examples/case_studies/item_response_nba.ipynb

{
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   "cell_type": "markdown",
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   "source": [
    "(item_response_nba)=\n",
    "# NBA Foul Analysis with Item Response Theory\n",
    "\n",
    ":::{post} Apr 17, 2022\n",
    ":tags: hierarchical model, case study, generalized linear model \n",
    ":category: intermediate, tutorial\n",
    ":author:  Austin Rochford, Lorenzo Toniazzi\n",
    ":::"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on PyMC v4.0.0b6\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "import arviz as az\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pymc as pm\n",
    "\n",
    "%matplotlib inline\n",
    "print(f\"Running on PyMC v{pm.__version__}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "RANDOM_SEED = 8927\n",
    "rng = np.random.default_rng(RANDOM_SEED)\n",
    "az.style.use(\"arviz-darkgrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "This tutorial shows an application of Bayesian Item Response Theory {cite:p}`fox2010bayesian` to NBA basketball foul calls data using PyMC. Based on Austin Rochford's blogpost [NBA Foul Calls and Bayesian Item Response Theory](https://www.austinrochford.com/posts/2017-04-04-nba-irt.html).\n",
    "\n",
    "### Motivation\n",
    "Our scenario is that we observe a binary outcome (a foul being called or not) from an interaction (a basketball play) of two agents with two different roles (the player committing the alleged foul and the player disadvantaged in the play). Moreover, each committing or disadvantaged agent is an individual which might be observed several times (say LeBron James observed committing a foul in more than one play). Then it might be that not only the agent's role, but also the abilities of the single individual player contribute to the observed outcome. And so we'd like to __estimate the contribution to the observed outcome of each individual's (latent) ability as a committing or disadvantaged agent.__ This would allow us, for example, to rank players from more to less effective, quantify uncertainty in this ranking and discover extra hierarchical structures involved in foul calls. All pretty useful stuff! \n",
    " \n",
    "\n",
    "So how can we study this common and complex __multi-agent interaction__ scenario, with __hierarchical__ structures between  more than a thousand individuals? \n",
    "\n",
    "Despite the scenario's overwhelming complexity, Bayesian Item Response Theory combined with modern powerful statistical software allows for quite elegant and effective modeling options. One of these options employs a {term}`Generalized Linear Model` called [Rasch model](https://en.wikipedia.org/wiki/Rasch_model), which we now discuss in more detail.\n",
    "\n",
    "\n",
    "### Rasch Model\n",
    "We sourced our data from the official [NBA Last Two Minutes Reports](https://official.nba.com/2020-21-nba-officiating-last-two-minute-reports/) with game data between 2015 to 2021. In this dataset, each row `k`  is one play involving two players (the committing and the disadvantaged) where a foul has been either called or not. So we model the probability `p_k` that a referee calls a foul in play `k` as a function of the players involved. Hence we define two latent variables for each player, namely:\n",
    "- `theta`: which estimates the player's ability to have a foul called when disadvantaged, and\n",
    "- `b`: which estimates the player's ability  to have a foul not called when committing.\n",
    "\n",
    "Note that the higher these player's parameters, the better the outcome for the player's team. These two parameters are then estimated using a standard Rasch model, by assuming the log-odds-ratio of `p_k` equals `theta-b` for the corresponding players involved in play `k`. Also, we place hierarchical hyperpriors on all `theta`'s and all `b`'s to account for shared abilities between players and largely different numbers of observations for different players.\n",
    "\n",
    "\n",
    "### Discussion \n",
    "Our analysis gives an estimate of the latent skills `theta` and `b` for each player in terms of posterior distributions. We analyze this outcome in three ways. \n",
    "\n",
    "We first display the role of shared hyperpriors, by showing how posteriors of players with little observations are drawn to the league average.\n",
    "\n",
    "Secondly, we rank the posteriors by their mean to view best and worst committing and disadvantaged players, and observe that several players still rank in the top 10 of the same model estimated in [Austin Rochford blogpost](https://www.austinrochford.com/posts/2017-04-04-nba-irt.html) on different data.\n",
    "\n",
    "Thirdly, we show how we spot that grouping payers by their position is likely to be an informative extra hierarchical layer to introduce in our model, and leave this as an exercise for the interested reader. Let us conclude by mentioning that this opportunity of easily adding informed hierarchical structure to a model is one of the features that makes Bayesian modelling very flexible and powerful for quantifying uncertainty in scenarios where introducing (or discovering) problem-specific knowledge is crucial.\n",
