rugby_analytics.ipynb 1.16 MB
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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "# A Hierarchical model for Rugby prediction"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "Based on the following blog post: [Daniel Weitzenfeld's](http://danielweitzenfeld.github.io/passtheroc/blog/2014/10/28/bayes-premier-league/), which based on the work of [Baio and Blangiardo](http://discovery.ucl.ac.uk/16040/1/16040.pdf).\n",
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    "\n",
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    "In this example, we're going to reproduce the first model described in the paper using PyMC3.\n",
    "\n",
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    "Since I am a rugby fan I decide to apply the results of the paper to the Six Nations Championship, which is a competition between Italy, Ireland, Scotland, England, France and Wales."
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "## Motivation\n",
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    "Your estimate of the strength of a team depends on your estimates of the other strengths\n",
    "\n",
    "Ireland are a stronger team than Italy for example - but by how much?\n",
    "\n",
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    "Source for Results 2014 are Wikipedia. I've added the subsequent years, 2015, 2016, 2017. Manually pulled from Wikipedia. \n",
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    "\n",
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    "* We want to infer a latent parameter - that is the 'strength' of a team based only on their **scoring intensity**, and all we have are their scores and results, we can't accurately measure the 'strength' of a team. \n",
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    "* Probabilistic Programming is a brilliant paradigm for modeling these **latent** parameters\n",
    "* Aim is to build a model for the upcoming Six Nations in 2018."
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   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 1,
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   "metadata": {},
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   "outputs": [],
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   "source": [
    "!date\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "try:\n",
    "    from StringIO import StringIO\n",
    "except ImportError:\n",
    "    from io import StringIO\n",
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    "import pymc3 as pm, theano.tensor as tt\n",
    "import matplotlib.pyplot as plt\n",
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    "from matplotlib.ticker import StrMethodFormatter\n",
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    "import seaborn as sns\n",
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    "%matplotlib inline"
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   ]
  },
  {
   "cell_type": "markdown",
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   "metadata": {},
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   "source": [
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    "This is a Rugby prediction exercise. So we'll input some data. We've taken this from Wikipedia and BBC sports. "
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   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 5,
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   "metadata": {},
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   "outputs": [],
   "source": [
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    "try:\n",
    "    df_all = pd.read_csv('../data/rugby.csv')\n",
    "except:\n",
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    "    df_all = pd.read_csv(pm.get_data('rugby.csv'), index_col=0)"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "## What do we want to infer?\n",
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    "\n",
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    "* We want to infer the latent paremeters (every team's strength) that are generating the data we observe (the scorelines).\n",
    "* Moreover, we know that the scorelines are a noisy measurement of team strength, so ideally, we want a model that makes it easy to quantify our uncertainty about the underlying strengths.\n",
    "* Often we don't know what the Bayesian Model is explicitly, so we have to 'estimate' the Bayesian Model'\n",
    "* If we can't solve something, approximate it.\n",
    "* Markov-Chain Monte Carlo (MCMC) instead draws samples from the posterior.\n",
    "* Fortunately, this algorithm can be applied to almost any model.\n",
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    "\n",
    "## What do we want?\n",
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    "\n",
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    "* We want to quantify our uncertainty\n",
    "* We want to also use this to generate a model\n",
    "* We want the answers as distributions not point estimates"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "### Visualization/EDA\n",
    "We should do some some exploratory data analysis of this dataset. \n",
    "\n",
    "The plots should be fairly self-explantory, we'll look at things like difference between teams in terms of their scores. \n"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 6,
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   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>home_score</th>\n",
       "      <th>away_score</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>60.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>60.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>23.500000</td>\n",
       "      <td>19.983333</td>\n",
       "      <td>2015.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14.019962</td>\n",
       "      <td>12.911028</td>\n",
       "      <td>1.127469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2014.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>2014.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>20.500000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>2015.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>27.250000</td>\n",
       "      <td>23.250000</td>\n",
       "      <td>2016.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>67.000000</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>2017.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
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       "       home_score  away_score         year\n",
       "count   60.000000   60.000000    60.000000\n",
       "mean    23.500000   19.983333  2015.500000\n",
       "std     14.019962   12.911028     1.127469\n",
       "min      0.000000    0.000000  2014.000000\n",
       "25%     16.000000   10.000000  2014.750000\n",
       "50%     20.500000   18.000000  2015.500000\n",
       "75%     27.250000   23.250000  2016.250000\n",
       "max     67.000000   63.000000  2017.000000"
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      ]
     },
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     "execution_count": 6,
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     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_all.describe()"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 7,
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   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>home_team</th>\n",
       "      <th>away_team</th>\n",
       "      <th>home_score</th>\n",
       "      <th>away_score</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Italy</td>\n",
       "      <td>France</td>\n",
       "      <td>18</td>\n",
       "      <td>40</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>England</td>\n",
       "      <td>Scotland</td>\n",
       "      <td>61</td>\n",
       "      <td>21</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Scotland</td>\n",
       "      <td>Italy</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>France</td>\n",
       "      <td>Wales</td>\n",
       "      <td>20</td>\n",
       "      <td>18</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Ireland</td>\n",
       "      <td>England</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
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       "   home_team away_team  home_score  away_score  year\n",
       "55     Italy    France          18          40  2017\n",
       "56   England  Scotland          61          21  2017\n",
       "57  Scotland     Italy          29           0  2017\n",
       "58    France     Wales          20          18  2017\n",
       "59   Ireland   England          13           9  2017"
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      ]
     },
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     "execution_count": 7,
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     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's look at the tail end of this dataframe\n",
    "df_all.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a few things here that we don't need. We don't need the year for our model. \n",
    "But that is something that could improve a future model. \n",
    "\n",
    "Firstly let us look at differences in scores by year. "
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 8,
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   "metadata": {},
   "outputs": [],
   "source": [
    "df_all['difference'] = np.abs(df_all['home_score']-df_all['away_score'])"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 9,
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   "metadata": {},
   "outputs": [
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
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       "<Figure size 432x288 with 1 Axes>"
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      ]
     },
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     "metadata": {
      "needs_background": "light"
     },
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     "output_type": "display_data"
    }
   ],
   "source": [
    "(df_all.groupby('year')['difference']\n",
    "      .mean()\n",
    "      \n",
    "      .plot(kind='bar', title='Average magnitude of scores difference Six Nations', yerr=df_all.groupby('year')['difference'].std())\n",
    "      .set_ylabel('Average (abs) point difference'));\n",
    "                                                 \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that the standard error is large. So we can't say anything about the differences.\n",
    "Let's look country by country. "
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 10,
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   "metadata": {},
   "outputs": [],
   "source": [
    "df_all['difference_non_abs']=df_all['home_score']-df_all['away_score']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us first loook at a Pivot table with a sum of this, broken down by year."
