FBREF League & Team Data Exploration.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Intro to using beautiful soup to scrape web football data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Install these Dependecies to ensure the code runs. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting beautifulsoup4\n",
      "  Downloading beautifulsoup4-4.10.0-py3-none-any.whl (97 kB)\n",
      "     |████████████████████████████████| 97 kB 13.1 MB/s            \n",
      "\u001b[?25hCollecting soupsieve>1.2\n",
      "  Downloading soupsieve-2.3.1-py3-none-any.whl (37 kB)\n",
      "Installing collected packages: soupsieve, beautifulsoup4\n",
      "Successfully installed beautifulsoup4-4.10.0 soupsieve-2.3.1\n",
      "\u001b[33mWARNING: You are using pip version 21.3.1; however, version 22.0.4 is available.\n",
      "You should consider upgrading via the '/usr/local/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "# pip install beautifulsoup4\n",
    "# pip install highlight-text\n",
    "# pip install adjustText\n",
    "# pip install tabulate\n",
    "\n",
    "# FIX LOGOS ON FINAL VIZ & CLEAN CODE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## We will now want to import all the necessary packages require for scraping and analysis:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import requests\n",
    "import pandas as pd\n",
    "from bs4 import BeautifulSoup\n",
    "import seaborn as sb\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import warnings\n",
    "import numpy as np\n",
    "from math import pi\n",
    "from urllib.request import urlopen\n",
    "import matplotlib.patheffects as pe\n",
    "from highlight_text import fig_text\n",
    "from adjustText import adjust_text\n",
    "from tabulate import tabulate\n",
    "import matplotlib.style as style\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_squadlist(url):\n",
    "    html = requests.get(url).text\n",
    "    data = BeautifulSoup(html, 'html5')\n",
    "    table = data.find('table')\n",
    "    cols = []\n",
    "\n",
    "    for header in table.find_all('th'):\n",
    "        cols.append(header.string)\n",
    "\n",
    "    columns = cols[8:37] #gets necessary column headers\n",
    "    players = cols[37:-2]\n",
    "\n",
    "    #display(columns)\n",
    "    rows = [] #initliaze list to store all rows of data\n",
    "    for rownum, row in enumerate(table.find_all('tr')): #find all rows in table\n",
    "        if len(row.find_all('td')) > 0: \n",
    "            rowdata = [] #initiliaze list of row data\n",
    "            for i in range(0,len(row.find_all('td'))): #get all column values for row\n",
    "                rowdata.append(row.find_all('td')[i].text)\n",
    "            rows.append(rowdata)\n",
    "    df = pd.DataFrame(rows, columns=columns)\n",
    "\n",
    "    df.drop(df.tail(2).index,inplace=True)\n",
    "    df[\"Player\"] = players\n",
    "    df.drop('Matches', axis=1, inplace=True)\n",
    "    df['Nation'] = df['Nation'].str[3:]\n",
    "    # df[\"team\"] = name\n",
    "    df.set_index(\"Player\")\n",
    "\n",
    "    return df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Nation</th>\n",
       "      <th>Pos</th>\n",
       "      <th>Age</th>\n",
       "      <th>MP</th>\n",
       "      <th>Starts</th>\n",
       "      <th>Min</th>\n",
       "      <th>90s</th>\n",
       "      <th>Gls</th>\n",
       "      <th>Ast</th>\n",
       "      <th>G-PK</th>\n",
       "      <th>...</th>\n",
       "      <th>xG</th>\n",
       "      <th>npxG</th>\n",
       "      <th>xA</th>\n",
       "      <th>npxG+xA</th>\n",
       "      <th>xG</th>\n",
       "      <th>xA</th>\n",
       "      <th>xG+xA</th>\n",
       "      <th>npxG</th>\n",
       "      <th>npxG+xA</th>\n",
       "      <th>Player</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BRA</td>\n",
       "      <td>DF</td>\n",
       "      <td>24-247</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>270</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.06</td>\n",
       "      <td>Gabriel Dos Santos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GHA</td>\n",
       "      <td>MF</td>\n",
       "      <td>29-071</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>270</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.11</td>\n",
       "      <td>Thomas Partey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ENG</td>\n",
       "      <td>GK</td>\n",
       "      <td>24-101</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>270</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>Aaron Ramsdale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FRA</td>\n",
       "      <td>DF</td>\n",
       "      <td>21-152</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>270</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>William Saliba</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SUI</td>\n",
       "      <td>MF</td>\n",
       "      <td>29-330</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>267</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.28</td>\n",
