Understanding gender differences in professional European football through Machine Learning interpretability and match actions data.
This repository contains the completed version of codes for the paper "Understanding gender differences in professional European football through Machine Learning interpretability and match actions data" by Marc Garnica Caparrós and Daniel Memmert.
Install the required python packages
pip install -r requirements.txt
To handle heterogeneity and performance efficiently, we use PySpark from Apache Spark. PySpark enables an end-user API for Spark jobs. You might want to check how to set up a local or remote Spark cluster in their documentation.
This repository is organized as follows:
- Preprocessed data from the two different data streams is collecting in the data folder. For the Opta files, it contains the event-based metrics computed from each match of the 2017 Women's Championship and a single file calculating the event-based metrics from the 2016 Men's Championship published here. Even though we cannot publish the original data source, the two python scripts implemented to homogenize and integrate both data streams into event-based metrics are included in the data gathering folder folder contains the graphical images and media used for the report.
- The data cleaning folder contains descriptor scripts for both data streams and the final integration
- Classification contains all the Jupyter notebooks for each model present in the experiment as well as some persistent models for testing.
@article{garnicacaparros2021gender,
title={Understanding gender differences in professional European football through Machine Learning interpretability and match actions data},
author={Garnica-Caparrós, Marc and Memmert, Daniel},
journal={Scientific reports},
publisher={Nature Publishing Group}
}
This paper can be accessed on : "Understanding gender differences in professional European football through Machine Learning interpretability and match actions data".
Please email to m.garnica@dshs-koeln.de should you have any questions, comments or suggestions.