Understat-simulator.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import asyncio\n",
    "import nest_asyncio\n",
    "nest_asyncio.apply()\n",
    "import json\n",
    "import aiohttp\n",
    "from understat import Understat\n",
    "\n",
    "import random\n",
    "def calculateWinner(home, away):\n",
    "    HomeGoals = 0\n",
    "    AwayGoals = 0\n",
    "    \n",
    "    def testShots(shots):\n",
    "        Goals = 0\n",
    "        \n",
    "        for shot in shots:\n",
    "            if random.random() <= shot:\n",
    "                Goals += 1\n",
    "        return Goals\n",
    "    \n",
    "    HomeGoals = testShots(home)\n",
    "    AwayGoals = testShots(away)\n",
    "    \n",
    "    #This is all that changes from above\n",
    "    #We now pass a simple string, rather than ask for a print out.\n",
    "    if HomeGoals > AwayGoals:\n",
    "        return(\"home\")\n",
    "    elif AwayGoals > HomeGoals:\n",
    "        return(\"away\")\n",
    "    else:\n",
    "        return(\"draw\")\n",
    "        \n",
    "        \n",
    "        #Run xG calculator 10000 times to test winner %\n",
    "def calculateChance(team1, team2):\n",
    "    home = 0;\n",
    "    away = 0;\n",
    "    draw = 0;\n",
    "    \n",
    "    for i in range(0,10000):\n",
    "        matchWinner = calculateWinner(team1,team2)\n",
    "        if matchWinner == \"home\":\n",
    "            home +=1\n",
    "        elif matchWinner == \"away\":\n",
    "            away +=1\n",
    "        else:\n",
    "            draw +=1\n",
    "    home = home/100\n",
    "    away = away/100\n",
    "    draw = draw/100\n",
    "    #print(\"Over 10000 games, home wins {}%, away wins {}% and there is a draw in {}% of games.\".format(home, away, draw))\n",
    "    return home, away, draw\n",
    "\n",
    "\n",
    "import asyncio\n",
    "import json\n",
    "\n",
    "import aiohttp\n",
    "\n",
    "from understat import Understat\n",
    "\n",
    "#Here enter the undersat match_id for the game\n",
    "#https://understat.com/match/12010 -  this is the Spurs 3-0 Leicester game, so match_id is 12010\n",
    "\n",
    "match_id = 13427\n",
    "async def get_win_percent(match_id):\n",
    "    async with aiohttp.ClientSession() as session:\n",
    "        understat = Understat(session)\n",
    "        players = await understat.get_match_shots(match_id)\n",
    "        d = json.dumps(players)\n",
    "        with open('data.json', 'w') as f:\n",
    "            json.dump(players, f)\n",
    "        home = pd.DataFrame.from_dict(players['h'], orient='columns')\n",
    "        away = pd.DataFrame.from_dict(players['a'], orient='columns')\n",
    "        fixtures = await understat.get_league_results(\"epl\",2019)\n",
    "        results = pd.DataFrame.from_dict(fixtures, orient='columns')\n",
    "        homexg = home['xG'].tolist()\n",
    "        awayxg = away['xG'].tolist()\n",
    "        #print(home)\n",
    "        #print(away)\n",
    "        h_team = home.iloc[0]['h_team']\n",
    "        a_team = away.iloc[0]['a_team']\n",
    "        homexg = list(map(float, homexg))\n",
    "        awayxg = list(map(float, awayxg))\n",
    "        h,a, d = calculateChance(homexg, awayxg)\n",
    "        print(\"Over 10000 games, {} wins {}%, {} wins {}% and there is a draw in {}% of games.\".format(h_team,h,a_team, a, d))\n",
    "loop = asyncio.get_event_loop()\n",
    "#loop.run_until_complete(main())\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "async def get_table(season_id,league):\n",
    "    async with aiohttp.ClientSession() as session:\n",
    "        understat = Understat(session)\n",
    "        fixtures = await understat.get_league_results(league,season_id)\n",
    "        results = pd.DataFrame.from_dict(fixtures, orient='columns')\n",
    "        l = len(results)\n",
    "        print(l)\n",
    "        for i in range(0,l):\n",
    "            matc_id = results.iloc[i]['id']\n",
    "            players = await understat.get_match_shots(matc_id)\n",
    "            home = pd.DataFrame.from_dict(players['h'], orient='columns')\n",
    "            away = pd.DataFrame.from_dict(players['a'], orient='columns')\n",
    "            homexg = home['xG'].tolist()\n",
    "            awayxg = away['xG'].tolist()\n",
    "            #print(homexg)\n",
    "            #print(awayxg)\n",
    "            homexg = list(map(float, homexg))\n",
    "            awayxg = list(map(float, awayxg))\n",
    "            h,a,d = calculateChance(homexg, awayxg)\n",
    "            h_team = home.iloc[0]['h_team']\n",
    "            a_team = away.iloc[0]['a_team']\n",
    "            pts.iloc[1][h_team] = pts.iloc[1][h_team] + 1.0\n",
    "            pts.iloc[1][a_team] = pts.iloc[1][a_team] + 1.0\n",
    "            pts.iloc[0][h_team] = pts.iloc[0][h_team] + (h/100)*3\n",
    "            pts.iloc[0][a_team] = pts.iloc[0][a_team] + (a/100)*3\n",
    "            pts.iloc[0][h_team] = pts.iloc[0][h_team] + (d/100)*1\n",
    "            pts.iloc[0][a_team] = pts.iloc[0][a_team] + (d/100)*1\n",
    "loop = asyncio.get_event_loop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Over 10000 games, Newcastle United wins 13.64%, Tottenham wins 63.87% and there is a draw in 22.49% of games.\n"
