About

This canvas predicts NBA players' peak-season performance using machine learning models trained on early-career stats (years 1–3) and trajectory features (career-year deltas and growth rates). The workflow ingests NBA player statistics and potential data, builds predictive models (Ridge for points, Random Forest for rebounds/assists), evaluates them via 5-fold cross-validation with comprehensive feature importance analysis, and outputs player predictions paired with actual peak-season stats and physical attributes.