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Authors: Hugo Muacho 1 ; Ricardo Ribeiro 2 ; 1 and Rui J. Lopes 1 ; 3

Affiliations: 1 Iscte - Instituto Universitário de Lisboa, Portugal ; 2 INESC-ID Lisboa, Portugal ; 3 Instituto de Telecomunicações, Lisboa, Portugal

Keyword(s): Machine Learning, Decision Trees, Soccer, Performance Analysis, Pass Success.

Abstract: Machine learning has in recent years been increasingly used in the soccer realm. This paper focuses on investigating the factors influencing pass success, a chief element in team performance. Decision tree techniques are used aiming to identify which features are the most important in pass success. This process is applied to a data set of 13 matches of the men’s French “Ligue 1”. Two experiments are conducted using different feature sets: one containing the positional data and Voronoi area off all players, the second considering only the ball carrier and closest teammates and opponents. The results obtained with the first feature set indicate that the relative importance of features is match dependent and somehow related to teams’ formation and players’ tactical mission. The second feature set, being more directly related to the passing process, provided a more consistent ranking of features. Features related to the interaction with the opponent standout. Low precision and recall val ues show that the features and factors leading to pass success are in fact elusive. (More)

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Paper citation in several formats:
Muacho, H.; Ribeiro, R. and Lopes, R. (2022). The Elusive Features of Success in Soccer Passes: A Machine Learning Perspective. In Proceedings of the 10th International Conference on Sport Sciences Research and Technology Support - icSPORTS; ISBN Not Available; ISSN 2184-3201, SciTePress, pages 110-116. DOI: 10.5220/0011541700003321

@conference{icsports22,
author={Hugo Muacho. and Ricardo Ribeiro. and Rui J. Lopes.},
title={The Elusive Features of Success in Soccer Passes: A Machine Learning Perspective},
booktitle={Proceedings of the 10th International Conference on Sport Sciences Research and Technology Support - icSPORTS},
year={2022},
pages={110-116},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011541700003321},
isbn={Not Available},
issn={2184-3201},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Sport Sciences Research and Technology Support - icSPORTS
TI - The Elusive Features of Success in Soccer Passes: A Machine Learning Perspective
SN - Not Available
IS - 2184-3201
AU - Muacho, H.
AU - Ribeiro, R.
AU - Lopes, R.
PY - 2022
SP - 110
EP - 116
DO - 10.5220/0011541700003321
PB - SciTePress

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