{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[![img](..\\ep8_2018-57x57.png)](http://endlesspint.com/)\n",
    "\n",
    "# Spence/Garcia, What Were the Odds of That?\n",
    "\n",
    "**post @** [endlesspint.com](http://endlesspint.com/2019-03-18-spence-garcia-what-were-the-odds/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as  pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.style.use('ggplot')\n",
    "%matplotlib inline  \n",
    "\n",
    "from scipy.stats import binom, poisson, zscore"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Coming into the Fight\n",
    "\n",
    "![img](img/spence-garcia-compubox-punch-stats.jpg)\n",
    "\n",
    "**source:** https://www.boxingscene.com/errol-spence-vs-mikey-garcia-compubox-historical-review--137148"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## (mis)Using Poisson to Get an Idea of Expected Fighter Output\n",
    "\n",
    "Spence could be expected to be busier, but by how much and where?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(8)\n",
    "\n",
    "sim_cnt_poi = 10000\n",
    "\n",
    "spence_tot_poi, spence_jab_poi, spence_pow_poi = np.random.poisson(64, sim_cnt_poi), \\\n",
    "                                                    np.random.poisson(31, sim_cnt_poi), \\\n",
    "                                                    np.random.poisson(33, sim_cnt_poi)\n",
    "garcia_tot_poi, garcia_jab_poi, garcia_pow_poi = np.random.poisson(53, sim_cnt_poi), \\\n",
    "                                                    np.random.poisson(32, sim_cnt_poi), \\\n",
    "                                                    np.random.poisson(21, sim_cnt_poi)\n",
    "\n",
    "\n",
    "plt.figure(figsize=(16,6))\n",
    "\n",
    "    # SPENCE\n",
    "    \n",
    "ax1 = plt.subplot(231)\n",
    "plt.hist(spence_tot_poi, 14, density=True, color='green')\n",
    "plt.title(\"Spence Total Punches/Rd\")\n",
    "\n",
    "ax2 = plt.subplot(232, sharey=ax1)\n",
    "plt.hist(spence_jab_poi, 14, density=True, color='green')\n",
    "plt.title(\"Spence Jabs/Rd\")\n",
    "\n",
    "ax3 = plt.subplot(233, sharey=ax1)\n",
    "plt.hist(spence_pow_poi, 14, density=True, color='green')\n",
    "plt.title(\"Spence Power Punches/Rd\")\n",
    "\n",
    "\n",
    "    # GARCIA\n",
    "    \n",
    "plt.subplot(234, sharex=ax1, sharey=ax1)\n",
    "plt.hist(garcia_tot_poi, 14, density=True)\n",
    "plt.title(\"Garcia Total Punches/Rd\")\n",
    "\n",
    "plt.subplot(235, sharex=ax2, sharey=ax1)\n",
    "plt.hist(garcia_jab_poi, 14, density=True)\n",
    "plt.title(\"Garcia Jabs/Rd\")\n",
    "\n",
    "plt.subplot(236, sharex=ax3, sharey=ax1)\n",
    "plt.hist(garcia_pow_poi, 14, density=True)\n",
    "plt.title(\"Garcia Power Punches/Rd\")\n",
    "\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fight Night\n",
    "\n",
    "![img](img/spence-garcia-compubox-punch-stats_1.jpg)\n",
    "\n",
    "**source:** https://www.boxingscene.com/errol-spence-vs-mikey-garcia-compubox-punch-stats--137161"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A look at actual thrown performance v expectations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "spence_total_thrown = [46, 55, 75, 89, 86, 95, 70, 102, 121, 125, 118, 100]\n",
    "spence_jabs_thrown = [39, 43, 53, 61, 62, 56, 50, 60, 56, 58, 45, 35]\n",
    "spence_power_thrown = [7, 12, 22, 28, 24, 39, 20, 42, 65, 67, 73, 65]\n",
    "\n",
    "garcia_total_thrown = [12, 28, 31, 35, 41, 43, 26, 41, 32, 62, 15, 40]\n",
    "garcia_jabs_thrown = [9, 13, 18, 20, 17, 19, 10, 22, 17, 25, 2, 16]\n",
