MA Chidambaram Stadium, Chepauk                           2.083333   \n",
       "Sardar Patel Stadium, Motera                                   0.0   \n",
       "Barabati Stadium                                         14.285714   \n",
       "Subrata Roy Sahara Stadium                                    6.25   \n",
       "Himachal Pradesh Cricket Association Stadium             55.555556   \n",
       "Dr DY Patil Sports Academy                                     0.0   \n",
       "Nehru Stadium                                                  0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                   0.0   \n",
       "New Wanderers Stadium                                         12.5   \n",
       "SuperSport Park                                                0.0   \n",
       "Kingsmead                                                13.333333   \n",
       "OUTsurance Oval                                               50.0   \n",
       "St George's Park                                         14.285714   \n",
       "De Beers Diamond Oval                                    33.333333   \n",
       "Buffalo Park                                                   0.0   \n",
       "Newlands                                                 14.285714   \n",
       "\n",
       "                                                   Delhi Daredevils  \\\n",
       "Narendra Modi Stadium, Ahmedabad                                0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                        0.0   \n",
       "Wankhede Stadium, Mumbai                                        0.0   \n",
       "M Chinnaswamy Stadium, Bengaluru                                0.0   \n",
       "Eden Gardens, Kolkata                                           0.0   \n",
       "Arun Jaitley Stadium, Delhi                                     0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...              0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...              0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...              0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                  0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...              0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                             0.0   \n",
       "Brabourne Stadium, Mumbai                                       0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                              0.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                   0.0   \n",
       "Dubai International Cricket Stadium                        2.173913   \n",
       "Sharjah Cricket Stadium                                    3.571429   \n",
       "Zayed Cricket Stadium, Abu Dhabi                                0.0   \n",
       "Sheikh Zayed Stadium                                            0.0   \n",
       "Rajiv Gandhi International Stadium                              0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...         7.692308   \n",
       "MA Chidambaram Stadium                                          0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                    0.0   \n",
       "Wankhede Stadium                                           2.739726   \n",
       "M.Chinnaswamy Stadium                                           0.0   \n",
       "Arun Jaitley Stadium                                      28.571429   \n",
       "Eden Gardens                                               1.298701   \n",
       "Sawai Mansingh Stadium                                      2.12766   \n",
       "Maharashtra Cricket Association Stadium                    9.090909   \n",
       "Holkar Cricket Stadium                                          0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                  8.163265   \n",
       "M Chinnaswamy Stadium                                      4.615385   \n",
       "Feroz Shah Kotla                                          38.333333   \n",
       "Green Park                                                     25.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...              0.0   \n",
       "Saurashtra Cricket Association Stadium                         10.0   \n",
       "Shaheed Veer Narayan Singh International Stadium          66.666667   \n",
       "JSCA International Stadium Complex                              0.0   \n",
       "Brabourne Stadium                                               0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                 2.857143   \n",
       "MA Chidambaram Stadium, Chepauk                            4.166667   \n",
       "Sardar Patel Stadium, Motera                               8.333333   \n",
       "Barabati Stadium                                                0.0   \n",
       "Subrata Roy Sahara Stadium                                     6.25   \n",
       "Himachal Pradesh Cricket Association Stadium              11.111111   \n",
       "Dr DY Patil Sports Academy                                 5.882353   \n",
       "Nehru Stadium                                                  20.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                    0.0   \n",
       "New Wanderers Stadium                                          12.5   \n",
       "SuperSport Park                                           16.666667   \n",
       "Kingsmead                                                      20.0   \n",
       "OUTsurance Oval                                                50.0   \n",
       "St George's Park                                          14.285714   \n",
       "De Beers Diamond Oval                                           0.0   \n",
       "Buffalo Park                                              33.333333   \n",
       "Newlands                                                  14.285714   \n",
       "\n",
       "                                                   Rising Pune Supergiant  \\\n",
       "Narendra Modi Stadium, Ahmedabad                                      0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                              0.0   \n",
       "Wankhede Stadium, Mumbai                                              0.0   \n",
       "M Chinnaswamy Stadium, Bengaluru                                      0.0   \n",
       "Eden Gardens, Kolkata                                                 0.0   \n",
       "Arun Jaitley Stadium, Delhi                                           0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...                    0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...                    0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...                    0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                        0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                    0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                                   0.0   \n",
       "Brabourne Stadium, Mumbai                                             0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                                    0.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                         0.0   \n",
       "Dubai International Cricket Stadium                                   0.0   \n",
       "Sharjah Cricket Stadium                                               0.0   \n",
       "Zayed Cricket Stadium, Abu Dhabi                                      0.0   \n",
       "Sheikh Zayed Stadium                                                  0.0   \n",
       "Rajiv Gandhi International Stadium                                    0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...                    0.0   \n",
       "MA Chidambaram Stadium                                                0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                          0.0   \n",
       "Wankhede Stadium                                                 2.739726   \n",
       "M.Chinnaswamy Stadium                                                 0.0   \n",
       "Arun Jaitley Stadium                                                  0.0   \n",
       "Eden Gardens                                                     1.298701   \n",
