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NBA Sports Betting Using Machine Learning 🏀

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.

Packages Used

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

Usage

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 -xgb

Enter under/over and odds for today's games.

Contributing

All contributions welcomed and encouraged.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].

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kyleskom / NBA-Machine-Learning-Sports-Betting

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NBA Sports Betting Using Machine Learning 🏀

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