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This project aims to aid in the process of benching players using effective machine learning models to learn outcomes from various scenarios and predict the right players to bench according to various features like playing styles, consecutive matches, etc.

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aadit2697/NBA-Roster-Optimization

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Project Agenda:

Model 1:

  • First predict whether the teams wins/looses a game. Use the historical games data from the API to train the model. Create a new column called won/lost and populate it by runnin the model on the data.

Model 2:

  • Use the updated table from above and predict whether the player will be benched or not.

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This project aims to aid in the process of benching players using effective machine learning models to learn outcomes from various scenarios and predict the right players to bench according to various features like playing styles, consecutive matches, etc.

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