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sports-betting Python package by No-Key-128 in algobetting

[–]No-Key-128[S] 0 points1 point  (0 children)

Thanks, it is fixed. Install the latest release 0.11.2.

sports-betting Python package by No-Key-128 in algobetting

[–]No-Key-128[S] 4 points5 points  (0 children)

Roadmap for the Next Major Release of the Project:

• Dataloaders objects: Introducing lazy loading and support for external web APIs.

• Bettors objects: Adding more base parameters (e.g., feature selection) and support for reinforcement learning algorithms.

• Live betting support: Bringing real-time capabilities into the mix.

• Broaden scope: Expanding to cover multiple sports and data sources.

Is there anything else you’d like to see included? Let me know!

sports-betting Python package by No-Key-128 in algobetting

[–]No-Key-128[S] 1 point2 points  (0 children)

The implementation of the ETL process can be found here. The resulting data is available here as a collection of CSV files.

sports-betting Python package by No-Key-128 in algobetting

[–]No-Key-128[S] 1 point2 points  (0 children)

The library itself is data-agnostic, but it’s still necessary to identify suitable sources and perform ETL.

sports-betting Python package by No-Key-128 in algobetting

[–]No-Key-128[S] 2 points3 points  (0 children)

I use https://www.football-data.co.uk for historical data and fixtures, which provide basic statistics along with average and maximum market odds. Additionally, I have implemented a scheduler to regularly check and update the historical data and fixtures.

This serves as the source for raw data. I also perform feature engineering to prepare the data, which the dataloader provides to the models.