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Original Source: The Quant's Playbook

This system stores the data in MySQL databases and the models in Colab notebooks. If you don’t have experience in setting these up, it is highly recommend visiting: Machine Learning for Sports Betting: MLB Edition, where we walk through the entire process with a similar workflow, going from data all the way to production.

The workflow for this algorithm is as follows:

  1. Register for a prop-odds API key

  2. Run the “mlb-runline-dataset-builder.py” file

    • This builds the original dataset and takes about 15-30 minutes

  3. Run the “mlb-runline-daily.py” file

    • This is the dataset that will be used to get the predictions for the games of that day.

  4. In Google Colab, run the “MLB_Runline_Training.ipynb” file

    • This file is responsible for comparing and training the dozens of available models. It isn't necessary to make any changes to the model, but you have the freedom to experiment.

    • Running the file will create a .pkl file containing the model of your choice, be sure to upload this to your drive.

  5. In Google Colab, run the “MLB_Runline_Production.ipynb" file

    • This file will deploy the model you saved and generate predictions and theoretical odds.

  6. In order to update new, future data points without having to re-build the entire dataset, run the “mlb-runline-dataset-production.py” in lieu of the “mlb-runline-dataset-builder.py”.

  7. To start tracking predictions before going live, visit the action network.

  8. Finally, you're all set! 😄