A machine learning AI used to predict the winners and under/overs of NBA games. Takes all team data from the 2007-08 season to current season, matched with odds of those games, using a neural network to predict winning bets for today's games. Achieves ~75% accuracy on money lines and ~58% on under/overs. Outputs expected value for teams money lines to provide better insight.
Use Python 3.8. In particular the packages/libraries used are...
- Tensorflow - Machine learning library
- XGBoost - Gradient boosting framework
- Numpy - Package for scientific computing in Python
- Pandas - Data manipulation and analysis
- Colorama - Color text output
- Tqdm - Progress bars
- Requests - Http library
- Scikit_learn - Machine learning library
Make sure all packages above are installed.
$ git clone https://github.com/kyleskom/NBA-Machine-Learning-Sports-Betting.git
$ cd NBA-Machine-Learning-Sports-Betting
$ pip3 install -r requirements.txt
$ python3 main.py -xgbEnter under/over and odds for today's games.
All contributions welcomed and encouraged.