presentation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predicting 3 Point Field Goal Percentages."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gathering and Cleaning Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get started on the problem of predicting 3 point percentages (3PP) for the coming season, I decided first to gather some data. If I were starting this process from scratch, I would probably use the API at stats.nba.com (see here for a rundown of how: http://www.gregreda.com/2015/02/15/web-scraping-finding-the-api/). Since I already had code to scrape and interpret tables on sports reference sites, I just adopted that after I made some adjustments.\n",
    "\n",
    "But first, some boilerplate imports."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import sixers    # My own code\n",
    "import pandas as pd\n",
    "import matplotlib.pylab as plt\n",
    "import seaborn as sns\n",
    "sns.set_style(\"whitegrid\")\n",
    "sns.set_context(\"notebook\", font_scale=1.5, rc={\"lines.linewidth\": 2.5})\n",
    "pd.options.mode.chained_assignment = None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, I'll actually gather, write, and then read in the data. Briefly, a few more details: I loop over each team's basketball-reference page for each of their seasons since 1983 (example page: http://www.basketball-reference.com/teams/PHI/2012.html). I extract the table called \"Totals\" and convert that html to a data structure called a DataFrame which is defined in the `pandas` python module. From there, I clean and reorganize the data before saving it to the file resources/data.csv."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sixers.gather_data()   # Writes data.csv\n",
    "df = pd.io.parsers.read_csv(\"resources/data.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point, all the data is available from that file, but it is not organized in a way for me to conveniently run regressions on it. I wanted each row in my DataTable to be a year with a known 3PP while the other columns show whatever data would have been available before that player recorded that 3PP. Then I can experiment with those columns and find out which ones are most predictive of 3PP. This organizational step was the most time consuming of the project, but is probably the least interesting to talk about. You can find the details in the clean.py file if you're interested."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sixers.clean_all()    # Writes clean_data.csv and past_years.csv\n",
    "pastdf = pd.io.parsers.read_csv(\"resources/past_years.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After gathering all the data, I want to make some general plots to get a feel for what I'm looking at. I assumed this statistic was going to be different for different positions. I also wanted to see how much it changed over a player's career. I already knew that the 3 point percentage league wide had been going up ever since the shot was introduced, but now I could plot that and quantify it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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+xof6tYp3Tu/evendu3exr/8oJBAWQgghhMlLzFM6zekpnBHesPcKx85HG+Va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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1084c8668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pos_age_gbdf = df.groupby([\"pos\", \"Age\"])\n",
    "pos_age_series = pos_age_gbdf[\"3P\"].aggregate(\"sum\") / pos_age_gbdf[\"3PA\"].aggregate(\"sum\") * 100\n",
    "plt.figure(figsize=(12, 7))\n",
    "for pos in range(1, 6) :\n",
    "    pos_age_series.loc[(pos)].plot(marker=\"o\", label=pos)\n",
    "plt.ylim(15, 45)\n",
    "legend = plt.legend(loc=\"upper right\")\n",
    "title = plt.title(\"3 Point Percentage by Position and Age\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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iIgUxTBMRERERKYhhmoiIiIhIQQzTREREREQKYpgmIiIiIlIQwzQRERERkYI0\nlF0AEVFNfb7hMkKjkgEA7Z0s8M3s7kquiIiIXnYM00TUKHy+4TJuRibLbt+MTMbUJcexeHpXONkZ\nK7EyImoM+GGc6gvbPIioUSj9JVhWamYBlm4OUkI1RNSYLFp/CTcjkyEIgCA8+zAeFZuh7NKoCWCY\nJiKV9yQ5B4JQ+X35BcXIyC5s2IKISOVlZBfi1NVH+O6Pq7gVlVLhfn4Yp7rCNg8iUlmJaXn4++Rd\nnL7+uMp18gqLMe2bE+jVwRbDezqibUuTBqyQiFSFIAh4GJ+FqxEJuBaRiHuP0qv8EF4qv7AYgiBA\nJBI1TJHUJDFME5HKScnIx65T93DyagyKS579NtTSVIO4SAIA0NfVhKWJLqKfZKG4RIKzwbE4GxyL\nNi2MMbynA3q2bw4tTXVlPQUiagDiohLcikqRBeiUjPwK6zTT1YSmhhrSK/kGK6+gGN//eQ3zx3tB\nX1ezIUqmJohhmohURnp2AfacjsTRKw9RVCyRLffxsMbEIS4okQiyr2UXT++K1s2NEBGdhsOXonH5\n1hOUSAREPs7Ayh03sOlgOIb42GNot1awNNFT0jMiorqWllWAaxGJuBaRgJuRySgUl1RYp4WVAbq4\nWcHbzRou9iZQV1fD1CXHkZpZAAAwaqYFbU11JKXn40pYPKKfZOLjKd68mJkUwjBNREqXlSvGP2cj\n8e+laLlfjJ1cLOE31AVtWjxr3fjjiyFyj3V3NIO7oxlSM/NxPDAGx648RHp2IbJyxdh9OhJ7z0Si\nq4cNXunhAE8nc36dS9QIlB15w9PJHFOHu+NaeAKu3klE1OOKFw1qqIvg4WgOb3creLtaw8Zcv8I6\ni6d3lfswbmWqh5U7QnAtIhEJqXn4aM0FvPlaOwz1sef7BNUKwzQRKU1OfhH2B0Th4PkHyC8sli33\ndDLHpKGucHUwrfG2zIx0MXGIC8YOaIsrYU/w78Vo3HmYBokAXAmLx5WweLSwaoZXujugX+cW0NPh\nV7pEqqj8MJihkSl4f2VAhfUM9bXQ2dUKXdys4eVsUe3PtJOdcYUP44undcX+gCj8eeQOiool+L89\noQi/n4q5Y9tDV5sRiWqG/6cQUYPLKyjCoYsPsO/cfeTmF8mWu7YyxaRhLvB0slB425oaaujtZYfe\nXna4H5uBw5eiERASC3GxBI8Tc7BhXxj+PHIHAzq3gG8PB/y6L4xjzxIpkSAIiE/NRcSDVEREp8kF\n6fJa2RiUgaEKAAAgAElEQVTC200aoNu0NIG62oudQVZTE+H1fm3gbG+KH7ZeR1pWAQJuxOJ+XAY+\n8feGvbXhC22fXg4M00TUYArExThy6SH2no1EVq5YttyphTEmD3WFl7NFnX692trOGO+O98K0V91x\nMugRjlyORmJaHvILi/HvpWj8eylabn1OBENU/0okAqKfZMrCc0R0aqUXB5ZnYqCNNQv71UtN7o5m\nWPVBX6zYHoybkcmITcrBBz+fx9wxnujfuWW97JMqaqwT6zBME1G9KH1TFATA82oBfDxssPv0Pblf\nmq1sDDFpqAu6uFvXa4+igZ4WXu/nhJF9WiP4v0QcvhiNkLtJla5bOvZs+a+DiUgxhUUluBeTjojo\nVIQ/SMV/MelybV1l6WqrQ0NdDdl5RXLLzYx0sHh613qt09hAG1+91Q27Tt7FjpN3IS4qwcodN3D7\nfipmve4J7QYaHaixBEpF6xQEAQXiEuQVFCGvoBi5BUXIyy/G5kO3EZOQLVuvMZ3cYJgmojpXvufx\nVlSK3KQJdpbNMHGIC3p42kLtBb+mrQ11NRG6uFmji5s14pJzMHvZ6QbbN5EqqI+gVn6bH07ujDvR\n0rPO4dGpuB+bITfEZVnGBtpwdzCDm6Mp3BzM4GBjWGHkDTMjnQb7cKuuJsKEIS5wdTDF/7YHIzNH\njJNXHyHysbTto7lFs3rdf/n3TlUNlJXV+cbiI+jbsTn0dDSRm18mKBcUS28XFiPv6d8SSTUDgD/V\nWE5uMEwTUZ2rbOpvQNqf+N4bXujtZffCvY4vqrlFM3RoY1Fpf+aovk5KqIio/hSIi7Fo/SXce/Rs\nJIybkckY/cm/aOdkBiN9bYhEgJpIBJFIVObf0r9RxX0XQuOQlJYvt02/L45WWYetuT7cHc3g5mAK\nN0cz2JjpV/qtVPmRNxpah7aWWPVBX/yw9ToiotPwMD4L768MwLvjO6Bn++b1ss/UzPxK349UMVCG\nVlJnbn4RDl96WOf7KhCXoEQiKP13xvMwTBNRgzEx0Ea/Ti2UXYbMN7O7y50BK7X5UDh0tTUwuKu9\nkiojUkxRsQRPknMQk5CFRwnZiEnIQkxCNhJScyudDVBcVILgO5W3PL0oNRHg2NwIbo5mcHOQBmgT\nA50aPbaykTcampmRLr6b0wNbj97B3rNRyC8sxvIt1xHeIxXTR7hDU0Pxtg9BEJCYlofb91Nx+0EK\nwh+kIiE177nrq4ISiYBjl6PxvGrU1UTQ09GEvq4G9LQ1oaerAX0dTejpPP1bVxN62hrQ09WEvo6G\ndF0dTWw6dBt3Y9IrbC83vwgLVgVgzuuecLav+QhPDYlhmojqXNuWJhXeFBui51ERZc+AjerjhC1H\n70BcVII1u24iLasA4we25ZizpBRlrzvocK1QriWjRCIgMTW3TGiWBue4pByU1PAr9FJqaiKYG+tC\nEAQIEgESQRreBAGQCAIEoeyyp/9+ul5xiaTSbRrqa2HjZwMb/RCU6upqmDrcHW6OZlj5Vwhy8ovw\n76Vo3H2Ujo+neMPKtGYTQgmCgNikHNx+kIrwpwG6/If45xEXleD0tUfo37mF0t6PHsRlYt2em3Lf\nbpRlYqCNT/y94drKVKEa//dub7mTGwZ6mtDV1kBSej7ux2Zi4eoLGNSlJfxfcYNRM+0Xei51TSQo\n6eNOcHAwOnXqpIxd10pjqfNlxmOkWkokAj5ecwF3Hz0L0w3Z8/ii/otJw5LfAmUXQA3r1gqzXvdU\n6a8YXxR/hlRP+Z5UANDT0YC7gxnSsgvwOCEb4uLKg2wpkQiwNtOHvbUB7K0NEXg7Xu4CL+DZh1xF\n+3Erq/NFt6mqEtPysHzLNUQ+nTRGX1cTlia6eBifJf3A0+ZZD7pEIiAmIUvuzHNmjrjS7epqa8DN\nwRTujmZo19oc3/95DWlZ0kCpqaEmNxusm4MpZr/uCQdbo3p+ts/kFxbjr+P/4eCFB7JeZ0tTPeQX\nFCM7T/qc6uo9Pio2Q669x86yGfacicQ/Z6Nkr0MzXU1M8XXFYJ9WtXpfrs/3OYbpajSWOl9mPEaq\n5d+LD/DLvjAAT6/MVwOWzO7ZqH6xPk7MxlcbryApXdoL6uNhjYWTOjfY1fwNjT9DqmfEwgOVtmVU\nxcJEF/bWhmhpZQB7GwO0tDaEnWUz6GjJfwFdHxf2KetiQWUoKpbg93/DcejCg0rv19PRgIONER4m\nZMmNoV+WgZ7m05lbzeHhaAYHW+lFl6XkAuW0LohPycNvB2/LAraamgiv9nTExCHO9X7mP/B2PH7Z\nF4aUDOl7obqaCK/1aY03BjsjNilHLvjW53v8k5Qc/LovDMH/PWtJam1nVKvWD6WH6YSEBHz33XcI\nCgqCRCJBr1698Mknn8DS0hIAMGbMGNy+fVvuMWPHjsU333xT5TYby5t3Y6nzZcZjpDqS0/Mx98fT\nyC8sgbWZHtYs7IfwsNBGeXxSM/Px9W+BiH6SBUA6ocznM7rCQE9LyZXVHbk2gjb1M7KDqm5TlUU+\nTscHP5+v9D6RSDpDqL21IVo+PePcwsoA+ro1C1Xlz/zVRQCqj22qukuhT7Bsy7UarWtsoA0PRzPp\nn9bmaGFlUOtRjPIKirDjxF25s8OmhtqYMcIDvTo0r/PWj+T0fPy6/xYCbyfIlrm2MsXbY9qjlY1y\nJrIRBAFB4QnYuD9MdqIDAAZ3tccUX9dqWz+UGqYFQcDIkSNhbm6Ojz/+GIIg4Ntvv0Vubi7++ecf\nCIKAjh07YunSpfDx8ZE9TkdHB/r6+lVut7EEoMZS58uMx0g1CIKAb3+/iqBw6Zvvkre6wcvZslEf\nn9z8Inz3x1XZsH4trAzw9ZvdYGGiq+TKXlxNvp4XBAElEgHiohKIiyQQF5egqFjy9HYJxLJ/S1BU\nXIKdJ+/hcaJ8G4Gejgb6d24BU0Odp9sEBAh4+p/07KsgyP4tyP4t/dUUEBIr94uzsjqbikcJWdh2\n7D9cCYuv9H4TQ218McOnyT3vxmrEggOVXoinJgJ6d7SDh6M5PFqbwda88hFLFPEwPgvr94YiIjpN\ntszTyRyzX/dECyuDF95+SYkEhy5G46/jd5BfWAJA2s4ybbgbBnWxb9ChTKtSIC7GnjOR2HsmStaz\nX5PWD6WG6ZSUFHz//fdYsGABbG1tAQCnTp3CO++8g2vXriE9PR2DBw/G6dOn0bx5zYeLaSy/YBtL\nnS8zHiPVcOnWEyz7U3qmpl8nO3wwUXpMGvvxKSqWTtxw4WYcAGmQ+/rNbrBX0tmZulJVG4GaCNDX\n1ZIG56IS1PJatgajo6WO9yd0RDsn80b/bUFCai7+Ov4fzoXEyo6JhroIGupqKBBLA01Tb59ojCr7\nQGpioI0vZtbvBx5BEHA2+DE2HwqX9WFrqIvwWh8njB/YFjraio0tce9ROtbtCcWDuEzZsr4d7TB9\nhHuNR2FpSJW1fjjZGWF2Fa0f9fm7qNpX3NzcHCtWrJDdTkhIwN9//w1PT08YGBggKCgIOjo6sqBN\nRC+fnPwi/PLPLQDS2QZnjPBQckV1R1NDHQv9OsHEQBsHLzxAamYBPl57AYund4VHa3Nll6e4KkKy\nRIDsoiJleDqkMSASQQRUOTJFgbgE3/95DSIR4GBrBE8nc7RvYwE3B9NGM4JEamY+/j51DycCY2TP\nU00E9OvcAhMGuyA7T4ylm4MgFhep5Eg4L7vyQ2s21AcekUiE/p1booubNbYevYOjVx6iuETAnjOR\nCLgRizdHtoOPR81nlc3NL8K2o3dw+HK07MOcjbk+5rzuCS9ny/p7Ii/I1rwZvpzpI9f6EfV01I+a\ntn7UlVp9fHn77bdx5swZGBkZYcuWLQCAyMhIGBgYYOHChbh69SqMjY0xevRo+Pv7czgpopfEn4cj\nZNOEzxzpoXLDFr0oNTURZo70gJmRDn7/NwK5BcX44tcrWODXCT08G9+JhGsRCdLEWi6nammqw6ut\nBcyMdKClqS79o6Em+1uz/DJNNWhpqEPz6e01u2/iTpmvnwHA1FAHH0/pjNZ2xhBBGpYBkVxoVhOh\nyt8XlZ3901BXk7WgCIJ0yK4HcZnYH3AfamoitG1hDM82FvB0ModrK1NoqdiFo1m5Yuw9E4l/Lz6Q\nG5GjR3tb+A1xkX1db2Wqhz++GILg4GC2dqio0qE1lfGBp5meFuaMbo9BXeyx/p9Q3HuUgeT0fHz3\nx1V0drXCW6+1g4151e22giDg0q0n2Lg/DGlZ0vdvDXURRvdvg3ED2qrcz01lRCIRfDxs0KGtBfac\njsTes9LWjxNBMbh86wmmvOKGS6FxuBWVgi8n2NVfHbUZzePevXsoKCjA+vXrERoain379uGHH37A\n+fPnsWjRIri7uyM4OBg//PADpk2bhnnz5lW5rcby1W9jqfNlxmOkXOEPUvHJuosApBexLZnVTS4Y\nNbXjczb4MVbtvIESiQCRCJj1Wju80tNR2WXV2ImgGKzbE1phOl9VHtmhsm0WFpXgv+g0hEYl41Zk\nCiIfp1fakqKpoQbXVqbwbGOO9k4WcGphDA11NaVc1JhXUIQDAfexL+A+8guLZcs7uVhi0jDXKgNz\nU/sZaoqUfYwkEgEngmLw5+EI5DwdRURTQw1j+7fB6P5tKgTjxLQ8bPjnFq7fSZQt82hthrdHt6+T\n3mtleZKcg1/3y7d+lPpqop1qDY1XUFCAPn36YPr06XjrrbeQl5cnd7Hhxo0bsWHDBgQHB1e5DWX/\nj1dTjaXOlxmPkfIUFZfg3RXnEJuUAy1Ndaxd2K/CmZCmeHxC7ibh+z+uyvpZxw5og8nDXFX62zhB\nELDjxF3sOHEXAKCloYZJw1xx4Px9iMVFdTZ8obJGi8jNL0J4dCpuRabgVlSybBSW8nS11aGhriYb\nR7xUfV7UWFhUgiOXorH7dKRcC42bgymm+LrB3dHsuY9vij9DTY2qHKPMnEL8eTgCJ68+ki2zMdOH\nrrYGouOlvdDWZvpIzSyAuEj6/mWgp4Xpr7pjgLfyJoSpS4IgIPB2An47ID/qh1LDdGpqKgIDA/HK\nK6/ILR87diw8PT3x+eefV3hMQEAAZs2ahevXr6NZs2aVbvd5QZuIGodzYVk4FyYNLQM7GKGnW+M9\no1FbT9LE2H4uBbkF0q/pOzjq4dUuJio5uUuJRMC/19Jx4750umJdbTVM7G2GFhZNqx2nrNyCEjxM\nKkR0ovRPalZxtY/R1BChXztDmBlowNRAAybNNKChrvjxLJEIuHE/FwG3s5Cd/6ydw9pEEwPaG8HJ\nRrtJhBdSPY+TC3H4egYS0isf67pUB0c9DOpgBH0d1W/pqC1xsQTf7Xoiu12fYbranum4uDgsWLAA\n9vb28PCQXlSUnZ2N6OhojBo1CmPGjIGXlxcWLVoke0xYWBisrKyqDNKlVOFTXHVU5dMmVY3HSDke\nJ2bj4t/nAAAOtoaYO7E3NMpMPFCqqR6fTgA6e+Xiy1+vID41Fzcf5EFdqxk+meKt8NX09aGgsBjL\nt16XBWlLUz18/aYP7CyfffBpqseod5l/p2bm41ZUCm5FpuDUtUeVrl9ULODEjWcjGaiJAHMTPdia\n68PGXB+25s1ga6EPGzN9WJvpQ1Pj2f/vZdtGPJ3MMcC7Jf46+R8SUvNk69hZNsOkoa7o1s6mVkOM\nNdXj05So2jHqBODVQRIcvhyNjftvV7qOob4Wvpk7qGELa2AdblS85qI+VPuO365dO3Tu3BmLFy/G\nkiVLoKGhgRUrVsDMzAyjRo1CQUEBfv75Z7i7u6Njx44ICgrCpk2b5MI1ETUtEomAtbtvorhEAjUR\n8M7YDpUG6abOxlwfP8zrha83BSLqcQaC/0vCog2X8MUMH5W4CDMjuxBLNgXKpj92bG6Er2b6wMRQ\n9Ya5qm9mRrro16kF+nVqgeSMPIRGpsjdr64ugmaZoegA6cgmSWl5SErLw8178r+Q1USAhYkebMz1\n8TgxW9bTDQChkSly27c00cXEIS7o29FObqY7ovqkrq6GEb1a47f9tysdvKfsh8GmqvyIK/Wl2jAt\nEomwZs0a/PDDD5g9ezYKCwvRq1cvbN26Fbq6upg+fTrU1dWxfv16xMfHo3nz5vjss88wZsyYei2c\niJTnRFCMbNKA4b0c0baliZIrUh5jA218N6cHlv15DSF3k3DvUQamLz2BoiIJIFLejH1PUnLw1a+B\niE/NBQB4tbXAJ/7ejWbYuPq0dHaPSi9qFAQBmTlixKfk4klKDp6k5OJJcg7iU3PxJDlX7qJBiSC9\niCsxLa+q3cguUB3sYw9Njab3NTo1Du3bWFQ5QdPLoHTElfpUo+8iTUxM8P3331d5v7+/P/z9/eus\nKCJSXWlZBfjj33AAgIWJLiYNdVVyRcqnq62Bz2d0xZpdN3Hm+mOIi572xwrAzchkTF1yvEFn7Lv3\nKB1LNgXKJnTo37kF5o17Ob89qErZX7CloUIkEsHYQBvGBtpwdZCf9EEQBGTkFEqDdrI0bEtDd67c\nJBdlmRjoNKqRXqhpUtZ42KrCyc5YNsRkfVGdxj4iahR+3ReG3ALpGbq3R7eHrgr1ByuThroa3nvD\nC2euP65wX2pmAZZuDmqQX2BXIxLww9brKHzarjB+YFv4DXXhhW7llP6CrSmRSAQTAx2YGOjAzUF+\n9I3FGy5VaBt5mc78keqr7MMj1R3+FiSiGgu6HY9Lt6RXR/fq0BydXa2UXJFqEYmkk5FUNkZSZk4h\nzgU/Ro/2zeutV/F44EP8355QSARpT+/s0e0xrFuretkXPVNV2wiRqqjth0eqHX7nR0Q1kldQhPVP\npwzX19XEmyObzpThdam9k0Wly4tLBKz4KwQzlp7AjhN3kZ5ddxfECIKA7cf+w9rd0iCtpamOz6Z2\nYZBuQIund4WZkQ7PSBO9hHhmmohqZOvRO7Izb9NfdX8pR4SoifL9iSYG2hjsY49jVx4iM0eM9OxC\n/HX8P+w6dQ+9vZrj1V6OL9RLXVwiwf/tCZVN0mCgp4UvZnSFSyvTah5JdYln/oheXgzTRFSt/2LS\ncPhSNADplLODurRUckWqrXx/opOdMcYNaIsLN+Nw8MIDPIjLRHGJBGeuP8aZ64/h2soUI3o7opuH\nTa2GTssvLMbyLddkU+damerh67e6obnF88f4JyKiusMwTUTPVVwiwdpdNyEI0nFJ545pz4vZqlHZ\nWUotTXUM8G6J/p1bICI6DYcuPsCVsHhIJALuPEzDnYdpMDfSgW8PBwzxaQVDfa3n7iM9uwBLNgUh\n6ukY0q3tjPDljJdzDGkiImVimCai5/rnbBRiErIBSEeGKDtzHtWeSCSCu6MZ3B3NkJSeh6OXH+J4\n4ENk5xUhJbMAW47cwc4Td9G3Uwu82ssRrWwMK2zjSXIOvtx4RTa7XkdnS3w8pTPHkCYiUgKGaSKq\n0pPkHOw8eRcA0NLaAK/3a6PkipoWSxM9+L/ihvGD2iIgJA6HLtxHTEI2xMUSnAiKwYmgGHg6mePV\nXo749+ID3IpKAQRATU2EEol0yJAB3i1e2hkoiYhUAcM0EVVKEASs2xOKomIJRCJg3tgOL8X0s8qg\no6WBIT72GNy1JcLup+Dg+Qe4GpEAQQBuRaVIQ3QZpUF6UNeWmDe2A9tuiIiUiGGaiCp1+tojWYgb\n1q0VR4doACKRCJ5OFvB0skBCai4OX4rGyaAY2SQ55YX8l8QgTUSkZAzTRI3M5xsuIzQqGYB0TONv\nZnev831kZBdi00HplOGmhjqY4utW5/ug57M208eMER6YOMQF4z47rOxyiIioCvzOlqgR+XzDZdyM\nTIYgSGfZuxmZjKlLjiMqNqNO97PxQBhy8osAALNf94S+Li9sUxZdbQ10aFNxIhhODkJEpBoYpoka\nkdDI5ArLUjML8Nn/XULg7XgkpedBqGwu61q4ficR52/EAQC6tbNBt3Y2L7Q9enHfzO4OM6NnQ96V\nTlf9IpO9EBFR3WCbB5GKS8nIx/kbsTgbHIuqYnJ+YTG+/f0qAMBATxOOzY3g2NwYrZsbwbG5EWwt\nmkFdrfre2oLCYqzfGwoA0NPRwKxR7erqadALKj8RDBERqQaGaSIVlJNfhEuhTxAQEovbD1LwvJPN\namoiSCTPVsjOK0JoZApCI5+NAKGtpQ4HG0M4NjdCaztjODY3gr21ATQ11AE868Muux//V9xgZqRb\n58+NFMPpqomIVBPDNJGKKCouwbWIRJwLicW1iEQUl0jk7rezbIa+He3w76VoZGQXAnj2dX9eQRGi\nn2ThflwGHsRl4kFcJh4lZMuGUCsUl+C/mHT8F5Mu2566mggtrQ2QmVOItKxCuX1pqIvQhi0ERERE\n1WKYJlIiiURA+INUnAuJxaXQuApDoJkYaKO3lx36drJD6+ZGEIlE6ORqVeHrfj0dTdmseqWKiksQ\nk5CNB3GZuB8rDdnR8VkoFJcAkI5VHP0kq9K6iksEfPvHVZ4JJSIiqgbDNJESRD/JREBILAJCYpGS\nWSB3n662Brq1s0HfjnbwbGNRode5pl/3a2qow8nOWHqRWld7ANIA/SQ5Rxqw4zLxIC5Drh2EiIiI\naodhmhqtsn2+Ha4V1st4yy+q7JjQrq1M0dnVCgEhsYhJyJZbT11NhE4uVujb0Q7e7lbQ0aqfH011\nNRFaWBmghZUB+nS0AwAs3nCpQqDmsGtEREQ1wzBNjVLpeMulSsdbXjy9q8oMF1a+xojoNEREp8mt\n49rKFP062aFH++Yw1Ndq6BIBAEtn98DUJceR+vQMeWkfNhEREVWPYZoanfuxGXIhtVRqZgGWbg5S\nmSBYeka6PHU1ESYOcUGfjnawMtVr4Koqx2HXiIiIFMMwTY3G/dgM7DhxF0HhCVWuU1LyYhOW1JXQ\ne8lVDmdnbKCNcQPbNmxB1eCwa0RERIphmCaVV5MQXSonX4x/zkZhZJ/WNZqkpK4VFBbjz8MR+PdS\ndKX3sxeZiIioaWGYJpVVWYhWVxNhgHdLjB3QBp+suyjr89XVVkeBuATFJQJ+/zccgbfj8d4bXrC1\naNZg9