statcast

Pull current and historical baseball statistics using Python (Statcast, Baseball Reference, FanGraphs)

A package written for R focused on baseball analysis. Currently in development.

MCP server for advanced baseball analytics (statcast, fangraphs, baseball reference, mlb stats API)

A Python application and library that generates comprehensive advanced stat summary sheets for MLB players, customizable by year, providing in-depth analysis and visualizations. It can also be used as a library module, enabling users to develop their own features and extend functionality for custom applications and data processing needs.

A Discord bot that integrates with the MLB API to allow servers to follow the team of their choice. Currently supporting the unofficial Discord server for the Cleveland Guardians.

Go Wrapper for MLB StatsAPI

A data visualization tool that is an extension of pybaseball

Small client used to retrieve statcast data from Baseball Savant.

NineLens is an open-source baseball intelligence platform combining schedules, rosters, player profiles, box scores, season stats, and Statcast data into searchable player and team profiles, leaderboards, trends, benchmarks, game analysis, situational insights, and side-by-side comparisons—built for deeper research and better baseball decisions.

Query MLB Statcast data using plain English through an MCP server that connects AI assistants to Baseball Savant, FanGraphs, and Baseball Reference.

Python package: matplotlib baseball field, Statcast spray charts and strike-zone plots

Python tools for baseball data from Statcast, the MLB Stats API, FanGraphs, Baseball-Reference, Retrosheet, and the Lahman Database.

Python package: Baseball Savant leaderboards with date ranges and season checks (bat tracking, ABS challenges, minors)

Predicting MLB hit probability from 2026 Statcast data with random forests and neural networks.

XGBoost win probability model for MLB games, with WPA, Leverage Index, and a benchmark against classical sabermetrics. Live dashboard with pitch-by-pitch game replay.

Chase+ measures the run value of a hitter's chase decisions by comparing swing outcomes with the estimated value of taking. It adjusts for count, distance outside the zone, and the pitches each hitter was shown, and is scaled so 100 is league average each season.

R Shiny App displaying visualization and trackman metrics for baseball players. (The app was made for the CWL Players and Scouts)

ML model predicting an MLB pitcher's next pitch type from game state and sequence history, comparing logistic regression, random forest, and HistGradientBoosting.

A Python baseball project for rating MLB players and teams and using those ratings to predict games. Starting with pitchers, then adding batters and team ratings.

⚾ Herramienta profesional para analizar probabilidades de bateo de jugadores de MLB con predicciones basadas en datos de Statcast