       "Sawai Mansingh Stadium                                                0.0   \n",
       "Maharashtra Cricket Association Stadium                         22.727273   \n",
       "Holkar Cricket Stadium                                                0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                        2.040816   \n",
       "M Chinnaswamy Stadium                                            1.538462   \n",
       "Feroz Shah Kotla                                                      0.0   \n",
       "Green Park                                                            0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                    0.0   \n",
       "Saurashtra Cricket Association Stadium                                0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium                      0.0   \n",
       "JSCA International Stadium Complex                                    0.0   \n",
       "Brabourne Stadium                                                     0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                            0.0   \n",
       "MA Chidambaram Stadium, Chepauk                                       0.0   \n",
       "Sardar Patel Stadium, Motera                                          0.0   \n",
       "Barabati Stadium                                                      0.0   \n",
       "Subrata Roy Sahara Stadium                                            0.0   \n",
       "Himachal Pradesh Cricket Association Stadium                          0.0   \n",
       "Dr DY Patil Sports Academy                                            0.0   \n",
       "Nehru Stadium                                                         0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                          0.0   \n",
       "New Wanderers Stadium                                                 0.0   \n",
       "SuperSport Park                                                       0.0   \n",
       "Kingsmead                                                             0.0   \n",
       "OUTsurance Oval                                                       0.0   \n",
       "St George's Park                                                      0.0   \n",
       "De Beers Diamond Oval                                                 0.0   \n",
       "Buffalo Park                                                          0.0   \n",
       "Newlands                                                              0.0   \n",
       "\n",
       "                                                   Gujarat Lions  \\\n",
       "Narendra Modi Stadium, Ahmedabad                             0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                     0.0   \n",
       "Wankhede Stadium, Mumbai                                     0.0   \n",
       "M Chinnaswamy Stadium, Bengaluru                             0.0   \n",
       "Eden Gardens, Kolkata                                        0.0   \n",
       "Arun Jaitley Stadium, Delhi                                  0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...           0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...           0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...           0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                               0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...           0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                          0.0   \n",
       "Brabourne Stadium, Mumbai                                    0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                           0.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                0.0   \n",
       "Dubai International Cricket Stadium                          0.0   \n",
       "Sharjah Cricket Stadium                                      0.0   \n",
       "Zayed Cricket Stadium, Abu Dhabi                             0.0   \n",
       "Sheikh Zayed Stadium                                         0.0   \n",
       "Rajiv Gandhi International Stadium                           0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...           0.0   \n",
       "MA Chidambaram Stadium                                       0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                 0.0   \n",
       "Wankhede Stadium                                        1.369863   \n",
       "M.Chinnaswamy Stadium                                        0.0   \n",
       "Arun Jaitley Stadium                                         0.0   \n",
       "Eden Gardens                                            2.597403   \n",
       "Sawai Mansingh Stadium                                       0.0   \n",
       "Maharashtra Cricket Association Stadium                 4.545455   \n",
       "Holkar Cricket Stadium                                       0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                    0.0   \n",
       "M Chinnaswamy Stadium                                   1.538462   \n",
       "Feroz Shah Kotla                                        1.666667   \n",
       "Green Park                                                  50.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...     18.181818   \n",
       "Saurashtra Cricket Association Stadium                      30.0   \n",
       "Shaheed Veer Narayan Singh International Stadium             0.0   \n",
       "JSCA International Stadium Complex                           0.0   \n",
       "Brabourne Stadium                                            0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                   0.0   \n",
       "MA Chidambaram Stadium, Chepauk                              0.0   \n",
       "Sardar Patel Stadium, Motera                                 0.0   \n",
       "Barabati Stadium                                             0.0   \n",
       "Subrata Roy Sahara Stadium                                   0.0   \n",
       "Himachal Pradesh Cricket Association Stadium                 0.0   \n",
       "Dr DY Patil Sports Academy                                   0.0   \n",
       "Nehru Stadium                                                0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                 0.0   \n",
       "New Wanderers Stadium                                        0.0   \n",
       "SuperSport Park                                              0.0   \n",
       "Kingsmead                                                    0.0   \n",
       "OUTsurance Oval                                              0.0   \n",
       "St George's Park                                             0.0   \n",
       "De Beers Diamond Oval                                        0.0   \n",
       "Buffalo Park                                                 0.0   \n",
       "Newlands                                                     0.0   \n",
       "\n",
       "                                                   Rising Pune Supergiants  \\\n",
       "Narendra Modi Stadium, Ahmedabad                                       0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                               0.0   \n",
       "Wankhede Stadium, Mumbai                                               0.0   \n",
       "M Chinnaswamy Stadium, Bengaluru                                       0.0   \n",
       "Eden Gardens, Kolkata                                                  0.0   \n",
       "Arun Jaitley Stadium, Delhi                                            0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...                     0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...                     0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...                     0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                         0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                     0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                                    0.0   \n",
       "Brabourne Stadium, Mumbai                                              0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                                     0.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                          0.0   \n",