    "\n",
    "\n",
    "The analysis in this notebook is performed in four main steps: \n",
    "\n",
    "1. Data collection and processing.\n",
    "2. Definition and instantiation of the Rasch model. \n",
    "3. Posterior sampling and convergence checks.\n",
    "4. Analysis of the posterior results.\n",
    "\n",
    "## Data collection and processing\n",
    "We first import data from the original data set, which can be found at [this URL](https://raw.githubusercontent.com/polygraph-cool/last-two-minute-report/32f1c43dfa06c2e7652cc51ea65758007f2a1a01/output/all_games.csv). Each row corresponds to a play between the NBA seasons 2015-16 and 2020-21. We imported only five columns, namely\n",
    "- `committing`: the  name of the committing player in the play.\n",
    "- `disadvantaged`: the name of the disadvantaged player in the play.\n",
    "- `decision`: the reviewed decision of the play, which can take four values, namely:\n",
    "    - `CNC`: correct noncall, `INC`: incorrect noncall, `IC`: incorrect call, `CC`: correct call.\n",
    "- `committing_position`: the position of the committing player which can take values\n",
    "    - `G`: guard, `F`: forward, `C`: center, `G-F`, `F-G`, `F-C`, `C-F`.\n",
    "- `disadvantaged_position`: the position of the disadvantaged player, with possible values as above.\n",
    "\n",
    "We note that we  already removed  from the original  dataset the plays where less than two players are involved (for example travel calls or clock violations). Also, the original dataset does not contain information on the players' position, which we added ourselves."
   ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>committing</th>\n",
       "      <th>disadvantaged</th>\n",
       "      <th>decision</th>\n",
       "      <th>committing_position</th>\n",
       "      <th>disadvantaged_position</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>play_id</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>1</th>\n",
       "      <td>Avery Bradley</td>\n",
       "      <td>Stephen Curry</td>\n",
       "      <td>CNC</td>\n",
       "      <td>G</td>\n",
       "      <td>G</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Isaiah Thomas</td>\n",
       "      <td>Andre Iguodala</td>\n",
       "      <td>CNC</td>\n",
       "      <td>G</td>\n",
       "      <td>G-F</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Jae Crowder</td>\n",
       "      <td>Harrison Barnes</td>\n",
       "      <td>INC</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Draymond Green</td>\n",
       "      <td>Isaiah Thomas</td>\n",
       "      <td>CC</td>\n",
       "      <td>F</td>\n",
       "      <td>G</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Avery Bradley</td>\n",
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      "text/plain": [
       "             committing    disadvantaged decision committing_position  \\\n",
       "play_id                                                                 \n",
       "1         Avery Bradley    Stephen Curry      CNC                   G   \n",
       "3         Isaiah Thomas   Andre Iguodala      CNC                   G   \n",
       "4           Jae Crowder  Harrison Barnes      INC                   F   \n",
       "6        Draymond Green    Isaiah Thomas       CC                   F   \n",
       "7         Avery Bradley    Stephen Curry       CC                   G   \n",
       "\n",
       "        disadvantaged_position  \n",
       "play_id                         \n",
       "1                            G  \n",
       "3                          G-F  \n",
       "4                            F  \n",
       "6                            G  \n",
       "7                            G  "
      ]
     },
     "execution_count": 3,
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   ],
   "source": [
    "try:\n",
    "    df_orig = pd.read_csv(os.path.join(\"..\", \"data\", \"item_response_nba.csv\"), index_col=0)\n",
    "except FileNotFoundError:\n",
    "    df_orig = pd.read_csv(pm.get_data(\"item_response_nba.csv\"), index_col=0)\n",
    "df_orig.head()"
   ]
  },
  {
   "cell_type": "markdown",
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    "We now process our data in three steps:\n",
    " 1. We create a dataframe `df` by removing the position information from `df_orig`, and we create a dataframe `df_position` collecting all players with the respective position. (This last dataframe will not be used until the very end of the notebook.)\n",
    " 2. We add a  column to `df`, called `foul_called`, that assigns 1 to a play if a foul was called, and 0 otherwise.\n",
    " 3. We assign IDs to committing and disadvantaged players and use this indexing to identify the respective players in each observed play.\n",
    "\n",
    "Finally, we display the head of our main dataframe `df` along with some basic statistics."
