NHL Elo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2010 scraped\n",
      "2011 scraped\n",
      "2012 scraped\n",
      "2013 scraped\n",
      "2014 scraped\n",
      "2015 scraped\n",
      "2016 scraped\n",
      "2017 scraped\n",
      "2018 scraped\n",
      "2019 scraped\n",
      "no playoffs available yet\n",
      "2020 scraped\n"
     ]
    }
   ],
   "source": [
    "df_lists = pd.DataFrame()\n",
    "start_year= 2010\n",
    "end_year = 2020\n",
    "\n",
    "#scrapes data from hockeyreference.com\n",
    "for year in range (start_year,end_year+1):\n",
    "    k=1\n",
    "\n",
    "    # 2005 was the lockout so there is no data to be scraped\n",
    "    if year == 2005:\n",
    "        print(\"2005 was the lockout\")\n",
    "\n",
    "    else:\n",
    "        url = r'https://www.hockey-reference.com/leagues/NHL_' + str(year) + r'_games.html' \n",
    "\n",
    "        df_temp_reg = pd.DataFrame(pd.read_html(url)[0])\n",
    "        df_temp_reg['season'] = year\n",
    "\n",
    "    # use commented out code if playoff data is desired\n",
    "\n",
    "        try:\n",
    "            df_temp_post = pd.DataFrame(pd.read_html(url)[1])\n",
    "            df_temp_post['season'] = year\n",
    "\n",
    "        except IndexError as e:\n",
    "            k = 0\n",
    "            print('no playoffs available yet')\n",
    "        \n",
    "        print (str(year) + \" scraped\")\n",
    "\n",
    "    df_lists = df_lists.append(df_temp_reg)\n",
    "\n",
    "    if k == 1:\n",
    "        df_lists.append(df_temp_post)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Date', 'Visitor', 'G', 'Home', 'G.1', 'Unnamed: 5', 'Att.', 'LOG',\n",
       "       'Notes', 'season'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>G</th>\n",
       "      <th>Home</th>\n",
       "      <th>G.1</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "      <th>Att.</th>\n",
       "      <th>LOG</th>\n",
       "      <th>Notes</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1266</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Chicago Blackhawks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New York Rangers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1267</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Pittsburgh Penguins</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ottawa Senators</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1268</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Anaheim Ducks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1269</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1270</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Vegas Golden Knights</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date               Visitor   G                 Home  G.1  \\\n",
       "1266  2020-04-04    Chicago Blackhawks NaN     New York Rangers  NaN   \n",
       "1267  2020-04-04   Pittsburgh Penguins NaN      Ottawa Senators  NaN   \n",
       "1268  2020-04-04         Anaheim Ducks NaN      San Jose Sharks  NaN   \n",
       "1269  2020-04-04    Montreal Canadiens NaN  Toronto Maple Leafs  NaN   \n",
       "1270  2020-04-04  Vegas Golden Knights NaN    Vancouver Canucks  NaN   \n",
       "\n",
       "     Unnamed: 5  Att.  LOG Notes  season  \n",
       "1266        NaN   NaN  NaN   NaN    2020  \n",
       "1267        NaN   NaN  NaN   NaN    2020  \n",
       "1268        NaN   NaN  NaN   NaN    2020  \n",
       "1269        NaN   NaN  NaN   NaN    2020  \n",
       "1270        NaN   NaN  NaN   NaN    2020  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13147, 10)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Boston Bruins', 'Calgary Flames', 'Colorado Avalanche',\n",
       "       'Toronto Maple Leafs', 'Carolina Hurricanes', 'Chicago Blackhawks',\n",
       "       'Detroit Red Wings', 'Pittsburgh Penguins', 'Anaheim Ducks',\n",
       "       'Atlanta Thrashers', 'Buffalo Sabres', 'Columbus Blue Jackets',\n",
       "       'Dallas Stars', 'Edmonton Oilers', 'Florida Panthers',\n",
       "       'Los Angeles Kings', 'New Jersey Devils', 'New York Islanders',\n",
       "       'New York Rangers', 'St. Louis Blues', 'Washington Capitals',\n",
       "       'Vancouver Canucks', 'Minnesota Wild', 'Philadelphia Flyers',\n",
       "       'Nashville Predators', 'Ottawa Senators', 'San Jose Sharks',\n",
       "       'Tampa Bay Lightning', 'Phoenix Coyotes', 'Montreal Canadiens',\n",
       "       'Winnipeg Jets', 'Arizona Coyotes', 'Vegas Golden Knights'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists['Home'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>G</th>\n",
       "      <th>Home</th>\n",
       "      <th>G.1</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "      <th>Att.</th>\n",
       "      <th>LOG</th>\n",
       "      <th>Notes</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Washington Capitals</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Boston Bruins</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17565.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Calgary Flames</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19289.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Colorado Avalanche</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18007.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>3.0</td>\n",
       "      <td>OT</td>\n",
       "      <td>19617.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009-10-02</td>\n",
       "      <td>Philadelphia Flyers</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Carolina Hurricanes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18680.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date              Visitor    G                 Home  G.1 Unnamed: 5  \\\n",
       "0  2009-10-01  Washington Capitals  4.0        Boston Bruins  1.0        NaN   \n",
       "1  2009-10-01    Vancouver Canucks  3.0       Calgary Flames  5.0        NaN   \n",
       "2  2009-10-01      San Jose Sharks  2.0   Colorado Avalanche  5.0        NaN   \n",
       "3  2009-10-01   Montreal Canadiens  4.0  Toronto Maple Leafs  3.0         OT   \n",