       "Dubai International Cricket Stadium                                    0.0   \n",
       "Sharjah Cricket Stadium                                                0.0   \n",
       "Zayed Cricket Stadium, Abu Dhabi                                       0.0   \n",
       "Sheikh Zayed Stadium                                                   0.0   \n",
       "Rajiv Gandhi International Stadium                                     0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...               15.384615   \n",
       "MA Chidambaram Stadium                                                 0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                           0.0   \n",
       "Wankhede Stadium                                                  1.369863   \n",
       "M.Chinnaswamy Stadium                                                  0.0   \n",
       "Arun Jaitley Stadium                                                   0.0   \n",
       "Eden Gardens                                                           0.0   \n",
       "Sawai Mansingh Stadium                                                 0.0   \n",
       "Maharashtra Cricket Association Stadium                                0.0   \n",
       "Holkar Cricket Stadium                                                 0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                         2.040816   \n",
       "M Chinnaswamy Stadium                                                  0.0   \n",
       "Feroz Shah Kotla                                                  1.666667   \n",
       "Green Park                                                             0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                     0.0   \n",
       "Saurashtra Cricket Association Stadium                                 0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium                       0.0   \n",
       "JSCA International Stadium Complex                                     0.0   \n",
       "Brabourne Stadium                                                      0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                             0.0   \n",
       "MA Chidambaram Stadium, Chepauk                                        0.0   \n",
       "Sardar Patel Stadium, Motera                                           0.0   \n",
       "Barabati Stadium                                                       0.0   \n",
       "Subrata Roy Sahara Stadium                                             0.0   \n",
       "Himachal Pradesh Cricket Association Stadium                           0.0   \n",
       "Dr DY Patil Sports Academy                                             0.0   \n",
       "Nehru Stadium                                                          0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                           0.0   \n",
       "New Wanderers Stadium                                                  0.0   \n",
       "SuperSport Park                                                        0.0   \n",
       "Kingsmead                                                              0.0   \n",
       "OUTsurance Oval                                                        0.0   \n",
       "St George's Park                                                       0.0   \n",
       "De Beers Diamond Oval                                                  0.0   \n",
       "Buffalo Park                                                           0.0   \n",
       "Newlands                                                               0.0   \n",
       "\n",
       "                                                   Pune Warriors  \\\n",
       "Narendra Modi Stadium, Ahmedabad                             0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                     0.0   \n",
       "Wankhede Stadium, Mumbai                                     0.0   \n",
       "M Chinnaswamy Stadium, Bengaluru                             0.0   \n",
       "Eden Gardens, Kolkata                                        0.0   \n",
       "Arun Jaitley Stadium, Delhi                                  0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...           0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...           0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...           0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                               0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...           0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                          0.0   \n",
       "Brabourne Stadium, Mumbai                                    0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                           0.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                0.0   \n",
       "Dubai International Cricket Stadium                          0.0   \n",
       "Sharjah Cricket Stadium                                      0.0   \n",
       "Zayed Cricket Stadium, Abu Dhabi                             0.0   \n",
       "Sheikh Zayed Stadium                                         0.0   \n",
       "Rajiv Gandhi International Stadium                           0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...           0.0   \n",
       "MA Chidambaram Stadium                                       0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                 0.0   \n",
       "Wankhede Stadium                                        1.369863   \n",
       "M.Chinnaswamy Stadium                                        0.0   \n",
       "Arun Jaitley Stadium                                         0.0   \n",
       "Eden Gardens                                                 0.0   \n",
       "Sawai Mansingh Stadium                                       0.0   \n",
       "Maharashtra Cricket Association Stadium                      0.0   \n",
       "Holkar Cricket Stadium                                       0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal               2.040816   \n",
       "M Chinnaswamy Stadium                                        0.0   \n",
       "Feroz Shah Kotla                                        1.666667   \n",
       "Green Park                                                   0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...           0.0   \n",
       "Saurashtra Cricket Association Stadium                       0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium             0.0   \n",
       "JSCA International Stadium Complex                     14.285714   \n",
       "Brabourne Stadium                                            0.0   \n",
       "Punjab Cricket Association Stadium, Mohali              2.857143   \n",
       "MA Chidambaram Stadium, Chepauk                         2.083333   \n",
       "Sardar Patel Stadium, Motera                                 0.0   \n",
       "Barabati Stadium                                             0.0   \n",
       "Subrata Roy Sahara Stadium                                  25.0   \n",
       "Himachal Pradesh Cricket Association Stadium                 0.0   \n",
       "Dr DY Patil Sports Academy                             11.764706   \n",
       "Nehru Stadium                                                0.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha                 0.0   \n",
       "New Wanderers Stadium                                        0.0   \n",
       "SuperSport Park                                              0.0   \n",
       "Kingsmead                                                    0.0   \n",
       "OUTsurance Oval                                              0.0   \n",
       "St George's Park                                             0.0   \n",
       "De Beers Diamond Oval                                        0.0   \n",
       "Buffalo Park                                                 0.0   \n",
       "Newlands                                                     0.0   \n",
       "\n",
       "                                                   Deccan Chargers  \\\n",
       "Narendra Modi Stadium, Ahmedabad                               0.0   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                       0.0   \n",