d6JTsPKnSGIT8kFIJ0oRUNdDbn5RQDYi0xERNQUMUyTyqkuRFub6QN41ucrFhdhyeyeKCqS\nyMLsnYdpmLfiHKYNd4Nvdweo1eNZ6qLiEmw/9h/2nYtC6USErq1M8d4EL+QVFLMXmYiIqAljmCaV\nUdMQXaq0zzc4OFg2gsfqBX2x5cgdHLrwAOKiEvyyLwxXwuLx7nivernY735sBlbuCJENdaehrobJ\nw1zl2kx4NpqIiKjpYpgmpattiH4eHS0NvPVaO/h4WGPVzhtISs/HragUzPvfGcwY4YHBXe0hEr34\nWeriEgl2n47E3yfvyqbsdrIzwnsTOsLe2vCFt09ERESNA8M0KU1dhujyPJ0ssGZhP2w+FI7jgTHI\nLyzB2t2huBwWj3fHdYCZka7C236UkIWVO28g6nGGrObxg5wxdkAbaKirKbxdIiIianwYpqlBlJ0J\nsE0LY5gY6NRLiC5LT0cT74ztgG7tbLBm102kZhYg5L8kzP3xLN56rR36dbKr1VnqEomAg+fvY+vR\nOygqlgAAWlob4P03OsKphWpMFENEREQNi2Ga6l35mQDvPcqQ/bs+QnR5nVyssPbD/ti4Pwxnrj9G\nbn4RVu4IweVbTzB3bHuYGOhUu434lFys+vsGwh+kAgBEIuD1vk6YOMQFWprq9VI3ERERqT6GaapX\nhUUllc5WCADamupY+2G/egvRZTXT1cT7EzqiWzsbrNsdioycQgSFJyAiOg1vj/FEz/bNK32cIAg4\nduUhNh8KR4G4BABgY66P997wgpuDWb3XTURERKqNYZrqRfSTTJwIjMHZkNgq12mmp9kgQbosHw8b\nuLYyxYZ/buFi6BNk54mxfMt1XO4Qj9mve8JQX0u2bnJ6PtbsuoEb9559GBjewwH+r7hBR5s/OkRE\nRMQwTXUor6AIF27G4URQjFwrR2WUOROgUTNtfDzFG91vxmH93lvIzhPjws04XAl7guISASIR0MLS\nAKmZ+cgtKAYAmBvrYv74DujQ1lIpNRMREZFqYpimFyIIAiIfZ+B4YAwu3IxFfmGJ7D6RCOjQxgKD\nfeyxcf9tpGVJZytUlZkAe3VoDg9HM6zbE4qg8AQUl0iHuBME4FFitmy9gd4tMXOkB/R1NZVVKhER\nEakohmlSSE6eGOdCYnE8MAYP47Pk7jM11MGgLi0xsEtLWRuHtZm+Ss4EaGKog0XTumDEwoOV3m+g\np4n5b3g1cFVERETUWDBMU40JgoDwB6k4ERSDS6FPIH46PBwAqImAzq7WGOJjj04ullAvN95y6WyF\nqkgkEkEkkp6RLo8jdRAREdHzMExTBWXHhG7vZIGFkzrh9LXHOBEUg7jkHLl1LU31MLhrSwz0bvlC\nE6EoW3sniwqjjiizr5uIiIgaB4ZpklN+TOibkcmY9OUxuXU01EXo6mGDIV3t0b6NBdTUXnx6bmX7\nZnZ3TF1yHKmZqtXXTURERKqNYZrklJ6Rrkxzi2YY4mOP/p1bwKiZdgNW1TAWT++qkn3dREREpLoY\npklOZX3DAGCor4X1H/ev1fTbjY0q93UTERGRamKYJpkTQTGVLi/tHW7KQZqIiIhIEQzTBEEQsPds\nFP48HFHhPvYOExEREVVNrfpVqCmTSARsPhQuC9LNdDUxf7wXzIx0OJoFERERUTV4ZvolVlwiwZpd\nN3Hm+mMA0slWlszqBntrQwzs0lLJ1RERERGpPobpl1SBuBg/bL2OaxGJAABbc30smdUdVqZ6Sq6M\niIiIqPFgmH4J5eQX4ZtNgYiITgMAONkZ4cuZ3WBs0PSGuyMiIiKqTwzTL5m0rAJ8+esVPIzPAgB4\nOplj0bQu0NPRVHJlRERERI0Pw/RL5ElKDr745QoS0/IAAN09bbDQrxM0NdSVXBkRERFR48Qw/ZK4\nH5uBr34LREZ2IQBgiI895oxuD/UmMBU4ERERkbIwTL8Ewu6nYOnmIOQVFAMAxg1si0lDXTgJCxER\nEUnGPE4AACAASURBVNELYphu4q6ExePHbddRVCwBALw50gMjerdWclVERERETQPDdBN2MigGa3ff\nhEQA1NVEeO8NL/Tt1ELZZRERERE1GQzTTdTeM5H44+mshlqa6vjU3xudXa2UXBURERFR08Iw3cRI\nJAL+OByBfeeiAAD6upr4coYPXB1MlVwZERERUdOjVpOVEhIS8O6776Jr167w9vbGBx98gKSkJNn9\nFy9exMiRI9G+fXuMGDEC58+fr7eCqWrFJRKs+vuGLEibGupg+dyeDNJERERE9aTaMC0IAt566y3k\n5ORgy5Yt2Lp1K5KTkzF79mwAQFRUFObMmQNfX1/s378fAwYMwNy5cxEVFVXvxdMzhUUl+O6Pqzhz\n/TEA6fTgP8zrBXsbQyVXRkRERNR0VdvmkZqaijZt2mDBggWwtbUFAPj7++Odd95BVlYWtmzZAi8v\nL8yaNQsAMH/+fAQHB2PLli1YsmRJ/VZP+HzDZYRGJUMQni1rbWeErzg9OBEREVG9q/bMtLm5OVas\nWCEL0gkJCfj777/h6ekJQ0NDXL9+HV26dJF7TJcuXXD9+vX6qZhkPt9wGTcj5YO0proaZo7wYJAm\nIiIiagA16pku9fbbb6Nv3764desWvvnmGwBAYmIirKzkR4mwtLREfHx83VVJlQqNSq6wrKhEgv9t\nD1ZCNUREREQvn1qF6ffeew+7du1Cx44dMW3aNCQmJqKgoADa2vJnQbW0tCAWi+u0UJInCILcGWki\nIiIiani1CtNt27aFp6cnVq5ciZKSEuzfvx/a2toVgrNYLIaurm6dFkryDl14UOlyMyMdLJ7etYGr\nISIiIno51egCxMDAQLzyyiuyZTo6OmjZsiUSExNhY2MjN0weACQlJcHa2rranQcHN452BFWrMyq+\nANvPpQAARCLIzlAb6Kpj3ivmyEy8j+BEJRaoBKp2jEgej4/q4zFSbTw+qo/H6OVVbZiOi4vDggUL\nYG9vDw8PDwBAdnY2oqOjMWrUKBQXF+PatWtyjwkKCkLnzp2r3XmnTp0ULLvhBAcHq1SdT5Jz8OO+\n8xAEQEtDDe+M64D/b+/Ow2u88/+Pv46sllTK1JZ2aotISWVBEJoabX1FJ6TiS1utrTPSbxf026le\ntuuablOKJpYJo4syvaq+hv7oRmmjiy0JWtSSpK1lLAmKiGxyPr8/cMZBhfskOUfyfFxXLsl9n3Of\n95339eaVjzv3ee/COx1OHBGt1rcHurnCqudpPYIz+uP56JFnoz+ejx55vsr8YafcMB0WFqaOHTtq\n4sSJeumll+Tt7a3p06erYcOGSkhI0IEDB/TQQw9p1qxZiouL08cff6zt27frr3/9a6UVXVMVFJbq\n5Xc2qaCwVJI0enCE7om4XT2j7nBzZQAAADVTuddM22w2zZo1S6GhoUpKStJjjz2mgIAALVq0SLVr\n11abNm00Z84crVq1SgkJCUpLS1NqaqpatmxZFfXXGGV2ozf+maGDuWckSQN7BeueiNvdXBUAAEDN\nVu7KtCTdeuut+tvf/vab+2NjYxUbG1thReFKCz/5UZm7z1+bHt2uiYb8V6ibKwIAAMAN3c0D7vFl\nxgEtSzv/9uy/bxKg5x6JVK1aNjdXBQAAAMK0h9uz74Rm/982SVJAHR9NGhGtOv4+bq4KAAAAEmHa\nox0/VajXFmxW6Tm7atWy6cWhndSkYV13lwUAAIALCNMeqri0TK+8u1knThdLkv7cP0x3t77NzVUB\nAADgUoRpD2SM0awPtyn7wElJUp+uzdU3poWbqwIAAMDlCNMe6F9fZWvd1oOSpPatGupP/cPcXBEA\nAACuhjDtYTbvPKKFn55/R8NGDeroxcc7ycebNgEAAHgiUpoH2XfktKa9nyFjJH9fL00c3ln16/m5\nuywAAAD8BsK0hzhdUKJX3tmkwuIySdJzj0SpRbP6bq4KAAAA10KY9gDnyuyasjBdR46flSQN+a+2\n6hrW1M1VAQAAoDyEaQ/w9v/boR+yj0mSYjo003/f18bNFQEAAOB6EKbd7PMNv+jj736WJLUMqq8x\ngyJks/FW4QAAADcDwrQb7cg5prnLfpAkBdbz04ThneXv5+3mqgAAAHC9CNNuknvirP72XrrK7Ebe\nXjaNH9ZZjW6t4+6yAAAAcANYBv0Nk+au1/fZeTJGCk8v1stJ3Srs2IXF5/TyO5t0uqBEkvQ/Azoo\ntEWDCjs+AAAAqgZh+iomzV2vbVl5jq+3ZeVp2EurNHFEtFrfHujScS8G9Ivi72mp+6PvdKVcAAAA\nuAlh+iq+z867YtvxU0V6YdY36hB8m3x9asnX20s+3rXk5+MlHx8v+XrXks+F7ec/d/7z/c93K+ff\np5yO6eNdS7HhQVV1WgAAAKhghOkbUHrOroxdRyv0eK+9l64Fk3tX2DEBAABQdQjTV9GuRUPt+Om4\n0zYf71oKuq2evLxsKim1q/Rc2X/+PGdXSWmZ0+UbAAAAqP4I01dxV0vnMN2wvn+5q8fGGJXZjUpK\ny1R6zq7iC39e/Dr1X98r+6DzZR4N6/tr4ojoSjkHAAAAVD7C9GXOnC3Rym9+kiR5e9lU29d2XYHX\nZrPJ28smb6+r323wzbH3athLq3T8VJGk6wvoAAAA8GzcZ/oyK775SYXF5yRJE4ZH638Tmrl0B49L\nTRwRrYb1/VmRBgAAqCZYmb5EQWGpVnydI0lqfUegoto20pYtByvs+K1vD2Q1GgAAoBphZfoSH3/7\nkwqKzq9KP3x/iGw2m5srAgAAgCcjTF9wtqhUH607vyrdsll9dbqrsZsrAgAAgKcjTF/wyXc/60xh\nqSRp8ANtWJUGAABAuQjTkgqLz2l52vlV6eZNb1F0u6ZurggAAAA3A8K0pM/W/6z8syWSpMH3h6hW\nLValAQAAUL4aH6aLSs5pWVq2JOmOxgHqGsaqNAAAAK5PjQ/Tn2/Yp1NnLq5Kt2FVGgAAANetRofp\n4tIyLfsqS5IUdFs9xXQIcnNFAAAAuJnU6DC9euM+/ZpfLEkadH8bebEqDQAAgBtQY8N0SWmZln55\nflW66e/q6p5wVqUBAABwY2psmF6Tvl8nThdJkv67Vxt5edXYbwUAAAAsqpEJsvScXf+39vyqdOMG\ndXRv1O1urggAAAA3oxoZpr/M2K9jJwslSQN7tZE3q9IAAACwoMalyHNldi25sCrd6Nba+kPHO9xc\nEQAAAG5WNS5Mf5VxQLknzkqSEnu1kY93jfsWAAAAoILUqCRZVmbXkrV7JUm/q++v+zqxKg0AAADr\nalSYXrf1oI4cv7Aq/Ydg+Xh7ubkiAAAA3MxqTJgusxt9+MX5VekGt/jp/ug73VwRAAAAbnY1Jkx/\ns+3fOnSsQJI0oGewfH1YlQYAAIBrakSYLrMbLVmzR5IUGOCnB7qwKg0AAADX1Ygwvf6HQzpw9Iwk\n6aF7W8vf19vNFQEAAKA6qPZh2m43+vCL86vSt9T1VZ+uzd1bEAAAAKqNah+mN+44rH1H8iVJCfe2\nlr8fq9IAAACoGNU6TNvtRosvrEoH1PFRXLfm7i0IAAAA1Uq1DtObfzyinw+dliT1j22tOv4+bq4I\nAAAA1Um1DdPG/GdVum5tHz3YvYWbKwIAAEB1U23DdMauo8o5eEqS1O+eVqxKAwAAoMJVyzB96ap0\nHX9v/bFHSzdXBAAAgOqoWobprXvytHf/SUnSH3u0VL3arEoDAACg4lW7MG2M0Qerd0uSavt5qd89\nrdxcEQAAAKqrcm+6fOzYMb3xxhv67rvvVFxcrLvvvlsvvviigoODJUmJiYnasWOH03MGDhyol19+\nuXIqLscPWce0e9+vkqQHu7dUQB1ft9QBAACA6u+aYdput+vpp5+WJKWmpqpOnTqaNWuWhg0bpk8/\n/VS33HKLcnJyNH36dHXp0sXxPH9//8qt+ho+uHCttL8vq9IAAACoXNcM07t379a2bdv06aefqmXL\n87/EN3XqVEVHRystLU0REREqLCxUeHi4GjZsWCUFX8v2nGPa+dNxSVJctxaqX8/PzRUBAACgOrvm\nNdPNmjXTvHnz1KLFf+7RbLPZJEmnT5/W3r175e/vr2bNmlVulddp8erzq9K+Pl7qfy+r0gAAAKhc\n11yZDgwMVGxsrNO2RYsWqaioSDExMVq1apUCAgL0/PPPa/PmzQoMDNSAAQM0dOhQR+iuCpPmrtf3\nWXkyF76O69Zctwa471ITAAAA1Aw3dDePtWvXasaMGRo+fLhatmyp7OxsFRUVqUePHnrnnXf06KOP\naubMmZo9e3Zl1XuFSXPXa9slQVqS1m05qOyDJ6usBgAAANRM5d7N46Jly5Zp8uTJ6tu3r1544QVJ\n0rRp03T27FnVrVtXkhQcHKz8/HzNnTtXzzzzTOVUfJnvs/Ou2PZrfrFeeWeTFkzuXSU1AAAAoGay\nGWNMeQ9KTU1VSkqKhgwZookTJ17zsevWrdOoUaOUkZGhevXq/ebjMjMzb7zay+SdKtWcT45edV9A\nbS/9b0JTl18DAAAAN7+oqKhKOW65K9Pz589XSkqKxowZo6SkJKd9iYmJioiI0IQJExzbtm/frsaN\nG18zSF9k9aSMMVqbfkBvffHDVfc3rO+viSOi1fr2QEvHv1RmZmalffNRMeiRZ6M/no8eeTb64/no\nkeeriEXc31LurfHefPNNJSYmKjExUXl5/7mkom7duoqLi1NycrLatWunyMhIbdq0SW+//bZTuK5o\nZ4tKlfqvH5S25aAkyWaT/H29VVh8TtL5IM3lHQAAAKgK1wzTn332mex2u5YuXaqlS5c67bu4Uu3l\n5aXU1FQdPnxYQUFBGj9+vBITEyul2OwDJzX1nxk6fKxAkhQY4KfnHo5UQF1fvfLOJknSxBHRlfLa\nAAAAwOWuGabHjh2rsWPHXvMAQ4cO1dChQyu0qMvZ7UYrvsnRe5/8qHNl5y/xjgxppDEPRzhugcdq\nNAAAAKradd/Nw11OnSlW8uKtyth1/hcNvWrZ9HhcqPrHtlatWlV3L2sAAADgch4dpn/IztP09zN1\n4nSxJKlRgzp6YUiUQu5s4ObKAAAAAA8N02Vldn3wxR4tWbNXF2/c1yM8SE8ldlDd2j7uLQ4AAAC4\nwOPCdO6vZzX9/Uz9+PMJSZKvj5dGJYTp/s6/r9K3KAcAAADK41FhesP2w5r54VadKSyVJN3ZJEAv\nPNZRv29yi5srAwAAAK7kEWG6pLRM76zcqU+++9mxrU/X5hrZr738fLzcWBkAAADw29wepg8czdfU\nRRn65fBpSVJdf289MyhCMXc3c3NlAAAAwLW5NUz/z9S1yv21UMUlZZKktnfequeHdFTjBnXcWRYA\nAABwXdwapg8cPeP4fGCvYD3Su628vWq5sSIAAADg+rn9Mg9JuqWurx6Pu8vdZQAAAAA3xCOWgX28\nPaIMAAAA4Ia4PcU2rO+viSOi3V0GAAAAcMPceplHw/r+WjC5tztLAAAAACxz68o0K9IAAAC4mbk1\nTLe+PdCdLw8AAAC4xO3XTAMAAAA3K8I0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYR\npgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYB\nAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAA\nAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACL\nCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWlRumjx07pnHj\nxql79+7q1KmTRo4cqaysLMf+b7/9Vv369VOHDh0UHx+vr7/+ulILBgAAADzFNcO03W7X008/rX37\n9ik1NVWLFy9WQECAhg0bppMnTyo7O1tPPvmk4uLi9NFHH6lXr1566qmnlJ2dXVX1AwAAAG5zzTC9\ne/dubdu2Ta+99prCwsLUqlUrTZ06VWfPnlVaWpoWLlyoiIgIjRo1Si1atNDo0aMVERGhhQsXVlX9\nAAAAgNtcM0w3a9ZM8+bNU4sWLRzbbDabJOn06dPKzMxU586dnZ7TuXNnZWRkVEKpAAAAgGe5ZpgO\nDAxUbGysI0BL0qJFi1RcXKyYmBgdOXJEjRs3dnpOo0aNdPjw4cqpFgAAAPAgN3Q3j7Vr12rGjBka\nPny4WrVqpaKiIvn5+Tk9xtfXVyUlJRVaJAAAAOCJrjtML1u2TKNHj1bfvn31l7/8RZLk5+d3RXAu\nKSlR7dq1K7ZKAAAAwAN5X8+DUlNTlZKSoiFDhmjixImO7U2bNlVubq7TY3Nzc9WkSZPrevHMzMwb\nKNV9bpY6azJ65Nnoj+ejR56N/ng+elRzlRum58+fr5SUFI0ZM0ZJSUlO+6KiopSenu60bdOmTerY\nseN1vXhUVNQNlOoemZmZN0WdNRk98mz0x/PRI89GfzwfPfJ8lfnDTrm3xnvzzTeVmJioxMRE5eXl\nOT4KCws1ZMgQpaena9asWcrJyVFKSoq2b9+uxx9/vNIKBgAAADzFNVemP/vsM9ntdi1dulRLly51\n2ndxpXrOnDl64403NH/+fLVq1Uqpqalq2bJlpRYNAAAAeIJrhumxY8dq7Nix1zxAbGysYmNjK7Qo\nAAAA4GZwQ7fGAwAAAPAfhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYR\npgEAAACLCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYB\nAAAAiwjTAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAA\nAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABYRpgEAAACL\nCNMAAACARYRpAAAAwCLCNAAAAGARYRoAAACwiDANAAAAWESYBgAAACwiTAMAAAAWEaYBAAAAiwjT\nAAAAgEWEaQAAAMAiwjQAAABgEWEaAAAAsIgwDQAAAFhEmAYAAAAsIkwDAAAAFhGmAQAAAIsI0wAA\nAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABY5H2jT5g8ebLsdrteeeUVx7bExETt2LHD6XED\nBw7Uyy+/7HqFAAAAgIe67jBtjNHMmTO1ZMkSDRw40Gl7Tk6Opk+fri5duji2+/v7V2ylAAAAgIe5\nrjB94MABjR8/XtnZ2WrWrNkV+woLCxUeHq6GDRtWSpEAAACAJ7qua6a3bt2qoKAgffzxxwoKCnLa\nt3fvXvn7+18RsgEAAIDq7rpWpuPj4xUfH3/VfVlZWQoICNDzzz+vzZs3KzAwUAMGDNDQoUNls9kq\ntFgAAADAk9zwLyBeLjs7W0VFRerRo4eSkpKUmZmpqVOnKj8/X88880xF1AgAAAB4JJfD9LRp03T2\n7FnVrVtXkhQcHKz8/HzNnTuXMA0AAIBqzeUwbbPZHEH6ojZt2qigoEBnzpxRvXr1fvO5mZmZrr58\nlbhZ6qzJ6JFnoz+ejx55Nvrj+ehRzeVymE5MTFRERIQmTJjg2LZ9+3Y1btz4mkE6KirK1ZcGAAAA\n3MpSmDbGOD6Pi4tTcnKy2rVrp8jISG3atElvv/22U7gGAAAAqiNLYfrSu3SMGDFCXl5eSk1N1eHD\nhxUUFKTx48crMTGxwooEAAAAPJHNXLrMDAAAAOC6XdebtgAAAAC4EmEaAAAAsKhGhenJkydr4sSJ\nTts++ugjPfjgg4qIiNCgQYO0YcMGp/179+7VyJEj1bFjR3Xv3l2TJk1Sfn6+Y39BQYHatm17xcfK\nlSur5JyqGys9+uWXX/SnP/1JnTp10r333qvZs2fLbrc7PWbBggXq2bOnwsPDNWLECO3bt6/Sz6W6\nqoweMUeuO3bsmMaNG6fu3burU6dOGjlypLKyshz7v/32W/Xr108dOnRQfHy8vv76a6fnHz9+XKNH\nj1anTp3UrVs3TZs2TWVlZU6PYY6sq+z+MEOuc7VHF5WUlCg+Pl4rVqy4Yh8zZF1l98elGTI1gN1u\nN8nJySYkJMRMnDjRsX3lypUmNDTUzJ8/3/zyyy9m0aJFJiwszKSnpxtjjCkqKjI9evQwTz/9tMnJ\nyTFbtmwxffr0Mc8++6zjGNu2bTNt27Y1Bw8eNMeOHXN8FBcXV/l53sys9ujkyZOmW7duZsSIEWbX\nrl0mPT3d9O7d20yaNMlxjCVLlpjIyEizatUqs2fPHpOUlGTuu+8+enSDKrNHzJFrysrKzKBBg8yg\nQYPMDz/8YLKzs83o0aNNt27dzK+//mqysrJM+/btzdy5c81PP/1kkpOTTfv27U1WVpbjGA8//LAZ\nMmSI2b17t0lLSzNdu3Y1M2bMcOxnjqyriv4wQ66piB4ZY0x+fr554oknTEhIiFmxYoXTPmbIuqro\njyszVO3D9P79+82QIUNMly5dTM+ePZ1CQHx8vBk3bpzT41988UUzfPhwY4wxP/74owkJCTF79+51\n7P/nP/9pIiMjHV8vWbLE9OzZs5LPonpzpUfvvvuuiYyMNPn5+Y79mzdvNm3btjVHjhwxxhjzwAMP\nmFmzZjn2FxQUmIiICLNy5crKPK1qpbJ7xBy5ZufOnSYkJMTk5OQ4thUXF5vw8HCzfPlyM2nSJPPY\nY485Peexxx5z/ECzZcsWExISYg4ePOjYv3z5chMZGWlKSkqMMcyRK6qiP8yQa1ztkTHGfPfdd6ZX\nr14mISHhqmGNGbKuKvrjygxV+8s8tm7dqqCgIH388ccKCgpy2rd//35FRkY6bQsNDVVGRoYk6Y47\n7lCDBg304YcfqqSkRCdOnNDnn3+usLAwx+OzsrLUqlWryj+RasyVHu3bt0/BwcFObxAUGhoqY4wy\nMjJ0/Phx7du3T9HR0Y79derUUfv27R3HQPkqs0cSc+SqZs2aad68eWrRooVj28VbmJ4+fVqZmZnq\n3Lmz03M6d+7s+P5nZGQoKCjIqbedOnVSQUGBdu3axRy5qLL7IzFDrnK1R5L01VdfKSEhQYsXL77i\n+MyQayq7P5JrM1Ttw3R8fLxef/11NWzY8Ip9jRo10qFDh5y2/fvf/1ZJSYnjrdD/8Y9/aMWKFQoP\nD1e3bt104sQJzZgxw/H4rKwsFRQU6PHHH1dMTIwGDx78m9fp4Oqs9ig/P1+NGjXS0aNHnd5I6ODB\ng5LO/+V15MgRSVLjxo2vOO7FfShfZfZIYo5cFRgYqNjYWKf3AFi0aJGKi4sVExOjI0eOXHUGDh8+\nLEk6evToVfdL0pEjR5gjF1V2fyRmyFWu9kiSJkyYoKeeekq+vr5XHJ8Zck1l90dybYaqfZi+lvj4\neL3//vvauHGjysrKtGHDBi1fvlw2m82xEv3ss88qMjJSixcv1ttvvy0vLy+NHTvW8ctT2dnZOnXq\nlJKSkvTWW28pMjJSo0aN0saNG918dtXDtXpUWlqquLg4HT9+XG+88YaKioqUm5urV199Vd7e3iot\nLVVhYaEkyc/Pz+m4Pj4+Ki4udscpVTuu9khijira2rVrNWPGDA0fPlytWrVSUVHRFTPg6+urkpIS\nSVJhYeEV/8D4+PjIZrOpuLiYOapgFd0fiRmqaDfao/IwQxWrovsjuTZDlt4Bsbr485//rBMnTuiJ\nJ56Q3W5XSEiIRo4cqTfffFMBAQF69913VVhYqOTkZPn7+0uS5syZo/vvv1/r1q1Tz549tXbtWkly\n/EUXGhqqrKwsLViwQF26dHHbuVUX5fWoQYMGSk5O1uTJk7VgwQLVq1dPo0eP1t69exUQEODo2+UD\nVVJSojp16rjjlKodV3skiTmqQMuWLdPkyZPVt29f/eUvf5F0/h/wq81A7dq1JUn+/v5X7C8tLZUx\nRrVr12aOKlBl9EdihiqSlR6VhxmqOJXRH8m1GarRK9M+Pj6aNGmStm7dqm+++UbLly+Xr6+vmjRp\nIh8fHx06dEgtWrRwDIF0/jrqW2+9Vfv375d0/pt++YpBcHAw/21TQcrrkST94Q9/0Lfffquvv/5a\n69evV9++fXXq1Cndcccdatq0qSQpNzfX6bi5ublX/JcQrHG1RxJzVFFSU1M1fvx4DR48WFOmTHFs\nb9q06VVnoEmTJpKkJk2aKC8v74r90vn/lmaOKkZl9UdihiqK1R6VhxmqGJXVH8m1GarRYTo5OVnz\n58+Xj4+P41rQNWvWKCYmRpLUvHlz/fLLL04/7eTm5urkyZNq3ry5jh8/rqioKH3xxRdOx92xY4eC\ng4Or7kSqsfJ6lJmZqWHDhslut+t3v/udvL29tWbNGtWrV08RERFq2LCh7rzzTm3evNlxzIKCAu3c\nuVMdO3Z0yzlVN672iDmqGPPnz1dKSorGjBlzxX3Ao6KilJ6e7rRt06ZNjhmIiorSgQMHnP7R2LRp\nk+rWravQ0FDmqAJURn/q1aun0NBQZqiCuNKj8jBDrqvM/rg8Q5buAXKTGjJkiJkwYYLj6yVLlpio\nqCizbt06s3//fvPSSy+Zjh07mv379xtjjDl16pSJiYkxo0ePNllZWeb77783gwcPNgkJCaasrMwY\nY8yoUaNMr169zIYNG0xOTo6ZMmWKufvuu012drZbzvFmd6M9On78uOnYsaN5/fXXzf79+83q1atN\nZGSkeeuttxzH+OCDD0x4eLj55JNPzJ49e8yoUaNM7969TWlpaZWfX3VQGT1ijlyza9cuExoaaiZM\nmGDy8vJMbm6u4+Ps2bNmz549pl27dmbmzJkmOzvbJCcnmw4dOjjdZuriPVx37tzpuI/xpbfxYo6s\nq4r+MEOuqYgeXepqt15jhqyriv64MkM1Lkxfen9cY4z5+9//bmJjY014eLgZOnSo2blzp9P+MuZS\nhAAABNZJREFUffv2maSkJBMdHW1iYmLMuHHjzIkTJxz78/PzzUsvvWR69OhhwsLCzODBg01GRkaV\nnE91ZKVHGRkZZuDAgaZDhw7mgQceMIsWLbriuPPmzTPdu3c34eHh5oknnjAHDhyo1POoziqjR8yR\na2bMmGFCQkKu+pGammqMMSYtLc307dvXhIWFmf79+5v169c7HSMvL8889dRTJjw83MTExDi9IchF\nzJE1VdEfZsg1FdGjS10trBnDDFlVFf1xZYZsxlxyvyoAAAAA161GXzMNAAAAuIIwDQAAAFhEmAYA\nAAAsIkwDAAAAFhGmAQAAAIsI0wAAAIBFhGkAAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGgCo0\nZcoURURE6OzZs07bp0+fru7du6usrEzp6el69NFHFR4eri5dumjSpEnKz893evymTZs0YsQIde7c\nWe3bt9d9992nOXPmyBgjSTp48KDatm2r9957T71791ZERIQ++eSTKjtPAKgpCNMAUIUSExNVWFio\n1atXO7bZ7XatWLFC/fr105YtWzR8+HAFBAQoJSVFL7zwgtLS0jRy5EiVlZVJknbu3KkRI0botttu\nU0pKiubNm6eoqCjNmjVLn3/+udPrzZ49W08++aRef/11denSpUrPFQBqAm93FwAANUmrVq3UoUMH\nrVixQv3795ckbdy4UUePHtVDDz2kCRMmKDg4WHPnznU856677lJCQoI+/fRT/fGPf1RWVpZ69Oih\nKVOmOB7TtWtXffnll8rIyFCfPn0c2/v27et4HQBAxWNlGgCq2IABA7Rx40bl5eVJkpYvX66wsDAF\nBQXp+++/V2xsrM6dO+f4aN26tZo2bar169dLkvr376+5c+equLhYu3fv1urVqzVz5kydO3dOpaWl\nTq8VGhpa5ecHADUJYRoAqlhcXJx8fX21cuVKFRQUaM2aNXrooYd06tQpGWM0d+5ctW/f3unj8OHD\nys3NlSQVFRVpwoQJ6tixoxISEjRt2jQdOnRIPj4+jmumL6pTp447ThEAagwu8wCAKlavXj098MAD\n+uyzz9SkSROVlZXpwQcflM1mk81m08iRI50u1ZAkY4zq1q0rSXr11Vf1xRdfaObMmeratav8/f0l\nnb/UAwBQtQjTAOAGAwYM0LBhw/TBBx+oV69eCggIkHT+soyffvpJ7dq1czz2zJkzeu6559S3b1+1\naNFCmZmZ6tatm3r27Ol4zI4dO/Trr7/KbrdX+bkAQE3GZR4A4AbR0dEKCgpSenq6EhISHNvHjBmj\ntLQ0jRs3TuvWrdOaNWs0cuRIZWRkOAJ2hw4dtG7dOi1ZskSbN2/WwoULlZSUpPr1619xyz0AQOVi\nZRoA3OSee+7RmjVr1KNHD6dtb731lmbPnq3Ro0fLz89Pd999txYtWqTWrVtLkl588UWVlpZqxowZ\nKioqUnh4uJKTk7Vq1SqtWbPGXacDADWSzVz+2yoAgEpXVlamPn36KC4uTmPGjHF3OQAAi1iZBoAq\ndObMGS1YsEBbt25VXl6eHnnkEXeXBABwAWEaAKqQn5+fFi9eLEl67bXX1KhRIzdXBABwBZd5AAAA\nABZxNw8AAADAIsI0AAAAYBFhGgAAALCIMA0AAABYRJgGAAAALCJMAwAAABb9fxo8mTemRpbCAAAA\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x107895be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "year_gbdf = df.groupby([\"year\"])\n",
