{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "590466c4-32bc-4d3e-89b1-66f15ef61d56",
   "metadata": {},
   "source": [
    "# Massey Ratings\n",
    "\n",
    "Massey Ratings provide a mathematically robust method for evaluating and ranking football teams based on their match results. \n",
    "\n",
    "The Massey Rating system considers the strength of each team's opponents and the margins of victory or defeat, resulting in ratings that accurately reflect relative team performance. \n",
    "\n",
    "This makes it particularly useful for predicting outcomes, comparing team quality across leagues, and informing betting decisions by identifying teams whose performance might be underrated or overrated by bookmakers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a23baca5-1387-4d56-9c8a-59bf2633bd84",
   "metadata": {},
   "outputs": [],
   "source": [
    "import penaltyblog as pb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bea84cd8-7e75-4863-9ece-349870e19e53",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>datetime</th>\n",
       "      <th>season</th>\n",
       "      <th>competition</th>\n",
       "      <th>div</th>\n",
       "      <th>time</th>\n",
       "      <th>team_home</th>\n",
       "      <th>team_away</th>\n",
       "      <th>fthg</th>\n",
       "      <th>ftag</th>\n",
       "      <th>...</th>\n",
       "      <th>b365_cahh</th>\n",
       "      <th>b365_caha</th>\n",
       "      <th>pcahh</th>\n",
       "      <th>pcaha</th>\n",
       "      <th>max_cahh</th>\n",
       "      <th>max_caha</th>\n",
       "      <th>avg_cahh</th>\n",
       "      <th>avg_caha</th>\n",
       "      <th>goals_home</th>\n",
       "      <th>goals_away</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1599868800---crystal_palace---southampton</th>\n",
       "      <td>2020-09-12</td>\n",
       "      <td>2020-09-12 15:00:00</td>\n",
       "      <td>2020-2021</td>\n",
       "      <td>ENG Premier League</td>\n",
       "      <td>E0</td>\n",
       "      <td>15:00</td>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2.13</td>\n",
       "      <td>1.79</td>\n",
       "      <td>2.17</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2.18</td>\n",
       "      <td>1.79</td>\n",
       "      <td>2.12</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1599868800---fulham---arsenal</th>\n",
       "      <td>2020-09-12</td>\n",
       "      <td>2020-09-12 12:30:00</td>\n",
       "      <td>2020-2021</td>\n",
       "      <td>ENG Premier League</td>\n",
       "      <td>E0</td>\n",
       "      <td>12:30</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>Arsenal</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>2.01</td>\n",
       "      <td>1.89</td>\n",
       "      <td>2.02</td>\n",
       "      <td>1.91</td>\n",
       "      <td>2.13</td>\n",
       "      <td>1.92</td>\n",
       "      <td>2.02</td>\n",
       "      <td>1.87</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1599868800---liverpool---leeds</th>\n",
       "      <td>2020-09-12</td>\n",
       "      <td>2020-09-12 17:30:00</td>\n",
       "      <td>2020-2021</td>\n",
       "      <td>ENG Premier League</td>\n",
       "      <td>E0</td>\n",
       "      <td>17:30</td>\n",
       "      <td>Liverpool</td>\n",
       "      <td>Leeds</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2.05</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2.08</td>\n",
       "      <td>1.90</td>\n",
       "      <td>2.16</td>\n",
       "      <td>1.84</td>\n",
       "      <td>2.04</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1599868800---west_ham---newcastle</th>\n",
       "      <td>2020-09-12</td>\n",
       "      <td>2020-09-12 20:00:00</td>\n",
       "      <td>2020-2021</td>\n",
       "      <td>ENG Premier League</td>\n",
       "      <td>E0</td>\n",
       "      <td>20:00</td>\n",
       "      <td>West Ham</td>\n",
       "      <td>Newcastle</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2.03</td>\n",
       "      <td>1.87</td>\n",
       "      <td>2.04</td>\n",
       "      <td>1.88</td>\n",
       "      <td>2.09</td>\n",
       "      <td>1.91</td>\n",
       "      <td>2.02</td>\n",
       "      <td>1.86</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1599955200---tottenham---everton</th>\n",
       "      <td>2020-09-13</td>\n",