       "Wankhede Stadium, Mumbai                                       0.0   \n",
       "M Chinnaswamy Stadium, Bengaluru                               0.0   \n",
       "Eden Gardens, Kolkata                                          0.0   \n",
       "Arun Jaitley Stadium, Delhi                                    0.0   \n",
       "Himachal Pradesh Cricket Association Stadium, D...             0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...             0.0   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...             0.0   \n",
       "Sawai Mansingh Stadium, Jaipur                                 0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...             0.0   \n",
       "Barsapara Cricket Stadium, Guwahati                            0.0   \n",
       "Brabourne Stadium, Mumbai                                      0.0   \n",
       "Dr DY Patil Sports Academy, Mumbai                             0.0   \n",
       "Maharashtra Cricket Association Stadium, Pune                  0.0   \n",
       "Dubai International Cricket Stadium                            0.0   \n",
       "Sharjah Cricket Stadium                                        0.0   \n",
       "Zayed Cricket Stadium, Abu Dhabi                               0.0   \n",
       "Sheikh Zayed Stadium                                           0.0   \n",
       "Rajiv Gandhi International Stadium                             0.0   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...             0.0   \n",
       "MA Chidambaram Stadium                                         0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium                   0.0   \n",
       "Wankhede Stadium                                          1.369863   \n",
       "M.Chinnaswamy Stadium                                          0.0   \n",
       "Arun Jaitley Stadium                                           0.0   \n",
       "Eden Gardens                                                   0.0   \n",
       "Sawai Mansingh Stadium                                         0.0   \n",
       "Maharashtra Cricket Association Stadium                        0.0   \n",
       "Holkar Cricket Stadium                                         0.0   \n",
       "Rajiv Gandhi International Stadium, Uppal                 6.122449   \n",
       "M Chinnaswamy Stadium                                     1.538462   \n",
       "Feroz Shah Kotla                                          3.333333   \n",
       "Green Park                                                     0.0   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...             0.0   \n",
       "Saurashtra Cricket Association Stadium                         0.0   \n",
       "Shaheed Veer Narayan Singh International Stadium               0.0   \n",
       "JSCA International Stadium Complex                             0.0   \n",
       "Brabourne Stadium                                              0.0   \n",
       "Punjab Cricket Association Stadium, Mohali                     0.0   \n",
       "MA Chidambaram Stadium, Chepauk                           4.166667   \n",
       "Sardar Patel Stadium, Motera                                   0.0   \n",
       "Barabati Stadium                                         42.857143   \n",
       "Subrata Roy Sahara Stadium                                    6.25   \n",
       "Himachal Pradesh Cricket Association Stadium             22.222222   \n",
       "Dr DY Patil Sports Academy                               11.764706   \n",
       "Nehru Stadium                                                 20.0   \n",
       "Vidarbha Cricket Association Stadium, Jamtha             66.666667   \n",
       "New Wanderers Stadium                                         25.0   \n",
       "SuperSport Park                                          16.666667   \n",
       "Kingsmead                                                13.333333   \n",
       "OUTsurance Oval                                                0.0   \n",
       "St George's Park                                               0.0   \n",
       "De Beers Diamond Oval                                    33.333333   \n",
       "Buffalo Park                                                   0.0   \n",
       "Newlands                                                 28.571429   \n",
       "\n",
       "                                                   Kochi Tuskers Kerala  \n",
       "Narendra Modi Stadium, Ahmedabad                                    0.0  \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                            0.0  \n",
       "Wankhede Stadium, Mumbai                                            0.0  \n",
       "M Chinnaswamy Stadium, Bengaluru                                    0.0  \n",
       "Eden Gardens, Kolkata                                               0.0  \n",
       "Arun Jaitley Stadium, Delhi                                         0.0  \n",
       "Himachal Pradesh Cricket Association Stadium, D...                  0.0  \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...                  0.0  \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...                  0.0  \n",
       "Sawai Mansingh Stadium, Jaipur                                      0.0  \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                  0.0  \n",
       "Barsapara Cricket Stadium, Guwahati                                 0.0  \n",
       "Brabourne Stadium, Mumbai                                           0.0  \n",
       "Dr DY Patil Sports Academy, Mumbai                                  0.0  \n",
       "Maharashtra Cricket Association Stadium, Pune                       0.0  \n",
       "Dubai International Cricket Stadium                                 0.0  \n",
       "Sharjah Cricket Stadium                                             0.0  \n",
       "Zayed Cricket Stadium, Abu Dhabi                                    0.0  \n",
       "Sheikh Zayed Stadium                                                0.0  \n",
       "Rajiv Gandhi International Stadium                                  0.0  \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...                  0.0  \n",
       "MA Chidambaram Stadium                                              0.0  \n",
       "Punjab Cricket Association IS Bindra Stadium                        0.0  \n",
       "Wankhede Stadium                                               1.369863  \n",
       "M.Chinnaswamy Stadium                                               0.0  \n",
       "Arun Jaitley Stadium                                                0.0  \n",
       "Eden Gardens                                                   1.298701  \n",
       "Sawai Mansingh Stadium                                              0.0  \n",
       "Maharashtra Cricket Association Stadium                             0.0  \n",
       "Holkar Cricket Stadium                                        11.111111  \n",
       "Rajiv Gandhi International Stadium, Uppal                           0.0  \n",
       "M Chinnaswamy Stadium                                               0.0  \n",
       "Feroz Shah Kotla                                               1.666667  \n",
       "Green Park                                                          0.0  \n",
       "Punjab Cricket Association IS Bindra Stadium, M...                  0.0  \n",
       "Saurashtra Cricket Association Stadium                              0.0  \n",
       "Shaheed Veer Narayan Singh International Stadium                    0.0  \n",
       "JSCA International Stadium Complex                                  0.0  \n",
       "Brabourne Stadium                                                   0.0  \n",
       "Punjab Cricket Association Stadium, Mohali                          0.0  \n",
       "MA Chidambaram Stadium, Chepauk                                     0.0  \n",
       "Sardar Patel Stadium, Motera                                        0.0  \n",
       "Barabati Stadium                                                    0.0  \n",
       "Subrata Roy Sahara Stadium                                          0.0  \n",
       "Himachal Pradesh Cricket Association Stadium                        0.0  \n",
