- Basketball Reference Crawler: Uses Wikipedia to statistics for every player for a given set of seasons. The granularity is per match.
- Deep Learning for predicting shot hit/miss: Applies Deep Learning methods to build a model that prevents if a shot will be successful or not based on its trajectory. Another repo that implements this is this one and this one
- Basketball-Analytics: Uses basketball-reference to get information on players and teams
- Machine-March-Madness: Deep learning model to predict March Madness outcomes
- basketball: Uses basketball-reference to build a NBA database that can be used for analytics
- Basketball Line-up Analyzer: Gets XML files as input and finds the most efficient combinations of players / lineups
- Basketball League Manager: Django app to manage a basketball league
- basketballdatabase: Parses basketball-reference and collects data
- NBA Player Movements: Visualizes NBA games based on raw logs from SportsVU
- NBA-STATS: Uses the NBA Player Movements repo and tries to build on that and do some analysis in order to identify the player actions
- basketballcrawler: Python module that scrapes basketball-reference
- nba: Uses NBA Stats API to retrieve data
- nba.js: Uses data.nba.net and stats.nba.com to retrieve data
- Basketball Data: Basketball data in XML format
- nba: Scripts that scrape and analyze basketball data
- Basketball GM: Web-based basketball GM game
@TODO