       "4  2009-10-02  Philadelphia Flyers  2.0  Carolina Hurricanes  0.0        NaN   \n",
       "\n",
       "      Att.  LOG Notes  season  \n",
       "0  17565.0  NaN   NaN    2010  \n",
       "1  19289.0  NaN   NaN    2010  \n",
       "2  18007.0  NaN   NaN    2010  \n",
       "3  19617.0  NaN   NaN    2010  \n",
       "4  18680.0  NaN   NaN    2010  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>VisitingGoals</th>\n",
       "      <th>Home</th>\n",
       "      <th>HomeGoals</th>\n",
       "      <th>OTSO</th>\n",
       "      <th>Att.</th>\n",
       "      <th>LOG</th>\n",
       "      <th>Notes</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Washington Capitals</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Boston Bruins</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17565.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Calgary Flames</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19289.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Colorado Avalanche</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18007.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>3.0</td>\n",
       "      <td>OT</td>\n",
       "      <td>19617.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009-10-02</td>\n",
       "      <td>Philadelphia Flyers</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Carolina Hurricanes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18680.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date              Visitor  VisitingGoals                 Home  \\\n",
       "0  2009-10-01  Washington Capitals            4.0        Boston Bruins   \n",
       "1  2009-10-01    Vancouver Canucks            3.0       Calgary Flames   \n",
       "2  2009-10-01      San Jose Sharks            2.0   Colorado Avalanche   \n",
       "3  2009-10-01   Montreal Canadiens            4.0  Toronto Maple Leafs   \n",
       "4  2009-10-02  Philadelphia Flyers            2.0  Carolina Hurricanes   \n",
       "\n",
       "   HomeGoals OTSO     Att.  LOG Notes  season  \n",
       "0        1.0  NaN  17565.0  NaN   NaN    2010  \n",
       "1        5.0  NaN  19289.0  NaN   NaN    2010  \n",
       "2        5.0  NaN  18007.0  NaN   NaN    2010  \n",
       "3        3.0   OT  19617.0  NaN   NaN    2010  \n",
       "4        0.0  NaN  18680.0  NaN   NaN    2010  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.rename(columns={'G':'VisitingGoals',\n",
    "                       'G.1':'HomeGoals',\n",
    "                       'Unnamed: 5':'OTSO',\n",
    "                       }, inplace = True)\n",
    "df_lists.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date              object\n",
       "Visitor           object\n",
       "VisitingGoals    float64\n",
       "Home              object\n",
       "HomeGoals        float64\n",
       "OTSO              object\n",
       "Att.             float64\n",
       "LOG               object\n",
       "Notes             object\n",
       "season             int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_lists.drop(['Att.','LOG','Notes'], axis = 1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>VisitingGoals</th>\n",
       "      <th>Home</th>\n",
       "      <th>HomeGoals</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Washington Capitals</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Boston Bruins</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Calgary Flames</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Colorado Avalanche</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>3.0</td>\n",
       "      <td>OT</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009-10-02</td>\n",
       "      <td>Philadelphia Flyers</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Carolina Hurricanes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date              Visitor  VisitingGoals                 Home  \\\n",
       "0  2009-10-01  Washington Capitals            4.0        Boston Bruins   \n",
       "1  2009-10-01    Vancouver Canucks            3.0       Calgary Flames   \n",
       "2  2009-10-01      San Jose Sharks            2.0   Colorado Avalanche   \n",
       "3  2009-10-01   Montreal Canadiens            4.0  Toronto Maple Leafs   \n",
       "4  2009-10-02  Philadelphia Flyers            2.0  Carolina Hurricanes   \n",
       "\n",
       "   HomeGoals OTSO  season  \n",
       "0        1.0  NaN    2010  \n",
       "1        5.0  NaN    2010  \n",
       "2        5.0  NaN    2010  \n",
       "3        3.0   OT    2010  \n",
       "4        0.0  NaN    2010  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date              object\n",
       "Visitor           object\n",
       "VisitingGoals    float64\n",
       "Home              object\n",
       "HomeGoals        float64\n",
       "OTSO              object\n",
       "season             int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_lists.loc[:,'Date'] = pd.to_datetime(df_lists['Date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date             datetime64[ns]\n",
       "Visitor                  object\n",
       "VisitingGoals           float64\n",
       "Home                     object\n",
       "HomeGoals               float64\n",
       "OTSO                     object\n",
       "season                    int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'OT', 'SO'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists['OTSO'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Boston Bruins', 'Calgary Flames', 'Colorado Avalanche',\n",
       "       'Toronto Maple Leafs', 'Carolina Hurricanes', 'Chicago Blackhawks',\n",
       "       'Detroit Red Wings', 'Pittsburgh Penguins', 'Anaheim Ducks',\n",
       "       'Atlanta Thrashers', 'Buffalo Sabres', 'Columbus Blue Jackets',\n",
       "       'Dallas Stars', 'Edmonton Oilers', 'Florida Panthers',\n",
       "       'Los Angeles Kings', 'New Jersey Devils', 'New York Islanders',\n",
       "       'New York Rangers', 'St. Louis Blues', 'Washington Capitals',\n",
       "       'Vancouver Canucks', 'Minnesota Wild', 'Philadelphia Flyers',\n",
