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Pulled data from nba stats API using a Python library, created features in Python, then fed the data into pretty basic machine learning models. Only achieved slight gains over just assuming a player's performance was going to be his average over the past year.

But a big part that was pretty effective and not even predictive related was using a modified knapsack algorithm to fit the best predicted value into one day's roster.

I never proved the algorithm, though...




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