     ]
    }
   ],
   "source": [
    "#TO SIMULATE ANY MATCH ON UNDERSTAT\n",
    "#Enter any match id you want, 12000 is the match_id of this game - https://understat.com/match/12000\n",
    "match_id = 12000\n",
    "asyncio.run(get_win_percent(match_id))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#The following cells are for expected points tables for any league"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "360\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\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>Expected points</th>\n",
       "      <th>Games played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Atalanta</th>\n",
       "      <td>73.6246</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inter</th>\n",
       "      <td>73.3020</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Juventus</th>\n",
       "      <td>68.7623</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Roma</th>\n",
       "      <td>65.3592</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Napoli</th>\n",
       "      <td>62.8755</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AC Milan</th>\n",
       "      <td>60.1564</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lazio</th>\n",
       "      <td>58.7810</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bologna</th>\n",
       "      <td>50.6944</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fiorentina</th>\n",
       "      <td>50.3592</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Verona</th>\n",
       "      <td>47.1674</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sampdoria</th>\n",
       "      <td>47.1185</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Udinese</th>\n",
       "      <td>45.9925</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Genoa</th>\n",
       "      <td>45.4450</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sassuolo</th>\n",
       "      <td>43.1383</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cagliari</th>\n",
       "      <td>38.7489</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parma Calcio 1913</th>\n",
       "      <td>37.8850</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Torino</th>\n",
       "      <td>37.2005</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lecce</th>\n",
       "      <td>32.7574</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brescia</th>\n",
       "      <td>32.3953</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SPAL 2013</th>\n",
       "      <td>29.7287</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Expected points  Games played\n",
       "Atalanta                   73.6246          36.0\n",
       "Inter                      73.3020          36.0\n",
       "Juventus                   68.7623          36.0\n",
       "Roma                       65.3592          36.0\n",
       "Napoli                     62.8755          36.0\n",
       "AC Milan                   60.1564          36.0\n",
       "Lazio                      58.7810          36.0\n",
       "Bologna                    50.6944          36.0\n",
       "Fiorentina                 50.3592          36.0\n",
       "Verona                     47.1674          36.0\n",
       "Sampdoria                  47.1185          36.0\n",
       "Udinese                    45.9925          36.0\n",
       "Genoa                      45.4450          36.0\n",
       "Sassuolo                   43.1383          36.0\n",
       "Cagliari                   38.7489          36.0\n",
       "Parma Calcio 1913          37.8850          36.0\n",
       "Torino                     37.2005          36.0\n",
       "Lecce                      32.7574          36.0\n",
       "Brescia                    32.3953          36.0\n",
       "SPAL 2013                  29.7287          36.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pts = pd.DataFrame({'Juventus': [0], 'Atalanta':[0], 'Inter':[0], 'Lazio':[0], 'Roma':[0], 'AC Milan':[0], 'Napoli':[0], 'Sassuolo':[0], 'Verona':[0], 'Parma Calcio 1913':[0], 'Fiorentina':[0], 'Bologna':[0], 'Cagliari':[0], 'Sampdoria':[0], 'Udinese':[0], 'Torino':[0], 'Genoa':[0], 'Lecce':[0], 'Brescia':[0], 'SPAL 2013':[0]})\n",
    "pts.loc[len(pts)] = 0\n",
    "pts = pts.astype(float)\n",
    "asyncio.run(get_table(2019,\"serie a\"))\n",
    "table = pts.transpose()\n",
    "table.columns = ['Expected points','Games played']\n",
    "table = table.sort_values(['Expected points'], ascending=[False])\n",
    "table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "380\n"
     ]
    },
    {
     "data": {
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Expected points</th>\n",
       "      <th>Games played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Manchester City</th>\n",
       "      <td>87.0164</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Liverpool</th>\n",
       "      <td>74.3158</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chelsea</th>\n",
       "      <td>73.5333</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manchester United</th>\n",
       "      <td>70.8105</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolverhampton Wanderers</th>\n",
       "      <td>63.3472</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leicester</th>\n",
