An API Client package to access the APIs for NBA.com
Visualization and analysis of NBA player tracking data
Using data analytics and machine learning to create a comprehensive and profitable system for predicting the outcomes of NBA games.
Repository which contains various scripts and work with various basketball statistics
Predicts Daily NBA Games Using a Logistic Regression Model
An R package to quickly obtain clean and tidy men's basketball play by play data.
sportsdataverse python package
Python wrapper for the MySportsFeeds Sports Data API
NodeJS wrapper for the MySportsFeeds Sports Data API
Stattleship R Wrapper
Feature requests for the MySportsFeeds Sports Data API.
Short, offhand analyses of the NBA
Create NBA shot charts using data scrapped from stats.nba.com and R package ggplot2.
🏀 JavaScript Client for stats from NBA.com
Hover on an NBA player's name on any web page to quickly view their career stats. Thousands of active users across Chrome, Firefox, Opera, and Edge.
R wrapper functions for the MySportsFeeds Sports Data API
A sport predictions full-stack application that generates betting recommendations & data on Prize Picks using linear regression.
2017 Example NBA basketball website using nba_py for people to learn how to use NBA Stats Python API.
Python package for filling in information about players on court in NBA play-by-play data.
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