   ]
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of observed plays: 46861\n",
      "Number of disadvanteged players: 770\n",
      "Number of committing players: 789\n",
      "Global probability of a foul being called: 23.3%\n",
      "\n",
      "\n"
     ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>committing</th>\n",
       "      <th>disadvantaged</th>\n",
       "      <th>decision</th>\n",
       "      <th>foul_called</th>\n",
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       "      <td>Avery Bradley</td>\n",
       "      <td>Stephen Curry</td>\n",
       "      <td>CNC</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Isaiah Thomas</td>\n",
       "      <td>Andre Iguodala</td>\n",
       "      <td>CNC</td>\n",
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       "      <th>4</th>\n",
       "      <td>Jae Crowder</td>\n",
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       "             committing    disadvantaged decision  foul_called\n",
       "play_id                                                       \n",
       "1         Avery Bradley    Stephen Curry      CNC            0\n",
       "3         Isaiah Thomas   Andre Iguodala      CNC            0\n",
       "4           Jae Crowder  Harrison Barnes      INC            0\n",
       "6        Draymond Green    Isaiah Thomas       CC            1\n",
       "7         Avery Bradley    Stephen Curry       CC            1"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1. Construct df and df_position\n",
    "df = df_orig[[\"committing\", \"disadvantaged\", \"decision\"]]\n",
    "\n",
    "df_position = pd.concat(\n",
    "    [\n",
    "        df_orig.groupby(\"committing\").committing_position.first(),\n",
    "        df_orig.groupby(\"disadvantaged\").disadvantaged_position.first(),\n",
    "    ]\n",
    ").to_frame()\n",
    "df_position = df_position[~df_position.index.duplicated(keep=\"first\")]\n",
    "df_position.index.name = \"player\"\n",
    "df_position.columns = [\"position\"]\n",
    "\n",
    "# 2. Create the binary foul_called variable\n",
    "def foul_called(decision):\n",
    "    \"\"\"Correct and incorrect noncalls (CNC and INC) take value 0.\n",
    "    Correct and incorrect calls (CC and IC) take value 1.\n",
    "    \"\"\"\n",
    "    out = 0\n",
    "    if (decision == \"CC\") | (decision == \"IC\"):\n",
    "        out = 1\n",
    "    return out\n",
    "\n",
    "\n",
    "df = df.assign(foul_called=lambda df: df[\"decision\"].apply(foul_called))\n",
    "\n",
    "# 3 We index observed calls by committing and disadvantaged players\n",
    "committing_observed, committing = pd.factorize(df.committing, sort=True)\n",
    "disadvantaged_observed, disadvantaged = pd.factorize(df.disadvantaged, sort=True)\n",
    "df.index.name = \"play_id\"\n",
    "\n",
    "# Display of main dataframe with some statistics\n",
    "print(f\"Number of observed plays: {len(df)}\")\n",
    "print(f\"Number of disadvanteged players: {len(disadvantaged)}\")\n",
    "print(f\"Number of committing players: {len(committing)}\")\n",
    "print(f\"Global probability of a foul being called: \" f\"{100*round(df.foul_called.mean(),3)}%\\n\\n\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Item Response Model\n",
    "\n",
    "### Model definition\n",
    "\n",
    "We denote by:\n",
    "- $N_d$ and $N_c$ the number of disadvantaged and committing players, respectively, \n",
    "- $K$ the number of plays,\n",
    "- $k$ a play, \n",
    "- $y_k$ the observed call/noncall in play $k$,\n",
    "- $p_k$ the probability of a foul being called in play $k$,\n",
    "- $i(k)$ the disadvantaged player in play $k$, and by\n",
    "- $j(k)$ the committing player in play $k$.\n",
    "\n",
    "We assume that each disadvantaged player is described by the latent variable: \n",
    "- $\\theta_i$ for $i=1,2,...,N_d$,\n",
    "\n",
    "and each committing player is described by the latent variable: \n",
    "- $b_j$ for $j=1,2,...,N_c$.\n",
    "\n",
    "Then we model each observation $y_k$ as the result of an independent Bernoulli trial with probability $p_k$, where\n",
    "\n",