    "year_series = year_gbdf[\"3P\"].aggregate(\"sum\") / year_gbdf[\"3PA\"].aggregate(\"sum\") * 100\n",
    "plt.figure(figsize=(12, 7))\n",
    "year_series.plot(marker=\"o\")\n",
    "plt.ylim(15, 45)\n",
    "title = plt.title(\"3 Point Percentage by Season\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the most part, these plots just confirmed my suspicions. The process of making them was more important in order to focus me on how I should gather, clean, and make the data available for my own explorations. One thing that I did take away from this is that position needs to be a part of whatever model I build."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Research"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Throughout this process, I was researching what has already been done in the area to help improve my own models. I found these links particularly useful:\n",
    "- http://counting-the-baskets.typepad.com/my-blog/2014/09/prediction-are-hard-especially-about-three-point-shooting.html\n",
    "- http://nyloncalculus.com/2014/08/29/long-take-three-point-shooting-stabilize/\n",
    "- http://fivethirtyeight.com/features/carmelo-anthonys-contract-could-doom-the-knicks-to-mediocrity/\n",
    "\n",
    "From the first article I learned that past years' 3PP, free throw percentage, and three point attempts correlate well with 3PP. From the second article I learned that 3PP is subject to a lot of variance. The third article is the one that got me to understand PECOTA. Given more time, I would try to relate each current player to similar players from the past. Then I would use statistics from those past players to help predict the current player's upcoming statistics."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "I wrote some code to carry out linear regressions in order to explore how well past statistics predict future 3PP. I weighted the regression according to how many three point attempts were made in the year to be predicted. This drags the model to a place where it makes better predictions for players that take more three point shots. The code to run these fits can be found in regression.py, but I also show it in the block below since it drives most of the rest my analysis. The implementation of this ordinary least squares linear regression is in a python module called `statsmodels`, but I'm calling it from an interface in the `pandas` module below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def r2_from_feature_set(df, usecols):\n",
    "    return pd.stats.api.ols(y=df[\"pred3PP\"],\n",
    "                            x=df[usecols],\n",
    "                            weights=df[\"pred3PA\"] / df[\"pred3PA\"].max()).r2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I gathered statistics from previous years (labeled \"prev\" and then the number of seasons before the season to be predicted). I also gathered average statistics from all the previous years, if they'd been played (labeled \"avg\" and then the number of seasons prior). The average stats produced better fits (in the form of higher r-squared metrics) and so I used \"avg4\" stats in the models I built."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avg4_3PP 0.19028162277658822\n",
      "prev1_3PP 0.1581233629513764\n"
     ]
    }
   ],
   "source": [
    "preddf = pastdf[pd.isnull(pastdf[\"pred3PP\"]) == False]\n",
    "\n",
    "for feature in [\"avg4_3PP\", \"prev1_3PP\"] :\n",
    "    print(\"{} {}\".format(feature, sixers.r2_from_feature_set(preddf, [feature])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following is a list of the candidate features that I explored for possible use in my final linear regression. Again, the \"avg4\" prefix means that these statistics are averaged from a player's previous four seasons, if played. For example, Otto Porter has only played two seasons in the league, so his \"avg4\" statistics will just be the average of those two seasons.\n",
    "\n",
    "(MP: minutes played, 3PA: three point attempts, 3PP: three point field goal percentage, 2PA: two point attempts, 2PP: two point field goal percentage, FTA: free throw attmpts, FTP: free throw field goal percentage, ORB: offensive rebounds, DRB: defensive rebounds, TRB: total rebounds, AST: assists, STL: steals, BLK: blocks, TOV: turnovers, PF: personal fouls, PTS: points)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Age',\n",
       " 'pos',\n",
       " 'avg4_MP',\n",
       " 'avg4_3PA',\n",
       " 'avg4_3PP',\n",
       " 'avg4_2PA',\n",
       " 'avg4_2PP',\n",
       " 'avg4_FTA',\n",
       " 'avg4_FTP',\n",
       " 'avg4_ORB',\n",
       " 'avg4_DRB',\n",
       " 'avg4_TRB',\n",
       " 'avg4_AST',\n",
       " 'avg4_STL',\n",
       " 'avg4_BLK',\n",
       " 'avg4_TOV',\n",
       " 'avg4_PF',\n",
       " 'avg4_PTS']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidate_features = [\"Age\", \"pos\"] + sixers.get_feature_list(\"avg\", 4)\n",
    "candidate_features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I then use greedy forward feature selection to decide which of these variables to include in a final predictive model. I run a linear regression with each of the candidate features and pick the one that provides the best fit. Then, I loop over the remaining variables and run a regression with each of them added to the variables that have already been chosen. I choose the one that improves the fit the most. I continue this process until the results of the regression are not improving by much. The result, shown below, is the set of features that best predicts 3PP by linear regression. The code with the details for how this is done can be found in regression.py."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['avg4_3PP', 'avg4_FTP', 'avg4_TOV', 'avg4_3PA', 'pos', 'avg4_BLK', 'avg4_2PP']\n"
     ]
    }
   ],
   "source": [
    "feature_set = sixers.greedy_forward_feature_selection(preddf, candidate_features)\n",
    "print(feature_set)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following block, I show the linear regression of each of the chosen variables with 3PP. The square pattern around avg4_3PP corresponds to players that do not take many three point shots, and so they end up with 0%, 50%, or 100% as their 3PP. Remember, these data points will not affect the linear fit greatly because we weighted it by the number of three point attempts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avg4_3PP r-squared = 0.19028162277658822\n"
     ]
    },
    {
     "data": {
      "image/png": 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UVaPXHyEYVjEARVEyDmA0DIMTrT62NbawY48XXzA6rOUZc3cNq9XK2rVrWbt27aDXli5d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R8/fhzV1dV49tlnsWbNGqxduxZPPfVUSj+b84Wxrn/p0qX43ve+h29961uor6/HunXr0NjYiHvv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\nUr/joCiWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e7364a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avg4_FTP r-squared = 0.06659978783497422\n"
     ]
    },
    {
     "data": {
      "image/png": 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HTtaz71gdh6saCEdj/Mstk/p9jB4DhuXLl/d7p0IIMRbEA45Rr9NJxpt+utJi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\nHox2NL34zYyQ+85x+GRDWuPuxchmV81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I524gr39QjvpmN3yKqhWX6jAk4fJo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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1079732e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avg4_TOV r-squared = 0.0072534918315606545\n"
     ]
    },
    {
     "data": {
      "image/png": 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VVCiq9t/2ulZ43XayQIwwZLkgiLEhbXrqt99+Gz/5yU/wla98BV/+8pfx6KOP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\nCMIj/h8WH881+5NfhwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c2a3e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avg4_3PA r-squared = 0.07328946298582562\n"
     ]
    },
    {
     "data": {
      "image/png": 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Ow75ype1rlkxKyoGIbZv6syzLgAyAAdRvpYggYc2SSXEdcarpgUymDIZjPtzV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\n9iX8HmL0kAGW2kw64yEYDOLVV1/F448/jksvvRQA8Pzzz2PdunXYv38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mWuJ6FzSicwPC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7SKigrU19fjjTfeSPn5G41GAMC9996La6+9FoBqTNbU1Izr/Kes50Hr0Bnvn9mzZ494//Tp0wEg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\nQQghhBDT8hfb7YeeSE6w3QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10cebe588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pos r-squared = 0.008039153153260203\n"
     ]
    },
    {
     "data": {
      "image/png": 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YfPvb38YFF/DFL9OVFpiRY9Jj/9FWhMNhjCrR89NwH0oLzDjBsrFElCESLivs3r0bt9xy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\nRAxUDkRERMRA5UBEREQM/gfaE5wxibIGWwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c891ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avg4_BLK r-squared = 0.025700037161654254\n"
     ]
    },
    {
     "data": {
      "image/png": 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5N2Ey9mcqep3Xth6msvp03A6ko33C5FD97o2ECZPydyo18pxSN1DPKumwRTQ9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DAAAK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\nIYQQQqLy/wGP273PUpDPCwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10cec2208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "avg4_2PP r-squared = 4.9306814631888685e-05\n"
     ]
    },
    {
     "data": {
      "image/png": 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AlVdeSUlJSZ/HI5EI8+bN49FHH+XCCy8c1kaOJJuqYqAQ0XQ6AjFqT3dS19RF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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c70a780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d30c668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for feature in feature_set:\n",
    "    print(\"{} r-squared = {}\".format(feature, sixers.r2_from_feature_set(preddf, [feature])))\n",
    "    sns.regplot(x=feature, y=\"pred3PP\", data=preddf)\n",
    "    plt.show()\n",
    "    plt.clf()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The final linear regression model is created with that feature set shown above. I fit the final model here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "-------------------------Summary of Regression Analysis-------------------------\n",
       "\n",
       "Formula: Y ~ <avg4_3PP> + <avg4_FTP> + <avg4_TOV> + <avg4_3PA> + <pos>\n",
       "             + <avg4_BLK> + <avg4_2PP> + <intercept>\n",
       "\n",
       "Number of Observations:         7323\n",
       "Number of Degrees of Freedom:   8\n",
       "\n",
       "R-squared:         0.2361\n",
       "Adj R-squared:     0.2354\n",
       "\n",
       "Rmse:              0.0214\n",
       "\n",
       "F-stat (7, 7315):   323.0075, p-value:     0.0000\n",
       "\n",
       "Degrees of Freedom: model 7, resid 7315\n",
       "\n",
       "-----------------------Summary of Estimated Coefficients------------------------\n",
       "      Variable       Coef    Std Err     t-stat    p-value    CI 2.5%   CI 97.5%\n",
       "--------------------------------------------------------------------------------\n",
       "      avg4_3PP     0.2895     0.0027     108.32     0.0000     0.2843     0.2948\n",
       "      avg4_FTP     0.1114     0.0032      34.95     0.0000     0.1051     0.1176\n",
       "      avg4_TOV    -0.0002     0.0000     -30.69     0.0000    -0.0002    -0.0001\n",
       "      avg4_3PA     0.0001     0.0000      20.19     0.0000     0.0001     0.0001\n",
       "           pos     0.0011     0.0003       3.98     0.0001     0.0005     0.0016\n",
       "--------------------------------------------------------------------------------\n",
       "      avg4_BLK    -0.0002     0.0000     -19.11     0.0000    -0.0002    -0.0002\n",
       "      avg4_2PP     0.0783     0.0060      13.04     0.0000     0.0665     0.0900\n",
       "     intercept     0.1428     0.0035      40.54     0.0000     0.1359     0.1497\n",
       "---------------------------------End of Summary---------------------------------"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linear_model = pd.stats.api.ols(y=preddf[\"pred3PP\"],\n",
    "                                x=preddf[feature_set],\n",
    "                                weights=preddf[\"pred3PA\"] / preddf[\"pred3PA\"].max())\n",
    "linear_model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, I use the model to make predictions for the upcoming season."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "modeldf = pastdf[pastdf[\"year\"] == 2016]\n",
    "results = linear_model.predict(x=modeldf[feature_set])\n",
    "modeldf[\"predicted_3PP\"] = results\n",
    "modeldf = modeldf[pd.isnull(modeldf[\"predicted_3PP\"]) == False]\n",
    "modeldf = modeldf.sort(\"predicted_3PP\", ascending=False)\n",
    "outputdf = modeldf[[\"pid\", \"Player\", \"predicted_3PP\", \"prev1_3PA\", \"avg4_3PP\"]].copy()\n",
    "outputdf.to_csv(\"resources/final_predictions.csv\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This next table shows the top ten predicted percentages. A couple players that average very few attempts show up in this list, but otherwise it's a reasonable list with names that I may have expected to be on it before I started this whole exercise. The prev1_3PA column shows how many 3PA each player had in the previous season. The avg4_3PP shows the average 3PP over the last four seasons for that player."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pid</th>\n",
       "      <th>Player</th>\n",
       "      <th>predicted_3PP</th>\n",
       "      <th>prev1_3PA</th>\n",
