"I'd walk through hell in a gasoline suit to play baseball." - Pete Rose (Charlie Hustle). Python scripts to pull MLB Gameday and stats data, build models, predict outcomes, make plays.

Predict what an MLB pitcher will throw next

Pybaseball Database: Using the Pybaseball Python Package to create a historical baseball database for any use.

V3.0 of my MLB Game Outcome Prediction Model

Simple pitch visualization tool that uses StatCast to generate charts for pitcher movement, velocity distribution, and pitch usage.

Early Data & Game Analytics Report — automated Mariners & Rainiers dashboard built with pybaseball, mlb-statsapi, and nightly GitHub Actions.

an end‑to‑end machine‑learning application that recommends the most appropriate reliever to bring into a game given the current game state

Calibrated probability models for MLB game and prop markets

A python application to view baseball statistics and if the player is available in the provided Fantrax league. DISCLAIMER: This a personal project for education and research.

Reverse-engineered MLB The Show 26 rating formulas, with a Flask app that builds cards from real MLB stats. Any player, any season, 1897–2025.

Daily MLB Statcast ingestion pipeline → Snowflake. Powers HR & win prediction models in mlb_py.

Using the Pybaseball-database to create a Points based ranking dashboard

MLB HR & game winner prediction models built on Statcast data. XGBoost/LightGBM with barrel rate, exit velocity, wind, platoon splits, and pitcher matchup features. Daily pipeline with betting edge calculation. AUC: 0.620.