    "$$\n",
    "p_k =\\text{sigmoid}(\\eta_k)=\\left(1+e^{-\\eta_k}\\right)^{-1},\\quad\\text{with}\\quad \\eta_k=\\theta_{i(k)}-b_{j(k)},\n",
    "$$\n",
    "\n",
    "for $k=1,2,...,K$, by defining (via a [non-centered parametrisation](https://twiecki.io/blog/2017/02/08/bayesian-hierchical-non-centered/))\n",
    "\n",
    "\\begin{align*}\n",
    "\\theta_{i}&= \\sigma_\\theta\\Delta_{\\theta,i}+\\mu_\\theta\\sim \\text{Normal}(\\mu_\\theta,\\sigma_\\theta^2),  &i=1,2,...,N_d,\\\\\n",
    "b_{j}&= \\sigma_b\\Delta_{b,j}\\sim \\text{Normal}(0,\\sigma_b^2), &j=1,2,...,N_c,\n",
    "\\end{align*}\n",
    "\n",
    "with priors/hyperpriors\n",
    "\n",
    "\\begin{align*}\n",
    "\\Delta_{\\theta,i}&\\sim \\text{Normal}(0,1),  &i=1,2,...,N_d,\\\\\n",
    "\\Delta_{b,j}&\\sim \\text{Normal}(0,1), &j=1,2,...,N_c,\\\\\n",
    "\\mu_\\theta&\\sim \\text{Normal}(0,100),\\\\\n",
    "\\sigma_\\theta &\\sim \\text{HalfCauchy}(2.5),\\\\\n",
    "\\sigma_b &\\sim \\text{HalfCauchy}(2.5).\n",
    "\\end{align*}\n",
    "\n",
    "Note that $p_k$ is always dependent on $\\mu_\\theta,\\,\\sigma_\\theta$ and $\\sigma_b$ (\"pooled priors\") and also depends on the actual players involved in the play due to  $\\Delta_{\\theta,i}$ and $\\Delta_{b,j}$ (\"unpooled priors\"). This means our model features partial pooling. Morover, note that we do not pool $\\theta$'s with $b$'s, hence assuming these skills are independent even for the same player. Also, note that  we normalised the mean of $b_{j}$ to zero. \n",
    "\n",
    "Finally, notice how we worked backwards from our data to construct this model. This is a very natural way to construct a model, allowing us to quickly see how each variable connects to others and their intuition. Meanwhile, when instantiating the model below, the construction goes in the opposite direction, i.e. starting from priors and moving up to the observations.\n",
    "\n",
    "### PyMC implementation\n",
    "We now implement the model above in PyMC. Note that, to easily keep track of the players (as we have hundreds of them being both committing and disadvantaged), we make use of the `coords` argument for {class}`pymc.Model`. (For tutorials on this functionality see the notebook {ref}`data_container` or [this blogpost](https://oriolabrilpla.cat/python/arviz/pymc3/xarray/2020/09/22/pymc3-arviz.html).) We choose our priors to be the same as in [Austin Rochford's post](https://www.austinrochford.com/posts/2017-04-04-nba-irt.html), to make the comparison consistent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "coords = {\"disadvantaged\": disadvantaged, \"committing\": committing}\n",
    "\n",
    "with pm.Model(coords=coords) as model:\n",
    "\n",
    "    # Data\n",
    "    foul_called_observed = pm.Data(\"foul_called_observed\", df.foul_called, mutable=False)\n",
    "\n",
    "    # Hyperpriors\n",
    "    mu_theta = pm.Normal(\"mu_theta\", 0.0, 100.0)\n",
    "    sigma_theta = pm.HalfCauchy(\"sigma_theta\", 2.5)\n",
    "    sigma_b = pm.HalfCauchy(\"sigma_b\", 2.5)\n",
    "\n",
    "    # Priors\n",
    "    Delta_theta = pm.Normal(\"Delta_theta\", 0.0, 1.0, dims=\"disadvantaged\")\n",
    "    Delta_b = pm.Normal(\"Delta_b\", 0.0, 1.0, dims=\"committing\")\n",
    "\n",
    "    # Deterministic\n",
    "    theta = pm.Deterministic(\"theta\", Delta_theta * sigma_theta + mu_theta, dims=\"disadvantaged\")\n",
    "    b = pm.Deterministic(\"b\", Delta_b * sigma_b, dims=\"committing\")\n",
    "    eta = pm.Deterministic(\"eta\", theta[disadvantaged_observed] - b[committing_observed])\n",
    "\n",
    "    # Likelihood\n",
    "    y = pm.Bernoulli(\"y\", logit_p=eta, observed=foul_called_observed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now plot our model to show the hierarchical structure (and the non-centered parametrisation) on the variables `theta` and `b`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
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    "pm.model_to_graphviz(model)"
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   "source": [
    "## Sampling and convergence\n",
    "\n",
    "We now sample from our Rasch model."