       "      <th>avg4_3PP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8197</th>\n",
       "      <td>k/korveky01</td>\n",
       "      <td>Kyle Korver</td>\n",
       "      <td>0.419707</td>\n",
       "      <td>449</td>\n",
       "      <td>0.464022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9686</th>\n",
       "      <td>m/mcneaje01</td>\n",
       "      <td>Jerel McNeal</td>\n",
       "      <td>0.416551</td>\n",
       "      <td>2</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11967</th>\n",
       "      <td>r/redicjj01</td>\n",
       "      <td>J.J. Redick</td>\n",
       "      <td>0.408778</td>\n",
       "      <td>458</td>\n",
       "      <td>0.403760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3275</th>\n",
       "      <td>c/curryst01</td>\n",
       "      <td>Stephen Curry</td>\n",
       "      <td>0.406468</td>\n",
       "      <td>646</td>\n",
       "      <td>0.443748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3763</th>\n",
       "      <td>d/dienggo01</td>\n",
       "      <td>Gorgui Dieng</td>\n",
       "      <td>0.405253</td>\n",
       "      <td>6</td>\n",
       "      <td>0.583333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2203</th>\n",
       "      <td>b/buyckdw01</td>\n",
       "      <td>Dwight Buycks</td>\n",
       "      <td>0.404861</td>\n",
       "      <td>11</td>\n",
       "      <td>0.465241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10174</th>\n",
       "      <td>m/morroan01</td>\n",
       "      <td>Anthony Morrow</td>\n",
       "      <td>0.404277</td>\n",
       "      <td>325</td>\n",
       "      <td>0.406963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>a/anderry01</td>\n",
       "      <td>Ryan Anderson</td>\n",
       "      <td>0.403629</td>\n",
       "      <td>359</td>\n",
       "      <td>0.381035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9924</th>\n",
       "      <td>m/millspa02</td>\n",
       "      <td>Patrick Mills</td>\n",
       "      <td>0.401586</td>\n",
       "      <td>182</td>\n",
       "      <td>0.398440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15397</th>\n",
       "      <td>w/wilcocj01</td>\n",
       "      <td>C.J. Wilcox</td>\n",
       "      <td>0.399532</td>\n",
       "      <td>19</td>\n",
       "      <td>0.368421</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               pid          Player  predicted_3PP  prev1_3PA  avg4_3PP\n",
       "8197   k/korveky01     Kyle Korver       0.419707        449  0.464022\n",
       "9686   m/mcneaje01    Jerel McNeal       0.416551          2  0.500000\n",
       "11967  r/redicjj01     J.J. Redick       0.408778        458  0.403760\n",
       "3275   c/curryst01   Stephen Curry       0.406468        646  0.443748\n",
       "3763   d/dienggo01    Gorgui Dieng       0.405253          6  0.583333\n",
       "2203   b/buyckdw01   Dwight Buycks       0.404861         11  0.465241\n",
       "10174  m/morroan01  Anthony Morrow       0.404277        325  0.406963\n",
       "431    a/anderry01   Ryan Anderson       0.403629        359  0.381035\n",
       "9924   m/millspa02   Patrick Mills       0.401586        182  0.398440\n",
       "15397  w/wilcocj01     C.J. Wilcox       0.399532         19  0.368421"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "modeldf[[\"pid\", \"Player\", \"predicted_3PP\", \"prev1_3PA\", \"avg4_3PP\"]].head(n=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The bottom of the list, shown in the next table, is also dominated by players that do not attempt many three pointers. Restricting the list to those who have averaged more than 50 3PA in the past seasons shows some guards with a history of poor shooting, as shown in the second table.  (Perhaps this is a recreation of the model you must have used before trading Michael Carter-Williams.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>predicted_3PP</th>\n",
       "      <th>prev1_3PA</th>\n",
       "      <th>avg4_3PP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3973</th>\n",
       "      <td>Andre Drummond</td>\n",
       "      <td>0.247573</td>\n",
       "      <td>2</td>\n",
       "      <td>0.166667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1399</th>\n",
       "      <td>Vander Blue</td>\n",
       "      <td>0.246799</td>\n",
       "      <td>10</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8452</th>\n",
       "      <td>David Lee</td>\n",
       "      <td>0.245782</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1316</th>\n",
       "      <td>Tarik Black</td>\n",
       "      <td>0.242867</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5366</th>\n",
       "      <td>Drew Gordon</td>\n",
       "      <td>0.241870</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1689</th>\n",
       "      <td>Elton Brand</td>\n",
       "      <td>0.236526</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11544</th>\n",
       "      <td>Mason Plumlee</td>\n",
       "      <td>0.234292</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6370</th>\n",
       "      <td>J.J. Hickson</td>\n",
       "      <td>0.230355</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12363</th>\n",
       "      <td>Thomas Robinson</td>\n",
       "      <td>0.229160</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10607</th>\n",
       "      <td>Joakim Noah</td>\n",
       "      <td>0.222470</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Player  predicted_3PP  prev1_3PA  avg4_3PP\n",
       "3973    Andre Drummond       0.247573          2  0.166667\n",
       "1399       Vander Blue       0.246799         10  0.100000\n",
       "8452         David Lee       0.245782          2  0.000000\n",
       "1316       Tarik Black       0.242867          1  0.000000\n",
       "5366       Drew Gordon       0.241870          3  0.000000\n",
       "1689       Elton Brand       0.236526          1  0.000000\n",
       "11544    Mason Plumlee       0.234292          3  0.000000\n",
       "6370      J.J. Hickson       0.230355          2  0.000000\n",
       "12363  Thomas Robinson       0.229160          2  0.000000\n",
       "10607      Joakim Noah       0.222470          2  0.000000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "modeldf[[\"Player\", \"predicted_3PP\", \"prev1_3PA\", \"avg4_3PP\"]].tail(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>predicted_3PP</th>\n",
       "      <th>prev1_3PA</th>\n",
       "      <th>avg4_3PP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6033</th>\n",
       "      <td>Gary Harris</td>\n",
       "      <td>0.317344</td>\n",
       "      <td>103</td>\n",
       "      <td>0.203883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12601</th>\n",
       "      <td>Brandon Rush</td>\n",
       "      <td>0.317092</td>\n",
       "      <td>27</td>\n",
       "      <td>0.225898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5507</th>\n",
       "      <td>Jerami Grant</td>\n",
       "      <td>0.317051</td>\n",
       "      <td>156</td>\n",
       "      <td>0.314103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11706</th>\n",
       "      <td>Phil Pressey</td>\n",
       "      <td>0.316333</td>\n",
       "      <td>65</td>\n",
       "      <td>0.255152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16123</th>\n",
       "      <td>Tony Wroten</td>\n",
       "      <td>0.314234</td>\n",
       "      <td>142</td>\n",
       "      <td>0.241110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13603</th>\n",
       "      <td>Lance Stephenson</td>\n",
       "      <td>0.311914</td>\n",
       "      <td>105</td>\n",
       "      <td>0.246752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7443</th>\n",
       "      <td>James Johnson</td>\n",
       "      <td>0.309142</td>\n",
       "      <td>51</td>\n",
       "      <td>0.220116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14958</th>\n",
       "      <td>John Wall</td>\n",
       "      <td>0.302748</td>\n",
       "      <td>217</td>\n",
       "      <td>0.247071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12450</th>\n",
       "      <td>Rajon Rondo</td>\n",
       "      <td>0.300210</td>\n",
       "      <td>86</td>\n",
       "      <td>0.270234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2458</th>\n",
       "      <td>Michael Carter-Williams</td>\n",
       "      <td>0.294668</td>\n",
       "      <td>153</td>\n",
       "      <td>0.249859</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Player  predicted_3PP  prev1_3PA  avg4_3PP\n",
       "6033               Gary Harris       0.317344        103  0.203883\n",
       "12601             Brandon Rush       0.317092         27  0.225898\n",
       "5507              Jerami Grant       0.317051        156  0.314103\n",
       "11706             Phil Pressey       0.316333         65  0.255152\n",
       "16123              Tony Wroten       0.314234        142  0.241110\n",
       "13603         Lance Stephenson       0.311914        105  0.246752\n",
       "7443             James Johnson       0.309142         51  0.220116\n",
       "14958                John Wall       0.302748        217  0.247071\n",
       "12450              Rajon Rondo       0.300210         86  0.270234\n",
       "2458   Michael Carter-Williams       0.294668        153  0.249859"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "modeldf[modeldf[\"avg4_3PA\"] > 50][[\"Player\", \"predicted_3PP\", \"prev1_3PA\", \"avg4_3PP\"]].tail(n=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I've written my final predictions to a file called \"resources/final_predictions.csv\" and also printed all the predictions at the bottom of this notebook. I like that the model predicts some regression to the mean for the top guys. I'm sure someone will top that max predicted 3PP of 42% for Kyle Korver, but the model is just trying to minimize the mean squared error. It doesn't want to guess at who might break out this coming year."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Discussion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "The thing that I would most want to do with this project is to add in SportVU data. I feel that a lot of the inherent variability in three point field goal percentage is due to the pressure of the defense and how \"in rhythm\" the shooter is. First of all, I'd want to try and quantify \"in rhythm\", but that is probably a very difficult problem that would require a lot of time.\n",
    "\n",
    "The easier thing to do with SportVU data is quantify how close the defense was to the shooter for every three point attempt. Then, using league wide statistics and a player's past expectations, I could set a Bayesian prior for whether or not that shot would go in. This way, highly contested shots that are taken late in the shot clock won't affect a player's expected three point percentage greatly if they miss it. Also, wide open in rhythm shots would be expected to go in and any missed shots there would seriously affect a player's future expectations. I'm guessing that the Sixers and other analytically minded teams are already making adjustments like this.\n",
    "\n",
    "Given more time, there's also a lot of data cleaning and debugging issues that I'd want to work on before having absolute confidence in the data. Right now, I'm not making predictions for rookies. I'm making predictions for anyone who had a stat line in the last season without considering retirements. I'd like to take a look at players who have changed teams and what their different roles might be. Most of these issues could be handled with more time for engineering work or a more professional source of data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Final Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>predicted_3PP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8197</th>\n",
       "      <td>Kyle Korver</td>\n",
       "      <td>0.419707</td>\n",
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       "    <tr>\n",
       "      <th>9686</th>\n",
       "      <td>Jerel McNeal</td>\n",
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       "    <tr>\n",
       "      <th>11967</th>\n",
       "      <td>J.J. Redick</td>\n",
       "      <td>0.408778</td>\n",
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       "    <tr>\n",
       "      <th>3275</th>\n",
       "      <td>Stephen Curry</td>\n",
       "      <td>0.406468</td>\n",
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       "    <tr>\n",
       "      <th>3763</th>\n",
       "      <td>Gorgui Dieng</td>\n",
       "      <td>0.405253</td>\n",
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       "    <tr>\n",
       "      <th>2203</th>\n",
       "      <td>Dwight Buycks</td>\n",
       "      <td>0.404861</td>\n",
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       "    <tr>\n",
       "      <th>10174</th>\n",
       "      <td>Anthony Morrow</td>\n",
       "      <td>0.404277</td>\n",
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       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>Ryan Anderson</td>\n",
       "      <td>0.403629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9924</th>\n",
       "      <td>Patrick Mills</td>\n",
       "      <td>0.401586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15397</th>\n",
       "      <td>C.J. Wilcox</td>\n",
       "      <td>0.399532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14215</th>\n",
       "      <td>Klay Thompson</td>\n",
       "      <td>0.398007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9290</th>\n",
       "      <td>Wesley Matthews</td>\n",
       "      <td>0.397107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9717</th>\n",
       "      <td>Jodie Meeks</td>\n",
       "      <td>0.396934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9210</th>\n",
       "      <td>Kevin Martin</td>\n",
       "      <td>0.395153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5584</th>\n",
       "      <td>Danny Green</td>\n",
       "      <td>0.394872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1482</th>\n",
       "      <td>Matt Bonner</td>\n",
       "      <td>0.394690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4086</th>\n",
       "      <td>Mike Dunleavy</td>\n",
