NBA sports betting using machine learning

Visualization and analysis of NBA player tracking data

🏀 An application to build an NBA database backed by MariaDB/MySQL, Postgres compatible databases, or SQLite.

Labelling NBA action using deep learning 🏀

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.

Using AI to predict the outcomes of NBA games.

Tools to help developers and data scientists in sports

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.

Using machine learning to predict the outcome of NBA games.

Stattleship R Wrapper

NBA API Documentation

Python package for filling in information about players on court in NBA play-by-play data.

Feature requests for the MySportsFeeds Sports Data API.

Short, offhand analyses of the NBA

A sport predictions full-stack application that generates betting recommendations & data on Prize Picks using linear regression.

R wrapper functions for the MySportsFeeds Sports Data API

NBAShotTracker is a data visualization tool to track player shot performance.

Displaying team performance against player rotations during NBA games

NBA game prediction model