       "       'Nashville Predators', 'Ottawa Senators', 'San Jose Sharks',\n",
       "       'Tampa Bay Lightning', 'Phoenix Coyotes', 'Montreal Canadiens',\n",
       "       'Winnipeg Jets', 'Arizona Coyotes', 'Vegas Golden Knights'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists['Home'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "replace_dict= {'Home':{'Atlanta Thrashers': 'Winnipeg Jets',\n",
    "                      'Mighty Ducks of Anaheim': 'Anaheim Ducks',\n",
    "                      'Phoenix Coyotes': 'Arizona Coyotes'},\n",
    "              'Visitor':{'Atlanta Thrashers': 'Winnipeg Jets',\n",
    "                      'Mighty Ducks of Anaheim': 'Anaheim Ducks',\n",
    "                      'Phoenix Coyotes': 'Arizona Coyotes'}}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_lists.replace(replace_dict,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Boston Bruins', 'Calgary Flames', 'Colorado Avalanche',\n",
       "       'Toronto Maple Leafs', 'Carolina Hurricanes', 'Chicago Blackhawks',\n",
       "       'Detroit Red Wings', 'Pittsburgh Penguins', 'Anaheim Ducks',\n",
       "       'Winnipeg Jets', 'Buffalo Sabres', 'Columbus Blue Jackets',\n",
       "       'Dallas Stars', 'Edmonton Oilers', 'Florida Panthers',\n",
       "       'Los Angeles Kings', 'New Jersey Devils', 'New York Islanders',\n",
       "       'New York Rangers', 'St. Louis Blues', 'Washington Capitals',\n",
       "       'Vancouver Canucks', 'Minnesota Wild', 'Philadelphia Flyers',\n",
       "       'Nashville Predators', 'Ottawa Senators', 'San Jose Sharks',\n",
       "       'Tampa Bay Lightning', 'Arizona Coyotes', 'Montreal Canadiens',\n",
       "       'Vegas Golden Knights'], dtype=object)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists['Home'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "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>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>VisitingGoals</th>\n",
       "      <th>Home</th>\n",
       "      <th>HomeGoals</th>\n",
       "      <th>OTSO</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Washington Capitals</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Boston Bruins</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Calgary Flames</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Colorado Avalanche</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>3.0</td>\n",
       "      <td>OT</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009-10-02</td>\n",
       "      <td>Philadelphia Flyers</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Carolina Hurricanes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date              Visitor  VisitingGoals                 Home  \\\n",
       "0 2009-10-01  Washington Capitals            4.0        Boston Bruins   \n",
       "1 2009-10-01    Vancouver Canucks            3.0       Calgary Flames   \n",
       "2 2009-10-01      San Jose Sharks            2.0   Colorado Avalanche   \n",
       "3 2009-10-01   Montreal Canadiens            4.0  Toronto Maple Leafs   \n",
       "4 2009-10-02  Philadelphia Flyers            2.0  Carolina Hurricanes   \n",
       "\n",
       "   HomeGoals OTSO  season  \n",
       "0        1.0  NaN    2010  \n",
       "1        5.0  NaN    2010  \n",
       "2        5.0  NaN    2010  \n",
       "3        3.0   OT    2010  \n",
       "4        0.0  NaN    2010  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "ind = df_lists['OTSO'].isna()\n",
    "df_lists.loc[ind,'OTSO'] = 'REG'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['REG', 'OT', 'SO'], dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists['OTSO'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Anaheim Ducks', 'Arizona Coyotes', 'Boston Bruins',\n",
       "       'Buffalo Sabres', 'Calgary Flames', 'Carolina Hurricanes',\n",
       "       'Chicago Blackhawks', 'Colorado Avalanche',\n",
       "       'Columbus Blue Jackets', 'Dallas Stars', 'Detroit Red Wings',\n",
       "       'Edmonton Oilers', 'Florida Panthers', 'Los Angeles Kings',\n",
       "       'Minnesota Wild', 'Montreal Canadiens', 'Nashville Predators',\n",
       "       'New Jersey Devils', 'New York Islanders', 'New York Rangers',\n",
       "       'Ottawa Senators', 'Philadelphia Flyers', 'Pittsburgh Penguins',\n",
       "       'San Jose Sharks', 'St. Louis Blues', 'Tampa Bay Lightning',\n",
       "       'Toronto Maple Leafs', 'Vancouver Canucks', 'Vegas Golden Knights',\n",
       "       'Washington Capitals', 'Winnipeg Jets'], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# how come this doesnt work??? teams = df_lists['Home'].unique().sort()\n",
    "teams = df_lists['Home'].unique()\n",
    "teams.sort()\n",
    "teams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "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>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>VisitingGoals</th>\n",
       "      <th>Home</th>\n",
       "      <th>HomeGoals</th>\n",
       "      <th>OTSO</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Washington Capitals</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Boston Bruins</td>\n",
       "      <td>1.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Calgary Flames</td>\n",
       "      <td>5.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Colorado Avalanche</td>\n",
       "      <td>5.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>3.0</td>\n",
       "      <td>OT</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009-10-02</td>\n",
       "      <td>Philadelphia Flyers</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Carolina Hurricanes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date              Visitor  VisitingGoals                 Home  \\\n",
       "0 2009-10-01  Washington Capitals            4.0        Boston Bruins   \n",
       "1 2009-10-01    Vancouver Canucks            3.0       Calgary Flames   \n",
       "2 2009-10-01      San Jose Sharks            2.0   Colorado Avalanche   \n",
       "3 2009-10-01   Montreal Canadiens            4.0  Toronto Maple Leafs   \n",
       "4 2009-10-02  Philadelphia Flyers            2.0  Carolina Hurricanes   \n",
