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Lineup Optimizer.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We'll just locks for this example. Besides that we have some standard GPP constraints like:\n",
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"We'll just use locks for this example. Besides that we have some standard GPP constraints like:\n",
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"- don't face your starting defense\n",
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"- don't have too many players from one team\n",
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"- too many players from the same skill group on a team\n",
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"There you have it. All you have to do now is go to the lineups tab on draft kings and update this sheet. \n",
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"There you have it. All you have to do now is go to the lineups tab on draft kings and upload this sheet. \n",
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"I hope this served as a good example. The code needs serious refactoring, probably should just be scrapped, but this should give you a great starting point for your own lineup optimizer"
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]
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},

Power Rankings.ipynb

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"### We will use 538's Elo Algorithm\n",
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"- [538's Elo Introduction](https://fivethirtyeight.com/datalab/introducing-nfl-elo-ratings/)\n",
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"- [More Elo Description](https://fivethirtyeight.com/datalab/nfl-elo-ratings-are-back/) \n",
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"\n",
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"### The features for this model are:\n",
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"- game location (home, away, neutral)\n",
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"- team score\n",

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