       "Dr DY Patil Sports Academy                                          0.0  \n",
       "Nehru Stadium                                                      40.0  \n",
       "Vidarbha Cricket Association Stadium, Jamtha                        0.0  \n",
       "New Wanderers Stadium                                               0.0  \n",
       "SuperSport Park                                                     0.0  \n",
       "Kingsmead                                                           0.0  \n",
       "OUTsurance Oval                                                     0.0  \n",
       "St George's Park                                                    0.0  \n",
       "De Beers Diamond Oval                                               0.0  \n",
       "Buffalo Park                                                        0.0  \n",
       "Newlands                                                            0.0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the total number of matches played at each venue\n",
    "venue_match_counts = match_info_data['venue'].value_counts()\n",
    "\n",
    "# Create an empty DataFrame to store win percentages\n",
    "venue_win_percentages = pd.DataFrame(index=match_info_data['venue'].unique(), columns=match_info_data['team1'].unique())\n",
    "\n",
    "# Calculate the number of matches won by each team at each venue\n",
    "for venue in venue_win_percentages.index:\n",
    "    venue_matches = match_info_data[match_info_data['venue'] == venue]\n",
    "    for team in venue_win_percentages.columns:\n",
    "        venue_win_percentages.at[venue, team] = venue_matches[(venue_matches['winner'] == team)].shape[0]\n",
    "\n",
    "# Calculate win percentages\n",
    "for venue in venue_win_percentages.index:\n",
    "    venue_win_percentages.loc[venue] = venue_win_percentages.loc[venue] / venue_match_counts[venue] * 100\n",
    "\n",
    "# Analyze the win percentages to identify venues where teams tend to perform better or worse\n",
    "print(\"Win percentages at different venues:\")\n",
    "print(\"-\"*70)\n",
    "venue_win_percentages\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9199db2",
   "metadata": {
    "papermill": {
     "duration": 0.033252,
     "end_time": "2024-04-05T18:34:57.482768",
     "exception": false,
     "start_time": "2024-04-05T18:34:57.449516",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "How does the average winning margin vary across different venues?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "791768c9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:57.550707Z",
     "iopub.status.busy": "2024-04-05T18:34:57.550363Z",
     "iopub.status.idle": "2024-04-05T18:34:57.575251Z",
     "shell.execute_reply": "2024-04-05T18:34:57.574057Z"
    },
    "papermill": {
     "duration": 0.062608,
     "end_time": "2024-04-05T18:34:57.578697",
     "exception": false,
     "start_time": "2024-04-05T18:34:57.516089",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Winning Margin Across Different Venues:\n",
      "----------------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>venue</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Arun Jaitley Stadium</th>\n",
       "      <td>11.714286</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arun Jaitley Stadium, Delhi</th>\n",
       "      <td>15.636364</td>\n",
       "      <td>3.727273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barabati Stadium</th>\n",
       "      <td>10.428571</td>\n",
       "      <td>2.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barsapara Cricket Stadium, Guwahati</th>\n",
       "      <td>31.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cricket Stadium, Lucknow</th>\n",
       "      <td>11.428571</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brabourne Stadium</th>\n",
       "      <td>13.600000</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brabourne Stadium, Mumbai</th>\n",
       "      <td>13.352941</td>\n",
       "      <td>3.352941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Buffalo Park</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>2.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>De Beers Diamond Oval</th>\n",
       "      <td>17.666667</td>\n",
       "      <td>3.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr DY Patil Sports Academy</th>\n",
       "      <td>11.588235</td>\n",
       "      <td>3.764706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr DY Patil Sports Academy, Mumbai</th>\n",
       "      <td>14.150000</td>\n",
       "      <td>3.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium</th>\n",
       "      <td>21.692308</td>\n",
       "      <td>2.307692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dubai International Cricket Stadium</th>\n",
       "      <td>16.065217</td>\n",
       "      <td>3.021739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eden Gardens</th>\n",
       "      <td>11.311688</td>\n",
       "      <td>3.571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eden Gardens, Kolkata</th>\n",
       "      <td>18.666667</td>\n",
       "      <td>3.111111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Feroz Shah Kotla</th>\n",
       "      <td>14.600000</td>\n",
       "      <td>3.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Green Park</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Himachal Pradesh Cricket Association Stadium</th>\n",
       "      <td>31.000000</td>\n",
       "      <td>2.555556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Himachal Pradesh Cricket Association Stadium, Dharamsala</th>\n",
       "      <td>7.500000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Holkar Cricket Stadium</th>\n",
       "      <td>3.444444</td>\n",
       "      <td>6.444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JSCA International Stadium Complex</th>\n",
       "      <td>5.857143</td>\n",
       "      <td>3.428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kingsmead</th>\n",
       "      <td>10.600000</td>\n",
       "      <td>2.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M Chinnaswamy Stadium</th>\n",
       "      <td>19.200000</td>\n",
       "      <td>3.569231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M Chinnaswamy Stadium, Bengaluru</th>\n",
       "      <td>8.428571</td>\n",
       "      <td>2.142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>M.Chinnaswamy Stadium</th>\n",
       "      <td>5.733333</td>\n",
       "      <td>2.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA Chidambaram Stadium</th>\n",
       "      <td>17.333333</td>\n",
       "      <td>3.444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA Chidambaram Stadium, Chepauk</th>\n",
       "      <td>14.895833</td>\n",
       "      <td>2.312500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA Chidambaram Stadium, Chepauk, Chennai</th>\n",
       "      <td>11.315789</td>\n",
       "      <td>2.578947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maharashtra Cricket Association Stadium</th>\n",
       "      <td>16.181818</td>\n",
       "      <td>3.772727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maharashtra Cricket Association Stadium, Pune</th>\n",
       "      <td>27.153846</td>\n",
       "      <td>1.153846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Narendra Modi Stadium, Ahmedabad</th>\n",
       "      <td>15.437500</td>\n",
       "      <td>3.062500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nehru Stadium</th>\n",
       "      <td>22.000000</td>\n",
       "      <td>2.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Wanderers Stadium</th>\n",
       "      <td>3.125000</td>\n",
       "      <td>4.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Newlands</th>\n",
       "      <td>20.714286</td>\n",
       "      <td>2.571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OUTsurance Oval</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association IS Bindra Stadium</th>\n",
       "      <td>4.500000</td>\n",
       "      <td>4.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association IS Bindra Stadium, Mohali</th>\n",
       "      <td>6.818182</td>\n",
       "      <td>3.636364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association IS Bindra Stadium, Mohali, Chandigarh</th>\n",