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   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [mu_theta, sigma_theta, sigma_b, Delta_theta, Delta_b]\n"
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       "      100.00% [10000/10000 07:09<00:00 Sampling 4 chains, 0 divergences]\n",
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     "text": [
      "Sampling 4 chains for 1_500 tune and 1_000 draw iterations (6_000 + 4_000 draws total) took 431 seconds.\n"
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   "source": [
    "with model:\n",
    "    trace = pm.sample(1000, tune=1500, random_seed=RANDOM_SEED)"
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   "cell_type": "markdown",
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   "source": [
    "We plot below the energy difference of the obtained trace. Also, we assume our sampler has converged as it passed all automatic PyMC convergence checks."
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  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_energy(trace);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Posterior analysis\n",
    "### Visualisation of partial pooling\n",
    "Our first check is to plot \n",
    "- y: the difference between the raw mean probability (from the data) and the posterior mean probability for each disadvantaged and committing player\n",
    "- x: as a function of the number of observations per disadvantaged and committing player.\n",
    "\n",
    "These plots show, as expected, that the hierarchical structure of our model tends to estimate posteriors towards the global mean for players with a low amount of observations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Global posterior means of μ_theta and μ_b\n",
    "mu_theta_mean, mu_b_mean = trace.posterior[\"mu_theta\"].mean(), 0\n",
    "# Raw mean from data of each disadvantaged player\n",
    "disadvantaged_raw_mean = df.groupby(\"disadvantaged\")[\"foul_called\"].mean()\n",
    "# Raw mean from data of each committing player\n",
    "committing_raw_mean = df.groupby(\"committing\")[\"foul_called\"].mean()\n",
    "# Posterior mean of each disadvantaged player\n",
    "disadvantaged_posterior_mean = (\n",
    "    1 / (1 + np.exp(-trace.posterior[\"theta\"].mean(dim=[\"chain\", \"draw\"]))).to_pandas()\n",
    ")\n",
    "# Posterior mean of each committing player\n",
    "committing_posterior_mean = (\n",
    "    1\n",
    "    / (1 + np.exp(-(mu_theta_mean - trace.posterior[\"b\"].mean(dim=[\"chain\", \"draw\"])))).to_pandas()\n",
    ")\n",
    "\n",
    "# Compute difference of raw and posterior mean for each\n",
    "# disadvantaged and committing player\n",
    "def diff(a, b):\n",
    "    return a - b\n",
    "\n",
    "\n",
    "df_disadvantaged = pd.DataFrame(\n",
    "    disadvantaged_raw_mean.combine(disadvantaged_posterior_mean, diff),\n",
    "    columns=[\"Raw - posterior mean\"],\n",
    ")\n",
    "df_committing = pd.DataFrame(\n",
    "    committing_raw_mean.combine(committing_posterior_mean, diff), columns=[\"Raw - posterior mean\"]\n",
    ")\n",
    "# Add the number of observations for each disadvantaged and committing player\n",
    "df_disadvantaged = df_disadvantaged.assign(obs_disadvantaged=df[\"disadvantaged\"].value_counts())\n",
    "df_committing = df_committing.assign(obs_committing=df[\"committing\"].value_counts())\n",
    "\n",
    "# Plot the difference between raw and posterior means as a function of\n",
    "# the number of observations\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True)\n",
    "fig.suptitle(\n",
    "    \"Difference of raw and posterior mean of player's foul call probability as \"\n",
    "    \"\\na function of the player's number of observations\\n\",\n",
    "    fontsize=15,\n",
    ")\n",
    "ax1.scatter(data=df_disadvantaged, x=\"obs_disadvantaged\", y=\"Raw - posterior mean\", s=7, marker=\"o\")\n",
    "ax1.set_title(\"theta\")\n",