       "\n",
       "   HomeGoals OTSO  season  \n",
       "0        1.0  REG    2010  \n",
       "1        5.0  REG    2010  \n",
       "2        5.0  REG    2010  \n",
       "3        3.0   OT    2010  \n",
       "4        0.0  REG    2010  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lists.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Anaheim Ducks': 1500,\n",
       " 'Arizona Coyotes': 1500,\n",
       " 'Boston Bruins': 1500,\n",
       " 'Buffalo Sabres': 1500,\n",
       " 'Calgary Flames': 1500,\n",
       " 'Carolina Hurricanes': 1500,\n",
       " 'Chicago Blackhawks': 1500,\n",
       " 'Colorado Avalanche': 1500,\n",
       " 'Columbus Blue Jackets': 1500,\n",
       " 'Dallas Stars': 1500,\n",
       " 'Detroit Red Wings': 1500,\n",
       " 'Edmonton Oilers': 1500,\n",
       " 'Florida Panthers': 1500,\n",
       " 'Los Angeles Kings': 1500,\n",
       " 'Minnesota Wild': 1500,\n",
       " 'Montreal Canadiens': 1500,\n",
       " 'Nashville Predators': 1500,\n",
       " 'New Jersey Devils': 1500,\n",
       " 'New York Islanders': 1500,\n",
       " 'New York Rangers': 1500,\n",
       " 'Ottawa Senators': 1500,\n",
       " 'Philadelphia Flyers': 1500,\n",
       " 'Pittsburgh Penguins': 1500,\n",
       " 'San Jose Sharks': 1500,\n",
       " 'St. Louis Blues': 1500,\n",
       " 'Tampa Bay Lightning': 1500,\n",
       " 'Toronto Maple Leafs': 1500,\n",
       " 'Vancouver Canucks': 1500,\n",
       " 'Vegas Golden Knights': 1500,\n",
       " 'Washington Capitals': 1500,\n",
       " 'Winnipeg Jets': 1500}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team_elos = {}\n",
    "for team in teams:\n",
    "    team_elos[team] = 1500\n",
    "team_elos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "k_factor = 10\n",
    "def update_elo(w_elo, l_elo):\n",
    "    exp_win = expected_result(w_elo, l_elo)\n",
    "    change = k_factor * (1-exp_win)\n",
    "    w_elo = w_elo + change\n",
    "    l_elo = l_elo - change\n",
    "    return w_elo, l_elo\n",
    "\n",
    "def expected_result(elo_a, elo_b):\n",
    "    expect = 1.0/(1+10**((elo_b - elo_a)/400))\n",
    "    return expect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        Date              Visitor  VisitingGoals                 Home  \\\n",
      "1 2009-10-01    Vancouver Canucks            3.0       Calgary Flames   \n",
      "1 2010-10-07       Calgary Flames            0.0      Edmonton Oilers   \n",
      "1 2011-10-06   Montreal Canadiens            0.0  Toronto Maple Leafs   \n",
      "1 2013-01-19      Arizona Coyotes            3.0         Dallas Stars   \n",
      "1 2013-10-01        Winnipeg Jets            5.0      Edmonton Oilers   \n",
      "1 2014-10-08    Vancouver Canucks            4.0       Calgary Flames   \n",
      "1 2015-10-07     New York Rangers            3.0   Chicago Blackhawks   \n",
      "1 2016-10-12       Calgary Flames            4.0      Edmonton Oilers   \n",
      "1 2017-10-04      St. Louis Blues            5.0  Pittsburgh Penguins   \n",
      "1 2018-10-03   Montreal Canadiens            2.0  Toronto Maple Leafs   \n",
      "1 2019-10-02  Washington Capitals            NaN      St. Louis Blues   \n",
      "\n",
      "   HomeGoals OTSO  season  \n",
      "1        5.0  REG    2010  \n",
      "1        4.0  REG    2011  \n",
      "1        2.0  REG    2012  \n",
      "1        4.0  REG    2013  \n",
      "1        4.0  REG    2014  \n",
      "1        2.0  REG    2015  \n",
      "1        2.0  REG    2016  \n",
      "1        7.0  REG    2017  \n",
      "1        4.0   OT    2018  \n",
      "1        3.0   OT    2019  \n",
      "1        NaN  REG    2020  \n"
     ]
    }
   ],
   "source": [
    "#for row in df_lists.loc[1,:].itertuples():\n",
    "    #print(row)\n",
    "\n",
    "row = df_lists.loc[1,:]\n",
    "print(row)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "games = df_lists.reset_index() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "index                              1\n",
       "Date             2009-10-01 00:00:00\n",
       "Visitor            Vancouver Canucks\n",
       "VisitingGoals                      3\n",
       "Home                  Calgary Flames\n",
       "HomeGoals                          5\n",
       "OTSO                             REG\n",
       "season                          2010\n",
       "Name: 1, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games.loc[1,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>index</th>\n",
       "      <th>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>VisitingGoals</th>\n",
       "      <th>Home</th>\n",
       "      <th>HomeGoals</th>\n",
       "      <th>OTSO</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Washington Capitals</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Boston Bruins</td>\n",
       "      <td>1.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Calgary Flames</td>\n",
       "      <td>5.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Colorado Avalanche</td>\n",
       "      <td>5.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>3.0</td>\n",
       "      <td>OT</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2009-10-02</td>\n",
       "      <td>Philadelphia Flyers</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Carolina Hurricanes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index       Date              Visitor  VisitingGoals                 Home  \\\n",
       "0      0 2009-10-01  Washington Capitals            4.0        Boston Bruins   \n",
       "1      1 2009-10-01    Vancouver Canucks            3.0       Calgary Flames   \n",
       "2      2 2009-10-01      San Jose Sharks            2.0   Colorado Avalanche   \n",
       "3      3 2009-10-01   Montreal Canadiens            4.0  Toronto Maple Leafs   \n",
       "4      4 2009-10-02  Philadelphia Flyers            2.0  Carolina Hurricanes   \n",
       "\n",
       "   HomeGoals OTSO  season  \n",
       "0        1.0  REG    2010  \n",
       "1        5.0  REG    2010  \n",
       "2        5.0  REG    2010  \n",
       "3        3.0   OT    2010  \n",
