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sports-betting

sports-betting is a tool that makes it easy to create machine learning based models for sports betting and evaluate their performance. It is compatible with scikit-learn.

Documentation

Installation documentation, API documentation, and examples can be found on the documentation.

Dependencies

sports-betting is tested to work under Python 3.6+. The dependencies are the following:

• numpy(>=1.1)
• scikit-learn(>=0.21)

Additionally, to run the examples, you need matplotlib(>=2.0.0) and pandas(>=0.22).

Installation

sports-betting is currently available on the PyPi's repository and you can install it via pip:

pip install -U sports-betting

The package is released also in Anaconda Cloud platform:

conda install -c algowit sports-betting

If you prefer, you can clone it and run the setup.py file. Use the following commands to get a copy from GitHub and install all dependencies:

git clone https://github.com/AlgoWit/sports-betting.git
cd sports-betting
pip install .

Or install using pip and GitHub:

pip install -U git+https://github.com/AlgoWit/sports-betting.git

Testing

After installation, you can use pytest to run the test suite:

make test