    "ax1.set_ylabel(\"Raw mean - posterior mean\")\n",
    "ax1.set_xlabel(\"obs_disadvantaged\")\n",
    "ax2.scatter(data=df_committing, x=\"obs_committing\", y=\"Raw - posterior mean\", s=7)\n",
    "ax2.set_title(\"b\")\n",
    "ax2.set_xlabel(\"obs_committing\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top and bottom committing and disadvantaged players \n",
    "As we successfully estimated the skills of disadvantaged (`theta`) and committing (`b`) players, we can finally check which players perform better and worse in our model.\n",
    "So we now plot our posteriors using forest plots. We plot the 10 top and bottom players ranked with respect to the latent skill `theta` and `b`, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1700x1400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def order_posterior(inferencedata, var, bottom_bool):\n",
    "    xarray_ = inferencedata.posterior[var].mean(dim=[\"chain\", \"draw\"])\n",
    "    return xarray_.sortby(xarray_, ascending=bottom_bool)\n",
    "\n",
    "\n",
    "top_theta, bottom_theta = (\n",
    "    order_posterior(trace, \"theta\", False),\n",
    "    order_posterior(trace, \"theta\", True),\n",
    ")\n",
    "top_b, bottom_b = (order_posterior(trace, \"b\", False), order_posterior(trace, \"b\", True))\n",
    "\n",
    "amount = 10  # How many top players we want to display in each cathegory\n",
    "\n",
    "fig = plt.figure(figsize=(17, 14))\n",
    "fig.suptitle(\n",
    "    \"\\nPosterior estimates for top and bottom disadvantaged (theta) and \"\n",
    "    \"committing (b) players \\n(94% HDI)\\n\",\n",
    "    fontsize=25,\n",
    ")\n",
    "theta_top_ax = fig.add_subplot(221)\n",
    "b_top_ax = fig.add_subplot(222)\n",
    "theta_bottom_ax = fig.add_subplot(223, sharex=theta_top_ax)\n",
    "b_bottom_ax = fig.add_subplot(224, sharex=b_top_ax)\n",
    "\n",
    "# theta: plot top\n",
    "az.plot_forest(\n",
    "    trace,\n",
    "    var_names=[\"theta\"],\n",
    "    combined=True,\n",
    "    coords={\"disadvantaged\": top_theta[\"disadvantaged\"][:amount]},\n",
    "    ax=theta_top_ax,\n",
    "    labeller=az.labels.NoVarLabeller(),\n",
    ")\n",
    "theta_top_ax.set_title(f\"theta: top {amount}\")\n",
    "theta_top_ax.set_xlabel(\"theta\\n\")\n",
    "theta_top_ax.set_xlim(xmin=-2.5, xmax=0.1)\n",
    "theta_top_ax.vlines(mu_theta_mean, -1, amount, \"k\", \"--\", label=(\"League average\"))\n",
    "theta_top_ax.legend(loc=2)\n",
    "\n",
    "\n",
    "# theta: plot bottom\n",
    "az.plot_forest(\n",
    "    trace,\n",
    "    var_names=[\"theta\"],\n",
    "    colors=\"blue\",\n",
    "    combined=True,\n",
    "    coords={\"disadvantaged\": bottom_theta[\"disadvantaged\"][:amount]},\n",
    "    ax=theta_bottom_ax,\n",
    "    labeller=az.labels.NoVarLabeller(),\n",
    ")\n",
    "theta_bottom_ax.set_title(f\"theta: bottom {amount}\")\n",
    "theta_bottom_ax.set_xlabel(\"theta\")\n",
    "theta_bottom_ax.vlines(mu_theta_mean, -1, amount, \"k\", \"--\", label=(\"League average\"))\n",
    "theta_bottom_ax.legend(loc=2)\n",
    "\n",
    "# b: plot top\n",
    "az.plot_forest(\n",
    "    trace,\n",
    "    var_names=[\"b\"],\n",
    "    colors=\"blue\",\n",
    "    combined=True,\n",
    "    coords={\"committing\": top_b[\"committing\"][:amount]},\n",
    "    ax=b_top_ax,\n",
    "    labeller=az.labels.NoVarLabeller(),\n",
    ")\n",
    "b_top_ax.set_title(f\"b: top {amount}\")\n",
    "b_top_ax.set_xlabel(\"b\\n\")\n",
    "b_top_ax.set_xlim(xmin=-1.5, xmax=1.5)\n",
    "b_top_ax.vlines(0, -1, amount, \"k\", \"--\", label=\"League average\")\n",
    "b_top_ax.legend(loc=2)\n",
    "\n",
    "# b: plot bottom\n",
    "az.plot_forest(\n",
    "    trace,\n",
    "    var_names=[\"b\"],\n",
    "    colors=\"blue\",\n",
    "    combined=True,\n",
    "    coords={\"committing\": bottom_b[\"committing\"][:amount]},\n",
    "    ax=b_bottom_ax,\n",
    "    labeller=az.labels.NoVarLabeller(),\n",