       "      <td>17.400000</td>\n",
       "      <td>2.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Punjab Cricket Association Stadium, Mohali</th>\n",
       "      <td>14.314286</td>\n",
       "      <td>3.628571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajiv Gandhi International Stadium</th>\n",
       "      <td>17.666667</td>\n",
       "      <td>2.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajiv Gandhi International Stadium, Uppal</th>\n",
       "      <td>9.918367</td>\n",
       "      <td>3.755102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rajiv Gandhi International Stadium, Uppal, Hyderabad</th>\n",
       "      <td>14.000000</td>\n",
       "      <td>3.285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sardar Patel Stadium, Motera</th>\n",
       "      <td>15.000000</td>\n",
       "      <td>3.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saurashtra Cricket Association Stadium</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>4.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sawai Mansingh Stadium</th>\n",
       "      <td>11.489362</td>\n",
       "      <td>4.297872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sawai Mansingh Stadium, Jaipur</th>\n",
       "      <td>30.800000</td>\n",
       "      <td>2.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shaheed Veer Narayan Singh International Stadium</th>\n",
       "      <td>3.500000</td>\n",
       "      <td>4.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sharjah Cricket Stadium</th>\n",
       "      <td>13.107143</td>\n",
       "      <td>3.928571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sheikh Zayed Stadium</th>\n",
       "      <td>14.275862</td>\n",
       "      <td>3.620690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St George's Park</th>\n",
       "      <td>28.571429</td>\n",
       "      <td>3.142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Subrata Roy Sahara Stadium</th>\n",
       "      <td>16.625000</td>\n",
       "      <td>2.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SuperSport Park</th>\n",
       "      <td>6.750000</td>\n",
       "      <td>4.083333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vidarbha Cricket Association Stadium, Jamtha</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wankhede Stadium</th>\n",
       "      <td>12.821918</td>\n",
       "      <td>2.958904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wankhede Stadium, Mumbai</th>\n",
       "      <td>8.763158</td>\n",
       "      <td>3.763158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zayed Cricket Stadium, Abu Dhabi</th>\n",
       "      <td>9.875000</td>\n",
       "      <td>3.875000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    win_by_runs  \\\n",
       "venue                                                             \n",
       "Arun Jaitley Stadium                                  11.714286   \n",
       "Arun Jaitley Stadium, Delhi                           15.636364   \n",
       "Barabati Stadium                                      10.428571   \n",
       "Barsapara Cricket Stadium, Guwahati                   31.000000   \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...    11.428571   \n",
       "Brabourne Stadium                                     13.600000   \n",
       "Brabourne Stadium, Mumbai                             13.352941   \n",
       "Buffalo Park                                          29.000000   \n",
       "De Beers Diamond Oval                                 17.666667   \n",
       "Dr DY Patil Sports Academy                            11.588235   \n",
       "Dr DY Patil Sports Academy, Mumbai                    14.150000   \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...    21.692308   \n",
       "Dubai International Cricket Stadium                   16.065217   \n",
       "Eden Gardens                                          11.311688   \n",
       "Eden Gardens, Kolkata                                 18.666667   \n",
       "Feroz Shah Kotla                                      14.600000   \n",
       "Green Park                                             0.000000   \n",
       "Himachal Pradesh Cricket Association Stadium          31.000000   \n",
       "Himachal Pradesh Cricket Association Stadium, D...     7.500000   \n",
       "Holkar Cricket Stadium                                 3.444444   \n",
       "JSCA International Stadium Complex                     5.857143   \n",
       "Kingsmead                                             10.600000   \n",
       "M Chinnaswamy Stadium                                 19.200000   \n",
       "M Chinnaswamy Stadium, Bengaluru                       8.428571   \n",
       "M.Chinnaswamy Stadium                                  5.733333   \n",
       "MA Chidambaram Stadium                                17.333333   \n",
       "MA Chidambaram Stadium, Chepauk                       14.895833   \n",
       "MA Chidambaram Stadium, Chepauk, Chennai              11.315789   \n",
       "Maharashtra Cricket Association Stadium               16.181818   \n",
       "Maharashtra Cricket Association Stadium, Pune         27.153846   \n",
       "Narendra Modi Stadium, Ahmedabad                      15.437500   \n",
       "Nehru Stadium                                         22.000000   \n",
       "New Wanderers Stadium                                  3.125000   \n",
       "Newlands                                              20.714286   \n",
       "OUTsurance Oval                                        7.000000   \n",
       "Punjab Cricket Association IS Bindra Stadium           4.500000   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...     6.818182   \n",
       "Punjab Cricket Association IS Bindra Stadium, M...    17.400000   \n",
       "Punjab Cricket Association Stadium, Mohali            14.314286   \n",
       "Rajiv Gandhi International Stadium                    17.666667   \n",
       "Rajiv Gandhi International Stadium, Uppal              9.918367   \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...    14.000000   \n",
       "Sardar Patel Stadium, Motera                          15.000000   \n",
       "Saurashtra Cricket Association Stadium                 7.000000   \n",
       "Sawai Mansingh Stadium                                11.489362   \n",
       "Sawai Mansingh Stadium, Jaipur                        30.800000   \n",
       "Shaheed Veer Narayan Singh International Stadium       3.500000   \n",
       "Sharjah Cricket Stadium                               13.107143   \n",
       "Sheikh Zayed Stadium                                  14.275862   \n",
       "St George's Park                                      28.571429   \n",
       "Subrata Roy Sahara Stadium                            16.625000   \n",
       "SuperSport Park                                        6.750000   \n",
       "Vidarbha Cricket Association Stadium, Jamtha           5.000000   \n",
       "Wankhede Stadium                                      12.821918   \n",
       "Wankhede Stadium, Mumbai                               8.763158   \n",
       "Zayed Cricket Stadium, Abu Dhabi                       9.875000   \n",
       "\n",
       "                                                    win_by_wickets  \n",
       "venue                                                               \n",
       "Arun Jaitley Stadium                                      2.500000  \n",
       "Arun Jaitley Stadium, Delhi                               3.727273  \n",
       "Barabati Stadium                                          2.857143  \n",
       "Barsapara Cricket Stadium, Guwahati                       0.000000  \n",
       "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cr...        1.000000  \n",
       "Brabourne Stadium                                         2.500000  \n",
       "Brabourne Stadium, Mumbai                                 3.352941  \n",
       "Buffalo Park                                              2.333333  \n",
       "De Beers Diamond Oval                                     3.333333  \n",
       "Dr DY Patil Sports Academy                                3.764706  \n",