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 11,
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   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>year</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>England</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>20.666667</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>21.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>6.666667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-2.333333</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ireland</th>\n",
       "      <td>28.000000</td>\n",
       "      <td>8.500000</td>\n",
       "      <td>17.666667</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>-21.000000</td>\n",
       "      <td>-31.000000</td>\n",
       "      <td>-23.500000</td>\n",
       "      <td>-33.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scotland</th>\n",
       "      <td>-11.000000</td>\n",
       "      <td>-12.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>16.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wales</th>\n",
       "      <td>25.666667</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "year            2014       2015       2016       2017\n",
       "home_team                                            \n",
       "England     7.000000  20.666667   7.500000  21.333333\n",
       "France      6.666667   0.000000  -2.333333   4.000000\n",
       "Ireland    28.000000   8.500000  17.666667   7.000000\n",
       "Italy     -21.000000 -31.000000 -23.500000 -33.666667\n",
       "Scotland  -11.000000 -12.000000   2.500000  16.666667\n",
       "Wales      25.666667   1.000000  22.000000   4.000000"
      ]
     },
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     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_all.pivot_table('difference_non_abs', 'home_team', 'year')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's first plot this by home team without year. "
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {},
   "outputs": [
    {
     "data": {
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      "image/png": "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\n",
500
      "text/plain": [
501
       "<Figure size 432x288 with 1 Axes>"
502 503
      ]
     },
504 505 506
     "metadata": {
      "needs_background": "light"
     },
507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526
     "output_type": "display_data"
    }
   ],
   "source": [
    "(df_all.pivot_table('difference_non_abs', 'home_team')\n",
    "      .rename_axis(\"Home_Team\")\n",
    "      .plot(kind='bar', rot=0, legend=False)\n",
    "      .set_ylabel('Score difference Home team and away team')\n",
    ");\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see that Italy and Scotland have negative scores on average. You can also see that England, Ireland and Wales have been the strongest teams lately at home. "
   ]
  },
  {
   "cell_type": "code",
527
   "execution_count": 13,
528 529 530 531
   "metadata": {},
   "outputs": [
    {
     "data": {
532
      "image/png": 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\n",
533
      "text/plain": [
534
       "<Figure size 432x288 with 1 Axes>"
535 536
      ]
     },
537 538 539
     "metadata": {
      "needs_background": "light"
     },
540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569
     "output_type": "display_data"
    }
   ],
   "source": [
    "(df_all.pivot_table('difference_non_abs', 'away_team')\n",
    "      .rename_axis(\"Away_Team\")\n",
    "      .plot(kind='bar', rot=0, legend=False)\n",
    "      .set_ylabel('Score difference Home team and away team')\n",
    ");\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This indicates that Italy, Scotland and France all have poor away from home form. \n",
    "England suffers the least when playing away from home. This aggregate view doesn't take into account the strength of the teams. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us look a bit more at a timeseries plot of the average of the score difference over the year. \n",
    "\n",
    "We see some changes in team behaviour, and we also see that Italy is a poor team. "
   ]
  },
  {
   "cell_type": "code",
570
   "execution_count": 14,
571 572 573 574
   "metadata": {},
   "outputs": [
    {
     "data": {
575
      "image/png": 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\n",
576
      "text/plain": [
577
       "<Figure size 720x1080 with 6 Axes>"
578 579
      ]
     },
580 581 582
     "metadata": {
      "needs_background": "light"
     },
583 584 585 586
     "output_type": "display_data"
    }
   ],
   "source": [
587 588
    "g = sns.FacetGrid(df_all, col=\"home_team\", col_wrap=2, height=5)\n",
    "g = g.map(plt.scatter, \"year\", \"difference_non_abs\").set_axis_labels(\"Year\", \"Score Difference\")"
589 590 591 592
   ]
  },
  {
   "cell_type": "code",
593
   "execution_count": 15,
594 595 596 597
   "metadata": {},
   "outputs": [
    {
     "data": {
598
      "image/png": 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\n",
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      "text/plain": [
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       "<Figure size 720x1080 with 6 Axes>"
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      ]
     },
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     "metadata": {
      "needs_background": "light"
     },
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     "output_type": "display_data"
    }
   ],
   "source": [
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    "g = sns.FacetGrid(df_all, col=\"away_team\", col_wrap=2, height=5)\n",
    "g = g.map(plt.scatter, \"year\", \"difference_non_abs\").set_axis_labels(\"Year\", \"Score Difference\")"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see some interesting things here like Wales were good away from home in 2015. \n",
    "In that year they won three games away from home and won by 40 points or so away from home to Italy. \n",
    "\n",
    "So now we've got a feel for the data, we can proceed on with describing the model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What assumptions do we know for our 'generative story'?\n",
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    "\n",
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    "* We know that the Six Nations in Rugby only has 6 teams - they each play each other once\n",
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    "* We have data from the last few years\n",
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    "* We also know that in sports scoring is modelled as a Poisson distribution\n",
    "* We consider home advantage to be a strong effect in sports"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "## The model.\n",
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    "\n",
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    "The league is made up by a total of T= 6 teams, playing each other once \n",
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    "in a season. We indicate the number of points scored by the home and the away team in the g-th game of the season (15 games) as $y_{g1}$ and $y_{g2}$ respectively. </p>\n",
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    "The vector of observed counts $\\mathbb{y} = (y_{g1}, y_{g2})$ is modelled as independent Poisson:\n",
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    "$y_{gi}| \\theta_{gj} \\tilde\\;\\;  Poisson(\\theta_{gj})$\n",
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    "where the theta parameters represent the scoring intensity in the g-th game for the team playing at home (j=1) and away (j=2), respectively.</p>\n"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We model these parameters according to a formulation that has been used widely in the statistical literature, assuming a log-linear random effect model:\n",
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    "$$log \\theta_{g1} = home + att_{h(g)} + def_{a(g)} $$\n",
    "$$log \\theta_{g2} = att_{a(g)} + def_{h(g)}$$\n",
    "\n",
    "\n",
    "* The parameter home represents the advantage for the team hosting the game and we assume that this effect is constant for all the teams and throughout the season\n",
    "* The scoring intensity is determined jointly by the attack and defense ability of the two teams involved, represented by the parameters att and def, respectively\n",
    "\n",
    "* Conversely, for each t = 1, ..., T, the team-specific effects are modelled as exchangeable from a common distribution:\n",
    "\n",
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    "* $att_{t} \\; \\tilde\\;\\; Normal(\\mu_{att},\\tau_{att})$ and $def_{t} \\; \\tilde\\;\\;Normal(\\mu_{def},\\tau_{def})$"
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   ]
  },
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We restrict to only the useful columns for this model."