    ")\n",
    "b_bottom_ax.set_title(f\"b: bottom {amount}\")\n",
    "b_bottom_ax.set_xlabel(\"b\")\n",
    "b_bottom_ax.vlines(0, -1, amount, \"k\", \"--\", label=\"League average\")\n",
    "b_bottom_ax.legend(loc=2)\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By visiting [Austin Rochford post](https://www.austinrochford.com/posts/2017-04-04-nba-irt.html) and checking the analogous table for the Rasch model there (which uses data from the 2016-17 season),  the reader can see that several top players in both skills are still in the top 10 with our larger data set (covering seasons 2015-16 to 2020-21)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Discovering extra hierarchical structure\n",
    "\n",
    "A natural question to ask is whether players skilled as disadvantaged players (i.e. players with high `theta`) are also likely to be skilled as committing players  (i.e. with high `b`), and the other way around. So, the next two plots show the `theta` (resp. `b`) score for the top players with respect to `b` ( resp.`theta`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1700x1400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "amount = 20  # How many top players we want to display\n",
    "top_theta_players = top_theta[\"disadvantaged\"][:amount].values\n",
    "top_b_players = top_b[\"committing\"][:amount].values\n",
    "\n",
    "top_theta_in_committing = set(committing).intersection(set(top_theta_players))\n",
    "top_b_in_disadvantaged = set(disadvantaged).intersection(set(top_b_players))\n",
    "if (len(top_theta_in_committing) < amount) | (len(top_b_in_disadvantaged) < amount):\n",
    "    print(\n",
    "        f\"Some players in the top {amount} for theta (or b) do not have observations for b (or theta).\\n\",\n",
    "        \"Plot not shown\",\n",
    "    )\n",
    "else:\n",
    "    fig = plt.figure(figsize=(17, 14))\n",
    "    fig.suptitle(\n",
    "        \"\\nScores as committing (b) for best disadvantaged (theta) players\"\n",
    "        \" and vice versa\"\n",
    "        \"\\n(94% HDI)\\n\",\n",
    "        fontsize=25,\n",
    "    )\n",
    "    b_top_theta = fig.add_subplot(121)\n",
    "    theta_top_b = fig.add_subplot(122)\n",
    "\n",
    "    az.plot_forest(\n",
    "        trace,\n",
    "        var_names=[\"b\"],\n",
    "        colors=\"blue\",\n",
    "        combined=True,\n",
    "        coords={\"committing\": top_theta_players},\n",
    "        figsize=(7, 7),\n",
    "        ax=b_top_theta,\n",
    "        labeller=az.labels.NoVarLabeller(),\n",
    "    )\n",
    "    b_top_theta.set_title(f\"\\nb score for top {amount} in theta\\n (94% HDI)\\n\\n\", fontsize=17)\n",
    "    b_top_theta.set_xlabel(\"b\")\n",
    "    b_top_theta.vlines(mu_b_mean, -1, amount, color=\"k\", ls=\"--\", label=\"League average\")\n",
    "    b_top_theta.legend(loc=\"upper right\", bbox_to_anchor=(0.46, 1.05))\n",
    "\n",
    "    az.plot_forest(\n",
    "        trace,\n",
    "        var_names=[\"theta\"],\n",
    "        colors=\"blue\",\n",
    "        combined=True,\n",
    "        coords={\"disadvantaged\": top_b_players},\n",
    "        figsize=(7, 7),\n",
    "        ax=theta_top_b,\n",
    "        labeller=az.labels.NoVarLabeller(),\n",
    "    )\n",
    "    theta_top_b.set_title(f\"\\ntheta score for top {amount} in b\\n (94% HDI)\\n\\n\", fontsize=17)\n",
    "    theta_top_b.set_xlabel(\"theta\")\n",
    "    theta_top_b.vlines(mu_theta_mean, -1, amount, color=\"k\", ls=\"--\", label=\"League average\")\n",
    "    theta_top_b.legend(loc=\"upper right\", bbox_to_anchor=(0.46, 1.05));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These plots suggest that scoring high in `theta` does not correlate with high or low scores in `b`. Moreover, with a little knowledge of NBA basketball, one can visually note that a higher score in `b` is expected from players playing center or forward rather than guards or point guards. \n",