       "      <td>61.2270</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southampton</th>\n",
       "      <td>57.2294</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Everton</th>\n",
       "      <td>55.7267</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arsenal</th>\n",
       "      <td>50.1899</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tottenham</th>\n",
       "      <td>49.7986</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burnley</th>\n",
       "      <td>49.7642</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sheffield United</th>\n",
       "      <td>49.3284</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brighton</th>\n",
       "      <td>47.9059</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Watford</th>\n",
       "      <td>47.6211</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bournemouth</th>\n",
       "      <td>39.5490</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Ham</th>\n",
       "      <td>38.8582</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crystal Palace</th>\n",
       "      <td>38.1106</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aston Villa</th>\n",
       "      <td>37.6167</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norwich</th>\n",
       "      <td>32.8529</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Newcastle United</th>\n",
       "      <td>31.7303</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Expected points  Games played\n",
       "Manchester City                  87.0164          38.0\n",
       "Liverpool                        74.3158          38.0\n",
       "Chelsea                          73.5333          38.0\n",
       "Manchester United                70.8105          38.0\n",
       "Wolverhampton Wanderers          63.3472          38.0\n",
       "Leicester                        61.2270          38.0\n",
       "Southampton                      57.2294          38.0\n",
       "Everton                          55.7267          38.0\n",
       "Arsenal                          50.1899          38.0\n",
       "Tottenham                        49.7986          38.0\n",
       "Burnley                          49.7642          38.0\n",
       "Sheffield United                 49.3284          38.0\n",
       "Brighton                         47.9059          38.0\n",
       "Watford                          47.6211          38.0\n",
       "Bournemouth                      39.5490          38.0\n",
       "West Ham                         38.8582          38.0\n",
       "Crystal Palace                   38.1106          38.0\n",
       "Aston Villa                      37.6167          38.0\n",
       "Norwich                          32.8529          38.0\n",
       "Newcastle United                 31.7303          38.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pts = pd.DataFrame({'Liverpool': [0], 'Manchester City':[0], 'Chelsea':[0], 'Leicester':[0], 'Manchester United':[0], 'Tottenham':[0], 'Wolverhampton Wanderers':[0], 'Sheffield United':[0], 'Burnley':[0], 'Arsenal':[0], 'Southampton':[0], 'Everton':[0], 'Newcastle United':[0], 'Crystal Palace':[0], 'West Ham':[0], 'Brighton':[0], 'Watford':[0], 'Aston Villa':[0], 'Bournemouth':[0], 'Norwich':[0]})\n",
    "pts.loc[len(pts)] = 0\n",
    "pts = pts.astype(float)\n",
    "asyncio.run(get_table(2019,\"epl\"))\n",
    "table = pts.transpose()\n",
    "table.columns = ['Expected points','Games played']\n",
    "table = table.sort_values(['Expected points'], ascending=[False])\n",
    "table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "306\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Expected points</th>\n",
       "      <th>Games played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bayern Munich</th>\n",
       "      <td>76.9747</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RasenBallsport Leipzig</th>\n",
       "      <td>68.7466</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Borussia M.Gladbach</th>\n",
       "      <td>62.7731</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Borussia Dortmund</th>\n",
       "      <td>62.1987</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolfsburg</th>\n",
       "      <td>55.5675</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayer Leverkusen</th>\n",
       "      <td>54.0509</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eintracht Frankfurt</th>\n",
       "      <td>52.4405</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hoffenheim</th>\n",
       "      <td>46.7040</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FC Cologne</th>\n",
       "      <td>44.0711</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Augsburg</th>\n",
       "      <td>39.9750</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Union Berlin</th>\n",
       "      <td>39.5973</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hertha Berlin</th>\n",
       "      <td>39.3694</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mainz 05</th>\n",
       "      <td>39.2870</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Freiburg</th>\n",
       "      <td>39.1769</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Schalke 04</th>\n",
