New Indicator for Centrality Measurements in Passing-network Analysis of Soccer

Masatoshi Kanbata, Ryohei Orihara, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga

Abstract

A number of fields including business, science, and sports, make use of data analytics. The evaluation of players and teams affect how tactics, training, and scouting are conducted in soccer teams. Data such as the number of shots and goals in match results are often used to evaluate players and teams. However, this is not enough to fully understand the potential of the players and teams. In this paper, we describe a new analysis method using passing-distribution data from soccer games. To evaluate the performance of players and teams, we applied graph mining. We also used an index called centrality, which evaluates individual contributions with an organization. In this research, we propose a new centrality model to improve existing conventional models. In the calculating the centrality of a given player pair, we consider not only the shortest sequence of passing but also longer ones. In this research, we verified the significance of these indicators by applying the data of UEFA EURO 2008, 2012, and 2016. As a result, we found our method to be more consistent with game results than conventional methods.

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Paper Citation


in Harvard Style

Kanbata M., Orihara R., Sei Y., Tahara Y. and Ohsuga A. (2019). New Indicator for Centrality Measurements in Passing-network Analysis of Soccer.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 616-623. DOI: 10.5220/0007377506160623


in Bibtex Style

@conference{icaart19,
author={Masatoshi Kanbata and Ryohei Orihara and Yuichi Sei and Yasuyuki Tahara and Akihiko Ohsuga},
title={New Indicator for Centrality Measurements in Passing-network Analysis of Soccer},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={616-623},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007377506160623},
isbn={978-989-758-350-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - New Indicator for Centrality Measurements in Passing-network Analysis of Soccer
SN - 978-989-758-350-6
AU - Kanbata M.
AU - Orihara R.
AU - Sei Y.
AU - Tahara Y.
AU - Ohsuga A.
PY - 2019
SP - 616
EP - 623
DO - 10.5220/0007377506160623