Strictness vs. flexibility: Simulation-based recognition of strategies and its success in soccer
Author:
Perl J.1, Imkamp J.2, Memmert D.2
Affiliation:
1. University of Mainz , Mainz , Germany 2. German University of Sport Science , Cologne , Germany
Abstract
Abstract
Introduction: Recognition and optimization of strategies in sport games is difficult in particular in case of team games, where a number of players are acting “independently” of each other. One way to improve the situation is to cluster the teams into a small number of tactical groups and to analyze the interaction of those groups. The aim of the study is the evaluation of the applicability of SOCCER© simulation in professional soccer by analyzing and simulation of the tactical group interaction.
Methods: The players’ positions of tactical groups in soccer can be mapped to formation-patterns and then reflect strategic behaviour and interaction. Based on this information, Monte Carlo-Simulation allows for generating strategies, which – at least from the mathematical point of view – are optimal. In practice, behaviour can be orientated in those optimal strategies but normally is changing depending on the opponent team’s activities. Analyzing the game under the aspect of such simulated strategies revealed how strictly resp. flexible a team follows resp. varies strategic patterns.
Approach: A Simulation- and Validation-Study on the basis of 40 position data sets of the 2014/15 German Bundesliga has been conducted to analyze and to optimize such strategic team behaviour in professional soccer.
Results: The Validation-Study demonstrated the applicability of our tactical model. The results of the Simulation-Study revealed that offensive player groups need less tactical strictness in order to gain successful ball possession whereas defensive player groups need tactical strictness to do so.
Conclusion: The strategic behaviour could be recognized and served as basis for optimization analysis: offensive players should play with a more flexible tactical orientation to stay in possession of the ball, whereas defensive players should play with a more planned orientation in order to be successful. The strategic behaviour of tactical groups can be recognized and optimized using Monte Carlo-based analysis, proposing a new and innovative approach to quantify tactical performance in soccer.
Publisher
Walter de Gruyter GmbH
Subject
Biomedical Engineering,General Computer Science
Reference22 articles.
1. Brefeld, U., Lasek, J., & Mair, S. (2018). Probalistic movement models and zones of control. In P. Lopes, W. Dubitzky, D. Berrar, & J. Davis, Machine Learning. Springer 2. Casal, C. A., Maneiro, R., Ardá, T., Marí, F. J., & Losada, J. L. (2017). Possession zone as a performance indicator in football. The game of the best teams. Frontiers in Psychology, 8, 1–11. https://doi.org/10.3389/fpsyg.2017.01176 3. Collet, C. (2012). The Possession Game? A Comparative Analysis of Ball Retention and Team Success in European and International Football, 2007-2010. Journal of Sports Science, 31, 123-136. 4. Duarte, R., Araújo, D., Davids, K., Travassos, B., Gazimba, V., & Sampaio, J. (2012). Interpersonal coordination tendencies shape 1-vs-1 sub-phase performance outcomes in youth soccer. Journal of Sports Sciences, 30(9), 871-877. 5. Kempe, M.; Vogelbein, M., Memmert, D., &, Nopp, S. (2014). Possession vs. Direct Play: Evaluating Tactical Behavior in Elite Soccer. International Journal of Sports Science. 4(6A), 35–41.
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