a-league-xg-race-fotmob.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['figure.dpi']= 300\n",
    "mpl.rcParams['pdf.fonttype'] = 42 # for Illustrator text compatibility\n",
    "mpl.rcParams['ps.fonttype'] = 42 # for Illustrator text compatibility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "COLOUR_BACKGROUND = '#f7f3ed'\n",
    "COLOUR_ALMOST_BLACK = '#323232'\n",
    "COLOUR_BLUE = '#1c7ed6'\n",
    "COLOUR_YELLOW = '#f59f00'\n",
    "COLOUR_RED = '#f03e3e'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_base = 'https://www.fotmob.com/api/'\n",
    "url_match_details = 'matchDetails?matchId='"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "match_id = 3978742"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_complete = url_base + url_match_details + str(match_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "match_summary = requests.get(url_complete).json()\n",
    "shot_summary = match_summary['content']['shotmap']['shots']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "home_team = match_summary['general']['homeTeam']['name']\n",
    "home_team_id = match_summary['general']['homeTeam']['id']\n",
    "away_team = match_summary['general']['awayTeam']['name']\n",
    "away_team_id = match_summary['general']['awayTeam']['id']\n",
    "round_name = match_summary['general']['leagueRoundName']\n",
    "match_result = match_summary['header']['status']['scoreStr']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_stats = [stat for stat in match_summary['content']['stats']['stats'] if stat['title'] == 'TOP STATS'][0]['stats']\n",
    "xg_score = [stat for stat in top_stats if stat['title'] == 'Expected goals (xG)'][0]['stats']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'4.44 xG - 0.59 xG'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xg_scoreline = xg_score[0] + ' xG - ' + xg_score[1] + ' xG'\n",
    "xg_scoreline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'reactKey': '48Card69297undefinedfalse',\n",
       "  'timeStr': 48,\n",
       "  'type': 'Card',\n",
       "  'time': 48,\n",
       "  'overloadTime': None,\n",
       "  'eventId': 9525968,\n",
       "  'player': {'id': 69297,\n",
       "   'name': 'Nikolai Topor-Stanley',\n",
       "   'profileUrl': '/players/69297/nikolai-topor-stanley'},\n",
       "  'profileUrl': '/players/69297/nikolai-topor-stanley',\n",
       "  'overloadTimeStr': False,\n",
       "  'isHome': False,\n",
       "  'nameStr': 'Nikolai Topor-Stanley',\n",
       "  'card': 'Red'}]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_cards = [event for event in match_summary['content']['matchFacts']['events']['events'] if event['type'] == 'Card']\n",
    "red_cards = [card for card in all_cards if card['card'] == 'Red']\n",
    "red_cards"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[48, 'Nikolai Topor-Stanley', 1079464]]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "red_cards_to_plot = [[red_card['time'], red_card['player']['name'], home_team_id if red_card['isHome'] else away_team_id] for red_card in red_cards]\n",
    "red_cards_to_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "shot_key_details = [(shot_summary['min'], shot_summary['expectedGoals'], shot_summary['eventType'], shot_summary['playerName'], shot_summary['teamId']) for shot_summary in shot_summary]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "team_colours = {}\n",
    "team_colours[home_team_id] = COLOUR_BLUE\n",
    "team_colours[away_team_id] = COLOUR_YELLOW"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# insert zero to start\n",
    "for team_id in [home_team_id, away_team_id]:\n",
    "    shot_key_details.insert(0, (0, 0, 'Kick off', np.nan, team_id))\n",
    "    shot_key_details.insert(0, (0, 0, 'Kick off', np.nan, team_id))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_shots = pd.DataFrame(shot_key_details, columns=['minute', 'xG', 'event', 'player', 'team'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_shots['goal'] = np.where(df_shots['event']=='Goal', 1, 0)\n",
    "df_shots['team_cumulative_xg'] = df_shots[['team', 'xG']].groupby('team').cumsum()\n",
    "df_shots['team_cumulative_goal'] = df_shots[['team', 'goal']].groupby('team').cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>minute</th>\n",
       "      <th>xG</th>\n",
       "      <th>event</th>\n",
       "      <th>player</th>\n",
       "      <th>team</th>\n",
       "      <th>goal</th>\n",
       "      <th>team_cumulative_xg</th>\n",
       "      <th>team_cumulative_goal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Kick off</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1079464</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Kick off</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1079464</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Kick off</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Kick off</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>0.081437</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Maximilien Balard</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.081437</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>0.088022</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Nectarios Triantis</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.169459</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>0.059210</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Maximilien Balard</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.228669</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6</td>\n",
       "      <td>0.025100</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Thomas Aquilina</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.253770</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>6</td>\n",
       "      <td>0.144657</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Brian Kaltak</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.398426</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>11</td>\n",
       "      <td>0.048227</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Jason Cummings</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.446654</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>12</td>\n",
       "      <td>0.035218</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Thomas Aquilina</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.481871</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>14</td>\n",