    "garcia_power_thrown = [3, 15, 13, 15, 24, 24, 16, 19, 15, 37, 13, 24]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A tale of two jabs: Spence pumped out that lead left at a ridiculous rate, neutralizing Garcia while setting-up the rest of his own offense"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SPENCE\n",
      "[0.9912, 0.882, 0.0963, 0.0015, 0.005, 0.0001, 0.2386, 0.0, 0.0, 0.0, 0.0, 0.0] 0.18455833333333335\n",
      "[0.093, 0.0245, 0.0001, 0.0, 0.0, 0.0, 0.0009, 0.0, 0.0, 0.0, 0.011, 0.2537] 0.031933333333333334\n",
      "[1.0, 1.0, 0.9827, 0.8285, 0.9537, 0.1682, 0.9959, 0.0747, 0.0, 0.0, 0.0, 0.0] 0.5003083333333334\n",
      "\n",
      "GARCIA\n",
      "[1.0, 1.0, 0.9997, 0.9969, 0.9615, 0.9309, 1.0, 0.9615, 0.9992, 0.1232, 1.0, 0.9713] 0.9120166666666667\n",
      "[1.0, 0.9999, 0.9971, 0.9905, 0.9981, 0.995, 1.0, 0.9725, 0.9981, 0.9089, 1.0, 0.9991] 0.9882666666666666\n",
      "[1.0, 0.927, 0.978, 0.927, 0.283, 0.283, 0.8865, 0.6958, 0.927, 0.0008, 0.978, 0.283] 0.6807583333333332\n"
     ]
    }
   ],
   "source": [
    "def chance_of_throwing_GE(sim, act):\n",
    "    return [np.sum(sim >= x)/len(sim) for x in  act]\n",
    "\n",
    "spence_comp_thrown = [(spence_tot_poi, spence_total_thrown), (spence_jab_poi, spence_jabs_thrown), (spence_pow_poi, spence_power_thrown)]\n",
    "\n",
    "garcia_comp_thrown = [(garcia_tot_poi, garcia_total_thrown), (garcia_jab_poi, garcia_jabs_thrown), (garcia_pow_poi, garcia_power_thrown)]\n",
    "\n",
    "\n",
    "print(\"SPENCE\")\n",
    "for spence in spence_comp_thrown:\n",
    "    spence_perf = chance_of_throwing_GE(spence[0], spence[1])\n",
    "    print(spence_perf, np.mean(spence_perf))\n",
    "    \n",
    "print(\"\\nGARCIA\")\n",
    "for garcia in garcia_comp_thrown:\n",
    "    garcia_perf = chance_of_throwing_GE(garcia[0], garcia[1])\n",
    "    print(garcia_perf, np.mean(garcia_perf))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What about contact? \"Everyone's gotta plan until they get hit.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "95 percent range for Garcia total: \t 103  -  138\n",
      "\t Garcia total actually landed: \t 75\n",
      "\t prob of landing this Garcia total count or less: 0%\n",
      "95 percent range for Garcia jabs: \t 29  -  49\n",
      "\t Garcia jabs actually landed: \t 21\n",
      "\t prob of landing this Garcia jabs count or less: 0%\n",
      "95 percent range for Garcia power: \t 80  -  107\n",
      "\t Garcia power actually landed: \t 54\n",
      "\t prob of landing this Garcia power count or less: 0%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s_plot = 1\n",
    "\n",
    "fig = plt.figure(figsize=(16,6))\n",
    "\n",
    "for stat in ((406, .298, \"Garcia total\", 75), (188, .209, \"Garcia jabs\", 21), (218, .431, \"Garcia power\", 54)):\n",
    "    n, p, category, N = stat[0], stat[1], stat[2], stat[3]\n",
    "    x = np.arange(binom.ppf(0.025, n, p),\n",
    "                  binom.ppf(0.975, n, p))\n",
    "    \n",
    "    sim_bouts = 10000\n",
    "    \n",
    "    print(\"95 percent range for %s: \\t\" % category, int(np.min(x)), \" - \", int(np.max(x)))\n",
    "    print(\"\\t %s actually landed: \\t\" % category, N)\n",
    "    print(\"\\t prob of landing this %s count or less:\" % category, \n",
    "          \"{0:.0f}%\".format(np.sum(np.random.binomial(n, p, sim_bouts) < N)/float(sim_bouts) * 100))\n",
    "    \n",
    "    ax = fig.add_subplot(1,3,s_plot)\n",
    "    ax.plot(x, binom.pmf(x, n, p), 'ro', ms=5, label='binom pmf')\n",
    "    plt.title(category)\n",
    "    ax.vlines(x, 0, binom.pmf(x, n, p), colors='r', lw=5, alpha=0.5)\n",
    "    ax.vlines(N, 0, np.max(binom.pmf(x, n, p)), lw=3, linestyles=\":\")\n",