       "      <td>2020-09-13 16:30:00</td>\n",
       "      <td>2020-2021</td>\n",
       "      <td>ENG Premier League</td>\n",
       "      <td>E0</td>\n",
       "      <td>16:30</td>\n",
       "      <td>Tottenham</td>\n",
       "      <td>Everton</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2.09</td>\n",
       "      <td>1.81</td>\n",
       "      <td>2.09</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2.16</td>\n",
       "      <td>1.86</td>\n",
       "      <td>2.08</td>\n",
       "      <td>1.81</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 111 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                date            datetime  \\\n",
       "id                                                                         \n",
       "1599868800---crystal_palace---southampton 2020-09-12 2020-09-12 15:00:00   \n",
       "1599868800---fulham---arsenal             2020-09-12 2020-09-12 12:30:00   \n",
       "1599868800---liverpool---leeds            2020-09-12 2020-09-12 17:30:00   \n",
       "1599868800---west_ham---newcastle         2020-09-12 2020-09-12 20:00:00   \n",
       "1599955200---tottenham---everton          2020-09-13 2020-09-13 16:30:00   \n",
       "\n",
       "                                              season         competition div  \\\n",
       "id                                                                             \n",
       "1599868800---crystal_palace---southampton  2020-2021  ENG Premier League  E0   \n",
       "1599868800---fulham---arsenal              2020-2021  ENG Premier League  E0   \n",
       "1599868800---liverpool---leeds             2020-2021  ENG Premier League  E0   \n",
       "1599868800---west_ham---newcastle          2020-2021  ENG Premier League  E0   \n",
       "1599955200---tottenham---everton           2020-2021  ENG Premier League  E0   \n",
       "\n",
       "                                            time       team_home    team_away  \\\n",
       "id                                                                              \n",
       "1599868800---crystal_palace---southampton  15:00  Crystal Palace  Southampton   \n",
       "1599868800---fulham---arsenal              12:30          Fulham      Arsenal   \n",
       "1599868800---liverpool---leeds             17:30       Liverpool        Leeds   \n",
       "1599868800---west_ham---newcastle          20:00        West Ham    Newcastle   \n",
       "1599955200---tottenham---everton           16:30       Tottenham      Everton   \n",
       "\n",
       "                                           fthg  ftag  ... b365_cahh  \\\n",
       "id                                                     ...             \n",
       "1599868800---crystal_palace---southampton     1     0  ...      1.78   \n",
       "1599868800---fulham---arsenal                 0     3  ...      2.01   \n",
       "1599868800---liverpool---leeds                4     3  ...      1.85   \n",
       "1599868800---west_ham---newcastle             0     2  ...      2.03   \n",
       "1599955200---tottenham---everton              0     1  ...      2.09   \n",
       "\n",
       "                                           b365_caha  pcahh pcaha max_cahh  \\\n",
       "id                                                                           \n",
       "1599868800---crystal_palace---southampton       2.13   1.79  2.17     1.85   \n",
       "1599868800---fulham---arsenal                   1.89   2.02  1.91     2.13   \n",
       "1599868800---liverpool---leeds                  2.05   1.85  2.08     1.90   \n",
       "1599868800---west_ham---newcastle               1.87   2.04  1.88     2.09   \n",
       "1599955200---tottenham---everton                1.81   2.09  1.85     2.16   \n",
       "\n",
       "                                           max_caha  avg_cahh  avg_caha  \\\n",
       "id                                                                        \n",
       "1599868800---crystal_palace---southampton      2.18      1.79      2.12   \n",
       "1599868800---fulham---arsenal                  1.92      2.02      1.87   \n",
       "1599868800---liverpool---leeds                 2.16      1.84      2.04   \n",
       "1599868800---west_ham---newcastle              1.91      2.02      1.86   \n",
       "1599955200---tottenham---everton               1.86      2.08      1.81   \n",