       "      <td>36.0533</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Werder Bremen</th>\n",
       "      <td>35.3543</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fortuna Duesseldorf</th>\n",
       "      <td>32.2851</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paderborn</th>\n",
       "      <td>29.2372</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Expected points  Games played\n",
       "Bayern Munich                   76.9747          34.0\n",
       "RasenBallsport Leipzig          68.7466          34.0\n",
       "Borussia M.Gladbach             62.7731          34.0\n",
       "Borussia Dortmund               62.1987          34.0\n",
       "Wolfsburg                       55.5675          34.0\n",
       "Bayer Leverkusen                54.0509          34.0\n",
       "Eintracht Frankfurt             52.4405          34.0\n",
       "Hoffenheim                      46.7040          34.0\n",
       "FC Cologne                      44.0711          34.0\n",
       "Augsburg                        39.9750          34.0\n",
       "Union Berlin                    39.5973          34.0\n",
       "Hertha Berlin                   39.3694          34.0\n",
       "Mainz 05                        39.2870          34.0\n",
       "Freiburg                        39.1769          34.0\n",
       "Schalke 04                      36.0533          34.0\n",
       "Werder Bremen                   35.3543          34.0\n",
       "Fortuna Duesseldorf             32.2851          34.0\n",
       "Paderborn                       29.2372          34.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pts = pd.DataFrame({'Bayern Munich': [0], 'Borussia Dortmund':[0], 'RasenBallsport Leipzig':[0], 'Borussia M.Gladbach':[0], 'Bayer Leverkusen':[0], 'Hoffenheim':[0], 'Wolfsburg':[0], 'Freiburg':[0], 'Eintracht Frankfurt':[0], 'Hertha Berlin':[0], 'Union Berlin':[0], 'Schalke 04':[0], 'Mainz 05':[0], 'FC Cologne':[0], 'Augsburg':[0], 'Werder Bremen':[0], 'Fortuna Duesseldorf':[0], 'Paderborn':[0]})\n",
    "pts.loc[len(pts)] = 0\n",
    "pts = pts.astype(float)\n",
    "asyncio.run(get_table(2019,\"bundesliga\"))\n",
    "table = pts.transpose()\n",
    "table.columns = ['Expected points','Games played']\n",
    "table = table.sort_values(['Expected points'], ascending=[False])\n",
    "table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "380\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>Expected points</th>\n",
       "      <th>Games played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Real Madrid</th>\n",
       "      <td>77.6798</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barcelona</th>\n",
       "      <td>73.2815</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Atletico Madrid</th>\n",
       "      <td>72.5775</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sevilla</th>\n",
       "      <td>65.5500</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Villarreal</th>\n",
       "      <td>63.8131</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Real Sociedad</th>\n",
       "      <td>57.0663</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Getafe</th>\n",
       "      <td>52.9770</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Granada</th>\n",
       "      <td>52.8489</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Osasuna</th>\n",
       "      <td>51.6254</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leganes</th>\n",
       "      <td>49.3816</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Real Betis</th>\n",
       "      <td>47.9463</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Celta Vigo</th>\n",
       "      <td>47.2394</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Valencia</th>\n",
       "      <td>44.8924</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Athletic Club</th>\n",
       "      <td>44.6769</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Levante</th>\n",
       "      <td>42.9446</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eibar</th>\n",
       "      <td>42.6479</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Espanyol</th>\n",
       "      <td>41.9486</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaves</th>\n",
       "      <td>41.7963</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Real Valladolid</th>\n",
       "      <td>39.5968</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mallorca</th>\n",
       "      <td>36.1979</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Expected points  Games played\n",
       "Real Madrid              77.6798          38.0\n",
       "Barcelona                73.2815          38.0\n",
       "Atletico Madrid          72.5775          38.0\n",
       "Sevilla                  65.5500          38.0\n",
       "Villarreal               63.8131          38.0\n",
       "Real Sociedad            57.0663          38.0\n",
       "Getafe                   52.9770          38.0\n",
       "Granada                  52.8489          38.0\n",
       "Osasuna                  51.6254          38.0\n",
       "Leganes                  49.3816          38.0\n",
       "Real Betis               47.9463          38.0\n",
       "Celta Vigo               47.2394          38.0\n",
       "Valencia                 44.8924          38.0\n",
