NBA sports betting using machine learning

Visualization and analysis of NBA player tracking data

Labelling NBA action using deep learning 🏀

Predicts Daily NBA Games Using a Logistic Regression Model

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

Using AI to predict the outcomes of NBA games.

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

🔮 Predicting NBA games using statistics (65% accuracy so far)

The NBA Statistics Dashboard is an innovative and user-focused project that harnesses daily data scraping to create a dynamic platform for sports bettors, NBA enthusiasts, and fantasy league participants.

A NBA player data explorer web app in Python using the Streamlit library

WebScraping NBA's Asian Handicaps and Over/Unders from OddsPortal, to evaluate the accuracy of NBA odds market

Machine Learning Technion Course Final Project - NBA Teams Playoffs Qualification

Predicting NBA regular season standings for the 2024-2025 season

Provides overview of in-game stats from parsed play-by-play stats from SportRadar

A machine learning project that applies a Decision Tree Classifier to predict NBA player inductions into the Hall of Fame. Using historical player statistics and performance metrics, the model provides an insightful evaluation of which factors contribute most significantly to a player's likelihood of reaching hof status.

Uses SportsVU Optical Tracking Data to check if screens occur in a play

Developed models used NBA play-by-play data to determine the value and effectiveness of late game timeouts.