       "\n",
       "                                           goals_home  goals_away  \n",
       "id                                                                 \n",
       "1599868800---crystal_palace---southampton           1           0  \n",
       "1599868800---fulham---arsenal                       0           3  \n",
       "1599868800---liverpool---leeds                      4           3  \n",
       "1599868800---west_ham---newcastle                   0           2  \n",
       "1599955200---tottenham---everton                    0           1  \n",
       "\n",
       "[5 rows x 111 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fbd = pb.scrapers.FootballData(\"ENG Premier League\", \"2020-2021\")\n",
    "df = fbd.get_fixtures()\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9fc2e8b0-d55f-45c4-bb23-69cf0fdcf56c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team</th>\n",
       "      <th>rating</th>\n",
       "      <th>offence</th>\n",
       "      <th>defence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Man City</td>\n",
       "      <td>1.275</td>\n",
       "      <td>1.486184</td>\n",
       "      <td>-0.211184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Man United</td>\n",
       "      <td>0.725</td>\n",
       "      <td>1.238962</td>\n",
       "      <td>-0.513962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Liverpool</td>\n",
       "      <td>0.65</td>\n",
       "      <td>1.10424</td>\n",
       "      <td>-0.45424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Tottenham</td>\n",
       "      <td>0.575</td>\n",
       "      <td>1.108406</td>\n",
       "      <td>-0.533406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Chelsea</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.832018</td>\n",
       "      <td>-0.282018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Leicester</td>\n",
       "      <td>0.45</td>\n",
       "      <td>1.115351</td>\n",
       "      <td>-0.665351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Arsenal</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.757018</td>\n",
       "      <td>-0.357018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>West Ham</td>\n",
       "      <td>0.375</td>\n",
       "      <td>0.952851</td>\n",
       "      <td>-0.577851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Aston Villa</td>\n",
       "      <td>0.225</td>\n",
       "      <td>0.76674</td>\n",
       "      <td>-0.54174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Leeds</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.962573</td>\n",
       "      <td>-0.762573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Everton</td>\n",
       "      <td>-0.025</td>\n",
       "      <td>0.558406</td>\n",
       "      <td>-0.583406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Brighton</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>0.370906</td>\n",
       "      <td>-0.520906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Newcastle</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>0.551462</td>\n",
       "      <td>-0.951462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Wolves</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>0.273684</td>\n",
       "      <td>-0.673684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Southampton</td>\n",
       "      <td>-0.525</td>\n",
       "      <td>0.586184</td>\n",
       "      <td>-1.111184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Burnley</td>\n",
       "      <td>-0.55</td>\n",
       "      <td>0.198684</td>\n",
       "      <td>-0.748684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>-0.625</td>\n",
       "      <td>0.425073</td>\n",
       "      <td>-1.050073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Fulham</td>\n",
       "      <td>-0.65</td>\n",
       "      <td>0.037573</td>\n",
       "      <td>-0.687573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>West Brom</td>\n",
       "      <td>-1.025</td>\n",
       "      <td>0.280629</td>\n",
       "      <td>-1.305629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Sheffield United</td>\n",
       "      <td>-1.075</td>\n",
       "      <td>-0.13326</td>\n",
       "      <td>-0.94174</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                team rating   offence   defence\n",