       "Athletic Club            44.6769          38.0\n",
       "Levante                  42.9446          38.0\n",
       "Eibar                    42.6479          38.0\n",
       "Espanyol                 41.9486          38.0\n",
       "Alaves                   41.7963          38.0\n",
       "Real Valladolid          39.5968          38.0\n",
       "Mallorca                 36.1979          38.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pts = pd.DataFrame({'Real Madrid': [0], 'Barcelona':[0], 'Atletico Madrid':[0], 'Sevilla':[0], 'Villarreal':[0], 'Real Sociedad':[0], 'Granada':[0], 'Getafe':[0], 'Valencia':[0], 'Osasuna':[0], 'Athletic Club':[0], 'Levante':[0], 'Real Valladolid':[0], 'Eibar':[0], 'Real Betis':[0], 'Alaves':[0], 'Celta Vigo':[0], 'Leganes':[0], 'Mallorca':[0], 'Espanyol':[0]})\n",
    "pts.loc[len(pts)] = 0\n",
    "pts = pts.astype(float)\n",
    "asyncio.run(get_table(2019,\"la liga\"))\n",
    "table = pts.transpose()\n",
    "table.columns = ['Expected points','Games played']\n",
    "table = table.sort_values(['Expected points'], ascending=[False])\n",
    "table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "279\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>Expected points</th>\n",
       "      <th>Games played</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Paris Saint Germain</th>\n",
       "      <td>65.7729</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lille</th>\n",
       "      <td>47.8114</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lyon</th>\n",
       "      <td>46.2682</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monaco</th>\n",
       "      <td>42.8116</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marseille</th>\n",
       "      <td>41.6525</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rennes</th>\n",
       "      <td>41.3054</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reims</th>\n",
       "      <td>40.0680</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montpellier</th>\n",
       "      <td>40.0108</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angers</th>\n",
       "      <td>37.9822</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Strasbourg</th>\n",
       "      <td>37.7217</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bordeaux</th>\n",
       "      <td>36.9426</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nantes</th>\n",
       "      <td>35.8934</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nice</th>\n",
       "      <td>35.8640</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Amiens</th>\n",
       "      <td>33.2162</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saint-Etienne</th>\n",
       "      <td>32.7312</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nimes</th>\n",
       "      <td>32.2665</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dijon</th>\n",
       "      <td>30.9380</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brest</th>\n",
       "      <td>30.5132</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Metz</th>\n",
       "      <td>28.9600</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Toulouse</th>\n",
       "      <td>27.9339</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Expected points  Games played\n",
       "Paris Saint Germain          65.7729          27.0\n",
       "Lille                        47.8114          28.0\n",
       "Lyon                         46.2682          28.0\n",
       "Monaco                       42.8116          28.0\n",
       "Marseille                    41.6525          28.0\n",
       "Rennes                       41.3054          28.0\n",
       "Reims                        40.0680          28.0\n",
       "Montpellier                  40.0108          28.0\n",
       "Angers                       37.9822          28.0\n",
       "Strasbourg                   37.7217          27.0\n",
       "Bordeaux                     36.9426          28.0\n",
       "Nantes                       35.8934          28.0\n",
       "Nice                         35.8640          28.0\n",
       "Amiens                       33.2162          28.0\n",
       "Saint-Etienne                32.7312          28.0\n",
       "Nimes                        32.2665          28.0\n",
       "Dijon                        30.9380          28.0\n",
       "Brest                        30.5132          28.0\n",
       "Metz                         28.9600          28.0\n",
       "Toulouse                     27.9339          28.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pts = pd.DataFrame({'Paris Saint Germain': [0], 'Marseille':[0], 'Rennes':[0], 'Lille':[0], 'Reims':[0], 'Nice':[0], 'Lyon':[0], 'Montpellier':[0], 'Monaco':[0], 'Angers':[0], 'Strasbourg':[0], 'Bordeaux':[0], 'Nantes':[0], 'Brest':[0], 'Metz':[0], 'Dijon':[0], 'Saint-Etienne':[0], 'Nimes':[0], 'Amiens':[0], 'Toulouse':[0]})\n",
    "pts.loc[len(pts)] = 0\n",
    "pts = pts.astype(float)\n",
    "asyncio.run(get_table(2019,\"ligue 1\"))\n",
    "table = pts.transpose()\n",
    "table.columns = ['Expected points','Games played']\n",
    "table = table.sort_values(['Expected points'], ascending=[False])\n",
    "table"
   ]
  }
 ],
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