       "4        0.0  REG    2010  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "games.drop('index', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>VisitingGoals</th>\n",
       "      <th>Home</th>\n",
       "      <th>HomeGoals</th>\n",
       "      <th>OTSO</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Washington Capitals</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Boston Bruins</td>\n",
       "      <td>1.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Calgary Flames</td>\n",
       "      <td>5.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Colorado Avalanche</td>\n",
       "      <td>5.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>3.0</td>\n",
       "      <td>OT</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009-10-02</td>\n",
       "      <td>Philadelphia Flyers</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Carolina Hurricanes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>REG</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date              Visitor  VisitingGoals                 Home  \\\n",
       "0 2009-10-01  Washington Capitals            4.0        Boston Bruins   \n",
       "1 2009-10-01    Vancouver Canucks            3.0       Calgary Flames   \n",
       "2 2009-10-01      San Jose Sharks            2.0   Colorado Avalanche   \n",
       "3 2009-10-01   Montreal Canadiens            4.0  Toronto Maple Leafs   \n",
       "4 2009-10-02  Philadelphia Flyers            2.0  Carolina Hurricanes   \n",
       "\n",
       "   HomeGoals OTSO  season  \n",
       "0        1.0  REG    2010  \n",
       "1        5.0  REG    2010  \n",
       "2        5.0  REG    2010  \n",
       "3        3.0   OT    2010  \n",
       "4        0.0  REG    2010  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "games.rename(columns={'season':'Season'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>VisitingGoals</th>\n",
       "      <th>Home</th>\n",
       "      <th>HomeGoals</th>\n",
       "      <th>OTSO</th>\n",
       "      <th>Season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13142</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Chicago Blackhawks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New York Rangers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13143</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Pittsburgh Penguins</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Ottawa Senators</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13144</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Anaheim Ducks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13145</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13146</th>\n",
       "      <td>2020-04-04</td>\n",
       "      <td>Vegas Golden Knights</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date               Visitor  VisitingGoals                 Home  \\\n",
       "13142 2020-04-04    Chicago Blackhawks            NaN     New York Rangers   \n",
       "13143 2020-04-04   Pittsburgh Penguins            NaN      Ottawa Senators   \n",
       "13144 2020-04-04         Anaheim Ducks            NaN      San Jose Sharks   \n",
       "13145 2020-04-04    Montreal Canadiens            NaN  Toronto Maple Leafs   \n",
       "13146 2020-04-04  Vegas Golden Knights            NaN    Vancouver Canucks   \n",
       "\n",
       "       HomeGoals OTSO  Season  \n",
       "13142        NaN  REG    2020  \n",
       "13143        NaN  REG    2020  \n",
       "13144        NaN  REG    2020  \n",
       "13145        NaN  REG    2020  \n",
       "13146        NaN  REG    2020  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pandas(Index=0, Date=Timestamp('2009-10-01 00:00:00'), Visitor='Washington Capitals', VisitingGoals=4.0, Home='Boston Bruins', HomeGoals=1.0, OTSO='REG', Season=2010)\n",
      "Pandas(Index=1, Date=Timestamp('2009-10-01 00:00:00'), Visitor='Vancouver Canucks', VisitingGoals=3.0, Home='Calgary Flames', HomeGoals=5.0, OTSO='REG', Season=2010)\n",
      "Pandas(Index=2, Date=Timestamp('2009-10-01 00:00:00'), Visitor='San Jose Sharks', VisitingGoals=2.0, Home='Colorado Avalanche', HomeGoals=5.0, OTSO='REG', Season=2010)\n",
      "Pandas(Index=3, Date=Timestamp('2009-10-01 00:00:00'), Visitor='Montreal Canadiens', VisitingGoals=4.0, Home='Toronto Maple Leafs', HomeGoals=3.0, OTSO='OT', Season=2010)\n",
      "Pandas(Index=4, Date=Timestamp('2009-10-02 00:00:00'), Visitor='Philadelphia Flyers', VisitingGoals=2.0, Home='Carolina Hurricanes', HomeGoals=0.0, OTSO='REG', Season=2010)\n"
     ]
    }
   ],
   "source": [
    "for row in games.head().itertuples():\n",
    "    print(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TeamElos(dict):\n",
    "    def __init__(self):\n",
    "        super().__init__(self)\n",
    "        for team in teams:\n",
    "            self[team] = 1500\n",
    "            \n",
    "    def update(self, game_tuple):\n",
    "        if game_tuple.VisitingGoals>game_tuple.HomeGoals:\n",
    "            winning_team = game_tuple.Visitor\n",
    "            losing_team = game_tuple.Home\n",
    "        else:\n",
    "            winning_team = game_tuple.Home\n",
    "            losing_team = game_tuple.Visitor\n",
    "        self[winning_team], self[losing_team] = update_elo(self[winning_team],self[losing_team])\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "elos = TeamElos()\n",
    "for row in games.itertuples():\n",
    "    if row.Date.date()< pd.Timestamp.today().date():\n",
    "        elos.update(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date             datetime64[ns]\n",
       "Visitor                  object\n",
       "VisitingGoals           float64\n",
       "Home                     object\n",
       "HomeGoals               float64\n",
       "OTSO                     object\n",
       "Season                    int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "elos=pd.DataFrame(elos, index = ['Elo Rating']).T.sort_values(by='Elo Rating', ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "ind = games['Date']> pd.Timestamp('today')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "games_future = games.loc[ind,:].reset_index()\n",
