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A quantitative sports modeling pipeline built with Python, XGBoost, and LightGBM that identifies +EV (Expected Value) opportunities in NBA and MLB markets.Tech Stack Machine Learning: Scikit-learn, XGBoost, LightGBM, Pandas, NumPy. APIs & Data: The-Odds-API (Live Lines), NBA_API, MLB-StatsAPI. Backend: Python 3.11, Supabase (Database/Auth).
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Paramarerize market blends and edge shrink factors in MLB ValueScanner
7c1ab39View on GitHubCache complete MLB season so historical boxscores are never refetched
abefbe0View on GitHub