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.
Using data analytics and machine learning to create a comprehensive and profitable system for predicting the outcomes of NBA games.
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.
Stattleship R Wrapper
Feature requests for the MySportsFeeds Sports Data API.
Tools to help developers and data scientists in sports
Short, offhand analyses of the NBA
Python package for filling in information about players on court in NBA play-by-play data.
NBA API Documentation
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.
R wrapper functions for the MySportsFeeds Sports Data API
Using machine learning to predict the outcome of NBA games.
NBAShotTracker is a data visualization tool to track player shot performance.
stats.nba.com library 🏀
Displaying team performance against player rotations during NBA games
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