LG Hoops Advanced Metric 1.0

I have been playing around with Python (a programming language) and data manipulation tools to create my own LG Hoops advanced metric. This is my first version of my own metric which utilizes machine learning and theories such as ‘random forest’ (an algorithm technique) to project the overall value of each player.

The stats leveraged were TS%, TRB%, AST%, 3P%, FT%, STL%, BLK%, TOV%, and USG%. I tried to incorporate stats touching every aspect of the game (free access stats only).

The average player would fall under the likes of guys like Saddiq Bey and Kevin Love, while there are some guys like Christian Wood standing out as a top 35 player.

I plan on editing and adding various intricacies and details to the algorithm over the next few months, but please reach out for any questions or recommendations!