An R package to quickly obtain clean and tidy men's basketball play by play data.

Data Extraction (from https://stats.nba.com) and Processing Scripts to Produce the NBA Database on Kaggle (https://kaggle.com/wyattowalsh/basketball)

Historical RAPTOR and other NBA data.

DeepShot is a machine learning model designed to predict NBA game outcomes using advanced team statistics and rolling averages. It combines historical performance trends with contextual game data to deliver highly accurate win predictions (71%)

Learn to build a NBA Fantasy Projection Model in Python with Pandas

I will predict the 2023 NBA Champion using Machine Learning

🏀🗑️ RESTful API about the best league in the world!

Scraper for NBA data

Using decision tree and random forest models, predict the winner of an NBA regular season game

NBA games' prediction

Compare 2 basketball players by reading/comparing NBA stats in an Excel sheet.

A curated list of awesome NBA Data and resources.

Analysis of NBA player stats and salaries of the 2016-17 for the 17-18 season

Machine learning models to predict NBA playoff teams based on regular season performance. Using Python: Sklearn, Joblib, NumPy, Pandas; HTML; CSS; Javascript.

web scrapes performed for Kaggle datasets.

🏀NBA Live data api based on TencentSport , ESPN

NBA Shots visualization