    "games_future.drop('index', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Date</th>\n",
       "      <th>Visitor</th>\n",
       "      <th>VisitingGoals</th>\n",
       "      <th>Home</th>\n",
       "      <th>HomeGoals</th>\n",
       "      <th>OTSO</th>\n",
       "      <th>Season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Edmonton Oilers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>Washington Capitals</td>\n",
       "      <td>NaN</td>\n",
       "      <td>St. Louis Blues</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>Ottawa Senators</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vegas Golden Knights</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Arizona Coyotes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anaheim Ducks</td>\n",
       "      <td>NaN</td>\n",
       "      <td>REG</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date              Visitor  VisitingGoals                  Home  \\\n",
       "0 2019-10-02    Vancouver Canucks            NaN       Edmonton Oilers   \n",
       "1 2019-10-02  Washington Capitals            NaN       St. Louis Blues   \n",
       "2 2019-10-02      Ottawa Senators            NaN   Toronto Maple Leafs   \n",
       "3 2019-10-02      San Jose Sharks            NaN  Vegas Golden Knights   \n",
       "4 2019-10-03      Arizona Coyotes            NaN         Anaheim Ducks   \n",
       "\n",
       "   HomeGoals OTSO  Season  \n",
       "0        NaN  REG    2020  \n",
       "1        NaN  REG    2020  \n",
       "2        NaN  REG    2020  \n",
       "3        NaN  REG    2020  \n",
       "4        NaN  REG    2020  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games_future.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "games_prediction = games_future.loc[0:10,['Date', 'Visitor', 'Home']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Elo Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Tampa Bay Lightning</th>\n",
       "      <td>1654.526896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington Capitals</th>\n",
       "      <td>1574.969030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Boston Bruins</th>\n",
       "      <td>1573.449994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nashville Predators</th>\n",
       "      <td>1556.701386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Columbus Blue Jackets</th>\n",
       "      <td>1549.891957</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Elo Rating\n",
       "Tampa Bay Lightning    1654.526896\n",
       "Washington Capitals    1574.969030\n",
       "Boston Bruins          1573.449994\n",
       "Nashville Predators    1556.701386\n",
       "Columbus Blue Jackets  1549.891957"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elos.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Date</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>Vancouver Canucks</td>\n",
       "      <td>Edmonton Oilers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>Washington Capitals</td>\n",
       "      <td>St. Louis Blues</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>Ottawa Senators</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>Vegas Golden Knights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Arizona Coyotes</td>\n",
       "      <td>Anaheim Ducks</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date              Visitor                  Home\n",
       "0 2019-10-02    Vancouver Canucks       Edmonton Oilers\n",
       "1 2019-10-02  Washington Capitals       St. Louis Blues\n",
       "2 2019-10-02      Ottawa Senators   Toronto Maple Leafs\n",
       "3 2019-10-02      San Jose Sharks  Vegas Golden Knights\n",
       "4 2019-10-03      Arizona Coyotes         Anaheim Ducks"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games_prediction.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>St. Louis Blues</td>\n",
       "      <td>1574.969030</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>Ottawa Senators</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>1401.631455</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>Vegas Golden Knights</td>\n",
       "      <td>1536.326902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Arizona Coyotes</td>\n",
       "      <td>Anaheim Ducks</td>\n",
       "      <td>1467.192211</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date              Visitor                  Home  Visitor Elo Rating\n",
       "0 2019-10-02    Vancouver Canucks       Edmonton Oilers         1433.398625\n",
       "1 2019-10-02  Washington Capitals       St. Louis Blues         1574.969030\n",
       "2 2019-10-02      Ottawa Senators   Toronto Maple Leafs         1401.631455\n",
       "3 2019-10-02      San Jose Sharks  Vegas Golden Knights         1536.326902\n",
       "4 2019-10-03      Arizona Coyotes         Anaheim Ducks         1467.192211"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games_prediction = pd.DataFrame.merge(games_prediction,elos,left_on= 'Visitor', right_index = True)\n",
    "games_prediction.rename(columns={'Elo Rating':'Visitor Elo Rating'\n",
    "                       }, inplace = True)\n",
    "games_prediction.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "games_prediction = pd.DataFrame.merge(games_prediction,elos,left_on= 'Home', right_index = True)\n",
    "games_prediction.rename(columns={'Elo Rating':'Home Elo Rating'\n",
    "                       }, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
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       "        Date              Visitor                  Home  Visitor Elo Rating  \\\n",
       "0 2019-10-02    Vancouver Canucks       Edmonton Oilers         1433.398625   \n",
       "1 2019-10-02  Washington Capitals       St. Louis Blues         1574.969030   \n",
       "2 2019-10-02      Ottawa Senators   Toronto Maple Leafs         1401.631455   \n",
       "3 2019-10-02      San Jose Sharks  Vegas Golden Knights         1536.326902   \n",
       "4 2019-10-03      Arizona Coyotes         Anaheim Ducks         1467.192211   \n",
       "\n",
