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.
Can you explain how your bot worked from a technical perspective? And/or what did you learn from the whole experience