       "      <td>0.392331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16178</th>\n",
       "      <td>Cody Zeller</td>\n",
       "      <td>0.391565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11071</th>\n",
       "      <td>Jannero Pargo</td>\n",
       "      <td>0.390662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2165</th>\n",
       "      <td>Caron Butler</td>\n",
       "      <td>0.389217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4287</th>\n",
       "      <td>Wayne Ellington</td>\n",
       "      <td>0.388907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10659</th>\n",
       "      <td>Steve Novak</td>\n",
       "      <td>0.388808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8441</th>\n",
       "      <td>Courtney Lee</td>\n",
       "      <td>0.388101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>715</th>\n",
       "      <td>Luke Babbitt</td>\n",
       "      <td>0.387874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4899</th>\n",
       "      <td>Channing Frye</td>\n",
       "      <td>0.387712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14277</th>\n",
       "      <td>Marcus Thornton</td>\n",
       "      <td>0.386726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4827</th>\n",
       "      <td>Randy Foye</td>\n",
       "      <td>0.386712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9754</th>\n",
       "      <td>Khris Middleton</td>\n",
       "      <td>0.386376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7462</th>\n",
       "      <td>Joe Johnson</td>\n",
       "      <td>0.386059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5929</th>\n",
       "      <td>Tim Hardaway</td>\n",
       "      <td>0.385385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4527</th>\n",
       "      <td>Jordan Farmar</td>\n",
       "      <td>0.384714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7236</th>\n",
       "      <td>John Jenkins</td>\n",
       "      <td>0.384491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16155</th>\n",
       "      <td>Nick Young</td>\n",
       "      <td>0.383835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14023</th>\n",
       "      <td>Jason Terry</td>\n",
       "      <td>0.383655</td>\n",
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       "    <tr>\n",
       "      <th>5673</th>\n",
       "      <td>Willie Green</td>\n",
       "      <td>0.383575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14852</th>\n",
       "      <td>Henry Walker</td>\n",
       "      <td>0.382596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5811</th>\n",
       "      <td>Justin Hamilton</td>\n",
       "      <td>0.382429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10480</th>\n",
       "      <td>Gary Neal</td>\n",
       "      <td>0.381956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12216</th>\n",
       "      <td>Brian Roberts</td>\n",
       "      <td>0.381823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3096</th>\n",
       "      <td>Jamal Crawford</td>\n",
       "      <td>0.381638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12512</th>\n",
       "      <td>Terrence Ross</td>\n",
       "      <td>0.381363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4875</th>\n",
       "      <td>Jimmer Fredette</td>\n",
       "      <td>0.380888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8609</th>\n",
       "      <td>Damian Lillard</td>\n",
       "      <td>0.380801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Arron Afflalo</td>\n",
       "      <td>0.379605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7991</th>\n",
       "      <td>Sean Kilpatrick</td>\n",
       "      <td>0.379437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14090</th>\n",
       "      <td>Isaiah Thomas</td>\n",
       "      <td>0.379169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6770</th>\n",
       "      <td>Robbie Hummel</td>\n",
       "      <td>0.379062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11171</th>\n",
       "      <td>Chris Paul</td>\n",
       "      <td>0.378991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3010</th>\n",
       "      <td>Chris Copeland</td>\n",
       "      <td>0.378497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536</th>\n",
       "      <td>Trevor Ariza</td>\n",
       "      <td>0.378486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14200</th>\n",
       "      <td>Hollis Thompson</td>\n",
       "      <td>0.378069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1067</th>\n",
       "      <td>Bradley Beal</td>\n",
       "      <td>0.378067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6909</th>\n",
       "      <td>Kyrie Irving</td>\n",
       "      <td>0.377955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14359</th>\n",
       "      <td>Anthony Tolliver</td>\n",
       "      <td>0.377858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4011</th>\n",
       "      <td>Jared Dudley</td>\n",
       "      <td>0.377839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8306</th>\n",
       "      <td>Jeremy Lamb</td>\n",
       "      <td>0.377816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15737</th>\n",
       "      <td>Mo Williams</td>\n",
       "      <td>0.377571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15046</th>\n",
       "      <td>C.J. Watson</td>\n",
       "      <td>0.377566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>Alan Anderson</td>\n",
       "      <td>0.377513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8501</th>\n",
       "      <td>Kawhi Leonard</td>\n",
       "      <td>0.377490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9861</th>\n",
       "      <td>Mike Miller</td>\n",
       "      <td>0.377320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2069</th>\n",
       "      <td>Chase Budinger</td>\n",
       "      <td>0.377098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6425</th>\n",
       "      <td>George Hill</td>\n",
       "      <td>0.377000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7215</th>\n",
       "      <td>Richard Jefferson</td>\n",
       "      <td>0.376816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4112</th>\n",
       "      <td>Kevin Durant</td>\n",
       "      <td>0.376716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13114</th>\n",
       "      <td>Kyle Singler</td>\n",
       "      <td>0.375818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2476</th>\n",
       "      <td>Vince Carter</td>\n",
       "      <td>0.375201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2409</th>\n",
       "      <td>DeMarre Carroll</td>\n",
       "      <td>0.374897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11462</th>\n",
       "      <td>Paul Pierce</td>\n",
       "      <td>0.374628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3668</th>\n",
       "      <td>Matthew Dellavedova</td>\n",
       "      <td>0.374249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1215</th>\n",
       "      <td>Patrick Beverley</td>\n",
       "      <td>0.374091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7705</th>\n",
       "      <td>James Jones</td>\n",
       "      <td>0.373702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9349</th>\n",
       "      <td>O.J. Mayo</td>\n",
       "      <td>0.373415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1802</th>\n",
       "      <td>Aaron Brooks</td>\n",
       "      <td>0.373323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3072</th>\n",
       "      <td>Allen Crabbe</td>\n",
       "      <td>0.373241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>671</th>\n",
       "      <td>D.J. Augustin</td>\n",
       "      <td>0.373138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6571</th>\n",
       "      <td>Rodney Hood</td>\n",
       "      <td>0.373019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5936</th>\n",
       "      <td>James Harden</td>\n",
       "      <td>0.372990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15748</th>\n",
       "      <td>Marvin Williams</td>\n",
       "      <td>0.372975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3046</th>\n",
       "      <td>Bryce Cotton</td>\n",
       "      <td>0.372555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13424</th>\n",
       "      <td>Tony Snell</td>\n",
       "      <td>0.372440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5364</th>\n",
       "      <td>Ben Gordon</td>\n",
       "      <td>0.371960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2909</th>\n",
       "      <td>Mike Conley</td>\n",
       "      <td>0.371882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1629</th>\n",
       "      <td>Avery Bradley</td>\n",
       "      <td>0.371203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5160</th>\n",
       "      <td>Paul George</td>\n",
       "      <td>0.370939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7338</th>\n",
       "      <td>Chris Johnson</td>\n",
       "      <td>0.370934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9644</th>\n",
       "      <td>Ben McLemore</td>\n",
       "      <td>0.370215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2733</th>\n",
       "      <td>Ian Clark</td>\n",
       "      <td>0.370112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1053</th>\n",
       "      <td>Jerryd Bayless</td>\n",
       "      <td>0.370044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>478</th>\n",
       "      <td>Carmelo Anthony</td>\n",
       "      <td>0.370033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8781</th>\n",
       "      <td>Kyle Lowry</td>\n",
       "      <td>0.369598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3200</th>\n",
       "      <td>Jared Cunningham</td>\n",
       "      <td>0.369174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350</th>\n",
       "      <td>Nate Robinson</td>\n",
       "      <td>0.369166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>Matt Barnes</td>\n",
       "      <td>0.369010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1890</th>\n",
       "      <td>Jabari Brown</td>\n",
       "      <td>0.368981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4953</th>\n",
       "      <td>Langston Galloway</td>\n",
       "      <td>0.368817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2827</th>\n",
       "      <td>Darren Collison</td>\n",
       "      <td>0.368440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9437</th>\n",
       "      <td>C.J. McCollum</td>\n",
       "      <td>0.368422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2619</th>\n",
       "      <td>Wilson Chandler</td>\n",
       "      <td>0.368014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10507</th>\n",
       "      <td>Jameer Nelson</td>\n",
       "      <td>0.367932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11138</th>\n",
       "      <td>Chandler Parsons</td>\n",
       "      <td>0.367849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10084</th>\n",
       "      <td>E'Twaun Moore</td>\n",
       "      <td>0.367293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9699</th>\n",
       "      <td>Josh McRoberts</td>\n",
       "      <td>0.367120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4416</th>\n",
       "      <td>James Ennis</td>\n",
       "      <td>0.367038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11590</th>\n",
       "      <td>Quincy Pondexter</td>\n",
       "      <td>0.366993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5374</th>\n",
       "      <td>Eric Gordon</td>\n",
       "      <td>0.366898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875</th>\n",
       "      <td>Harrison Barnes</td>\n",
       "      <td>0.366773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2577</th>\n",
       "      <td>Mario Chalmers</td>\n",
       "      <td>0.366687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8798</th>\n",
       "      <td>John Lucas</td>\n",
       "      <td>0.366686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6454</th>\n",
       "      <td>Solomon Hill</td>\n",
       "      <td>0.366612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Quincy Acy</td>\n",
       "      <td>0.366565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15549</th>\n",
       "      <td>Deron Williams</td>\n",
       "      <td>0.366325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1336</th>\n",
       "      <td>Steve Blake</td>\n",
       "      <td>0.366134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13579</th>\n",
       "      <td>Nik Stauskas</td>\n",
       "      <td>0.366124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2280</th>\n",
       "      <td>Kentavious Caldwell-Pope</td>\n",
       "      <td>0.365852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2335</th>\n",
       "      <td>Isaiah Canaan</td>\n",
       "      <td>0.365499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8766</th>\n",
       "      <td>Kevin Love</td>\n",
       "      <td>0.364736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12086</th>\n",
       "      <td>Jason Richardson</td>\n",
       "      <td>0.364569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15859</th>\n",
       "      <td>Shawne Williams</td>\n",
       "      <td>0.364283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15072</th>\n",
       "      <td>Travis Wear</td>\n",
       "      <td>0.364226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7876</th>\n",
       "      <td>Ryan Kelly</td>\n",
       "      <td>0.364147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6029</th>\n",
       "      <td>Devin Harris</td>\n",
       "      <td>0.364122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14750</th>\n",
       "      <td>Noah Vonleh</td>\n",
       "      <td>0.363979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2110</th>\n",
       "      <td>Trey Burke</td>\n",
       "      <td>0.363581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14665</th>\n",
       "      <td>Greivis Vasquez</td>\n",
       "      <td>0.363468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13669</th>\n",