   ]
  },
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  {
   "cell_type": "code",
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   "execution_count": 16,
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   "metadata": {},
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   "outputs": [],
   "source": [
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    "df = df_all[['home_team', 'away_team', 'home_score', 'away_score']]"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 17,
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   "metadata": {},
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   "outputs": [],
   "source": [
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    "teams = df.home_team.unique()\n",
    "teams = pd.DataFrame(teams, columns=['team'])\n",
    "teams['i'] = teams.index\n",
    "\n",
    "df = pd.merge(df, teams, left_on='home_team', right_on='team', how='left')\n",
    "df = df.rename(columns = {'i': 'i_home'}).drop('team', 1)\n",
    "df = pd.merge(df, teams, left_on='away_team', right_on='team', how='left')\n",
    "df = df.rename(columns = {'i': 'i_away'}).drop('team', 1)\n",
    "\n",
    "observed_home_goals = df.home_score.values\n",
    "observed_away_goals = df.away_score.values\n",
    "\n",
    "home_team = df.i_home.values\n",
    "away_team = df.i_away.values\n",
    "\n",
    "num_teams = len(df.i_home.drop_duplicates())\n",
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    "num_games = len(home_team)"
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   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "* We did some munging above and adjustments of the data to make it **tidier** for our model. \n",
    "* The log function to away scores and home scores is a standard trick in the sports analytics literature\n",
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    "\n",
    "## Building of the model \n",
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    "* We now build the model in PyMC3, specifying the global parameters, and the team-specific parameters and the likelihood function \n"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 18,
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   "metadata": {},
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   "outputs": [],
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   "source": [
    "with pm.Model() as model:\n",
    "    # global model parameters\n",
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    "    home = pm.Flat('home')\n",
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    "    sd_att = pm.HalfStudentT('sd_att', nu=3, sigma=2.5)\n",
    "    sd_def = pm.HalfStudentT('sd_def', nu=3, sigma=2.5)\n",
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    "    intercept = pm.Flat('intercept')\n",
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    "    \n",
    "    # team-specific model parameters\n",
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    "    atts_star = pm.Normal(\"atts_star\", mu=0, sigma=sd_att, shape=num_teams)\n",
    "    defs_star = pm.Normal(\"defs_star\", mu=0, sigma=sd_def, shape=num_teams)\n",
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    " \n",
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    "    atts = pm.Deterministic('atts', atts_star - tt.mean(atts_star))\n",
    "    defs = pm.Deterministic('defs', defs_star - tt.mean(defs_star))\n",
    "    home_theta = tt.exp(intercept + home + atts[home_team] + defs[away_team])\n",
    "    away_theta = tt.exp(intercept + atts[away_team] + defs[home_team])\n",
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    "    \n",
    "    # likelihood of observed data\n",
    "    home_points = pm.Poisson('home_points', mu=home_theta, observed=observed_home_goals)\n",
    "    away_points = pm.Poisson('away_points', mu=away_theta, observed=observed_away_goals)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* We specified the model and the likelihood function\n",
    "\n",
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    "* All this runs on a Theano graph under the hood"
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   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 19,
