A machine learning and explainability-driven methodology for identifying winning strategies in Rugby Union

Interest in predicting sports match outcomes has grown significantly, driven by advancements in machine learning techniques and widespread adoption. However, the utilization of these predictive models in enhancing tactical team performance remains relatively limited. We propose a methodology that co...

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Veröffentlicht in:	Decision analytics journal Jg. 15; S. 100568
Hauptverfasser:	Odet, Arnaud, Bechard, Thomas, Moretto, Pierre, Dejean, Sebastien, Pasquaretta, Cristian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.06.2025 Elsevier
Schlagworte:	Cognitive science Engineering Sciences Explainable artificial intelligence Life Sciences Machine learning Match prediction Performance analytics Physics Team evaluation Performance analytics Explainable artificial intelligence Match prediction Team evaluation Machine learning
ISSN:	2772-6622, 2772-6622
Online-Zugang:	Volltext
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