       "0           Man City  1.275  1.486184 -0.211184\n",
       "1         Man United  0.725  1.238962 -0.513962\n",
       "2          Liverpool   0.65   1.10424  -0.45424\n",
       "3          Tottenham  0.575  1.108406 -0.533406\n",
       "4            Chelsea   0.55  0.832018 -0.282018\n",
       "5          Leicester   0.45  1.115351 -0.665351\n",
       "6            Arsenal    0.4  0.757018 -0.357018\n",
       "7           West Ham  0.375  0.952851 -0.577851\n",
       "8        Aston Villa  0.225   0.76674  -0.54174\n",
       "9              Leeds    0.2  0.962573 -0.762573\n",
       "10           Everton -0.025  0.558406 -0.583406\n",
       "11          Brighton  -0.15  0.370906 -0.520906\n",
       "12         Newcastle   -0.4  0.551462 -0.951462\n",
       "13            Wolves   -0.4  0.273684 -0.673684\n",
       "14       Southampton -0.525  0.586184 -1.111184\n",
       "15           Burnley  -0.55  0.198684 -0.748684\n",
       "16    Crystal Palace -0.625  0.425073 -1.050073\n",
       "17            Fulham  -0.65  0.037573 -0.687573\n",
       "18         West Brom -1.025  0.280629 -1.305629\n",
       "19  Sheffield United -1.075  -0.13326  -0.94174"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "massey = pb.ratings.Massey(\n",
    "    df[\"goals_home\"], df[\"goals_away\"], df[\"team_home\"], df[\"team_away\"]\n",
    ")\n",
    "massey.get_ratings()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1e0c988e-2d52-479f-903e-1cac01731c4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 620,
       "width": 910
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "%config InlineBackend.figure_format='retina'\n",
    "plt.rcParams[\"figure.figsize\"] = [10, 7]\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "massey = pb.ratings.Massey(\n",
    "    df[\"goals_home\"], df[\"goals_away\"], df[\"team_home\"], df[\"team_away\"]\n",
    ")\n",
    "ratings = massey.get_ratings()\n",
    "ratings[\"colours\"] = np.where(ratings[\"rating\"] > 0, \"#33b864\", \"#a03623\")\n",
    "fig, ax = plt.subplots()\n",
    "y_pos = np.arange(len(ratings))\n",
    "performance = ratings[\"rating\"]\n",
    "ax.barh(y_pos, performance, align=\"center\", color=ratings[\"colours\"])\n",
    "ax.set_yticks(y_pos)\n",
    "ax.set_yticklabels(ratings[\"team\"], fontweight=\"bold\")\n",
    "ax.invert_yaxis()\n",
    "ax.set_xlabel(\"Massey Rating\")\n",
    "ax.set_title(\"Massey Ratings - EPL\", fontweight=\"bold\")\n",
    "\n",
    "rects = ax.patches\n",
    "for rect in rects:\n",
    "    x_value = rect.get_width()\n",
    "    y_value = rect.get_y() + rect.get_height() / 2\n",
    "    space = 2\n",
    "    ha = \"left\"\n",
    "\n",
    "    if x_value < 0:\n",
    "        space *= -1\n",
    "        ha = \"right\"\n",
    "\n",
    "    label = \"{:.2f}\".format(x_value)\n",
    "\n",
    "    # Create annotation\n",
    "    plt.annotate(\n",
    "        label,\n",
    "        (x_value, y_value),\n",
    "        xytext=(space, 0),\n",
    "        textcoords=\"offset points\",\n",
    "        va=\"center\",\n",
    "        ha=ha,\n",
    "        fontsize=8,\n",
    "        fontweight=\"bold\",\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "67ec3e47-da0c-4c78-a342-7707882940c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 620,
       "width": 910
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "%config InlineBackend.figure_format='retina'\n",
    "plt.rcParams[\"figure.figsize\"] = [10, 7]\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "massey = pb.ratings.Massey(\n",
    "    df[\"goals_home\"], df[\"goals_away\"], df[\"team_home\"], df[\"team_away\"]\n",
    ")\n",
    "ratings = massey.get_ratings()\n",
    "ratings[\"colours\"] = np.where(ratings[\"offence\"] > 0, \"#33b864\", \"#a03623\")\n",
    "ratings = ratings.sort_values(\"offence\", ascending=False)\n",
    "fig, ax = plt.subplots()\n",
    "y_pos = np.arange(len(ratings))\n",
    "performance = ratings[\"offence\"]\n",
    "ax.barh(y_pos, performance, align=\"center\", color=ratings[\"colours\"])\n",
    "ax.set_yticks(y_pos)\n",
    "ax.set_yticklabels(ratings[\"team\"], fontweight=\"bold\")\n",
    "ax.invert_yaxis()\n",
    "ax.set_xlabel(\"Massey Rating\")\n",
    "ax.set_title(\"Massey Offence Ratings - EPL\", fontweight=\"bold\")\n",
    "\n",
    "rects = ax.patches\n",
    "\n",
    "for rect in rects:\n",