       "      <td>David Stockton</td>\n",
       "      <td>0.363379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10419</th>\n",
       "      <td>Shabazz Napier</td>\n",
       "      <td>0.362716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8141</th>\n",
       "      <td>Brandon Knight</td>\n",
       "      <td>0.362631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6225</th>\n",
       "      <td>Gordon Hayward</td>\n",
       "      <td>0.362255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5616</th>\n",
       "      <td>Jeff Green</td>\n",
       "      <td>0.361791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10856</th>\n",
       "      <td>Kelly Olynyk</td>\n",
       "      <td>0.360811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>841</th>\n",
       "      <td>Jose Barea</td>\n",
       "      <td>0.360777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6537</th>\n",
       "      <td>Jrue Holiday</td>\n",
       "      <td>0.360690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5775</th>\n",
       "      <td>P.J. Hairston</td>\n",
       "      <td>0.360620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7550</th>\n",
       "      <td>Tyler Johnson</td>\n",
       "      <td>0.360361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11765</th>\n",
       "      <td>Tayshaun Prince</td>\n",
       "      <td>0.360243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7567</th>\n",
       "      <td>Wesley Johnson</td>\n",
       "      <td>0.359800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6953</th>\n",
       "      <td>Jarrett Jack</td>\n",
       "      <td>0.359784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8505</th>\n",
       "      <td>Meyers Leonard</td>\n",
       "      <td>0.359165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3699</th>\n",
       "      <td>Luol Deng</td>\n",
       "      <td>0.358818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12160</th>\n",
       "      <td>Luke Ridnour</td>\n",
       "      <td>0.358807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Jordan Adams</td>\n",
       "      <td>0.358785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13028</th>\n",
       "      <td>Iman Shumpert</td>\n",
       "      <td>0.358676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3156</th>\n",
       "      <td>Jae Crowder</td>\n",
       "      <td>0.358390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6484</th>\n",
       "      <td>Kirk Hinrich</td>\n",
       "      <td>0.358015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2115</th>\n",
       "      <td>Alec Burks</td>\n",
       "      <td>0.357890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5437</th>\n",
       "      <td>Danny Granger</td>\n",
       "      <td>0.357419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5344</th>\n",
       "      <td>Drew Gooden</td>\n",
       "      <td>0.356926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8411</th>\n",
       "      <td>Ty Lawson</td>\n",
       "      <td>0.356514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6035</th>\n",
       "      <td>Joe Harris</td>\n",
       "      <td>0.356467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2200</th>\n",
       "      <td>Rasual Butler</td>\n",
       "      <td>0.355783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2735</th>\n",
       "      <td>Jordan Clarkson</td>\n",
       "      <td>0.355761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5597</th>\n",
       "      <td>Erick Green</td>\n",
       "      <td>0.355747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8864</th>\n",
       "      <td>Shelvin Mack</td>\n",
       "      <td>0.354849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5127</th>\n",
       "      <td>Alonzo Gee</td>\n",
       "      <td>0.353300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10224</th>\n",
       "      <td>Shabazz Muhammad</td>\n",
       "      <td>0.353023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9140</th>\n",
       "      <td>Kendall Marshall</td>\n",
       "      <td>0.352945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14720</th>\n",
       "      <td>Charlie Villanueva</td>\n",
       "      <td>0.352874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13980</th>\n",
       "      <td>Jeff Teague</td>\n",
       "      <td>0.352318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3597</th>\n",
       "      <td>Austin Daye</td>\n",
       "      <td>0.352089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2178</th>\n",
       "      <td>Jimmy Butler</td>\n",
       "      <td>0.351984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6092</th>\n",
       "      <td>Tobias Harris</td>\n",
       "      <td>0.351314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8395</th>\n",
       "      <td>Zach LaVine</td>\n",
       "      <td>0.351070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6731</th>\n",
       "      <td>Lester Hudson</td>\n",
       "      <td>0.351006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12956</th>\n",
       "      <td>Ramon Sessions</td>\n",
       "      <td>0.350931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8618</th>\n",
       "      <td>Jeremy Lin</td>\n",
       "      <td>0.350898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2103</th>\n",
       "      <td>Reggie Bullock</td>\n",
       "      <td>0.350809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13815</th>\n",
       "      <td>Rodney Stuckey</td>\n",
       "      <td>0.350668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1542</th>\n",
       "      <td>Chris Bosh</td>\n",
       "      <td>0.350256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12470</th>\n",
       "      <td>Derrick Rose</td>\n",
       "      <td>0.349979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14879</th>\n",
       "      <td>Kemba Walker</td>\n",
       "      <td>0.349932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>Toney Douglas</td>\n",
       "      <td>0.349779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12672</th>\n",
       "      <td>John Salmons</td>\n",
       "      <td>0.349763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9386</th>\n",
       "      <td>Ray McCallum</td>\n",
       "      <td>0.349097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4576</th>\n",
       "      <td>Raymond Felton</td>\n",
       "      <td>0.348853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1077</th>\n",
       "      <td>Michael Beasley</td>\n",
       "      <td>0.348480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10155</th>\n",
       "      <td>Marcus Morris</td>\n",
       "      <td>0.347606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9491</th>\n",
       "      <td>Doug McDermott</td>\n",
       "      <td>0.347491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11666</th>\n",
       "      <td>Dwight Powell</td>\n",
       "      <td>0.347377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9100</th>\n",
       "      <td>Shawn Marion</td>\n",
       "      <td>0.347374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7053</th>\n",
       "      <td>Reggie Jackson</td>\n",
       "      <td>0.346748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6540</th>\n",
       "      <td>Justin Holiday</td>\n",
       "      <td>0.346636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10340</th>\n",
       "      <td>Mike Muscala</td>\n",
       "      <td>0.346286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13176</th>\n",
       "      <td>Marcus Smart</td>\n",
       "      <td>0.345192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6874</th>\n",
       "      <td>Andre Iguodala</td>\n",
       "      <td>0.345143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5114</th>\n",
       "      <td>Rudy Gay</td>\n",
       "      <td>0.345005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7805</th>\n",
       "      <td>Cory Joseph</td>\n",
       "      <td>0.344746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6298</th>\n",
       "      <td>Gerald Henderson</td>\n",
       "      <td>0.344695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14827</th>\n",
       "      <td>Dion Waiters</td>\n",
       "      <td>0.344096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2805</th>\n",
       "      <td>Norris Cole</td>\n",
       "      <td>0.343698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11149</th>\n",
       "      <td>Patrick Patterson</td>\n",
       "      <td>0.343280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1916</th>\n",
       "      <td>Markel Brown</td>\n",
       "      <td>0.343087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10150</th>\n",
       "      <td>Markieff Morris</td>\n",
       "      <td>0.343033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8380</th>\n",
       "      <td>Shane Larkin</td>\n",
       "      <td>0.341795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6168</th>\n",
       "      <td>Spencer Hawes</td>\n",
       "      <td>0.341548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15554</th>\n",
       "      <td>Derrick Williams</td>\n",
       "      <td>0.341039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9824</th>\n",
       "      <td>Andre Miller</td>\n",
       "      <td>0.340849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13938</th>\n",
       "      <td>Jeffery Taylor</td>\n",
       "      <td>0.340329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10781</th>\n",
       "      <td>Victor Oladipo</td>\n",
       "      <td>0.340007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1736</th>\n",
       "      <td>Corey Brewer</td>\n",
       "      <td>0.339906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10143</th>\n",
       "      <td>Darius Morris</td>\n",
       "      <td>0.338784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15215</th>\n",
       "      <td>Russell Westbrook</td>\n",
       "      <td>0.338723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4983</th>\n",
       "      <td>Francisco Garcia</td>\n",
       "      <td>0.338658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7758</th>\n",
       "      <td>Terrence Jones</td>\n",
       "      <td>0.338302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1063</th>\n",
       "      <td>Kent Bazemore</td>\n",
       "      <td>0.338236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12880</th>\n",
       "      <td>Mike Scott</td>\n",
       "      <td>0.338196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5352</th>\n",
       "      <td>Aaron Gordon</td>\n",
       "      <td>0.338052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7642</th>\n",
       "      <td>Dahntay Jones</td>\n",
       "      <td>0.337712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1975</th>\n",
       "      <td>Shannon Brown</td>\n",
       "      <td>0.336920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1374</th>\n",
       "      <td>Eric Bledsoe</td>\n",
       "      <td>0.336703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15001</th>\n",
       "      <td>T.J. Warren</td>\n",
       "      <td>0.336330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3712</th>\n",
       "      <td>DeMar DeRozan</td>\n",
       "      <td>0.335651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12174</th>\n",
       "      <td>Austin Rivers</td>\n",
       "      <td>0.334981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4137</th>\n",
       "      <td>Cleanthony Early</td>\n",
       "      <td>0.334906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9917</th>\n",
       "      <td>Paul Millsap</td>\n",
       "      <td>0.334637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3875</th>\n",
       "      <td>Chris Douglas-Roberts</td>\n",
       "      <td>0.332594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5595</th>\n",
       "      <td>Draymond Green</td>\n",
       "      <td>0.332378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13819</th>\n",
       "      <td>Jared Sullinger</td>\n",
       "      <td>0.332104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6595</th>\n",
       "      <td>Al Horford</td>\n",
       "      <td>0.332090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>955</th>\n",
       "      <td>Will Barton</td>\n",
       "      <td>0.331952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11617</th>\n",
       "      <td>Otto Porter</td>\n",
       "      <td>0.331809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13368</th>\n",
       "      <td>Russ Smith</td>\n",
       "      <td>0.331707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11747</th>\n",
       "      <td>Ronnie Price</td>\n",
       "      <td>0.330942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8528</th>\n",
       "      <td>Jon Leuer</td>\n",
       "      <td>0.330922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9907</th>\n",
       "      <td>Elijah Millsap</td>\n",
       "      <td>0.330670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4418</th>\n",
       "      <td>Tyler Ennis</td>\n",
       "      <td>0.330628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15558</th>\n",
       "      <td>Elliot Williams</td>\n",
       "      <td>0.330121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12321</th>\n",
       "      <td>Glenn Robinson</td>\n",
       "      <td>0.329475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13168</th>\n",
       "      <td>Donald Sloan</td>\n",
       "      <td>0.329108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11713</th>\n",
       "      <td>A.J. Price</td>\n",
       "      <td>0.328695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11102</th>\n",
       "      <td>Jabari Parker</td>\n",
       "      <td>0.328510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14508</th>\n",
       "      <td>Evan Turner</td>\n",
       "      <td>0.327936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9476</th>\n",
       "      <td>K.J. McDaniels</td>\n",
       "      <td>0.327790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14004</th>\n",