       "   Home Elo Rating  \n",
       "0      1448.834186  \n",
       "1      1548.674850  \n",
       "2      1521.389410  \n",
       "3      1518.673651  \n",
       "4      1483.145589  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
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   ],
   "source": [
    "games_prediction.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "games_prediction['Home Win%']= expected_result(games_prediction['Home Elo Rating'],games_prediction['Visitor Elo Rating'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.522943</td>\n",
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      "text/plain": [
       "        Date              Visitor                  Home  Visitor Elo Rating  \\\n",
       "0 2019-10-02    Vancouver Canucks       Edmonton Oilers         1433.398625   \n",
       "1 2019-10-02  Washington Capitals       St. Louis Blues         1574.969030   \n",
       "2 2019-10-02      Ottawa Senators   Toronto Maple Leafs         1401.631455   \n",
       "3 2019-10-02      San Jose Sharks  Vegas Golden Knights         1536.326902   \n",
       "4 2019-10-03      Arizona Coyotes         Anaheim Ducks         1467.192211   \n",
       "\n",
       "   Home Elo Rating  Home Win%  \n",
       "0      1448.834186   0.522199  \n",
       "1      1548.674850   0.462232  \n",
       "2      1521.389410   0.665829  \n",
       "3      1518.673651   0.474617  \n",
       "4      1483.145589   0.522943  "
      ]
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     "execution_count": 50,
     "metadata": {},
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   ],
   "source": [
    "games_prediction.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "games_prediction['Visitor Win%'] = 1-games_prediction['Home Win%']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2019-10-02</td>\n",
       "      <td>Ottawa Senators</td>\n",
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       "      <td>1401.631455</td>\n",
       "      <td>1521.389410</td>\n",
       "      <td>0.665829</td>\n",
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       "      <td>2019-10-02</td>\n",
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       "      <td>2019-10-03</td>\n",
       "      <td>Arizona Coyotes</td>\n",
       "      <td>Anaheim Ducks</td>\n",
       "      <td>1467.192211</td>\n",
       "      <td>1483.145589</td>\n",
       "      <td>0.522943</td>\n",
       "      <td>0.477057</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "        Date              Visitor                  Home  Visitor Elo Rating  \\\n",
       "0 2019-10-02    Vancouver Canucks       Edmonton Oilers         1433.398625   \n",
       "1 2019-10-02  Washington Capitals       St. Louis Blues         1574.969030   \n",
       "2 2019-10-02      Ottawa Senators   Toronto Maple Leafs         1401.631455   \n",
       "3 2019-10-02      San Jose Sharks  Vegas Golden Knights         1536.326902   \n",
       "4 2019-10-03      Arizona Coyotes         Anaheim Ducks         1467.192211   \n",
       "\n",
       "   Home Elo Rating  Home Win%  Visitor Win%  \n",
       "0      1448.834186   0.522199      0.477801  \n",
       "1      1548.674850   0.462232      0.537768  \n",
       "2      1521.389410   0.665829      0.334171  \n",
       "3      1518.673651   0.474617      0.525383  \n",
       "4      1483.145589   0.522943      0.477057  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games_prediction.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "games_prediction.drop(['Visitor Elo Rating','Home Elo Rating'], axis = 1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "games_prediction = games_prediction[['Date', 'Visitor', 'Visitor Win%','Home','Home Win%']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.537768</td>\n",
       "      <td>St. Louis Blues</td>\n",
       "      <td>0.462232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>Ottawa Senators</td>\n",
       "      <td>0.334171</td>\n",
       "      <td>Toronto Maple Leafs</td>\n",
       "      <td>0.665829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-10-02</td>\n",
       "      <td>San Jose Sharks</td>\n",
       "      <td>0.525383</td>\n",
       "      <td>Vegas Golden Knights</td>\n",
       "      <td>0.474617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Arizona Coyotes</td>\n",
       "      <td>0.477057</td>\n",
       "      <td>Anaheim Ducks</td>\n",
       "      <td>0.522943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Montreal Canadiens</td>\n",
       "      <td>0.453278</td>\n",
       "      <td>Carolina Hurricanes</td>\n",
       "      <td>0.546722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Calgary Flames</td>\n",
       "      <td>0.584290</td>\n",
       "      <td>Colorado Avalanche</td>\n",
       "      <td>0.415710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Boston Bruins</td>\n",
       "      <td>0.584372</td>\n",
       "      <td>Dallas Stars</td>\n",
       "      <td>0.415628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Minnesota Wild</td>\n",
       "      <td>0.392045</td>\n",
       "      <td>Nashville Predators</td>\n",
       "      <td>0.607955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Winnipeg Jets</td>\n",
       "      <td>0.670131</td>\n",
       "      <td>New York Rangers</td>\n",
       "      <td>0.329869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>Buffalo Sabres</td>\n",
       "      <td>0.303166</td>\n",
       "      <td>Pittsburgh Penguins</td>\n",
       "      <td>0.696834</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date              Visitor  Visitor Win%                  Home  \\\n",
       "0  2019-10-02    Vancouver Canucks      0.477801       Edmonton Oilers   \n",
       "1  2019-10-02  Washington Capitals      0.537768       St. Louis Blues   \n",
       "2  2019-10-02      Ottawa Senators      0.334171   Toronto Maple Leafs   \n",
       "3  2019-10-02      San Jose Sharks      0.525383  Vegas Golden Knights   \n",
       "4  2019-10-03      Arizona Coyotes      0.477057         Anaheim Ducks   \n",
       "5  2019-10-03   Montreal Canadiens      0.453278   Carolina Hurricanes   \n",