       "Dr DY Patil Sports Academy, Mumbai                        3.050000  \n",
       "Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Sta...        2.307692  \n",
       "Dubai International Cricket Stadium                       3.021739  \n",
       "Eden Gardens                                              3.571429  \n",
       "Eden Gardens, Kolkata                                     3.111111  \n",
       "Feroz Shah Kotla                                          3.200000  \n",
       "Green Park                                                5.500000  \n",
       "Himachal Pradesh Cricket Association Stadium              2.555556  \n",
       "Himachal Pradesh Cricket Association Stadium, D...        2.000000  \n",
       "Holkar Cricket Stadium                                    6.444444  \n",
       "JSCA International Stadium Complex                        3.428571  \n",
       "Kingsmead                                                 2.200000  \n",
       "M Chinnaswamy Stadium                                     3.569231  \n",
       "M Chinnaswamy Stadium, Bengaluru                          2.142857  \n",
       "M.Chinnaswamy Stadium                                     2.266667  \n",
       "MA Chidambaram Stadium                                    3.444444  \n",
       "MA Chidambaram Stadium, Chepauk                           2.312500  \n",
       "MA Chidambaram Stadium, Chepauk, Chennai                  2.578947  \n",
       "Maharashtra Cricket Association Stadium                   3.772727  \n",
       "Maharashtra Cricket Association Stadium, Pune             1.153846  \n",
       "Narendra Modi Stadium, Ahmedabad                          3.062500  \n",
       "Nehru Stadium                                             2.600000  \n",
       "New Wanderers Stadium                                     4.375000  \n",
       "Newlands                                                  2.571429  \n",
       "OUTsurance Oval                                           3.000000  \n",
       "Punjab Cricket Association IS Bindra Stadium              4.100000  \n",
       "Punjab Cricket Association IS Bindra Stadium, M...        3.636364  \n",
       "Punjab Cricket Association IS Bindra Stadium, M...        2.400000  \n",
       "Punjab Cricket Association Stadium, Mohali                3.628571  \n",
       "Rajiv Gandhi International Stadium                        2.800000  \n",
       "Rajiv Gandhi International Stadium, Uppal                 3.755102  \n",
       "Rajiv Gandhi International Stadium, Uppal, Hyde...        3.285714  \n",
       "Sardar Patel Stadium, Motera                              3.166667  \n",
       "Saurashtra Cricket Association Stadium                    4.800000  \n",
       "Sawai Mansingh Stadium                                    4.297872  \n",
       "Sawai Mansingh Stadium, Jaipur                            2.600000  \n",
       "Shaheed Veer Narayan Singh International Stadium          4.166667  \n",
       "Sharjah Cricket Stadium                                   3.928571  \n",
       "Sheikh Zayed Stadium                                      3.620690  \n",
       "St George's Park                                          3.142857  \n",
       "Subrata Roy Sahara Stadium                                2.625000  \n",
       "SuperSport Park                                           4.083333  \n",
       "Vidarbha Cricket Association Stadium, Jamtha              2.000000  \n",
       "Wankhede Stadium                                          2.958904  \n",
       "Wankhede Stadium, Mumbai                                  3.763158  \n",
       "Zayed Cricket Stadium, Abu Dhabi                          3.875000  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "venue_avg_win_margin = match_info_data.groupby('venue')[['win_by_runs', 'win_by_wickets']].mean()\n",
    "\n",
    "# Print the result\n",
    "print(\"Average Winning Margin Across Different Venues:\")\n",
    "print(\"-\"*70)\n",
    "venue_avg_win_margin"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b33a8949",
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### [F] Temporal Analysis:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04b6aba9",
   "metadata": {
    "papermill": {
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "\n",
    "\n",
    "How does the number of matches played vary across different seasons?\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "22d8f578",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:57.786883Z",
     "iopub.status.busy": "2024-04-05T18:34:57.786460Z",
     "iopub.status.idle": "2024-04-05T18:34:59.785386Z",
     "shell.execute_reply": "2024-04-05T18:34:59.784258Z"
    },
    "papermill": {
     "duration": 2.037059,
     "end_time": "2024-04-05T18:34:59.787981",
     "exception": false,
     "start_time": "2024-04-05T18:34:57.750922",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Assuming match_info_data is your DataFrame containing the match data\n",
    "# Assuming you have already loaded your data into a DataFrame called match_info_data\n",
    "\n",
    "# Count the number of matches played in each season\n",
    "matches_per_season = match_info_data['season'].value_counts().reset_index().rename(columns={'season': 'Season', 'count': 'Matches'})\n",
    "matches_per_season = matches_per_season.sort_values(by='Season')\n",
    "# Plotting the graph using Seaborn\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(x='Season', y='Matches', data=matches_per_season, palette='viridis')\n",
    "plt.title('Number of Matches Played Across Different Seasons')\n",
    "plt.xlabel('Season')\n",
    "plt.ylabel('Number of Matches Played')\n",
    "plt.xticks(rotation=45)\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1b45d95",
   "metadata": {
    "papermill": {
     "duration": 0.037159,
     "end_time": "2024-04-05T18:34:59.859847",
     "exception": false,
     "start_time": "2024-04-05T18:34:59.822688",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Is there any trend in the number of matches affected by the Duckworth-Lewis method over the years?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2c98c605",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:34:59.932444Z",
     "iopub.status.busy": "2024-04-05T18:34:59.931741Z",
     "iopub.status.idle": "2024-04-05T18:35:00.260066Z",
     "shell.execute_reply": "2024-04-05T18:35:00.258594Z"
    },
    "papermill": {
     "duration": 0.367245,
     "end_time": "2024-04-05T18:35:00.262774",
     "exception": false,
     "start_time": "2024-04-05T18:34:59.895529",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# Filter matches with the Duckworth-Lewis method applied\n",
    "dl_matches = match_info_data[match_info_data['dl_applied'] == 1]\n",
    "\n",
    "# Count the number of matches with DL method applied in each season\n",
    "dl_matches_per_season = dl_matches['season'].value_counts().sort_index()\n",
    "\n",
    "# Plotting the graph using Matplotlib\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(dl_matches_per_season.index, dl_matches_per_season.values, marker='o', color='blue', linestyle='-')\n",
    "plt.title('Number of Matches Affected by Duckworth-Lewis Method Over the Years')\n",
    "plt.xlabel('Season')\n",
    "plt.ylabel('Number of Matches with DL Method Applied')\n",
    "plt.xticks(rotation=45)\n",
    "plt.grid(True)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "194aba92",
   "metadata": {
    "papermill": {
     "duration": 0.036297,
     "end_time": "2024-04-05T18:35:00.335145",
     "exception": false,
     "start_time": "2024-04-05T18:35:00.298848",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### [G] Umpire Analysis:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42e3ffa2",
   "metadata": {
    "papermill": {
     "duration": 0.03772,
     "end_time": "2024-04-05T18:35:00.409054",
     "exception": false,
     "start_time": "2024-04-05T18:35:00.371334",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Who are the most frequent umpires in the dataset?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4d3335a7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:35:00.484358Z",
     "iopub.status.busy": "2024-04-05T18:35:00.483977Z",
     "iopub.status.idle": "2024-04-05T18:35:00.500532Z",
