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A Semi-Supervised Machine Learning Approach to Define Pressing Roles in Football Cover

A Semi-Supervised Machine Learning Approach to Define Pressing Roles in Football

International Journal of Computer Science in Sport
Volume 24 (2025): Issue 2 (June 2025)
By: Andrew Peters,  Nimai Parmar,  Michael Davies and  Nic James  
Open Access
|Dec 2025

Authors

Andrew Peters

Faculty of Science & Technology, Middlesex University, London, England

Nimai Parmar

Faculty of Science & Technology, Middlesex University, London, England

Michael Davies

Faculty of Science & Technology, Middlesex University, London, England

Nic James

Faculty of Science & Technology, Middlesex University, London, England
DOI: https://doi.org/10.2478/ijcss-2025-0013 | Journal eISSN: 1684-4769
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Language: English
Page range: 62 - 79
Published on: Dec 25, 2025
Published by: International Association of Computer Science in Sport
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
Pressing,
Dimensionality Reduction,
Player Role,
Umap
Related subjects:
Computer sciences,
Databases and data mining,
Computer sciences, other,
Sports and recreation,
Physical education,
Sports and recreation, other

© 2025 Andrew Peters, Nimai Parmar, Michael Davies, Nic James, published by International Association of Computer Science in Sport
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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