   "metadata": {},
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   "outputs": [
    {
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     "name": "stderr",
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     "output_type": "stream",
     "text": [
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      "Auto-assigning NUTS sampler...\n",
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      "Initializing NUTS using jitter+adapt_diag...\n",
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      "Multiprocess sampling (3 chains in 3 jobs)\n",
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      "NUTS: [defs_star, atts_star, intercept, sd_def, sd_att, home]\n",
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      "Sampling 3 chains, 0 divergences: 100%|████████████████████████████████████████| 6000/6000 [00:12<00:00, 479.34draws/s]\n"
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     ]
    },
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
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       "<Figure size 864x576 with 8 Axes>"
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      ]
     },
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     "metadata": {
      "needs_background": "light"
     },
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     "output_type": "display_data"
    }
   ],
   "source": [
    "with model:\n",
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    "    trace = pm.sample(1000, tune=1000, cores=3)\n",
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    "\n",
    "pm.traceplot(trace, var_names=['intercept', 'home', 'sd_att', 'sd_def']);"
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   ]
  },
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us apply good *statistical workflow* practices and look at the various evaluation metrics to see if our NUTS sampler converged."
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 22,
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   "metadata": {},
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   "outputs": [],
   "source": [
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    "bfmi = np.max(pm.stats.bfmi(trace))\n",
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    "max_gr = max(np.max(gr_stats) for gr_stats in pm.stats.rhat(trace).values()).values"
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   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 23,
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   "metadata": {},
   "outputs": [
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
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       "<Figure size 432x288 with 1 Axes>"
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(pm.energyplot(trace, legend=False, figsize=(6, 4))\n",
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    "   .set_title(\"BFMI = {}\\nGelman-Rubin = {}\".format(bfmi, max_gr)));"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our model has converged well and the Gelman-Rubin statistic looks good. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us look at some of the stats, just to verify that our model has returned the correct attributes. We can see that some teams are stronger than others. This is what we would expect with attack"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 24,
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   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "array([[ 0.0914411 ,  0.24983955],\n",
       "       [-0.17489496, -0.00180749],\n",
       "       [ 0.02865188,  0.18533115],\n",
       "       [-0.20199572, -0.02297896],\n",
       "       [-0.43666135, -0.22646324],\n",
       "       [ 0.18200205,  0.3341145 ]])"
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      ]
     },
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     "execution_count": 24,
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     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pm.stats.hpd(trace['atts'])"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": 26,