     "shell.execute_reply": "2024-04-05T18:35:00.499226Z"
    },
    "papermill": {
     "duration": 0.057048,
     "end_time": "2024-04-05T18:35:00.503046",
     "exception": false,
     "start_time": "2024-04-05T18:35:00.445998",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Umpires</th>\n",
       "      <th>Matches</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S Ravi</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Umpires  Matches\n",
       "0           S Ravi      131\n",
       "1     AK Chaudhary      121\n",
       "2      Nitin Menon       94\n",
       "3  HDPK Dharmasena       94\n",
       "4    C Shamshuddin       88"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_umpires = pd.concat([match_info_data['umpire1'], match_info_data['umpire2']], ignore_index=True).reset_index()\n",
    "umpire_counts = all_umpires[0].value_counts().reset_index().rename(columns={0: 'Umpires', \"count\": 'Matches'}).head()\n",
    "umpire_counts "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f9bbeb7",
   "metadata": {
    "papermill": {
     "duration": 0.037731,
     "end_time": "2024-04-05T18:35:00.579394",
     "exception": false,
     "start_time": "2024-04-05T18:35:00.541663",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Is there any correlation between specific umpires and match outcomes?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "51a7c145",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:35:00.656538Z",
     "iopub.status.busy": "2024-04-05T18:35:00.656077Z",
     "iopub.status.idle": "2024-04-05T18:35:00.689610Z",
     "shell.execute_reply": "2024-04-05T18:35:00.688070Z"
    },
    "papermill": {
     "duration": 0.076104,
     "end_time": "2024-04-05T18:35:00.692335",
     "exception": false,
     "start_time": "2024-04-05T18:35:00.616231",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p-value: 1.58e-09\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Assuming match_info_data is your DataFrame containing the match data\n",
    "# Assuming you have already loaded your data into a DataFrame called match_info_data\n",
    "\n",
    "# Create a contingency table\n",
    "umpire_outcome_table = pd.crosstab(match_info_data['umpire1'], match_info_data['winner'])\n",
    "\n",
    "# Perform chi-square test\n",
    "from scipy.stats import chi2_contingency\n",
    "chi2, p, dof, expected = chi2_contingency(umpire_outcome_table)\n",
    "\n",
    "\n",
    "# Format p-value for readability\n",
    "formatted_p_value = \"{:.2e}\".format(p)\n",
    "\n",
    "# Print the formatted p-value\n",
    "print(\"p-value:\", formatted_p_value)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdc3b3ec",
   "metadata": {
    "papermill": {
     "duration": 0.03611,
     "end_time": "2024-04-05T18:35:00.764443",
     "exception": false,
     "start_time": "2024-04-05T18:35:00.728333",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### [H] Miscellaneous:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b3cd871",
   "metadata": {
    "papermill": {
     "duration": 0.035581,
     "end_time": "2024-04-05T18:35:00.835803",
     "exception": false,
     "start_time": "2024-04-05T18:35:00.800222",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "How does the distribution of winning margins (runs/wickets) look like?\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e2823efe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T18:35:00.909545Z",
     "iopub.status.busy": "2024-04-05T18:35:00.908884Z",
     "iopub.status.idle": "2024-04-05T18:35:01.746988Z",
     "shell.execute_reply": "2024-04-05T18:35:01.746061Z"
    },
    "papermill": {
     "duration": 0.877893,
     "end_time": "2024-04-05T18:35:01.749508",
     "exception": false,
     "start_time": "2024-04-05T18:35:00.871615",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.10/site-packages/seaborn/_oldcore.py:1119: FutureWarning:\n",
      "\n",
      "use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.10/site-packages/seaborn/_oldcore.py:1119: FutureWarning:\n",
      "\n",
      "use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Filter out matches where there was no result\n",
    "valid_matches = match_info_data[match_info_data['result'] != 'no result']\n",
    "\n",
    "# Plotting the distribution of winning margins in terms of runs\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.histplot(valid_matches['win_by_runs'], bins=20, kde=True, color='skyblue')\n",
    "plt.title('Distribution of Winning Margins (Runs)')\n",
    "plt.xlabel('Winning Margin (Runs)')\n",
    "plt.ylabel('Frequency')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "# Plotting the distribution of winning margins in terms of wickets\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.histplot(valid_matches['win_by_wickets'], bins=20, kde=True, color='salmon')\n",
    "plt.title('Distribution of Winning Margins (Wickets)')\n",
    "plt.xlabel('Winning Margin (Wickets)')\n",
    "plt.ylabel('Frequency')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ec6287f7",
   "metadata": {
    "papermill": {
     "duration": 0.037563,
     "end_time": "2024-04-05T18:35:01.824820",
     "exception": false,
     "start_time": "2024-04-05T18:35:01.787257",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "d3d55f07",
   "metadata": {
    "papermill": {
     "duration": 0.037316,
     "end_time": "2024-04-05T18:35:01.899846",
     "exception": false,
     "start_time": "2024-04-05T18:35:01.862530",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## (2) DATASET 2 ANALYSIS : IPL ALL MATCHES BALL-BY-BALL ANALYSIS"
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    "Match Analysis:\n",
    "\n",
    "How many matches are included in the dataset?\n",
    "How many seasons are covered in the dataset?\n",
    "What is the distribution of matches across seasons?\n",
    "What is the distribution of matches across venues?\n",
    "Batting Analysis:\n",
    "\n",
    "Which teams have scored the highest and lowest total runs?\n",
    "What is the average runs scored by each team per match?\n",
    "Who are the top run-scorers in the IPL?\n",
    "How does the distribution of runs scored vary across innings?\n",
    "What is the distribution of runs scored by each batting team?\n",
    "Bowling Analysis:\n",
    "\n",
    "Which teams have conceded the most and least total runs?\n",
    "What is the average runs conceded by each team per match?\n",
    "Who are the top wicket-takers in the IPL?\n",
    "How does the distribution of wickets taken vary across innings?\n",
    "What is the distribution of runs conceded by each bowling team?\n",
    "Player Performance Analysis:\n",
    "\n",
    "Who are the most consistent batsmen in terms of scoring runs?\n",
    "Who are the most economical bowlers in terms of conceding runs?\n",
    "Which players have the highest strike rates?\n",
    "How does player performance vary across different seasons?\n",
    "Match Outcome Analysis:\n",
    "\n",
    "What are the most common types of dismissals (wicket_type)?\n",
    "How many matches were won by batting first and batting second?\n",
    "Is there a correlation between winning the toss and winning the match?\n",
    "How does the margin of victory vary across matches?\n",
    "Inning-wise Analysis:\n",
    "\n",
    "How does the scoring rate vary across different innings?\n",
    "What is the average number of runs scored in powerplays (first 6 overs)?\n",
    "How does the distribution of runs scored change in the middle and death overs?\n",
    "Extras Analysis:\n",
    "\n",
    "What is the distribution of different types of extras (wides, no balls, byes, leg byes)?\n",
    "How do extras contribute to the total runs scored in matches?\n",
    "Over-wise Analysis:\n",
    "\n",
    "How does the distribution of runs scored vary across different overs?\n",
    "Which overs are the most economical for bowlers?\n",
    "Partnership Analysis:\n",
    "\n",
    "How do partnership runs contribute to the team's total score?\n",
    "What is the average partnership score for different wickets?\n",
    "Match Situation Analysis:\n",
    "\n",
    "How does the scoring rate change in different match situations (e.g., chasing a target, setting a target)?"
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