This project identifies NBA player archetypes via clustering and uses them to predict team Net Rating with machine learning. Built using 10 seasons of player/team data.
5 Player Archetypes: Ball-Dominant Guards, 3PT Specialists, Versatile Wings, Stretch Bigs, Traditional Bigs
GLMNet, Cubist, XGBoost, Random Forest, Stacked Ensemble
Best Model: Stacked (GLMNet + Cubist)
SHAP highlights PER, OBPM, and Stretch Big share as key features
clustering_analysis.R – Player archetype discovery
predicting_team_ntrtg.R – Team Net Rating prediction
ML_ws_bpm_cluster.R – Player BPM prediction
Other scripts for preprocessing, aggregation, and visualization