       "      <td>Granit Xhaka</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Nation Pos     Age MP Starts  Min  90s Gls Ast G-PK         ...          \\\n",
       "0    BRA  DF  24-247  3      3  270  3.0   0   0    0         ...           \n",
       "1    GHA  MF  29-071  3      3  270  3.0   0   0    0         ...           \n",
       "2    ENG  GK  24-101  3      3  270  3.0   0   0    0         ...           \n",
       "3    FRA  DF  21-152  3      3  270  3.0   1   0    1         ...           \n",
       "4    SUI  MF  29-330  3      3  267  3.0   1   2    1         ...           \n",
       "\n",
       "    xG npxG   xA npxG+xA    xG    xA xG+xA  npxG npxG+xA              Player  \n",
       "0  0.2  0.2  0.0     0.2  0.06  0.00  0.06  0.06    0.06  Gabriel Dos Santos  \n",
       "1  0.3  0.3  0.0     0.3  0.11  0.00  0.11  0.11    0.11       Thomas Partey  \n",
       "2  0.0  0.0  0.0     0.0  0.00  0.00  0.00  0.00    0.00      Aaron Ramsdale  \n",
       "3  0.1  0.1  0.0     0.1  0.02  0.00  0.02  0.02    0.02      William Saliba  \n",
       "4  0.6  0.6  0.3     0.8  0.20  0.09  0.28  0.20    0.28        Granit Xhaka  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "team = \"https://fbref.com/en/squads/18bb7c10/Arsenal-Stats\"\n",
    "team_name = team[37:-6]\n",
    "squad_stats_per_team = generate_squadlist(team)\n",
    "squad_stats_per_team = squad_stats_per_team[squad_stats_per_team['90s'].notnull()]\n",
    "squad_stats_per_team.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def years_converter(variable_value):\n",
    "    years = variable_value[:-4]\n",
    "    days = variable_value[3:]\n",
    "    years_value = pd.to_numeric(years)\n",
    "    days_value = pd.to_numeric(days)\n",
    "    day_conv = days_value/365\n",
    "    final_val = years_value + day_conv\n",
    "\n",
    "    return final_val\n",
    "# squad_stats_per_team['age_new'] = squad_stats_per_team.apply(lambda x: years_converter(x['Age']), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def squad_age_profile_chart(df, team_name):\n",
    "        df[[\"Age\",\"90s\"]] = df[[\"Age\",\"90s\"]].apply(pd.to_numeric)\n",
    "\n",
    "        df[\"Min_pct\"] = 100*df[\"90s\"]/len(df)##number of matches in a Serie A season\n",
    "        df = df.dropna(subset=[\"Age\", \"Min_pct\"])\n",
    "        df = df.loc[:len(df)-1, :]\n",
    "        df[[\"Player\", \"Pos\", \"Age\", \"Min_pct\"]].head()\n",
    "\n",
    "        line_color = \"silver\"\n",
    "        marker_color = \"dodgerblue\"\n",
    "        fig, ax = plt.subplots(figsize=(12, 8)) \n",
    "\n",
    "        # plt.style.use('https://github.com/dhaitz/matplotlib-stylesheets/raw/master/pitayasmoothie-dark.mplstyle')\n",
    "        style.use('fivethirtyeight')\n",
    "        ax.scatter(df[\"Age\"], df[\"Min_pct\"],alpha=0.8) ##scatter points\n",
    "        ax.fill([24, 29, 29, 24], [-6, -6, 106, 106], color='limegreen',\n",
    "                alpha=0.3, zorder=2) ##the peak age shaded region\n",
    "        ax.text(26.5, 55, \"PEAK\", color=line_color, zorder=3, \n",
    "                alpha=2, fontsize=26, rotation=90, ha='center',\n",
    "                va='center', fontweight='bold') ## `PEAK` age text\n",
    "        texts = [] ##plot player names\n",
    "        for row in df.itertuples():\n",
    "                texts.append(ax.text(row.Age, row.Min_pct, row.Player, fontsize=8, ha='center', va='center', zorder=10))\n",
    "                adjust_text(texts,force_text=(2, 2),\n",
    "            arrowprops=dict(arrowstyle='-',color='red'),\n",
    "            autoalign='y',\n",
    "            only_move={'points':'y','text':'y'}) ## to remove overlaps between labels\n",
    "\n",
    "        ## update plot\n",
    "                ax.set(xlabel=\"Age\", ylabel=\"Share of Minutes Played %\", ylim=(-5, 105), xlim=(16, 40)) ## set labels and limits\n",
    "\n",
    "        ##grids and spines\n",
    "        ax.grid(color=line_color, linestyle='--', linewidth=0.8, alpha=0.5)   \n",
    "        for spine in [\"top\", \"right\"]:\n",
    "                ax.spines[spine].set_visible(False)\n",
    "                ax.spines[spine].set_color(line_color)\n",
    "        # ax.yaxis.set_major_formatter(mtick.PercentFormatter())\n",
    "        ax.xaxis.set_ticks(range(16, 44, 4)) ##fix the tick frequency \n",
    "        ax.xaxis.label.set(fontsize=10)\n",
    "        ax.yaxis.label.set(fontsize=10) ## increase the weight of the axis labels\n",
    "\n",
    "        ax.set_position([0.08, 0.08, 0.82, 0.78]) ## make space for the title on top of the axes\n",
    "\n",
    "        ## title and subtitle\n",
    "        fig.text(x=0.08, y=0.92, s=f\"{team_name} | Squad Age Profile\", \n",
    "                ha='left', fontsize=20, fontweight='book') \n",
    "        fig.text(x=0.08, y=0.88, s=f\"EPL | 2021-22\", ha='left', \n",
    "                fontsize=20, fontweight='book')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "squad_age_profile_chart(squad_stats_per_team,team_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def team_fixture_data(x):\n",