       "      <td>0.029181</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Samuel Silvera</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.511053</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>15</td>\n",
       "      <td>0.190903</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Storm Roux</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.701956</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>17</td>\n",
       "      <td>0.374564</td>\n",
       "      <td>Goal</td>\n",
       "      <td>Nicolas Milanovic</td>\n",
       "      <td>1079464</td>\n",
       "      <td>1</td>\n",
       "      <td>0.374564</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>24</td>\n",
       "      <td>0.029283</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Joshua Risdon</td>\n",
       "      <td>1079464</td>\n",
       "      <td>0</td>\n",
       "      <td>0.403847</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>28</td>\n",
       "      <td>0.136766</td>\n",
       "      <td>Goal</td>\n",
       "      <td>Connor Pain</td>\n",
       "      <td>1079464</td>\n",
       "      <td>1</td>\n",
       "      <td>0.540612</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>34</td>\n",
       "      <td>0.041048</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Jason Cummings</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.743004</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>42</td>\n",
       "      <td>0.036378</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Marco Tulio</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>0.779382</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>42</td>\n",
       "      <td>0.515701</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Jason Cummings</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>1.295083</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>45</td>\n",
       "      <td>0.080323</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Marco Tulio</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>1.375407</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>54</td>\n",
       "      <td>0.105703</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Jason Cummings</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>1.481109</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>63</td>\n",
       "      <td>0.081854</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Beni Nkololo</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>1.562964</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>67</td>\n",
       "      <td>0.041808</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Garang Kuol</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>1.604772</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>67</td>\n",
       "      <td>0.886792</td>\n",
       "      <td>Goal</td>\n",
       "      <td>Jason Cummings</td>\n",
       "      <td>8164</td>\n",
       "      <td>1</td>\n",
       "      <td>2.491564</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>70</td>\n",
       "      <td>0.152142</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Paul Ayongo</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>2.643706</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>70</td>\n",
       "      <td>0.083583</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Paul Ayongo</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>2.727289</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>73</td>\n",
       "      <td>0.053629</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Thomas Aquilina</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>2.780919</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>74</td>\n",
       "      <td>0.231268</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Jason Cummings</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>3.012187</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>74</td>\n",
       "      <td>0.912041</td>\n",
       "      <td>Goal</td>\n",
       "      <td>Beni Nkololo</td>\n",
       "      <td>8164</td>\n",
       "      <td>1</td>\n",
       "      <td>3.924228</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>76</td>\n",
       "      <td>0.076217</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Joshua Nisbet</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>4.000445</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>78</td>\n",
       "      <td>0.096831</td>\n",
       "      <td>Goal</td>\n",
       "      <td>Jacob Farrell</td>\n",
       "      <td>8164</td>\n",
       "      <td>1</td>\n",
       "      <td>4.097276</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>81</td>\n",
       "      <td>0.018037</td>\n",
       "      <td>AttemptSaved</td>\n",
       "      <td>Garang Kuol</td>\n",
       "      <td>8164</td>\n",
       "      <td>0</td>\n",
       "      <td>4.115314</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>88</td>\n",
       "      <td>0.392924</td>\n",
       "      <td>Goal</td>\n",
       "      <td>Paul Ayongo</td>\n",
       "      <td>8164</td>\n",
       "      <td>1</td>\n",
       "      <td>4.508238</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>90</td>\n",
       "      <td>0.049119</td>\n",
       "      <td>Miss</td>\n",
       "      <td>Alessandro Diamanti</td>\n",
       "      <td>1079464</td>\n",
       "      <td>0</td>\n",
       "      <td>0.589732</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    minute        xG         event               player     team  goal  \\\n",
       "0        0  0.000000      Kick off                  NaN  1079464     0   \n",
       "1        0  0.000000      Kick off                  NaN  1079464     0   \n",
       "2        0  0.000000      Kick off                  NaN     8164     0   \n",
       "3        0  0.000000      Kick off                  NaN     8164     0   \n",
       "4        3  0.081437          Miss    Maximilien Balard     8164     0   \n",
       "5        6  0.088022          Miss   Nectarios Triantis     8164     0   \n",
       "6        6  0.059210          Miss    Maximilien Balard     8164     0   \n",
       "7        6  0.025100  AttemptSaved      Thomas Aquilina     8164     0   \n",
       "8        6  0.144657  AttemptSaved         Brian Kaltak     8164     0   \n",