    "Given the last observation, we decide to plot a histogram for the occurrence of different positions for top disadvantaged (`theta`) and committing (`b`) players. Interestingly, we see below that the largest share of best disadvantaged players are guards, meanwhile, the largest share of best committing players are centers (and at the same time a very small share of guards)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "amount = 50  # How many top players we want to display\n",
    "top_theta_players = top_theta[\"disadvantaged\"][:amount].values\n",
    "top_b_players = top_b[\"committing\"][:amount].values\n",
    "\n",
    "positions = [\"C\", \"C-F\", \"F-C\", \"F\", \"G-F\", \"G\"]\n",
    "\n",
    "# Histogram of positions of top disadvantaged players\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "top_theta_position = fig.add_subplot(121)\n",
    "df_position.loc[df_position.index.isin(top_theta_players)].position.value_counts().loc[\n",
    "    positions\n",
    "].plot.bar(ax=top_theta_position, color=\"orange\", label=\"theta\")\n",
    "top_theta_position.set_title(f\"Positions of top {amount} disadvantaged (theta)\\n\", fontsize=12)\n",
    "top_theta_position.legend(loc=\"upper left\")\n",
    "\n",
    "# Histogram of positions of top committing players\n",
    "top_b_position = fig.add_subplot(122, sharey=top_theta_position)\n",
    "df_position.loc[df_position.index.isin(top_b_players)].position.value_counts().loc[\n",
    "    positions\n",
    "].plot.bar(ax=top_b_position, label=\"b\")\n",
    "top_b_position.set_title(f\"Positions of top {amount} committing (b)\\n\", fontsize=12)\n",
    "top_b_position.legend(loc=\"upper right\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The histograms above suggest that it might be appropriate to add a hierarchical layer to our model. Namely, group disadvantaged and committing players by the respective positions to account for the role of position in evaluating the latent skills `theta` and `b`. This can be done in our Rasch model by imposing mean and variance hyperpriors for each player grouped by the positions, which is left as an exercise for the reader. To this end, notice that the dataframe `df_orig` is set up precisely to add this hierarchical structure. Have fun!\n",
    "\n",
    "A warm thank you goes to [Eric Ma](https://github.com/ericmjl) for many useful comments that improved this notebook."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Authors\n",
    " \n",
    "* Adapted from Austin Rochford's [blogpost on NBA Foul Calls and Bayesian Item Response Theory](https://www.austinrochford.com/posts/2017-04-04-nba-irt.html) by [Lorenzo Toniazzi](https://github.com/ltoniazzi) on  3 Jul 2021 ([PR181](https://github.com/pymc-devs/pymc-examples/pull/181))\n",
    "* Re-executed by [Michael Osthege](https://github.com/michaelosthege) on  10 Jan 2022 ([PR266](https://github.com/pymc-devs/pymc-examples/pull/266))\n",
    "* Updated by [Lorenzo Toniazzi](https://github.com/ltoniazzi) on  25 Apr 2022 ([PR309](https://github.com/pymc-devs/pymc-examples/pull/309))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    ":::{bibliography}\n",
    ":filter: docname in docnames\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Watermark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last updated: Sat Apr 23 2022\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.9.12\n",
      "IPython version      : 8.2.0\n",
      "\n",
      "aesara: 2.6.2\n",
      "aeppl : 0.0.28\n",
      "xarray: 2022.3.0\n",
      "\n",
      "matplotlib: 3.5.1\n",
      "numpy     : 1.22.3\n",
      "pymc      : 4.0.0b6\n",
      "arviz     : 0.13.0.dev0\n",
      "pandas    : 1.4.2\n",
      "\n",
      "Watermark: 2.3.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -n -u -v -iv -w -p aesara,aeppl,xarray"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{include} ../page_footer.md\n",
    ":::"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}