    "    url = x\n",
    "    page = urlopen(url).read()\n",
    "    soup = BeautifulSoup(page)\n",
    "    count = 0 \n",
    "    table = soup.find(\"tbody\")\n",
    "\n",
    "    pre_df = dict()\n",
    "    features_wanted =  {\"date\" , \"time\",\"comp\",\"Round\",\"dayofweek\", \"venue\",\"result\",\"goals_for\",\"goals_against\",\"opponent\",\"xg_for\",\"xg_against\",\"possession\",\"attendance\",\"captain\", \"formation\",\"referee\"} #add more features here!!\n",
    "    rows = table.find_all('tr')\n",
    "    for row in rows:\n",
    "        for f in features_wanted:\n",
    "            if (row.find('th', {\"scope\":\"row\"}) != None) & (row.find(\"td\",{\"data-stat\": f}) != None):\n",
    "                cell = row.find(\"td\",{\"data-stat\": f})\n",
    "                a = cell.text.strip().encode()\n",
    "                text=a.decode(\"utf-8\")\n",
    "                if f in pre_df:\n",
    "                    pre_df[f].append(text)\n",
    "                else:\n",
    "                    pre_df[f]=[text]\n",
    "                \n",
    "    df = pd.DataFrame.from_dict(pre_df)\n",
    "    return df \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>result</th>\n",
       "      <th>xg_for</th>\n",
       "      <th>referee</th>\n",
       "      <th>goals_against</th>\n",
       "      <th>possession</th>\n",
       "      <th>time</th>\n",
       "      <th>venue</th>\n",
       "      <th>goals_for</th>\n",
       "      <th>formation</th>\n",
       "      <th>xg_against</th>\n",
       "      <th>captain</th>\n",
       "      <th>opponent</th>\n",
       "      <th>attendance</th>\n",
       "      <th>dayofweek</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>L</td>\n",
       "      <td>1.4</td>\n",
       "      <td>Michael Oliver</td>\n",
       "      <td>2</td>\n",
       "      <td>66</td>\n",
       "      <td>20:00</td>\n",
       "      <td>Away</td>\n",
       "      <td>0</td>\n",
       "      <td>4-2-3-1</td>\n",
       "      <td>1.3</td>\n",
       "      <td>Granit Xhaka</td>\n",
       "      <td>Brentford</td>\n",
       "      <td>16,479</td>\n",
       "      <td>Fri</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>L</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Paul Tierney</td>\n",
       "      <td>2</td>\n",
       "      <td>35</td>\n",
       "      <td>16:30</td>\n",
       "      <td>Home</td>\n",
       "      <td>0</td>\n",
       "      <td>4-2-3-1</td>\n",
       "      <td>2.9</td>\n",
       "      <td>Granit Xhaka</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>58,729</td>\n",
       "      <td>Sun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>L</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Martin Atkinson</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>12:30</td>\n",
       "      <td>Away</td>\n",
       "      <td>0</td>\n",
       "      <td>3-4-3</td>\n",
       "      <td>3.8</td>\n",
       "      <td>Pierre-Emerick Aubameyang</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>52,276</td>\n",
       "      <td>Sat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>W</td>\n",
       "      <td>2.8</td>\n",
       "      <td>Michael Oliver</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>15:00</td>\n",
       "      <td>Home</td>\n",
       "      <td>1</td>\n",
       "      <td>4-2-3-1</td>\n",
       "      <td>0.6</td>\n",
       "      <td>Pierre-Emerick Aubameyang</td>\n",
       "      <td>Norwich City</td>\n",
       "      <td>58,000</td>\n",
       "      <td>Sat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>W</td>\n",
       "      <td>1.2</td>\n",
       "      <td>Anthony Taylor</td>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>15:00</td>\n",
       "      <td>Away</td>\n",
       "      <td>1</td>\n",
       "      <td>4-1-4-1</td>\n",
       "      <td>1.3</td>\n",
       "      <td>Pierre-Emerick Aubameyang</td>\n",
       "      <td>Burnley</td>\n",
       "      <td>20,000</td>\n",
       "      <td>Sat</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  result xg_for          referee goals_against possession   time venue  \\\n",
       "0      L    1.4   Michael Oliver             2         66  20:00  Away   \n",
       "1      L    0.3     Paul Tierney             2         35  16:30  Home   \n",
       "2      L    0.1  Martin Atkinson             5         20  12:30  Away   \n",
       "3      W    2.8   Michael Oliver             0         52  15:00  Home   \n",
       "4      W    1.2   Anthony Taylor             0         54  15:00  Away   \n",
       "\n",
       "  goals_for formation xg_against                    captain         opponent  \\\n",
       "0         0   4-2-3-1        1.3               Granit Xhaka        Brentford   \n",
       "1         0   4-2-3-1        2.9               Granit Xhaka          Chelsea   \n",
       "2         0     3-4-3        3.8  Pierre-Emerick Aubameyang  Manchester City   \n",
