There are 7 repositories under sabermetrics topic.
Pull current and historical baseball statistics using Python (Statcast, Baseball Reference, FanGraphs)
A package written for R focused on baseball analysis. Currently in development.
Prebuilt Docker images with Retrosheet's complete baseball history data for many analytical frameworks. Includes Postgres, cstore_fdw, MySQL, SQLite, Clickhouse, Drill, Parquet, and CSV.
Using Machine Learning, Regression Analysis, Sabermetrics, and the Love of the Game to predict daily projections for MLB players
An open-source college baseball analysis package for Python. Includes functionality for data acquisition and calculation of advanced metrics.
I'm maintaining the original repo now. please go to github.com/jldbc/pybaseball
Download, parse, and wrangle Lahman and Retrosheet data to tidy csv files. Analyze with Python and Pandas in Jupyter notebooks.
JEFFBAGWELL wins above replacement (WAR) and various other metrics for MLB since 1901.
A tool to gather and analyze data from the Baseball Databank maintained by the Chadwick Bureau or the Lahman Database, maintained by Sean Lahman. Provides ETL and analysis tools for sabermetrics and advanced statistics.
Analyzing MLB teams' stats over the past few decades to create a machine-learning model that predicts a team's wins as well as (if not better than) Pythagorean Expectation.
A library of web-scraping software for popular SABRmetrics websites.
(a budding sabermetric tool for research of college teams)
Assignments and some notes for Sabermetrics class in SP18.
An example grader for use with https://github.com/bu-ist/bux-grader-framework
A data visualization tool that is an extension of pybaseball
Slash Line is a fantasy baseball application that incorporates customizable leagues, baseball analytics and current media in one site.
A set of Ansible playbooks for quick provisioning of external graders.
This repository contains a few of the assignments and projects I completed as part of my Sports Analytics course. The final project is titled "Random Forest Model Predicting NFL Comeback at Halftime", which accompanies the Powerpoint containing my interpretation of the model's performance and its usability.
Using Pandas to manipulate various baseball statistics
An analysis on the last 150 years of Major League Baseball and the impact that slugging and hitting percentages of batters are in terms of Sabermetrics and other sports statistics.
Hitting vs Pitching vs Fielding vs Baserunning (Feature Importance)
MLB Team Runs Allowed Prediction Project (Linear Regression)
MLB Team Runs Scored Prediction Project (Linear Regression)
This repository is an applicaiton that can store and fetch pitchers and thrown pitches. It's objective is to provide the basis to evaluate a pitcher's success on the mound or in the pullpen through measured pitching-data.
Exploring how MLB player performance ages with splines and statistics.