       "6  2019-10-03       Calgary Flames      0.584290    Colorado Avalanche   \n",
       "7  2019-10-03        Boston Bruins      0.584372          Dallas Stars   \n",
       "8  2019-10-03       Minnesota Wild      0.392045   Nashville Predators   \n",
       "9  2019-10-03        Winnipeg Jets      0.670131      New York Rangers   \n",
       "10 2019-10-03       Buffalo Sabres      0.303166   Pittsburgh Penguins   \n",
       "\n",
       "    Home Win%  \n",
       "0    0.522199  \n",
       "1    0.462232  \n",
       "2    0.665829  \n",
       "3    0.474617  \n",
       "4    0.522943  \n",
       "5    0.546722  \n",
       "6    0.415710  \n",
       "7    0.415628  \n",
       "8    0.607955  \n",
       "9    0.329869  \n",
       "10   0.696834  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "games_prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          Date   Elo Rating\n",
      "0   2009-10-01  1495.000000\n",
      "1   2009-10-03  1490.143872\n",
      "2   2009-10-06  1485.212717\n",
      "3   2009-10-10  1480.568860\n",
      "4   2009-10-12  1476.060727\n",
      "5   2009-10-13  1471.471198\n",
      "6   2009-10-17  1467.225651\n",
      "7   2009-10-24  1462.640051\n",
      "8   2009-10-26  1467.968267\n",
      "9   2009-10-28  1463.373857\n",
      "10  2009-10-30  1459.240126\n",
      "11  2009-10-31  1454.762293\n",
      "12  2009-11-03  1450.157516\n",
      "13  2009-11-06  1455.194347\n",
      "14  2009-11-07  1460.874827\n",
      "15  2009-11-10  1456.205054\n",
      "16  2009-11-13  1452.028734\n",
      "17  2009-11-14  1448.031073\n",
      "18  2009-11-17  1443.680444\n",
      "19  2009-11-19  1438.574509\n",
      "20  2009-11-21  1444.680857\n",
      "21  2009-11-23  1440.067551\n",
      "22  2009-11-25  1445.742114\n",
      "23  2009-11-27  1451.373237\n",
      "24  2009-11-30  1447.324491\n",
      "25  2009-12-01  1452.950971\n",
      "26  2009-12-03  1458.529390\n",
      "27  2009-12-05  1454.151243\n",
      "28  2009-12-07  1460.032699\n",
      "29  2009-12-09  1465.165873\n",
      "..         ...          ...\n",
      "756 2019-02-06  1561.323880\n",
      "757 2019-02-09  1565.387408\n",
      "758 2019-02-10  1558.806140\n",
      "759 2019-02-12  1562.106038\n",
      "760 2019-02-14  1566.657353\n",
      "761 2019-02-16  1559.973069\n",
      "762 2019-02-19  1554.771664\n",
      "763 2019-02-21  1549.716375\n",
      "764 2019-02-23  1553.870726\n",
      "765 2019-02-25  1557.244532\n",
      "766 2019-02-27  1560.751956\n",
      "767 2019-02-28  1555.143620\n",
      "768 2019-03-02  1558.489319\n",
      "769 2019-03-04  1563.296605\n",
      "770 2019-03-06  1556.313174\n",
      "771 2019-03-09  1560.048662\n",
      "772 2019-03-11  1556.205440\n",
      "773 2019-03-13  1549.992308\n",
      "774 2019-03-15  1554.413325\n",
      "775 2019-03-16  1547.245440\n",
      "776 2019-03-19  1542.246691\n",
      "777 2019-03-20  1545.490594\n",
      "778 2019-03-23  1538.751056\n",
      "779 2019-03-25  1543.005265\n",
      "780 2019-03-27  1537.399669\n",
      "781 2019-03-30  1530.516983\n",
      "782 2019-04-01  1535.460095\n",
      "783 2019-04-02  1530.228408\n",
      "784 2019-04-04  1526.850749\n",
      "785 2019-04-06  1521.389410\n",
      "\n",
      "[786 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "class TeamElos(dict):\n",
    "    def __init__(self,teams):\n",
    "        super().__init__(self)\n",
    "        for team in teams:\n",
    "            self[team] = 1500\n",
    "        self.history = HistoryList(teams)\n",
    "\n",
    "    def update(self, game_tuple):\n",
    "        if game_tuple.VisitingGoals > game_tuple.HomeGoals:\n",
    "            winning_team = game_tuple.Visitor\n",
    "            losing_team = game_tuple.Home\n",
    "        else:\n",
    "            winning_team = game_tuple.Home\n",
    "            losing_team = game_tuple.Visitor\n",
    "        self[winning_team], self[losing_team] = update_elo(\n",
    "            self[winning_team],\n",
    "            self[losing_team])\n",
    "        self.history.update(\n",
    "            winning_team = winning_team,\n",
    "            losing_team = losing_team,\n",
    "            win_elo = self[winning_team],\n",
    "            lose_elo = self[losing_team],\n",
    "            date = game_tuple.Date\n",
    "            )\n",
    "\n",
    "\n",
    "class HistoryList(dict):\n",
    "    def __init__(self, teams):\n",
    "        super().__init__(self)\n",
    "        for team in teams:\n",
    "            self[team] = pd.DataFrame(columns = ['Date', 'Elo Rating'])\n",
    "\n",
    "    def update(self, winning_team, losing_team, win_elo, lose_elo, date):\n",
    "        self[winning_team] = self[winning_team].append({'Date': date,'Elo Rating': win_elo}, ignore_index = True)\n",
    "        self[losing_team]= self[losing_team].append({'Date': date,'Elo Rating': lose_elo}, ignore_index = True)\n",
    "\n",
    "\n",
    "elos = TeamElos(teams)\n",
    "for row in games.itertuples():\n",
    "    if row.Date.date() < pd.Timestamp.today().date():\n",
    "        elos.update(row)\n",
    "\n",
    "print(elos.history['Toronto Maple Leafs'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_history(*args):      \n",
    "    fig = plt.figure()\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.set_ylim([1350,1700])\n",
    "    plt.xticks(rotation=45)\n",
    "    \n",
    "    for team in args:\n",
    "        cax = plt.plot(elos.history[team]['Date'],\n",
    "                elos.history[team]['Elo Rating'],\n",
    "                      label = team)\n",
    "        \n",
    "    plt.title(f'{args} Elo History')\n",
    "    plt.legend()\n",
    "    \n",
    "\n",
    "plot_history('Toronto Maple Leafs', 'Montreal Canadiens','Detroit Red Wings')\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Toronto', 'montreal', 'Canada')\n"
     ]
    }
   ],
   "source": [
    "def print_args(*args):\n",
    "    print(args)\n",
    "    \n",
    "print_args('Toronto',\"montreal\",'Canada')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}