       "3         1   4-2-3-1        0.6  Pierre-Emerick Aubameyang     Norwich City   \n",
       "4         1   4-1-4-1        1.3  Pierre-Emerick Aubameyang          Burnley   \n",
       "\n",
       "  attendance dayofweek  \n",
       "0     16,479       Fri  \n",
       "1     58,729       Sun  \n",
       "2     52,276       Sat  \n",
       "3     58,000       Sat  \n",
       "4     20,000       Sat  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "league_results = team_fixture_data(\"https://fbref.com/en/squads/18bb7c10/2021-2022/matchlogs/s11160/schedule/Arsenal-Scores-and-Fixtures-Premier-League\")\n",
    "# league_results = league_results.loc[(league_results['captain'] != '') & (league_results['comp'] == 'Serie A')]\n",
    "league_results.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_xg_analysis_chart(df):\n",
    "        window = 5\n",
    "        gd_color = \"green\"\n",
    "        xgd_color = \"blue\"\n",
    "        line_color = \"silver\"\n",
    "\n",
    "\n",
    "        df[[\"goals_for\",\"xg_for\",\"xg_against\",\"goals_against\"]] = df[[\"goals_for\",\"xg_for\",\"xg_against\",\"goals_against\"]].apply(pd.to_numeric)\n",
    "\n",
    "        df[\"GD\"] = df[\"goals_for\"] - df[\"goals_against\"]\n",
    "        df[\"xGD\"] = df[\"xg_for\"] - df[\"xg_against\"]\n",
    "\n",
    "        gd_rolling = df[\"GD\"].rolling(window).mean().values[window:]\n",
    "        xgd_rolling = df[\"xGD\"].rolling(window).mean().values[window:]\n",
    "\n",
    "        style.use('fivethirtyeight')\n",
    "        fig, ax = plt.subplots(figsize=(12, 8))\n",
    "\n",
    "        ax.plot(gd_rolling, color=gd_color,  linestyle=\"-.\", marker=\"o\",  mfc=gd_color, mec=\"white\", markersize=5, mew=0.4, zorder=10,linewidth=2)  ##goal-difference\n",
    "        ax.plot(xgd_rolling, color=xgd_color,  linestyle=\"-.\", marker = \"o\", mfc=xgd_color, mec=\"white\", markersize=5, mew=0.4, zorder=10, linewidth=2) ##expected goals difference\n",
    "\n",
    "        ax.fill_between(x=range(len(gd_rolling)), y1=gd_rolling, y2=xgd_rolling, where = gd_rolling>xgd_rolling, \n",
    "                        alpha=0.2, color=gd_color, interpolate=True, zorder=5) ##shade the areas in between\n",
    "        ax.fill_between(x=range(len(gd_rolling)), y1=gd_rolling, y2=xgd_rolling, where = gd_rolling<=xgd_rolling, \n",
    "                        alpha=0.2, color=xgd_color, interpolate=True, zorder=5)\n",
    "\n",
    "        ax.grid(color=line_color, linestyle='--', linewidth=0.8, alpha=0.5)   \n",
    "        for spine in [\"top\", \"right\"]:\n",
    "                ax.spines[spine].set_visible(False)\n",
    "                ax.spines[spine].set_color(line_color)\n",
    "        # ax.yaxis.set_major_formatter(mtick.PercentFormatter())\n",
    "        ax.xaxis.set_ticks(range(1, 44, 4)) ##fix the tick frequency \n",
    "        ax.xaxis.label.set(fontsize=10)\n",
    "        ax.yaxis.label.set(fontsize=10) ## increase the weight of the axis labels\n",
    "\n",
    "        ax.set_position([0.08, 0.08, 0.82, 0.78]) ## make       \n",
    "\n",
    "        ## labels, titles and subtitles\n",
    "        ax.set(xlabel=f\"{window} match rolling mean\", xlim=(-1, len(df)-window))     \n",
    "        ax.xaxis.label.set(fontsize=12)    \n",
    "\n",
    "        fig.text(x=0.08, y=0.92, s=f\"{team_name} | Performance Trend\", \n",
    "                ha='left', fontsize=24)   \n",
    "\n",
    "        fig_text(x=0.08, y=0.90, ha='left',\n",
    "                fontsize=18,\n",
    "                s='2021-22 | <Goal Difference> vs <Expected Goal Difference>',\n",
    "                highlight_textprops=[{\"color\": gd_color},\n",
    "                                        {\"color\": xgd_color}])\n",
    "        \n",
    "#     fig.savefig(\"xg-trend-line-chart\", dpi=180) ##save image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "generate_xg_analysis_chart(league_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_league_data(x):\n",
    "    url = x\n",
    "    page = urlopen(url).read()\n",
    "    soup = BeautifulSoup(page)\n",
    "    count = 0 \n",
    "    table = soup.find(\"tbody\")\n",
    "\n",
    "    pre_df = dict()\n",
    "    features_wanted =  {\"team\" , \"games\",\"wins\",\"draws\",\"losses\", \"goals_for\",\"goals_against\", \"points\", \"xg_for\",\"xg_against\",\"xg_diff\",\"attendance\",\"xg_diff_per90\", \"last_5\"} #add more features here!!\n",
    "    rows = table.find_all('tr')\n",
    "    for row in rows:\n",
    "        for f in features_wanted:\n",
    "            if (row.find('th', {\"scope\":\"row\"}) != None) & (row.find(\"td\",{\"data-stat\": f}) != None):\n",
    "                cell = row.find(\"td\",{\"data-stat\": f})\n",
    "                a = cell.text.strip().encode()\n",
    "                text=a.decode(\"utf-8\")\n",
    "                if f in pre_df:\n",
    "                    pre_df[f].append(text)\n",
    "                else:\n",
    "                    pre_df[f]=[text]\n",
    "                \n",
