An API Client package to access the APIs for NBA.com
Visualization and analysis of NBA player tracking data
#计算机科学#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
NBA play-by-play data from stats.nba.com, data.nba.com, pbpstats.com, and also shots information with season 1996/97
An R package to quickly obtain clean and tidy men's basketball play by play data.
sportsdataverse python package
NodeJS wrapper for the MySportsFeeds Sports Data API
#计算机科学#Using AI to predict the outcomes of NBA games.
Feature requests for the MySportsFeeds Sports Data API.
Tools to help developers and data scientists in sports
Python package for filling in information about players on court in NBA play-by-play data.
NBA API Documentation
Create NBA shot charts using data scrapped from stats.nba.com and R package ggplot2.
This repository contains CSV files containing comprehensive NBA data spanning from the year 2010 to 2024, offering valuable insights into player statistics, team performances, game outcomes, and more.
A sport predictions full-stack application that generates betting recommendations & data on Prize Picks using linear regression.
