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.
Labelling NBA action using deep learning 🏀
Predicts Daily NBA Games Using a Logistic Regression Model
Using AI to predict the outcomes of NBA games.
Tools to help developers and data scientists in sports
NBA game prediction 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
🔮 Predicting NBA games using statistics (65% accuracy so far)
Analysis of NBA player stats and salaries of the 2016-17 for the 17-18 season
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.
ShotGeek is an open source, NBA statistics and comparison platform built in Django.
A NBA player data explorer web app in Python using the Streamlit library
Machine Learning Technion Course Final Project - NBA Teams Playoffs Qualification
WebScraping NBA's Asian Handicaps and Over/Unders from OddsPortal, to evaluate the accuracy of NBA odds market
NBA Sports Stats and Analytics Application Utilizing the nba_api. Python, Flask, PostgreSQL, psycopg2
Advanced NBA odds tracking, betting analysis, and trivia MCP server for Claude Desktop with line movement detection and AI/ML game simulations
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