    "    df = pd.DataFrame.from_dict(pre_df)\n",
    "    df[\"games\"] = pd.to_numeric(df[\"games\"])\n",
    "    df[\"xg_diff_per90\"] = pd.to_numeric(df[\"xg_diff_per90\"])\n",
    "    df[\"minutes_played\"] = df[\"games\"] *90\n",
    "    return(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>losses</th>\n",
       "      <th>goals_against</th>\n",
       "      <th>team</th>\n",
       "      <th>xg_diff_per90</th>\n",
       "      <th>xg_against</th>\n",
       "      <th>last_5</th>\n",
       "      <th>goals_for</th>\n",
       "      <th>xg_diff</th>\n",
       "      <th>wins</th>\n",
       "      <th>games</th>\n",
       "      <th>xg_for</th>\n",
       "      <th>points</th>\n",
       "      <th>minutes_played</th>\n",
       "      <th>path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Arsenal</td>\n",
       "      <td>1.18</td>\n",
       "      <td>1.8</td>\n",
       "      <td>W W W</td>\n",
       "      <td>9</td>\n",
       "      <td>+3.5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5.4</td>\n",
       "      <td>9</td>\n",
       "      <td>270</td>\n",
       "      <td>Arsenal.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>1.45</td>\n",
       "      <td>2.3</td>\n",
       "      <td>W W D</td>\n",
       "      <td>9</td>\n",
       "      <td>+4.3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7</td>\n",
       "      <td>270</td>\n",
       "      <td>Manchester City.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Leeds United</td>\n",
       "      <td>0.52</td>\n",
       "      <td>3.0</td>\n",
       "      <td>W D W</td>\n",
       "      <td>7</td>\n",
       "      <td>+1.6</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4.6</td>\n",
       "      <td>7</td>\n",
       "      <td>270</td>\n",
       "      <td>Leeds United.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Tottenham</td>\n",
       "      <td>0.46</td>\n",
       "      <td>2.8</td>\n",
       "      <td>W D W</td>\n",
       "      <td>7</td>\n",
       "      <td>+1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4.1</td>\n",
       "      <td>7</td>\n",
       "      <td>270</td>\n",
       "      <td>Tottenham.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Brighton</td>\n",
       "      <td>0.54</td>\n",
       "      <td>2.6</td>\n",
       "      <td>W D W</td>\n",
       "      <td>4</td>\n",
       "      <td>+1.6</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4.2</td>\n",
       "      <td>7</td>\n",
       "      <td>270</td>\n",
       "      <td>Brighton.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Newcastle Utd</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>4.1</td>\n",
       "      <td>W D D</td>\n",
       "      <td>5</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5</td>\n",
       "      <td>270</td>\n",
       "      <td>Newcastle Utd.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>0.10</td>\n",
       "      <td>4.1</td>\n",
       "      <td>D D W</td>\n",
       "      <td>5</td>\n",
       "      <td>+0.3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4.4</td>\n",
       "      <td>5</td>\n",
       "      <td>270</td>\n",
       "      <td>Fulham.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Brentford</td>\n",
       "      <td>0.16</td>\n",
       "      <td>3.2</td>\n",
       "      <td>D W L</td>\n",
       "      <td>8</td>\n",
       "      <td>+0.5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3.7</td>\n",
       "      <td>4</td>\n",
       "      <td>270</td>\n",
       "      <td>Brentford.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>0.53</td>\n",
       "      <td>4.0</td>\n",
       "      <td>L D W</td>\n",
       "      <td>4</td>\n",
       "      <td>+1.6</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5.5</td>\n",
       "      <td>4</td>\n",
       "      <td>270</td>\n",
       "      <td>Crystal Palace.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Nott'ham Forest</td>\n",
       "      <td>-1.06</td>\n",
       "      <td>5.9</td>\n",
       "      <td>L W D</td>\n",
       "      <td>2</td>\n",
       "      <td>-3.2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4</td>\n",
       "      <td>270</td>\n",
       "      <td>Nott'ham Forest.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>-0.52</td>\n",
       "      <td>3.8</td>\n",
       "      <td>L D W</td>\n",
       "      <td>5</td>\n",
       "      <td>-1.6</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>4</td>\n",
       "      <td>270</td>\n",
       "      <td>Southampton.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>0.09</td>\n",
       "      <td>3.5</td>\n",
       "      <td>W D L</td>\n",
       "      <td>3</td>\n",
       "      <td>+0.3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3.7</td>\n",
       "      <td>4</td>\n",
       "      <td>270</td>\n",
       "      <td>Chelsea.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>Aston Villa</td>\n",
       "      <td>-0.51</td>\n",
       "      <td>5.0</td>\n",
       "      <td>L W L</td>\n",