       "      <td>Garrett Temple</td>\n",
       "      <td>0.327747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15376</th>\n",
       "      <td>Andrew Wiggins</td>\n",
       "      <td>0.326407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3770</th>\n",
       "      <td>Spencer Dinwiddie</td>\n",
       "      <td>0.326259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9368</th>\n",
       "      <td>Luc Mbah a Moute</td>\n",
       "      <td>0.326209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16140</th>\n",
       "      <td>James Young</td>\n",
       "      <td>0.325388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14925</th>\n",
       "      <td>Gerald Wallace</td>\n",
       "      <td>0.325374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12689</th>\n",
       "      <td>JaKarr Sampson</td>\n",
       "      <td>0.324096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1160</th>\n",
       "      <td>Anthony Bennett</td>\n",
       "      <td>0.323783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>Kyle Anderson</td>\n",
       "      <td>0.322505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>609</th>\n",
       "      <td>Darrell Arthur</td>\n",
       "      <td>0.321630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4482</th>\n",
       "      <td>Tyreke Evans</td>\n",
       "      <td>0.321170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15374</th>\n",
       "      <td>Shayne Whittington</td>\n",
       "      <td>0.320862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7261</th>\n",
       "      <td>Grant Jerrett</td>\n",
       "      <td>0.320520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5940</th>\n",
       "      <td>Maurice Harkless</td>\n",
       "      <td>0.319896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>Al-Farouq Aminu</td>\n",
       "      <td>0.319457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14805</th>\n",
       "      <td>Dwyane Wade</td>\n",
       "      <td>0.318710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16171</th>\n",
       "      <td>Thaddeus Young</td>\n",
       "      <td>0.318631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7526</th>\n",
       "      <td>Nick Johnson</td>\n",
       "      <td>0.317905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4630</th>\n",
       "      <td>Landry Fields</td>\n",
       "      <td>0.317878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2259</th>\n",
       "      <td>Nick Calathes</td>\n",
       "      <td>0.317617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6033</th>\n",
       "      <td>Gary Harris</td>\n",
       "      <td>0.317344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12601</th>\n",
       "      <td>Brandon Rush</td>\n",
       "      <td>0.317092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5507</th>\n",
       "      <td>Jerami Grant</td>\n",
       "      <td>0.317051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5350</th>\n",
       "      <td>Archie Goodwin</td>\n",
       "      <td>0.316983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11706</th>\n",
       "      <td>Phil Pressey</td>\n",
       "      <td>0.316333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>Tony Allen</td>\n",
       "      <td>0.316081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13490</th>\n",
       "      <td>Marreese Speights</td>\n",
       "      <td>0.315600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2223</th>\n",
       "      <td>Will Bynum</td>\n",
       "      <td>0.314940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16123</th>\n",
       "      <td>Tony Wroten</td>\n",
       "      <td>0.314234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3395</th>\n",
       "      <td>Brandon Davies</td>\n",
       "      <td>0.312126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13603</th>\n",
       "      <td>Lance Stephenson</td>\n",
       "      <td>0.311914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>LaMarcus Aldridge</td>\n",
       "      <td>0.310675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7731</th>\n",
       "      <td>Perry Jones</td>\n",
       "      <td>0.310606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12212</th>\n",
       "      <td>Andre Roberson</td>\n",
       "      <td>0.309162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7443</th>\n",
       "      <td>James Johnson</td>\n",
       "      <td>0.309142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4866</th>\n",
       "      <td>Tim Frazier</td>\n",
       "      <td>0.307744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15228</th>\n",
       "      <td>David West</td>\n",
       "      <td>0.307703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12063</th>\n",
       "      <td>Glen Rice</td>\n",
       "      <td>0.306427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13242</th>\n",
       "      <td>Ish Smith</td>\n",
       "      <td>0.302822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14958</th>\n",
       "      <td>John Wall</td>\n",
       "      <td>0.302748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5757</th>\n",
       "      <td>Jorge Gutierrez</td>\n",
       "      <td>0.301922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1491</th>\n",
       "      <td>Trevor Booker</td>\n",
       "      <td>0.300777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12450</th>\n",
       "      <td>Rajon Rondo</td>\n",
       "      <td>0.300210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11889</th>\n",
       "      <td>Zach Randolph</td>\n",
       "      <td>0.299995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3946</th>\n",
       "      <td>Larry Drew</td>\n",
       "      <td>0.299675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5700</th>\n",
       "      <td>Blake Griffin</td>\n",
       "      <td>0.298820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1911</th>\n",
       "      <td>Lorenzo Brown</td>\n",
       "      <td>0.295817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2458</th>\n",
       "      <td>Michael Carter-Williams</td>\n",
       "      <td>0.294668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2882</th>\n",
       "      <td>Nick Collison</td>\n",
       "      <td>0.294334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9875</th>\n",
       "      <td>Quincy Miller</td>\n",
       "      <td>0.290773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4444</th>\n",
       "      <td>Jeremy Evans</td>\n",
       "      <td>0.288644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2662</th>\n",
       "      <td>Will Cherry</td>\n",
       "      <td>0.287133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5608</th>\n",
       "      <td>JaMychal Green</td>\n",
       "      <td>0.284977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11216</th>\n",
       "      <td>Elfrid Payton</td>\n",
       "      <td>0.283141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3492</th>\n",
       "      <td>Glen Davis</td>\n",
       "      <td>0.281475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7194</th>\n",
       "      <td>Cory Jefferson</td>\n",
       "      <td>0.281126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11209</th>\n",
       "      <td>Adreian Payne</td>\n",
       "      <td>0.277384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10902</th>\n",
       "      <td>Kyle O'Quinn</td>\n",
       "      <td>0.276360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15969</th>\n",
       "      <td>Nate Wolters</td>\n",
       "      <td>0.270109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9058</th>\n",
       "      <td>Devyn Marble</td>\n",
       "      <td>0.267653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6451</th>\n",
       "      <td>Jordan Hill</td>\n",
       "      <td>0.266651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6362</th>\n",
       "      <td>Roy Hibbert</td>\n",
       "      <td>0.265238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4066</th>\n",
       "      <td>Tim Duncan</td>\n",
       "      <td>0.264432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5871</th>\n",
       "      <td>Tyler Hansbrough</td>\n",
       "      <td>0.264160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3060</th>\n",
       "      <td>DeMarcus Cousins</td>\n",
       "      <td>0.260135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3413</th>\n",
       "      <td>Anthony Davis</td>\n",
       "      <td>0.259363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9524</th>\n",
       "      <td>Mitch McGary</td>\n",
       "      <td>0.251289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3196</th>\n",
       "      <td>Dante Cunningham</td>\n",
       "      <td>0.247587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3973</th>\n",
       "      <td>Andre Drummond</td>\n",
       "      <td>0.247573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1399</th>\n",
       "      <td>Vander Blue</td>\n",
       "      <td>0.246799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8452</th>\n",
       "      <td>David Lee</td>\n",
       "      <td>0.245782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1316</th>\n",
       "      <td>Tarik Black</td>\n",
       "      <td>0.242867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5366</th>\n",
       "      <td>Drew Gordon</td>\n",
       "      <td>0.241870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1689</th>\n",
       "      <td>Elton Brand</td>\n",
       "      <td>0.236526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11544</th>\n",
       "      <td>Mason Plumlee</td>\n",
       "      <td>0.234292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6370</th>\n",
       "      <td>J.J. Hickson</td>\n",
       "      <td>0.230355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12363</th>\n",
       "      <td>Thomas Robinson</td>\n",
       "      <td>0.229160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10607</th>\n",
       "      <td>Joakim Noah</td>\n",
       "      <td>0.222470</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Player  predicted_3PP\n",
       "8197                Kyle Korver       0.419707\n",
       "9686               Jerel McNeal       0.416551\n",
       "11967               J.J. Redick       0.408778\n",
       "3275              Stephen Curry       0.406468\n",
       "3763               Gorgui Dieng       0.405253\n",
       "2203              Dwight Buycks       0.404861\n",
       "10174            Anthony Morrow       0.404277\n",
       "431               Ryan Anderson       0.403629\n",
       "9924              Patrick Mills       0.401586\n",
       "15397               C.J. Wilcox       0.399532\n",
       "14215             Klay Thompson       0.398007\n",
       "9290            Wesley Matthews       0.397107\n",
       "9717                Jodie Meeks       0.396934\n",
       "9210               Kevin Martin       0.395153\n",
       "5584                Danny Green       0.394872\n",
       "1482                Matt Bonner       0.394690\n",
       "4086              Mike Dunleavy       0.392331\n",
       "16178               Cody Zeller       0.391565\n",
       "11071             Jannero Pargo       0.390662\n",
       "2165               Caron Butler       0.389217\n",
       "4287            Wayne Ellington       0.388907\n",
       "10659               Steve Novak       0.388808\n",
       "8441               Courtney Lee       0.388101\n",
       "715                Luke Babbitt       0.387874\n",
       "4899              Channing Frye       0.387712\n",
       "14277           Marcus Thornton       0.386726\n",
       "4827                 Randy Foye       0.386712\n",
       "9754            Khris Middleton       0.386376\n",
       "7462                Joe Johnson       0.386059\n",
       "5929               Tim Hardaway       0.385385\n",
       "4527              Jordan Farmar       0.384714\n",
       "7236               John Jenkins       0.384491\n",
       "16155                Nick Young       0.383835\n",
       "14023               Jason Terry       0.383655\n",
       "5673               Willie Green       0.383575\n",
       "14852              Henry Walker       0.382596\n",
       "5811            Justin Hamilton       0.382429\n",
       "10480                 Gary Neal       0.381956\n",
       "12216             Brian Roberts       0.381823\n",
       "3096             Jamal Crawford       0.381638\n",
       "12512             Terrence Ross       0.381363\n",
       "4875            Jimmer Fredette       0.380888\n",
       "8609             Damian Lillard       0.380801\n",
       "106               Arron Afflalo       0.379605\n",
       "7991            Sean Kilpatrick       0.379437\n",
       "14090             Isaiah Thomas       0.379169\n",
       "6770              Robbie Hummel       0.379062\n",
       "11171                Chris Paul       0.378991\n",
       "3010             Chris Copeland       0.378497\n",
       "536                Trevor Ariza       0.378486\n",
       "14200           Hollis Thompson       0.378069\n",
       "1067               Bradley Beal       0.378067\n",
       "6909               Kyrie Irving       0.377955\n",
       "14359          Anthony Tolliver       0.377858\n",
       "4011               Jared Dudley       0.377839\n",
       "8306                Jeremy Lamb       0.377816\n",
       "15737               Mo Williams       0.377571\n",
       "15046               C.J. Watson       0.377566\n",
       "316               Alan Anderson       0.377513\n",
       "8501              Kawhi Leonard       0.377490\n",
       "9861                Mike Miller       0.377320\n",
       "2069             Chase Budinger       0.377098\n",
       "6425                George Hill       0.377000\n",
       "7215          Richard Jefferson       0.376816\n",
       "4112               Kevin Durant       0.376716\n",
       "13114              Kyle Singler       0.375818\n",
       "2476               Vince Carter       0.375201\n",
       "2409            DeMarre Carroll       0.374897\n",
       "11462               Paul Pierce       0.374628\n",
       "3668        Matthew Dellavedova       0.374249\n",
