A Python API to retrieve and read MLB GameDay data

An open-source college baseball analysis package for Python. Includes functionality for data acquisition and calculation of advanced metrics.

Python Baseball Data and Analysis

Public Repository for Baseball Prospectus

MLB Data Explorer

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

Download, parse, and wrangle Lahman and Retrosheet data to tidy csv files. Analyze with Python and Pandas in Jupyter notebooks.

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.

The repo for www.mlbtradetrees.com. Analyze any trade in baseball history!

Unofficial .NET SDK for the MLB Stats API.

Predicting MLB player salaries and team wins with machine learning regression models.

machine learning models for predictions on baseball data

Data Science Projects done at Data Trained Education during PG Data Science & ML Course

Identify the name of a pitch being thrown using a machine learning model.

AWS-hosted program to collect and prepare a database of MLB games to be used to build a machine learning model for predicting what team will win a game.

This project provides the formulas to calculate multiple advanced baseball statistics like wOBA, wRAA, wRC, ISO, BABIP, FIP, WHIP. It also provides an application that allows the user to interact with the data by selecting multiple players to compare their stats.

R package for importing historical baseball data from Retrosheet

Baseball pitch sequence prediction using 7 ML models (LSTM, Transformer, CNN, HMM, Random Forest, Logistic Regression, AutoGluon) with synthetic data generation, k-fold benchmarking, ablation studies, and MLflow tracking.