       "      <td>3</td>\n",
       "      <td>-1.5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3</td>\n",
       "      <td>270</td>\n",
       "      <td>Aston Villa.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>Manchester Utd</td>\n",
       "      <td>-0.24</td>\n",
       "      <td>4.9</td>\n",
       "      <td>L L W</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4.1</td>\n",
       "      <td>3</td>\n",
       "      <td>270</td>\n",
       "      <td>Manchester Utd.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>Bournemouth</td>\n",
       "      <td>-1.03</td>\n",
       "      <td>4.0</td>\n",
       "      <td>W L L</td>\n",
       "      <td>2</td>\n",
       "      <td>-3.1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.9</td>\n",
       "      <td>3</td>\n",
       "      <td>270</td>\n",
       "      <td>Bournemouth.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>0.21</td>\n",
       "      <td>4.5</td>\n",
       "      <td>D D L</td>\n",
       "      <td>4</td>\n",
       "      <td>+0.6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>5.1</td>\n",
       "      <td>2</td>\n",
       "      <td>270</td>\n",
       "      <td>Liverpool.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>Everton</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>4.3</td>\n",
       "      <td>L L D</td>\n",
       "      <td>2</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1</td>\n",
       "      <td>270</td>\n",
       "      <td>Everton.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Wolves</td>\n",
       "      <td>-0.21</td>\n",
       "      <td>3.4</td>\n",
       "      <td>L D L</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1</td>\n",
       "      <td>270</td>\n",
       "      <td>Wolves.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>Leicester City</td>\n",
       "      <td>-0.76</td>\n",
       "      <td>3.7</td>\n",
       "      <td>D L L</td>\n",
       "      <td>5</td>\n",
       "      <td>-2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1</td>\n",
       "      <td>270</td>\n",
       "      <td>Leicester City.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>West Ham</td>\n",
       "      <td>-0.69</td>\n",
       "      <td>5.3</td>\n",
       "      <td>L L L</td>\n",
       "      <td>0</td>\n",
       "      <td>-2.1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0</td>\n",
       "      <td>270</td>\n",
       "      <td>West Ham.png</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   losses goals_against             team  xg_diff_per90 xg_against last_5  \\\n",
       "0       0             2          Arsenal           1.18        1.8  W W W   \n",
       "1       0             3  Manchester City           1.45        2.3  W W D   \n",
       "2       0             3     Leeds United           0.52        3.0  W D W   \n",
       "3       0             3        Tottenham           0.46        2.8  W D W   \n",
       "4       0             1         Brighton           0.54        2.6  W D W   \n",
       "5       0             3    Newcastle Utd          -0.06        4.1  W D D   \n",
       "6       0             4           Fulham           0.10        4.1  D D W   \n",
       "7       1             5        Brentford           0.16        3.2  D W L   \n",
       "8       1             4   Crystal Palace           0.53        4.0  L D W   \n",
       "9       1             3  Nott'ham Forest          -1.06        5.9  L W D   \n",
       "10      1             7      Southampton          -0.52        3.8  L D W   \n",
       "11      1             5          Chelsea           0.09        3.5  W D L   \n",
       "12      2             6      Aston Villa          -0.51        5.0  L W L   \n",
       "13      2             7   Manchester Utd          -0.24        4.9  L L W   \n",
       "14      2             7      Bournemouth          -1.03        4.0  W L L   \n",
       "15      1             5        Liverpool           0.21        4.5  D D L   \n",
       "16      2             4          Everton          -0.18        4.3  L L D   \n",
       "17      2             3           Wolves          -0.21        3.4  L D L   \n",
       "18      2             8   Leicester City          -0.76        3.7  D L L   \n",
       "19      3             5         West Ham          -0.69        5.3  L L L   \n",
       "\n",
       "   goals_for xg_diff wins  games xg_for points  minutes_played  \\\n",
       "0          9    +3.5    3      3    5.4      9             270   \n",
       "1          9    +4.3    2      3    6.6      7             270   \n",
       "2          7    +1.6    2      3    4.6      7             270   \n",
       "3          7    +1.4    2      3    4.1      7             270   \n",
       "4          4    +1.6    2      3    4.2      7             270   \n",
       "5          5    -0.2    1      3    4.0      5             270   \n",
       "6          5    +0.3    1      3    4.4      5             270   \n",