    "    s_plot += 1\n",
    "    \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Both fighters had their rates affected but while Mikey fell off the chart, almost literally and in a bad sense, Spence's superiour activity with the jab allowed him to set up and deliver the power punches, especially in volume over the second half of the bout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "95 percent range for Spence total: \t 341  -  401\n",
      "\t Spence total actually landed: \t 345\n",
      "\t prob of landing this Spence total count or less: 4%\n",
      "95 percent range for Spence jabs: \t 103  -  141\n",
      "\t Spence jabs actually landed: \t 108\n",
      "\t prob of landing this Spence jabs count or less: 7%\n",
      "95 percent range for Spence power: \t 202  -  243\n",
      "\t Spence power actually landed: \t 237\n",
      "\t prob of landing this Spence power count or less: 90%\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s_plot = 1\n",
    "\n",
    "fig = plt.figure(figsize=(16,6))\n",
    "\n",
    "for stat in ((1082, .343, \"Spence total\", 345), (618, .198, \"Spence jabs\", 108), (464, .480, \"Spence power\", 237)):\n",
    "    n, p, category, N = stat[0], stat[1], stat[2], stat[3]\n",
    "    x = np.arange(binom.ppf(0.025, n, p),\n",
    "                  binom.ppf(0.975, n, p))\n",
    "    \n",
    "    sim_bouts = 10000\n",
    "    \n",
    "    print(\"95 percent range for %s: \\t\" % category, int(np.min(x)), \" - \", int(np.max(x)))\n",
    "    print(\"\\t %s actually landed: \\t\" % category, N)\n",
    "    print(\"\\t prob of landing this %s count or less:\" % category, \n",
    "          \"{0:.0f}%\".format(np.sum(np.random.binomial(n, p, sim_bouts) < N)/float(sim_bouts) * 100))\n",
    "    \n",
    "    ax = fig.add_subplot(1,3,s_plot)\n",
    "    ax.plot(x, binom.pmf(x, n, p), 'go', ms=5, label='binom pmf')\n",
    "    plt.title(category)\n",
    "    ax.vlines(x, 0, binom.pmf(x, n, p), colors='g', lw=5, alpha=0.5)\n",
    "    ax.vlines(N, 0, np.max(binom.pmf(x, n, p)), lw=3, linestyles=\":\")\n",
    "    s_plot += 1\n",
    "    \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## One more look at thrown punches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1.42441765, -0.84977684,  0.42720275,  1.32108846,  1.12954152,\n",
       "        1.70418233,  0.10795785,  2.15112519,  3.36425579,  3.61965171,\n",
       "        3.17270886,  2.02342723])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def standardized_fight_night(sim_rds, poi_lambda, n_times, act):\n",
    "    act_rds = len(act)\n",
    "    fight_night_zscore = np.zeros(act_rds)\n",
    "    \n",
    "    for i in range(n_times):\n",
    "        fight_night_zscore += zscore(np.append(np.random.poisson(poi_lambda, sim_rds), act))[-act_rds:]\n",
    "        \n",
    "    return fight_night_zscore/n_times\n",
    "\n",
    "spence_total_zscore = standardized_fight_night(60, 64, 100, spence_total_thrown)\n",
    "spence_total_zscore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-3.40959768, -1.96473539, -1.69382371, -1.33260814, -0.79078479,\n",
       "       -0.610177  , -2.14534318, -0.79078479, -1.60351982,  1.10559696,\n",
       "       -3.138686  , -0.88108868])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "garcia_total_zscore = standardized_fight_night(60, 53, 100, garcia_total_thrown)\n",
    "garcia_total_zscore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x245153e6f98>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(spence_total_zscore, garcia_total_zscore, 'go')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}