tra-analysis/data analysis/dep/2019/matches/frc-elo.ipynb

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   "cell_type": "code",
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    "import operator\n",
    "import csv\n",
    "#constants\n",
    "k=100\n",
    "rdf=400\n",
    "\n",
    "def win_prob(yas,oas):\n",
    "    return 1/(1+10**(1/rdf*(oas-yas)))\n",
    "def new_score(oscore,yas,oas,outcome):\n",
    "    return (oscore)+k*(outcome-win_prob(yas,oas))\n",
    "\n",
    "def readFile(filepath):\n",
    "\n",
    "    with open(filepath) as csvfile:\n",
    "        lines = csv.reader(csvfile, delimiter=',', quotechar='|')\n",
    "        data = []\n",
    "        try:\n",
    "            for row in lines:\n",
    "                data.append((', '.join(row)).split(\", \"))\n",
    "        except:\n",
    "            pass\n",
    "\n",
    "    return data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "sb=readFile('scoreboard.csv')\n",
    "teams=set([])\n",
    "for i in sb:\n",
    "    teams.add(i[2])\n",
    "    teams.add(i[3])\n",
    "    teams.add(i[4])\n",
    "    teams.add(i[5])\n",
    "    teams.add(i[6])\n",
    "    teams.add(i[7])\n",
    "list(teams)\n",
    "tsd={}\n",
    "for i in list(teams):\n",
    "    tsd[i]=500\n",
    "for i in sb:\n",
    "    ras=tsd[i[2]]+tsd[i[3]]+tsd[i[4]]\n",
    "    bas=tsd[i[5]]+tsd[i[6]]+tsd[i[7]]\n",
    "    outcome=0\n",
    "    if i[8]>i[9]:\n",
    "        outcome=1\n",
    "    elif i[9]==i[8]:\n",
    "        outcome=.5\n",
    "    for j in range(2,5,1):\n",
    "        tsd[i[j]]=new_score(tsd[i[j]],ras,bas,outcome)\n",
    "    for j in range(5,8,1):\n",
    "        tsd[i[j]]=new_score(tsd[i[j]],bas,ras,1-outcome)\n",
    "        \n",
    "rankinfs = sorted(tsd.items(), key=operator.itemgetter(1), reverse=True)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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     "execution_count": 3,
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    }
   ],
   "source": [
    "rankinfs"
   ]
  },
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