       "7          8    +0.5    1      3    3.7      4             270   \n",
       "8          4    +1.6    1      3    5.5      4             270   \n",
       "9          2    -3.2    1      3    2.8      4             270   \n",
       "10         5    -1.6    1      3    2.3      4             270   \n",
       "11         3    +0.3    1      3    3.7      4             270   \n",
       "12         3    -1.5    1      3    3.5      3             270   \n",
       "13         3    -0.7    1      3    4.1      3             270   \n",
       "14         2    -3.1    1      3    0.9      3             270   \n",
       "15         4    +0.6    0      3    5.1      2             270   \n",
       "16         2    -0.5    0      3    3.8      1             270   \n",
       "17         1    -0.6    0      3    2.7      1             270   \n",
       "18         5    -2.3    0      3    1.5      1             270   \n",
       "19         0    -2.1    0      3    3.2      0             270   \n",
       "\n",
       "                   path  \n",
       "0           Arsenal.png  \n",
       "1   Manchester City.png  \n",
       "2      Leeds United.png  \n",
       "3         Tottenham.png  \n",
       "4          Brighton.png  \n",
       "5     Newcastle Utd.png  \n",
       "6            Fulham.png  \n",
       "7         Brentford.png  \n",
       "8    Crystal Palace.png  \n",
       "9   Nott'ham Forest.png  \n",
       "10      Southampton.png  \n",
       "11          Chelsea.png  \n",
       "12      Aston Villa.png  \n",
       "13   Manchester Utd.png  \n",
       "14      Bournemouth.png  \n",
       "15        Liverpool.png  \n",
       "16          Everton.png  \n",
       "17           Wolves.png  \n",
       "18   Leicester City.png  \n",
       "19         West Ham.png  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = generate_league_data(\"https://fbref.com/en/comps/9/Premier-League-Stats\")\n",
    "df['path'] = df[\"team\"] + '.png'\n",
    "df[[\"team\",\"xg_for\",\"xg_against\", \"path\"]]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def p90_Calculator(variable_value, minutes_played):\n",
    "    \n",
    "    variable_value = pd.to_numeric(variable_value)\n",
    "    \n",
    "    ninety_minute_periods = minutes_played/90\n",
    "    \n",
    "    p90_value = variable_value/ninety_minute_periods\n",
    "    \n",
    "    return p90_value\n",
    "\n",
    "def form_ppg_calc(variable_value):\n",
    "    wins = variable_value.count(\"W\")\n",
    "    draws = variable_value.count(\"D\")\n",
    "    losses = variable_value.count(\"L\")\n",
    "    points = (wins*3) + (draws)\n",
    "    ppg = points/3\n",
    "    return ppg\n",
    "\n",
    "def getImage(path):\n",
    "    return OffsetImage(plt.imread(path), zoom=.05, alpha = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['xG_p90'] = df.apply(lambda x: p90_Calculator(x['xg_for'], x['minutes_played']), axis=1)\n",
    "df['xGA_p90'] = df.apply(lambda x: p90_Calculator(x['xg_against'], x['minutes_played']), axis=1)\n",
    "df['ppg_form'] = df.apply(lambda x: form_ppg_calc(x['last_5']), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>losses</th>\n",
       "      <th>goals_against</th>\n",
       "      <th>team</th>\n",
       "      <th>xg_diff_per90</th>\n",
       "      <th>xg_against</th>\n",
       "      <th>last_5</th>\n",
       "      <th>goals_for</th>\n",
       "      <th>xg_diff</th>\n",
       "      <th>wins</th>\n",
       "      <th>games</th>\n",
       "      <th>xg_for</th>\n",
       "      <th>points</th>\n",
       "      <th>minutes_played</th>\n",
       "      <th>path</th>\n",
       "      <th>xG_p90</th>\n",
       "      <th>xGA_p90</th>\n",
       "      <th>ppg_form</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Arsenal</td>\n",
       "      <td>1.18</td>\n",
       "      <td>1.8</td>\n",
       "      <td>W W W</td>\n",
       "      <td>9</td>\n",
       "      <td>+3.5</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5.4</td>\n",
       "      <td>9</td>\n",
       "      <td>270</td>\n",
       "      <td>Arsenal.png</td>\n",
       "      <td>1.800000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Manchester City</td>\n",
       "      <td>1.45</td>\n",
       "      <td>2.3</td>\n",
       "      <td>W W D</td>\n",
       "      <td>9</td>\n",
       "      <td>+4.3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7</td>\n",
       "      <td>270</td>\n",
       "      <td>Manchester City.png</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>0.766667</td>\n",
       "      <td>2.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Leeds United</td>\n",
       "      <td>0.52</td>\n",
       "      <td>3.0</td>\n",
       "      <td>W D W</td>\n",
       "      <td>7</td>\n",
       "      <td>+1.6</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4.6</td>\n",
       "      <td>7</td>\n",
       "      <td>270</td>\n",
       "      <td>Leeds United.png</td>\n",
       "      <td>1.533333</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Tottenham</td>\n",
