NBA sports betting using machine learning

Visualization and analysis of NBA player tracking data

Labelling NBA action using deep learning 🏀

Using data analytics and machine learning to create a comprehensive and profitable system for predicting the outcomes of NBA games.

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.

Stattleship R Wrapper

Feature requests for the MySportsFeeds Sports Data API.

Short, offhand analyses of the NBA

R wrapper functions for the MySportsFeeds Sports Data API

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

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

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.

stats.nba.com library 🏀

Displaying team performance against player rotations during NBA games

Being able to perform gameplay analysis of NBA players, NBA Predictive Analytics is a basketball coach's new best friend.

Interactive exploration of NBA roster turnover

NBA game prediction model

本项目综合运用d3、echarts来完成可视化工作，实现了对nba两场比赛的可视化数据分析，包括球员运动轨迹、个人数据、传球次数以及得分位置等多种可交互式图表。通过可视化方法，我们能够进一步深入分析球队的具体情况，便于制定更佳的战术。

Scraper for NBA data