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   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "array([ 0.17246227, -0.08510157,  0.10761194, -0.11491148, -0.33435058,\n",
       "        0.25571298])"
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      ]
     },
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     "execution_count": 26,
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     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
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    "np.quantile(trace['atts'], 0.5, axis=0)"
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   ]
  },
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  {
   "cell_type": "markdown",
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   "metadata": {},
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   "source": [
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    "## Results\n",
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    "From the above we can start to understand the different distributions of attacking strength and defensive strength.\n",
    "These are probabilistic estimates and help us better understand the uncertainty in sports analytics"
   ]
  },
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  {
   "cell_type": "code",
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   "execution_count": 27,
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   "metadata": {},
   "outputs": [
    {
     "data": {
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      "image/png": 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2f5fUfDTn66Ratu95klszMzOzzldOknYH0Aj8Jm8fAoiUqF0F7FeRyMzMzMzqWDlJ2i4RsUvJ9nRJf4uIXSR9sVKBmZmZmdWzcqbgWEPSTk0bknYE1sibHuVpZmZmVgHl1KQdA1wpaQ1SM+cbwDGSVgfOqWRwZmZmZvVqmUlaRDwMbCNpLUARMb/k8A0Vi8zMzMysji0zSZO0KnAQsDGwsiQAIuI7FY3MzMzMrI6V0yftFuAAUv+zt0u+zMxsBTJh6hymzpzPg8+8yi7n3sOEqXOKDsnM2lBOn7QNImLvSlxc0t7ARUA34IqIOLfZ8S2AXwI7AGdGxAWViMPMrKubMHUOY26azsLGxQDMmb+AMTdNB/A6kWY1qpyatPskbdPZF5bUDbgUGApsCRwqactmxV4Fvgo4OTMz64DzJ81gwaLGpfYtWNTI+ZNmFBSRmS1LOUnarsAjkmZImiZpuqRpnXDtHYGnIuLpiFgIXEdqVv2viHgpD1zwslRmZh0wd/6Cdu03s+KV09w5tELX7gfMKtmeDezUSlkzM+uAvr0amNNCQta3V0MB0ZhZOZZZkxYRzwEbArvnx++U87wyqKXLLffJpJGSpkiaMm/evA6EZWbW9YweMpCG7t2W2tfQvRujhwwsKCIzW5ZlJluSzgJOA8bkXd2BX3fCtWeTkr8mGwBzl/dkETEuIgZHxOA+ffp0ODgzs65k2KB+nHPgNqzSLf3b79ergXMO3MaDBsxqWDnNnZ8BBgF/B4iIuZLW7IRrPwwMkLQJMIe0cPvnO+G8ZmbWgmGD+nHtQzMBuP7YnQuOxkr5flhLyknSFkZESAqAvBxUh0XEe5JGAZNIU3BcGRGPSTouH79c0nrAFKAnsFjSScCWEfFGZ8RgZmZmVqvKSdJukDQW6CXpS8BRwM874+IRMRGY2Gzf5SWPXyA1g5qZmZnVlXLW7rxA0l6khdUHAt+KiLsqHpmZmZlZHWszScsTzk6KiD0BJ2ZmZmZmVdLm6M6IaATekbRWleIxMzMzM8rrk/YfYLqkuyhZWD0ivlqxqMzMzMzqXDlJ2u35q9RyTzprZmZmZstWTpLWKyIuKt0h6cQKxWNmZmZmlLe804gW9h3RyXGYmZmZWYlWa9IkHUpaAWATSbeWHOoJvFLpwMzMzMzqWVvNnfcBzwO9gR+V7H8TmFbJoMzMzMzqXatJWkQ8BzwH7Awg6f3Ax4C3IuK96oRnZmZmVp9a7ZMm6TZJW+fH6wOPkpaE+lVeQ9PMzMzMKqStgQObRMSj+fGRwF0RsR+wEylZMzMzM7MKaStJW1TyeA/yQugR8SawuJJBmZmZmdW7tgYOzJJ0AjAb2AH4A4CkBqB7FWIzM7NOdv2xOxcdgpmVqa2atKOBrUhzog2PiPl5/0eAX1Y4LjMzM7O61tbozpeA41rY/0fgj5UMyszMzKzelbPigJmZmZlVWaFJmqS9Jc2Q9JSk01s4Lkk/zcenSdqhiDjNzMzMqm2ZSZqktVvYt0lHLyypG3ApMBTYEjhU0pbNig0FBuSvkcDPOnpdMzMzsxVBOTVpv5fUs2kjJ1K/74Rr7wg8FRFPR8RC4DrggGZlDgCujuQBoFeeWNfMzMysSysnSfsBKVFbQ9KHgN8CX+yEa/cDZpVsz8772lsGAEkjJU2RNGXevHmdEJ6ZmZlZcdqaJw2AiLhdUnfgTmBNYFhEPNkJ11ZLl1uOMmlnxDhgHMDgwYNbLGNm1TV87P2A5+YyM1serSZpki5m6YSoJ/A0cIIkIuKrHbz2bGDDku0NgLnLUcbMzMysy2mrJm1Ks+1HOvnaDwMD8iCEOcAhwOeblbkVGCXpOtKaoa9HxPOdHIeZmZlZzWlrMtvxAJJWB/4TEY15uxuwakcvHBHvSRoFTAK6AVdGxGOSjsvHLyetF7oP8BTwDmmhdzMzM7Mub5l90oDJwJ7AW3m7gdQ/7aMdvXhETCQv3F6y7/KSxwF8paPXMTMzM1vRlDO6s0dENCVo5MerVS4ks/YbPvb+/3ZSNzMz6wrKSdLeLp3pP0/DsaByIZmZmZlZOc2dJwG/ldQ0qnJ9YHjlQjIzMzOzcuZJe1jSFsBA0rxlT0TEoopHZmZmZlbHyqlJg5SgbQn0AAbledKurlxYZmZmZvVtmUmapLOAT5CStImkRc//CjhJMzMzM6uQcgYOfBbYA3ghIo4EtqMT5kkzMzMzs9aVk6QtiIjFwHuSegIvAZtWNiwzMzOz+lZOn7QpknoBPyctDfUW8FBFozIzMzOrc+WM7vxyfni5pD8APSNiWmXDMjMzM6tvy2zulDS56XFEPBsR00r3mZmZmVnna7UmTVIP0vJPvSW9jzRHGkBPoG8VYjMzMzOrW201dx5LWm2gL6kvWlOS9gZwaYXjMjMzM6trrTZ3RsRFEbEJMDoiNo2ITfLXdqRBBGZmrZowdQ5TZ87nwWdeZZdz72HC1DlFh2RmtkIpZwqOI1rYd38nx2FmXciEqXMYc9N0FjYuBmDO/AWMuWm6EzUzs3Zoq0/aekA/oEHSIJbuk7ZaFWIzsxXU+ZNmsGBR41L7Fixq5PxJMxg2qF9BUZmZrVja6pM2hFSLtgHwI5YkaW8CZ3TkopLWBq4HNgaeBQ6OiNdaKHcl8GngpYjYuiPXNLPqmTt/Qbv2m5nZ/2qrT9r4iPgkcERE7B4Rn8xf+wN/6+B1TwcmR8QAYHLebslVwN4dvJaZVVnfXg3t2m9mZv9rmX3SIuJGAElrSTpK0t3A3zt43QOA8fnxeGBYK9f+M/BqB69lZlU2eshAGrp3W2pfQ/dujB4ysKCIzMxWPG2uOCCpAdgf+DywA7AmKaH6cwevu25EPA8QEc9LWqeD5zOzGtLU7+zrv5vGwsbF9OvVwOghA90fzcysHdoaOHAN8DHgTuAS4B7gqYi4t5wT5xq39Vo4dGb7wyzreiOBkQD9+/evxCXMrB2GDerHtQ/NBOD6Y3cuOBozsxVPWzVpWwOvAY8DT0REo6Qo98QRsWdrxyS9KGn9XIu2PvBS2RG3fr1xwDiAwYMHlx2nrfia5uNa2LiYXc69xzU2ZmbWJbQ1cGA74GDSlBt3S/oLsGaemqOjbgVG5McjgFs64ZxWhzwfl5mZdVVtDhyIiCci4lsRMRD4GnA18JCk+zp43XOBvSQ9CeyVt5HUV9LEpkKSriVNnDtQ0mxJR3fwutbFtDUfl5mZ2YqszYEDpSJiCjBF0qmkvmrLLSJeAfZoYf9cYJ+S7UM7ch3r+jwfl5mZdVXlLAu1lEj+VIlgzNrL83GZmVlX1e4kzayWeD4uMzPrqtpM0iStJOngagVj1l7DBvXjnAO3YZVu6U+5X68GzjlwG4/uNDOzFV6bfdIiYrGkUcANVYrHrN08H5eZmXVF5TR33iXpVEkbSlq76avikZmZmZnVsXJGdx6Vv3+lZF8Am3Z+OGZmZmYGZSRpEbFJNQIxMzMzsyWWmaRJ6g4cz5K50e4FxkbEogrGZWZmZlbXymnu/BnQHbgsbx+W9x1TqaDMzMzM6l05SdqH8zqeTe6R9M9KBWRmZmZm5Y3ubJS0WdOGpE2BxjbKm5mZmVkHlVOTNhr4o6SnAQEbAUdWNCozMzOzOlfO6M7JkgYAA0lJ2hMR8W7FIzMzMzOrY60maZJ2j4h7JB3Y7NBmkoiImyocm5mZmVndaqsm7ePAPcB+LRwLwEmambXJy3SZmS2/VpO0iDhL0krAHRHhtTvNzMzMqqjN0Z0RsRgYVaVYzMzMzCwrZIH1fI67JD2Zv7+vhTIbSvqjpMclPSbpxI5c08zMzGxFUk6SdhRpcfU/A4/krykdvO7pwOSIGABMztvNvQecEhEfBD4CfEXSlh28rpmZmdkKoagF1g8APpEfjyetB3pas+s+DzyfH78p6XGgH/CvCsRjZmZmVlOWWZMmaTVJ35A0Lm8PkPTpDl533ZyENSVj6ywjho2BQcCDbZQZKWmKpCnz5s3rYHhmZmZmxSpnxYFfkpo4P5q3ZwO/BW5r60mS7gbWa+HQme0JUNIawI3ASRHxRmvlImIcMA5g8ODB0Z5r2IrPUz2YmVlXU06StllEDJd0KEBELJCkZT0pIvZs7ZikFyWtHxHPS1ofeKmVct1JCdo1njzXzMzM6kk5AwcWSmogTWBLXmy9o8tC3QqMyI9HALc0L5ATwV8Aj0fEjzt4PTMzM7MVSjlJ2tnAH4ANJV1DGo15WpvPWLZzgb0kPQnslbeR1FfSxFxmF+AwYHdJ/8hf+3TwumZmZmYrhHJGd94p6RHSNBgCToyIlzty0Yh4Bdijhf1zgX3y47/m65mZmZnVnXJGd06OiFci4vaIuC0iXpY0uRrBmZmZmdWrVmvSJPUAVgN65xUBmmq1egJ9qxBbzRo+9n7AIwrNzMysctpq7jwWOImUkD3CkiTtDeDSCsdlZmZmVtdaTdIi4iLgIkknRMTFVYzJzMzMrO6VM7rzBUlrAuSVB26StEOF4zIzMzOra+Ukad/Ma2fuCgwhrbX5s8qGZWZmZlbfyknSGvP3fYGfRcQtwCqVC8nMzMzMyknS5kgaCxwMTJS0apnPMzMzM7PlVE6ydTAwCdg7IuYDawOjKxqVmZmZWZ1bZpIWEe8A/waGSBoFrBMRd1Y8MjMzM7M6Vs6KAycC1wDr5K9fSzqh0oGZmZmZ1bNlrt0JHA3sFBFvA0g6D7gf8NxpZmZmZhVSTp80sWSEJ/mxFz43MzMzq6ByatJ+CTwo6ea8PQz4ReVCMjMzM7NlJmkR8WNJ9wK7kmrQjoyIqZUOzMzMzKyetZqkSeoBHAdsDkwHLouI96oVmJmZmVk9a6tP2nhgMClBGwpcUJWIzMzMzKzN5s4tI2IbAEm/AB7qrItKWhu4HtgYeBY4OCJea1amB/BnYNUc5+8i4qzOisHMzMyslrVVk7ao6UEFmjlPByZHxABgct5u7l1g94jYDtge2FvSRzo5DjMzM7Oa1FZN2naS3siPBTTkbQERET07cN0DgE/kx+OBe4HTSgtERABv5c3u+Ss6cE0zMzOzFUarSVpEdKvgddeNiOfzdZ6XtE5LhSR1Ax4hDV64NCIebO2EkkYCIwH69+/f+RGbmZmZVVE586QtF0l3A+u1cOjMcs8REY3A9pJ6ATdL2joiHm2l7DhgHMDgwYNd42ZmZmYrtIolaRGxZ2vHJL0oaf1ci7Y+8NIyzjU/z9W2N9BikmZmZmbWlZSzLFQl3AqMyI9HALc0LyCpT65BQ1IDsCfwRNUiNDMzMytQUUnaucBekp4E9srbSOoraWIusz7wR0nTgIeBuyLitkKiNTMzM6uyijV3tiUiXgH2aGH/XGCf/HgaMKjKoZmZmZnVhKJq0lZYE6bOYerM+Tz4zKvscu49TJg6p+iQzMzMrAtyktYOE6bOYcxN01nYuBiAOfMXMOam6U7UzMzMrNM5SWuH8yfNYMGixqX2LVjUyPmTZhQUkZmZmXVVTtLaYe78Be3ab2ZmZra8nKS1Q99eDe3ab2ZmZra8nKS1w+ghA2novvRqWQ3duzF6yMCCIjIzM7OuqpApOFZUwwb1A+Drv5vGwsbF9OvVwOghA/+738zMzKyzOElrp2GD+nHtQzMBuP7YnQuOxszMzLoqN3eamZmZ1SAnaWZmZmY1yEmamZmZWQ1ykmZmZmZWg5ykmZmZmdUgJ2lmZmZmNchJmpmZmVkNcpJmZmZmVoMKSdIkrS3pLklP5u/va6NsN0lTJd1WzRjNzMzMilRUTdrpwOSIGABMztutORF4vCpRmZmZmdWIopK0A4Dx+fF4YFhLhSRtAOwLXFGluMzMzMxqQlFJ2roR8TxA/r5OK+UuBL4OLK5WYGZmZma1oGILrEu6G1ivhUNnlvn8TwMvRcQjkj5RRvmRwEiA/v37tyNSMzMzs9pTsSQtIvZs7ZikFyWtHxHPS1ofeKmFYrsA+0vaB+gB9JT064j4YivXGweMAxg8eHB0/CcwMzMzK05RzZ23AiPy4xHALc0LRMSYiNggIjYGDgHuaS1BMzMzM+tqikrSzgX2kvQksFfeRlJfSRMLisnMzMysZlSsubMtEfEKsEcL++cC+7Sw/17g3ooHZmZmZlYjvOKAmZmZWQ1ykmZmZmZWgw4YSq0AABONSURBVJykmZmZmdUgJ2lmZmZmNaiQgQMruuuP3bnoEMzMzKyLc02amZmZWQ1ykmZmZmZWg5ykmZmZmdUgJ2lmZmZmNchJmpmZmVkNcpJmZmZmVoOcpJmZmZnVICdpZmZmZjXISZqZmZlZDVJEFB1Dp5M0D3iuwpfpDbxc4WtY+/ie1Cbfl9rje1KbfF9qT7XuyUYR0af5zi6ZpFWDpCkRMbjoOGwJ35Pa5PtSe3xPapPvS+0p+p64udPMzMysBjlJMzMzM6tBTtKW37iiA7D/4XtSm3xfao/vSW3yfak9hd4T90kzMzMzq0GuSTMzMzOrQU7SzMzMzGqQkzQzMzOzGuQkzeqOpC0kfV7SykXHUs8kqa1tK4akPSTtVXQcZisKSetU6txO0jqJpEGStsqP/XutUZK6AXsAHwc+60StGJIUedSSpL45QXOSVhv6AJMkfaLoQOpd6QcXST2LjMValt9DLpF0dSXO72Si8xwC/BggIhYXHIu1QNJKEdEYEZcCc4E9gU/nxM2qqCRBOwm4GBgLfEHS6oUGVseaPlxGxHXAGcAESbsWG1X9avZB5jjgaElrFhyWNRMR7wHHAetKuqCzz+8kbTm1UFt2OjBH0s75uGsFakxT8izpeGAwsBVwJHCwa9SqT9IwYBhwMLANsGNEvO3XTjFKXh9fAd4PPADcLmnPQgOrUyUJ2rHAUcCNEfGmP1TWjpL/VZsD/wQO6uxEzUlaO0naWNK+EbFY0m6SDpe0c35BvQTsCkteYFZbJG0BHEFKDnYF7gQ+Buzrf36V1ULytTZposijgDeAU/L+DasZly2Ru2ycAFwcEXsDI4GbJO1WbGT1R9JKuYnzAOA04HVJI4GLJB1RaHAGpPd5SbsA1wN3A2cB20i6tLOu4SSt/T4IjJU0lPTGMgj4lqRvAQ+SqqS3KjJAW6KFxGAR0AMYGBGNwFXAOsDJwGeqG139aNZ0s03e/Qzp9/75iBgSEQslnQyc6prN6mjh9fEa8EhEzMz37HrgGuBPkj5a/QjrS+n9iIjFEfEG8HtSV5qrgIHAs8BgSd2LiNH+Ry/gmoi4k/RaORb4iKQLO+PkTtLaKSLuAL4MnA/0joivAYeSOtt+CNggf8c1M8VqlhisJ2mNiPg3cAswVNIHIuJtYBIwHbi3uGi7tpL78FXgCkm9SW82/wQmS9pH0mHAF4GxuZ+HVVCz18f6OUF4Cegr6SclrQF/IvUZfKWgUOtCs/txqKQz8ijbB0h9nr4UEacAzwMfAPz+UoAWPtg0AodJ6pf7PD8L3Ad8QtIHO3w9t8qVp/QFlLcPAs4GvhsRN+SErBspgRsJDI6IdwoJ1pr/wzsF2B94Hymh7gXsC+wC/J00gGBYTuCsQnLt83eAz0TE7LxvB2Bn0mjbBcD5EfFocVHWhzyIpqkP2onAMaQPKXflr/uAR0mJ2W7APhHxYjHRdm1N/6ua7omkLwOfJyXG3wbOjoirc9ljgBOBQ/06KY6kPYBPAndFxJ/ye8wRwOHAGsAo4IzOeE9xk0IZSl5E2+Zdr0TEjTmhPlvSexFxEymjvjA3Cwwg1RJYAUoStD2BvUj9OkYCV5BeQOcDfwE2AS5zglYVAdwaEbNzreZbEfF3SdMj4lJJq0bEu0UHWQ9KErSPk5rQvkSqnTmQ1B1gJ1K/zXVINZtO0Crng8C/coK2LrAtMAT4LPBv4Jpce7MBqSJgeET8q7Bo61RJHjAY+CHwCKl7087A5aSuND8AVgd+0lnvKU7SypBvzFDgJ8CvgSMlDc2JWgA/yjfwRklbk150rxUZs6W560j9A+ZGxHzgh5LeBS4BxuSma6uA5jXPWQDHSPpFRMzN5Y4A/gNc5wStevKb/jbAH4HvRMQDkp4C5pP6Zq4TEZcUGWNXl++BgFsk3R8Rh0fEi5JeAW4H3o2IvXLZ44GHgStyX1qrspwHDAIuAkZFxP2S9gF2J73P/DQifipp9aZR6p0xgNB90trQ1Pac25XPJzWR/QvoCUyRtHWuQfs6qS8HwBzgkxExs4CQ61oLfQVmkvpzrC1pf4CIuAiYQKoBbWjhOdZBzZqavyTpEkn7AZOBC0id0PfP/dNOAaYVGG7daNYpPSJiGvBN4BRJm0bEy8CfgYnAFpLWLijUupDvwWLS4LMdJP08H3qM9N58AaT+aaTa/9ecoBXuPVKN8xEAETGR1D2gPzBaUg/gnXysU/qSuU9aCyQ1AKtHxMuSNgYWAqsBfUnVmB+SdBFwPLBdRDyen9cpmbO1X7PE4EDgdVJt5j+Ar5GmdbgnIm7NZd4XEa7trCBJnyZ9gPkT6bXzDGni2gOAj5Ka1X7oppvKa/b62B1YC7gzf+I/DTgV2C0inlCa9mFxRLxVYMhdWknT2coR8Z6kNYCpwO0RcZKkM0kD0HoA6wIj3Aet+kruU09SvvS6pO2Bn5O6bnw3lxsKPBMRT3R2DG7ubNl2pAlOnybNoXVKRDwlaV/g1lzmXtInoPWBx8Fzo9WC3Al6OHADqdnmJ6Th6ycC++f+gxNJzTpWIfmf1jnAgRHxpKRPkfoGjiL1Aby6tPO6VVaz0bWHkgbMfEPSCRFxnqRFwL8kDYyIJ4uMtR6UvFf0zona7NyU9g9JiyJitKRewKbA7Ih4qfWzWSWUJGgHkAYEriTp6oj4laSjgUsl9YiIMyvZdcbNnSUkbSKpZ0Q8QPrk/13gjoiYpbTCwOvARpLOINUQHB8R97jJrDiSBkh6f34xfRTYmzRJ7TrAYlJy9llSDc5UUmdPJ9SdrIXXwCygN6mGhkhzCE0idX4+RmmOJ9+DCpO0YcnjT5EGBuwKPElaVeAbknaNiB8DX8Xrp1aUpD4lj08FriRNFvzlXHO5PWli7d9ExPyI+LsTtGLk95RPAd8irUzzT+BySV/JXQW+CnxK0uaVzAGcpC1tM+C5XPV8F3AjMETSdvkT/29Jb/JrAudExGPgN/yiSHofaf6gM/KnzsdIIzgPIU2vsTfwV1LfjmERcalHqXW+Zk1p60laLzfN7Emafft7ABFxN2lm7vERscivm8pR0pPU/+/EvPte0hQBw0lTamwMvAiMV1o15ZKI+L9CAq4DkjYDxuTXyLHAfhGxD6kl5lxJp+VEbSdgcy2Zu86qRFJfSZNKdq1N6tY0GPgwcBjwbUmnRsRUYPeIeKqS/8ucpJXIbyKfJ60ccENEHEOaK+jbkvoBDcCrpPlPbvULqFi5T9ntpNGBo0l9BmaRatEuy6MF5wHjgSmFBdrFlSRopwK/BG6V9KX8IeZoYFdJP8ll73XNQOXlTulvkJo2j8vNmgvzgKbNSfOgQRrd+Ripv6BVVjdga9L8WvcBIyR9jTRlwxBSAnd2RLwJ7BQRz/uDTHVFGnW+sqS/5e3rSLXORwLfjDRQcAJwvKS++V5VlJO0ZnLb8mhgqqS1SPOeTAFuJiVvLzS9cPwCKoakXpI2ypsvkkZwrgJ8PdcevEGqXfse6VPQFRHxXDHRdl2lH1JKagaGAk8AP5Z0ch5UcwJptGAff7CpvKbfce7z9yAwAviqpBNykQeB3SRdRaqJPjEiXigk2DqQu9GslWspzydNAdQn0sz0ewLfiIj7Sf2d985l/d5SZcpL0UXEHsBLkh7K268Bz5FWENgXWJU0V93cqsTlv4WWKc1/chFp5YDXJX0SWJD7q1lBlFZ22An4FKnP01qkRGwH0qoCb0fEWUojCzcmjej06MFO1qyJsw+pq8BclvR5+jFwB3BeRPxA0ioRsbCwgOtEs/uyM/BSRPxbaRqhW0mTcP6StMrD3sCvKjEizRJJHyA18c8AToqIF3Kn891Iq28cB7xNaqEZTErYZhUVb72T9MFYMlvDzcAGEfFhpRHRw4A9gNMi4raqxeQkrXWS9iY1lX0wIl4tOh5LJK0HXE3qZDsq0rJcK5FG4u6Xi30nIl4vKsZ6kd9wDiINzmggvV5OjTSVw69IK28M8b2oLqVlavYhJQdrkpKBDwK/Iq0g0CmLP1vbcu3MVaRlz+4hJWyrk1YVeJg0UKNpWbRjmvo5W/WUjOLcljRH4H0RcXA+dguwZkTsnrfXy4l21abbcnNnGyLiD8BRpCk5rEClzWS5aeZaUo3ARyXtERGLI+Je0j/C10hV0tbJcoLc9Hg3Us3ZYZHWqX2dtIzN8Ny0thj4nBO0ymvW9Lwj8KncbLMK6bWwMCKmkAYOHCZpbTc9V46k/pI+EBHvASeRRnHOJM3XuBOpD9pBwKSIOB3YywlaMXKCNpQ0m8NFwM6SrsnHDgAaJf09F3+p6TnVis81aWWqZuZsS2vWhDOUNL/fv0n90Y4kdYS+lNT0uS7pH58n4uxkuT/GWcCnSevUHUea4uS4iJiQyxxEmj9wD1wzUBXNXh+rkqY5GUV6fXyMtKD9u5J2jzRlkNdIrSBJqwMXkhLkmyNigqQRpAFOd5Kmd/ohMBT4eUQc6/eXYuQPKqsAvyMtTXeN0vRADwBPRcTwXG7HiHiokBj9d2ErCqX1675CqpI+EDiNNHx9H1L/mgHAHhHxVGFBdlG56f9M4Pu5hhlJq5HmCtoU+E2uyWwqv3pEvF1ErPWiqSasJEE7jrR03ZHANaQ+mx+JiEX52GeBg1yzWXm5xnkPUjL2PeAp0oeaH0TEI0oLqY8kvW46ZSFuW36SzgMejojf5e2tgftJXQNOzfsKSaSdpFnNy29GfUn9aY6NNIP9XqSk4dsR8UdJA4H/eBRn51Naw/Fl0uoBEyRtTlrz8cukFTf2IyXIN0fEXcVFWl+UlxTKj/chdc34SqRFuo8m9dnsQZpi40jgC+GlhapK0g7AeaR5N3ch1fYfnQdzeMWNApT0QdsCeIv0v21/UqvAiEirC20LHEMaoHZmRNxYVLzuk2Y1qVkftIiIOaRh0Jvl5pq7gN8Ax+Y3qxlO0CojD