       "1215           Patrick Beverley       0.374091\n",
       "7705                James Jones       0.373702\n",
       "9349                  O.J. Mayo       0.373415\n",
       "1802               Aaron Brooks       0.373323\n",
       "3072               Allen Crabbe       0.373241\n",
       "671               D.J. Augustin       0.373138\n",
       "6571                Rodney Hood       0.373019\n",
       "5936               James Harden       0.372990\n",
       "15748           Marvin Williams       0.372975\n",
       "3046               Bryce Cotton       0.372555\n",
       "13424                Tony Snell       0.372440\n",
       "5364                 Ben Gordon       0.371960\n",
       "2909                Mike Conley       0.371882\n",
       "1629              Avery Bradley       0.371203\n",
       "5160                Paul George       0.370939\n",
       "7338              Chris Johnson       0.370934\n",
       "9644               Ben McLemore       0.370215\n",
       "2733                  Ian Clark       0.370112\n",
       "1053             Jerryd Bayless       0.370044\n",
       "478             Carmelo Anthony       0.370033\n",
       "8781                 Kyle Lowry       0.369598\n",
       "3200           Jared Cunningham       0.369174\n",
       "12350             Nate Robinson       0.369166\n",
       "888                 Matt Barnes       0.369010\n",
       "1890               Jabari Brown       0.368981\n",
       "4953          Langston Galloway       0.368817\n",
       "2827            Darren Collison       0.368440\n",
       "9437              C.J. McCollum       0.368422\n",
       "2619            Wilson Chandler       0.368014\n",
       "10507             Jameer Nelson       0.367932\n",
       "11138          Chandler Parsons       0.367849\n",
       "10084             E'Twaun Moore       0.367293\n",
       "9699             Josh McRoberts       0.367120\n",
       "4416                James Ennis       0.367038\n",
       "11590          Quincy Pondexter       0.366993\n",
       "5374                Eric Gordon       0.366898\n",
       "875             Harrison Barnes       0.366773\n",
       "2577             Mario Chalmers       0.366687\n",
       "8798                 John Lucas       0.366686\n",
       "6454               Solomon Hill       0.366612\n",
       "57                   Quincy Acy       0.366565\n",
       "15549            Deron Williams       0.366325\n",
       "1336                Steve Blake       0.366134\n",
       "13579              Nik Stauskas       0.366124\n",
       "2280   Kentavious Caldwell-Pope       0.365852\n",
       "2335              Isaiah Canaan       0.365499\n",
       "8766                 Kevin Love       0.364736\n",
       "12086          Jason Richardson       0.364569\n",
       "15859           Shawne Williams       0.364283\n",
       "15072               Travis Wear       0.364226\n",
       "7876                 Ryan Kelly       0.364147\n",
       "6029               Devin Harris       0.364122\n",
       "14750               Noah Vonleh       0.363979\n",
       "2110                 Trey Burke       0.363581\n",
       "14665           Greivis Vasquez       0.363468\n",
       "13669            David Stockton       0.363379\n",
       "10419            Shabazz Napier       0.362716\n",
       "8141             Brandon Knight       0.362631\n",
       "6225             Gordon Hayward       0.362255\n",
       "5616                 Jeff Green       0.361791\n",
       "10856              Kelly Olynyk       0.360811\n",
       "841                  Jose Barea       0.360777\n",
       "6537               Jrue Holiday       0.360690\n",
       "5775              P.J. Hairston       0.360620\n",
       "7550              Tyler Johnson       0.360361\n",
       "11765           Tayshaun Prince       0.360243\n",
       "7567             Wesley Johnson       0.359800\n",
       "6953               Jarrett Jack       0.359784\n",
       "8505             Meyers Leonard       0.359165\n",
       "3699                  Luol Deng       0.358818\n",
       "12160              Luke Ridnour       0.358807\n",
       "69                 Jordan Adams       0.358785\n",
       "13028             Iman Shumpert       0.358676\n",
       "3156                Jae Crowder       0.358390\n",
       "6484               Kirk Hinrich       0.358015\n",
       "2115                 Alec Burks       0.357890\n",
       "5437              Danny Granger       0.357419\n",
       "5344                Drew Gooden       0.356926\n",
       "8411                  Ty Lawson       0.356514\n",
       "6035                 Joe Harris       0.356467\n",
       "2200              Rasual Butler       0.355783\n",
       "2735            Jordan Clarkson       0.355761\n",
       "5597                Erick Green       0.355747\n",
       "8864               Shelvin Mack       0.354849\n",
       "5127                 Alonzo Gee       0.353300\n",
       "10224          Shabazz Muhammad       0.353023\n",
       "9140           Kendall Marshall       0.352945\n",
       "14720        Charlie Villanueva       0.352874\n",
       "13980               Jeff Teague       0.352318\n",
       "3597                Austin Daye       0.352089\n",
       "2178               Jimmy Butler       0.351984\n",
       "6092              Tobias Harris       0.351314\n",
       "8395                Zach LaVine       0.351070\n",
       "6731              Lester Hudson       0.351006\n",
       "12956            Ramon Sessions       0.350931\n",
       "8618                 Jeremy Lin       0.350898\n",
       "2103             Reggie Bullock       0.350809\n",
       "13815            Rodney Stuckey       0.350668\n",
       "1542                 Chris Bosh       0.350256\n",
       "12470              Derrick Rose       0.349979\n",
       "14879              Kemba Walker       0.349932\n",
       "3899              Toney Douglas       0.349779\n",
       "12672              John Salmons       0.349763\n",
       "9386               Ray McCallum       0.349097\n",
       "4576             Raymond Felton       0.348853\n",
       "1077            Michael Beasley       0.348480\n",
       "10155             Marcus Morris       0.347606\n",
       "9491             Doug McDermott       0.347491\n",
       "11666             Dwight Powell       0.347377\n",
       "9100               Shawn Marion       0.347374\n",
       "7053             Reggie Jackson       0.346748\n",
       "6540             Justin Holiday       0.346636\n",
       "10340              Mike Muscala       0.346286\n",
       "13176              Marcus Smart       0.345192\n",
       "6874             Andre Iguodala       0.345143\n",
       "5114                   Rudy Gay       0.345005\n",
       "7805                Cory Joseph       0.344746\n",
       "6298           Gerald Henderson       0.344695\n",
       "14827              Dion Waiters       0.344096\n",
       "2805                Norris Cole       0.343698\n",
       "11149         Patrick Patterson       0.343280\n",
       "1916               Markel Brown       0.343087\n",
       "10150           Markieff Morris       0.343033\n",
       "8380               Shane Larkin       0.341795\n",
       "6168              Spencer Hawes       0.341548\n",
       "15554          Derrick Williams       0.341039\n",
       "9824               Andre Miller       0.340849\n",
       "13938            Jeffery Taylor       0.340329\n",
       "10781            Victor Oladipo       0.340007\n",
       "1736               Corey Brewer       0.339906\n",
       "10143             Darius Morris       0.338784\n",
       "15215         Russell Westbrook       0.338723\n",
       "4983           Francisco Garcia       0.338658\n",
       "7758             Terrence Jones       0.338302\n",
       "1063              Kent Bazemore       0.338236\n",
       "12880                Mike Scott       0.338196\n",
       "5352               Aaron Gordon       0.338052\n",
       "7642              Dahntay Jones       0.337712\n",
       "1975              Shannon Brown       0.336920\n",
       "1374               Eric Bledsoe       0.336703\n",
       "15001               T.J. Warren       0.336330\n",
       "3712              DeMar DeRozan       0.335651\n",
       "12174             Austin Rivers       0.334981\n",
       "4137           Cleanthony Early       0.334906\n",
       "9917               Paul Millsap       0.334637\n",
       "3875      Chris Douglas-Roberts       0.332594\n",
       "5595             Draymond Green       0.332378\n",
       "13819           Jared Sullinger       0.332104\n",
       "6595                 Al Horford       0.332090\n",
       "955                 Will Barton       0.331952\n",
       "11617               Otto Porter       0.331809\n",
       "13368                Russ Smith       0.331707\n",
       "11747              Ronnie Price       0.330942\n",
       "8528                  Jon Leuer       0.330922\n",
       "9907             Elijah Millsap       0.330670\n",
       "4418                Tyler Ennis       0.330628\n",
       "15558           Elliot Williams       0.330121\n",
       "12321            Glenn Robinson       0.329475\n",
       "13168              Donald Sloan       0.329108\n",
       "11713                A.J. Price       0.328695\n",
       "11102             Jabari Parker       0.328510\n",
       "14508               Evan Turner       0.327936\n",
       "9476             K.J. McDaniels       0.327790\n",
       "14004            Garrett Temple       0.327747\n",
       "15376            Andrew Wiggins       0.326407\n",
       "3770          Spencer Dinwiddie       0.326259\n",
       "9368           Luc Mbah a Moute       0.326209\n",
       "16140               James Young       0.325388\n",
       "14925            Gerald Wallace       0.325374\n",
       "12689            JaKarr Sampson       0.324096\n",
       "1160            Anthony Bennett       0.323783\n",
       "389               Kyle Anderson       0.322505\n",
       "609              Darrell Arthur       0.321630\n",
       "4482               Tyreke Evans       0.321170\n",
       "15374        Shayne Whittington       0.320862\n",
       "7261              Grant Jerrett       0.320520\n",
       "5940           Maurice Harkless       0.319896\n",
       "299             Al-Farouq Aminu       0.319457\n",
       "14805               Dwyane Wade       0.318710\n",
       "16171            Thaddeus Young       0.318631\n",
       "7526               Nick Johnson       0.317905\n",
       "4630              Landry Fields       0.317878\n",
       "2259              Nick Calathes       0.317617\n",
       "6033                Gary Harris       0.317344\n",
       "12601              Brandon Rush       0.317092\n",
       "5507               Jerami Grant       0.317051\n",
       "5350             Archie Goodwin       0.316983\n",
       "11706              Phil Pressey       0.316333\n",
       "260                  Tony Allen       0.316081\n",
       "13490         Marreese Speights       0.315600\n",
       "2223                 Will Bynum       0.314940\n",
       "16123               Tony Wroten       0.314234\n",
       "3395             Brandon Davies       0.312126\n",
       "13603          Lance Stephenson       0.311914\n",
       "177           LaMarcus Aldridge       0.310675\n",
       "7731                Perry Jones       0.310606\n",
       "12212            Andre Roberson       0.309162\n",
       "7443              James Johnson       0.309142\n",
       "4866                Tim Frazier       0.307744\n",
       "15228                David West       0.307703\n",
       "12063                 Glen Rice       0.306427\n",
       "13242                 Ish Smith       0.302822\n",
       "14958                 John Wall       0.302748\n",
       "5757            Jorge Gutierrez       0.301922\n",
       "1491              Trevor Booker       0.300777\n",
       "12450               Rajon Rondo       0.300210\n",
       "11889             Zach Randolph       0.299995\n",
       "3946                 Larry Drew       0.299675\n",
       "5700              Blake Griffin       0.298820\n",
       "1911              Lorenzo Brown       0.295817\n",
       "2458    Michael Carter-Williams       0.294668\n",
       "2882              Nick Collison       0.294334\n",
       "9875              Quincy Miller       0.290773\n",
       "4444               Jeremy Evans       0.288644\n",
       "2662                Will Cherry       0.287133\n",
       "5608             JaMychal Green       0.284977\n",
       "11216             Elfrid Payton       0.283141\n",
       "3492                 Glen Davis       0.281475\n",
       "7194             Cory Jefferson       0.281126\n",
       "11209             Adreian Payne       0.277384\n",
       "10902              Kyle O'Quinn       0.276360\n",
       "15969              Nate Wolters       0.270109\n",
       "9058               Devyn Marble       0.267653\n",
       "6451                Jordan Hill       0.266651\n",
       "6362                Roy Hibbert       0.265238\n",
       "4066                 Tim Duncan       0.264432\n",
       "5871           Tyler Hansbrough       0.264160\n",
       "3060           DeMarcus Cousins       0.260135\n",
       "3413              Anthony Davis       0.259363\n",
       "9524               Mitch McGary       0.251289\n",
       "3196           Dante Cunningham       0.247587\n",
       "3973             Andre Drummond       0.247573\n",
       "1399                Vander Blue       0.246799\n",
       "8452                  David Lee       0.245782\n",
       "1316                Tarik Black       0.242867\n",
       "5366                Drew Gordon       0.241870\n",
       "1689                Elton Brand       0.236526\n",
       "11544             Mason Plumlee       0.234292\n",
       "6370               J.J. Hickson       0.230355\n",
       "12363           Thomas Robinson       0.229160\n",
       "10607               Joakim Noah       0.222470"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_rows', len(modeldf))\n",
    "modeldf[[\"Player\", \"predicted_3PP\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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