Machine learning
NBA Win-Probability Prediction
End-to-end ML system that predicts NBA game win probabilities, served as an interactive web app with game-by-game backtest report cards.
Highlights
- Engineered a leakage-safe pipeline validated with walk-forward testing over 22,800+ held-out games across 19 seasons.
- Prioritized proper scoring rules (log loss, Brier) and probability calibration over raw accuracy.
- Best model (logistic regression on Elo + rolling form/rest features) beat a strong Elo baseline while staying well-calibrated.
- Benchmarked against the betting market and honestly reported no edge after the house margin after debugging a data error.
Stack
Pythonscikit-learnXGBoostStreamlit