5rZD/hW/uc1FvhnRLyday0nALOBfZTWvbUKk9QbeEpLFkH/MKn5bNO8/VvgCtJ9ATjECVr1RcTfSQnyq6R78THS8nQr4RU3qi4nxk0rCdxLmmLrF6T5Nq8Fxkq6kjTl1qWkfs//KShcwDVpVuOUZkvvSWo2OJvUGX18RPyfpC+ShrIf5/4clZebPCeSJnM+t1lNzkbAmx4FXT2S9iPNu7VTniboHGAr0jQO04qNzkrlfk49gB8BP4qIGQWHVFckrZYHN6G0QPpBpGXq/o/UhWZ70moC7wP6A3NIUzhdCHw2ClyJw0ma1ZRmL6bjSaPRjomIx5QmF/4xS0asbQoc5Tek6snNzBezJDHoHhGLio6rXuVmzp8CH8r34wzSnIHfi4h/FBudWfFyV5ivkD7ov0IaFLCQ1Jf5ZdLST6NI06AcHRHPSNqE1L3my0W/vzhJs5qR33A+RUrEZgE/I3XcnNqUvCmtq7oJ6dPOo27irL48wvZCYGfXnBVPJRNvk1bb+C6pFuCo8ATCVsdKJhO+OCKuzPs2IDVn/j4ivpP39SatjHJbRDyc9/WMtLRaoVYuOgAzAKUVAr4PnBURM3OftAHA7sDUpto1YPuI+CswvaBQ615E3CFpFeBuSYPJ3QaLjqteRcTE3IXzAVLi/A1J73eCZvVM0pakUc7fzgOeupFqxi6WNBz4vaTGiPh+RLws6XulrQK1kKCBBw5YDcjD1U8hNWtOkNQjv+lfAHw6971B0heAcZLWLzBcAyLiFuBjkSYRdoJWsIiYCIwBJufRa68UHZNZwdYGtmuawxH4A6kFhoh4mjQY6hhJ38n7arLbhmvSrBa8S5oc9T+SegCnS/o4aU271YGrJf0W2JHUifP54kK1Jp4wuLbkDzh3O2k2g4j4q6R9JT0NPA38ual5Mx9/WtJHSZOh1yz3SbPC5abNk0n90bYC7gb+CvwLOAB4Evg9QES8WFCYZma2gpG0B2kk5ypN89Ll5OwE4PiImF/LKz64Js0Kl+etGQvcR1rb7pbIy9ZIGglMc3JmZmbtFRGTJe1Pmm5jc0kDgMuB0yNifi5TkwkaOEmzGpGbzu7PXwBI+hywDWm0mpmZWbvlwTWLJb0DPAOcGhF3FB1XOdzcaTUnDwwYDnwJGO6Z0s3MrKNy02fPiLi56FjK5STNak5eWmh3YEZ4sXQzM+tEtdwHrTknaWZmZmY1yPOkmZmZmdUgJ2lmZmZmNchJmpmZmVkNcpJmZmZmVoM8T5qZ1R1J7wcm5831gEZgXt7e0YuTm1kt8OhOM6trks4G3oqIC4qOxcyslJs7zcxKSBoh6SFJ/5B0maSV8v5xkqZIekzSt0rKz5b0fUkPSHpY0g6S7pT0b0lfKu4nMbMVnZM0M7NM0tbAZ4CPRsT2pC4hh+TDp0fEYGA7YC9JW5Y89dmI+AjwAPCLpnPgJc3MrAPcJ83MbIk9gQ8DUyQBNACz8rFDJR1N+r/ZF9gS+Fc+dmv+Ph1YOSLeBt7O6wWukdemNTNrFydpZmZLCLgyIr651E5pAHAiaVDBfEm/BnqUFHk3f19c8rhp2/9nzWy5uLnTzGyJu4GDJfWGNApUUn+gJ/Am8Iak9YEhBcZoZnXCn/DMzLKImC7p28DdecDAIuA4YAqpafNR4Gngb8VFaWb1wlNwmJmZmdUgN3eamZmZ1SAnaWZmZmY1yEmamZmZWQ1ykmZmZmZWg5ykmZmZmdUgJ2lmZmZmNchJmpmZmVkNcpJmZmZmVoP+H/afJJ8/n9j/AAAAAElFTkSuQmCC\n",
905
      "text/plain": [
906
       "<Figure size 720x288 with 1 Axes>"
907 908
      ]
     },
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     "metadata": {
      "needs_background": "light"
     },
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     "output_type": "display_data"
    }
   ],
   "source": [
    "df_hpd = pd.DataFrame(pm.stats.hpd(trace['atts']), \n",
    "                      columns=['hpd_low', 'hpd_high'], \n",
    "                      index=teams.team.values)\n",
919
    "df_median = pd.DataFrame(np.quantile(trace['atts'], 0.5, axis=0), \n",
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    "                         columns=['hpd_median'], \n",
    "                         index=teams.team.values)\n",
    "df_hpd = df_hpd.join(df_median)\n",
    "df_hpd['relative_lower'] = df_hpd.hpd_median - df_hpd.hpd_low\n",
    "df_hpd['relative_upper'] = df_hpd.hpd_high - df_hpd.hpd_median\n",
    "df_hpd = df_hpd.sort_values(by='hpd_median')\n",
    "df_hpd = df_hpd.reset_index()\n",
    "df_hpd['x'] = df_hpd.index + .5\n",
    "\n",
    "\n",
    "fig, axs = plt.subplots(figsize=(10,4))\n",
    "axs.errorbar(df_hpd.x, df_hpd.hpd_median, \n",
    "             yerr=(df_hpd[['relative_lower', 'relative_upper']].values).T, \n",
    "             fmt='o')\n",
    "axs.set_title('HPD of Attack Strength, by Team')\n",
    "axs.set_xlabel('Team')\n",
    "axs.set_ylabel('Posterior Attack Strength')\n",
    "_= axs.set_xticks(df_hpd.index + .5)\n",
    "_= axs.set_xticklabels(df_hpd['index'].values, rotation=45)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is one of the powerful things about Bayesian modelling, we can have *uncertainty quantification* of some of our estimates. \n",
    "We've got a Bayesian credible interval for the attack strength of different countries. \n",
    "\n",
    "We can see an overlap between Ireland, Wales and England which is what you'd expect since these teams have won in recent years.\n",
    "\n",
    "Italy is well behind everyone else - which is what we'd expect and there's an overlap between Scotland and France which seems about right.\n",
    "\n",
    "There are probably some effects we'd like to add in here, like weighting more recent results more strongly. \n",
    "However that'd be a much more complicated model."
   ]
  },
  {
   "cell_type": "code",
958
   "execution_count": 29,
959
   "metadata": {},