       "9       11  0.048227  AttemptSaved       Jason Cummings     8164     0   \n",
       "10      12  0.035218  AttemptSaved      Thomas Aquilina     8164     0   \n",
       "11      14  0.029181  AttemptSaved       Samuel Silvera     8164     0   \n",
       "12      15  0.190903          Miss           Storm Roux     8164     0   \n",
       "13      17  0.374564          Goal    Nicolas Milanovic  1079464     1   \n",
       "14      24  0.029283          Miss        Joshua Risdon  1079464     0   \n",
       "15      28  0.136766          Goal          Connor Pain  1079464     1   \n",
       "16      34  0.041048  AttemptSaved       Jason Cummings     8164     0   \n",
       "17      42  0.036378  AttemptSaved          Marco Tulio     8164     0   \n",
       "18      42  0.515701  AttemptSaved       Jason Cummings     8164     0   \n",
       "19      45  0.080323          Miss          Marco Tulio     8164     0   \n",
       "20      54  0.105703  AttemptSaved       Jason Cummings     8164     0   \n",
       "21      63  0.081854          Miss         Beni Nkololo     8164     0   \n",
       "22      67  0.041808  AttemptSaved          Garang Kuol     8164     0   \n",
       "23      67  0.886792          Goal       Jason Cummings     8164     1   \n",
       "24      70  0.152142  AttemptSaved          Paul Ayongo     8164     0   \n",
       "25      70  0.083583  AttemptSaved          Paul Ayongo     8164     0   \n",
       "26      73  0.053629          Miss      Thomas Aquilina     8164     0   \n",
       "27      74  0.231268  AttemptSaved       Jason Cummings     8164     0   \n",
       "28      74  0.912041          Goal         Beni Nkololo     8164     1   \n",
       "29      76  0.076217          Miss        Joshua Nisbet     8164     0   \n",
       "30      78  0.096831          Goal        Jacob Farrell     8164     1   \n",
       "31      81  0.018037  AttemptSaved          Garang Kuol     8164     0   \n",
       "32      88  0.392924          Goal          Paul Ayongo     8164     1   \n",
       "33      90  0.049119          Miss  Alessandro Diamanti  1079464     0   \n",
       "\n",
       "    team_cumulative_xg  team_cumulative_goal  \n",
       "0             0.000000                     0  \n",
       "1             0.000000                     0  \n",
       "2             0.000000                     0  \n",
       "3             0.000000                     0  \n",
       "4             0.081437                     0  \n",
       "5             0.169459                     0  \n",
       "6             0.228669                     0  \n",
       "7             0.253770                     0  \n",
       "8             0.398426                     0  \n",
       "9             0.446654                     0  \n",
       "10            0.481871                     0  \n",
       "11            0.511053                     0  \n",
       "12            0.701956                     0  \n",
       "13            0.374564                     1  \n",
       "14            0.403847                     1  \n",
       "15            0.540612                     2  \n",
       "16            0.743004                     0  \n",
       "17            0.779382                     0  \n",
       "18            1.295083                     0  \n",
       "19            1.375407                     0  \n",
       "20            1.481109                     0  \n",
       "21            1.562964                     0  \n",
       "22            1.604772                     0  \n",
       "23            2.491564                     1  \n",
       "24            2.643706                     1  \n",
       "25            2.727289                     1  \n",
       "26            2.780919                     1  \n",
       "27            3.012187                     1  \n",
       "28            3.924228                     2  \n",
       "29            4.000445                     2  \n",
       "30            4.097276                     3  \n",
       "31            4.115314                     3  \n",
       "32            4.508238                     4  \n",
       "33            0.589732                     2  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_shots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "for red_card in red_cards_to_plot:\n",
    "    team = red_card[2]\n",
    "    minute = red_card[0]\n",
    "    df_shots_team_before_card = df_shots[(df_shots['team']==team) & (df_shots['minute']<=minute)]\n",
    "    team_xg_at_time_of_card = df_shots_team_before_card['team_cumulative_xg'].max()\n",
    "    red_card.append(team_xg_at_time_of_card)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[48, 'Nikolai Topor-Stanley', 1079464, 0.5406124591827393]]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "red_cards_to_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,6))\n",
    "\n",
    "for team in set(df_shots['team']):\n",
    "    colour = team_colours[team]\n",
    "    df_team_shots = df_shots[df_shots['team']==team]\n",
    "    df_team_goals = df_team_shots[df_team_shots['goal']==1]\n",
    "    red_cards_for_team = [red_card for red_card in red_cards_to_plot if red_card[2] == team]\n",
    "    ax.step(df_team_shots['minute'], df_team_shots['team_cumulative_xg'], where='post', color=colour, zorder=1)\n",
    "    ax.scatter(df_team_goals['minute'], df_team_goals['team_cumulative_xg'], s=100, color=colour, zorder=2)\n",
    "    for red_card in red_cards_for_team:\n",
    "        ax.scatter(red_card[0], red_card[3], s=100, color='red', marker='s', zorder=3)\n",
    "\n",
    "ax.set_xlim(xmin=0, xmax=90)\n",
    "ax.set_ylim(ymin=0)\n",
    "ax.set_ylabel('Cumulative xG')\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['left'].set_color(COLOUR_ALMOST_BLACK)\n",
    "ax.spines['bottom'].set_color(COLOUR_ALMOST_BLACK)\n",
    "\n",
    "fig.patch.set_color(COLOUR_BACKGROUND)\n",
    "ax.patch.set_color(COLOUR_BACKGROUND)\n",
    "\n",
    "plot_title = home_team + ' v ' + away_team + '\\n' + match_result + ' (' + xg_scoreline + ')' + '\\n' + round_name \n",
    "\n",
    "fig.suptitle(plot_title, ha='left', x=0.10, size=14, color=COLOUR_ALMOST_BLACK)\n",
    "\n",
    "fig.tight_layout()\n",
    "\n",
    "fig.savefig('img/temp.pdf', bbox_inches='tight')"
   ]
  }
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