NBA API Documentation

🏀🤖🏀 AI web app and API to analyze basketball shots and shooting pose on google colab

(Basketball Performance Tracker) 네이버 커넥트재단 AI Tech 5기 최종 프로젝트로 진행한 영상 기반 농구 점수 자동 기록 AI 서비스입니다.

A Mobile App with: 1) An easy & fast to use live-game management system 2) A user side to watch live games, team & player stats and a lot more. Also a Web App to choose your teams and create your own league. The given league is fictional but the teams, names etc. are from teams & players who are part of the Greek Basket League which is run by HEBA.

A set of analytical notebooks on Novo Basquete Brasil (NBB), Brazil's main basketball league

web scrapes performed for Kaggle datasets.

Predicting the outcome of shots based on the events and tracking data available for the 2015/16 season.

Basketball match winner prediction artificial intelligence

A Python package for scraping data from basketball-reference.com and stats.nba.com to provide opponent-adjusted statistics.

CopyMe is a project aimed at optimizing sports performance, using computer vision

Basketlytics is an intelligent web platform for automatic analysis of basketball games from video. It uses YOLO pretrained models and computer vision algorithms to provide advanced statistics, rich visualizations and tactical analysis of the game

Dunk Vision is a desktop basketball shot tracker and data capture tool built using Python and tkinter. Designed for youth coaches, players, and parents, it lets users track, visualize, and analyze shot data to improve individual and team performance as well as direct training efforts. For courtside users, data can be exported for later analysis.

Adjusted Plus Minus Models for WNBA players from the 2019 season. Adjusted Plus Minus (APM) and Regularized Adjusted Plus Minus (RAPM) models were fit providing an all in one player value metric for the WNBA.

Use AI technology to detect and track scoring shots during basketball games

🏀 Website that can calculate information about the trajectory of a basketball, and predict player's salaries.

dotnet webapi for nba stats

A ML application focused on EDA and basketball analytics, showcasing data visualization and insights using Python and relevant libraries.

This project leverages Machine Learning and Computer Vision to detect and analyze basketball shots in real-time. Utilizing the YOLOv8 model and OpenCV, the program processes video streams from live webcams or pre-recorded footage.

An end-to-end data project that scrapes and analyzes 5,900+ NCAA basketball games to map referee travel, build structured datasets, and visualize insights through an R Shiny dashboard. Built entirely without an API using Python and R.