       "      <td>0.46</td>\n",
       "      <td>2.8</td>\n",
       "      <td>W D W</td>\n",
       "      <td>7</td>\n",
       "      <td>+1.4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4.1</td>\n",
       "      <td>7</td>\n",
       "      <td>270</td>\n",
       "      <td>Tottenham.png</td>\n",
       "      <td>1.366667</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>2.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Brighton</td>\n",
       "      <td>0.54</td>\n",
       "      <td>2.6</td>\n",
       "      <td>W D W</td>\n",
       "      <td>4</td>\n",
       "      <td>+1.6</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4.2</td>\n",
       "      <td>7</td>\n",
       "      <td>270</td>\n",
       "      <td>Brighton.png</td>\n",
       "      <td>1.400000</td>\n",
       "      <td>0.866667</td>\n",
       "      <td>2.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  losses goals_against             team  xg_diff_per90 xg_against last_5  \\\n",
       "0      0             2          Arsenal           1.18        1.8  W W W   \n",
       "1      0             3  Manchester City           1.45        2.3  W W D   \n",
       "2      0             3     Leeds United           0.52        3.0  W D W   \n",
       "3      0             3        Tottenham           0.46        2.8  W D W   \n",
       "4      0             1         Brighton           0.54        2.6  W D W   \n",
       "\n",
       "  goals_for xg_diff wins  games xg_for points  minutes_played  \\\n",
       "0         9    +3.5    3      3    5.4      9             270   \n",
       "1         9    +4.3    2      3    6.6      7             270   \n",
       "2         7    +1.6    2      3    4.6      7             270   \n",
       "3         7    +1.4    2      3    4.1      7             270   \n",
       "4         4    +1.6    2      3    4.2      7             270   \n",
       "\n",
       "                  path    xG_p90   xGA_p90  ppg_form  \n",
       "0          Arsenal.png  1.800000  0.600000  3.000000  \n",
       "1  Manchester City.png  2.200000  0.766667  2.333333  \n",
       "2     Leeds United.png  1.533333  1.000000  2.333333  \n",
       "3        Tottenham.png  1.366667  0.933333  2.333333  \n",
       "4         Brighton.png  1.400000  0.866667  2.333333  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.offsetbox import OffsetImage, AnnotationBbox\n",
    "fig, ax = plt.subplots(figsize=(6, 4), dpi=120)\n",
    "ax.scatter(df[\"ppg_form\"], df[\"xg_diff_per90\"],s=1)\n",
    "\n",
    "for index, row in df.iterrows():\n",
    "    ab = AnnotationBbox(getImage(os.path.join(\"team_logos/\"+row[\"path\"])), (row[\"ppg_form\"], row[\"xg_diff_per90\"]), frameon=False)\n",
    "    ax.add_artist(ab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set font and background colour\n",
    "bgcol = '#fafafa'\n",
    "\n",
    "# Create initial plot\n",
    "fig, ax = plt.subplots(figsize=(6, 4), dpi=120)\n",
    "fig.set_facecolor(bgcol)\n",
    "ax.set_facecolor(bgcol)\n",
    "ax.scatter(df['ppg_form'], df['xg_diff_per90'], c=bgcol)\n",
    "\n",
    "# Change plot spines\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.spines['left'].set_color('#ccc8c8')\n",
    "ax.spines['bottom'].set_color('#ccc8c8')\n",
    "\n",
    "# Change ticks\n",
    "plt.tick_params(axis='x', labelsize=12, color='#ccc8c8')\n",
    "plt.tick_params(axis='y', labelsize=12, color='#ccc8c8')\n",
    "\n",
    "# Plot badges\n",
    "def getImage(path):\n",
    "    return OffsetImage(plt.imread(path), zoom=.07, alpha = 1)\n",
    "\n",
    "for index, row in df.iterrows():\n",
    "    ab = AnnotationBbox(getImage(os.path.join(\"team_logos/\"+row[\"path\"])), (row['ppg_form'], row['xg_diff_per90']), frameon=False)\n",
    "    ax.add_artist(ab)\n",
    "\n",
    "# Add average lines\n",
    "plt.hlines(df['xg_diff_per90'].mean(), (df['ppg_form'].min()-0.4), (df['ppg_form'].max()+1), color='#c2c1c0')\n",
    "plt.vlines(df['ppg_form'].mean(), df['xg_diff_per90'].min(), df['xg_diff_per90'].max(), color='#c2c1c0')\n",
    "ax.axvspan(2.0, 3,0, ymax=1, alpha=0.2, color='green',label= \"Title's on\")\n",
    "\n",
    "ax.axvspan(0.0, 0.8, alpha=0.2, ymin=0.5, ymax=-0.5,color='red',label= \"Oh Dear\")\n",
    "ax.legend([\"Title's on\", \"Oh Dear\"], frameon=False, loc='center left', bbox_to_anchor=(1, 1))\n",
    "# Text\n",
    "\n",
    "## Title & comment\n",
    "fig.text(-.008,.98,'Points Per Game (Last 5)  vs xG Difference per 90',size=12)\n",
    "\n",
    "## Avg line explanation\n",
    "fig.text(-.002,.64,'xG Difference per 90', size=9, color='#575654',rotation=90)\n",
    "fig.text(.4,-0.002,'Last 5 ppg', size=9, color='#575654')\n",
    "\n",
    "## Axes titles\n",
    "fig.text(.76,.535,'Avg. xG Difference per 90', size=6, color='#c2c1c0')\n",
    "fig.text(.425,.29,'Avg. Last 5 ppg', size=6, color='#c2c1c0',rotation=90)\n",
    "\n",
    "## Save plot\n",
    "plt.savefig('xGChart.png', dpi=1200, bbox_inches = \"tight\")"
   ]
  },
  {
   "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}