    "    x_value = rect.get_width()\n",
    "    y_value = rect.get_y() + rect.get_height() / 2\n",
    "    space = 2\n",
    "    ha = \"left\"\n",
    "\n",
    "    if x_value < 0:\n",
    "        space *= -1\n",
    "        ha = \"right\"\n",
    "\n",
    "    label = \"{:.2f}\".format(x_value)\n",
    "\n",
    "    # Create annotation\n",
    "    plt.annotate(\n",
    "        label,\n",
    "        (x_value, y_value),\n",
    "        xytext=(space, 0),\n",
    "        textcoords=\"offset points\",\n",
    "        va=\"center\",\n",
    "        ha=ha,\n",
    "        fontsize=8,\n",
    "        fontweight=\"bold\",\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ed0812dd-0dd3-4d98-94fe-66bbf7375042",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "module 'penaltyblog' has no attribute 'massey'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Input \u001b[0;32mIn [6]\u001b[0m, in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      6\u001b[0m plt\u001b[38;5;241m.\u001b[39mrcParams[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfigure.figsize\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m7\u001b[39m]\n\u001b[1;32m      7\u001b[0m sns\u001b[38;5;241m.\u001b[39mset_style(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwhitegrid\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m----> 9\u001b[0m ratings \u001b[38;5;241m=\u001b[39m \u001b[43mpb\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmassey\u001b[49m\u001b[38;5;241m.\u001b[39mratings(df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgoals_home\u001b[39m\u001b[38;5;124m\"\u001b[39m], df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgoals_away\u001b[39m\u001b[38;5;124m\"\u001b[39m], df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mteam_home\u001b[39m\u001b[38;5;124m\"\u001b[39m], df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mteam_away\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m     10\u001b[0m ratings[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcolours\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mwhere(ratings[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdefence\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m#33b864\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m#a03623\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     11\u001b[0m ratings \u001b[38;5;241m=\u001b[39m ratings\u001b[38;5;241m.\u001b[39msort_values(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdefence\u001b[39m\u001b[38;5;124m\"\u001b[39m, ascending\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n",
      "\u001b[0;31mAttributeError\u001b[0m: module 'penaltyblog' has no attribute 'massey'"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "%config InlineBackend.figure_format='retina'\n",
    "plt.rcParams[\"figure.figsize\"] = [10, 7]\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "ratings = pb.massey.ratings(\n",
    "    df[\"goals_home\"], df[\"goals_away\"], df[\"team_home\"], df[\"team_away\"]\n",
    ")\n",
    "ratings[\"colours\"] = np.where(ratings[\"defence\"] > 0, \"#33b864\", \"#a03623\")\n",
    "ratings = ratings.sort_values(\"defence\", ascending=False)\n",
    "fig, ax = plt.subplots()\n",
    "y_pos = np.arange(len(ratings))\n",
    "performance = ratings[\"defence\"]\n",
    "ax.barh(y_pos, performance, align=\"center\", color=ratings[\"colours\"])\n",
    "ax.set_yticks(y_pos)\n",
    "ax.set_yticklabels(ratings[\"team\"], fontweight=\"bold\")\n",
    "ax.invert_yaxis()\n",
    "ax.set_xlabel(\"Massey Rating\")\n",
    "ax.set_title(\"Massey Defence Ratings - EPL\", fontweight=\"bold\")\n",
    "\n",
    "rects = ax.patches\n",
    "\n",
    "for rect in rects:\n",
    "    x_value = rect.get_width()\n",
    "    y_value = rect.get_y() + rect.get_height() / 2\n",
    "    space = 2\n",
    "    ha = \"left\"\n",
    "\n",
    "    if x_value < 0:\n",
    "        space *= -1\n",
    "        ha = \"right\"\n",
    "\n",
    "    label = \"{:.2f}\".format(x_value)\n",
    "\n",
    "    plt.annotate(\n",
    "        label,\n",
    "        (x_value, y_value),\n",
    "        xytext=(space, 0),\n",
    "        textcoords=\"offset points\",\n",
    "        va=\"center\",\n",
    "        ha=ha,\n",
    "        fontsize=8,\n",
    "        fontweight=\"bold\",\n",
    "    )"
   ]
  }
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