{"title":"Strictness vs. flexibility: Simulation-based recognition of strategies and its success in soccer","authors":"J. Perl, Jonas Imkamp, D. Memmert","doi":"10.2478/ijcss-2021-0003","DOIUrl":null,"url":null,"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.","PeriodicalId":38466,"journal":{"name":"International Journal of Computer Science in Sport","volume":"20 1","pages":"43 - 54"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Science in Sport","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/ijcss-2021-0003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
严格性与灵活性:基于模拟的策略识别及其在足球中的成功
摘要简介:体育游戏中策略的识别和优化很困难,尤其是在团队游戏中,许多玩家彼此“独立”行动。改善这种情况的一种方法是将团队分成少数战术小组,并分析这些小组的互动。本研究的目的是通过对战术小组互动的分析和模拟,评估足球模拟在职业足球中的适用性。方法:足球战术组球员的位置可以映射到队形模式,然后反映策略行为和互动。基于这些信息,蒙特卡罗模拟允许生成策略,至少从数学角度来看,这些策略是最优的。在实践中,行为可以以这些最佳策略为导向,但通常会根据对手团队的活动而变化。在这种模拟策略的层面上分析游戏揭示了如何严格地应对。灵活的团队分别遵循。不同的战略模式。方法:基于2014/15赛季德甲联赛的40个位置数据集进行了模拟和验证研究,以分析和优化职业足球中的这种战略团队行为。结果:验证研究证明了我们的战术模型的适用性。模拟研究的结果表明,进攻球员组需要较少的战术严格性才能成功控球,而防守球员组则需要战术严格性。结论:战略行为可以被识别并作为优化分析的基础:进攻球员应该以更灵活的战术取向打球以保持控球权,而防守球员应该以更有计划的取向打球以取得成功。战术小组的战略行为可以通过基于蒙特卡洛的分析来识别和优化,从而提出了一种新的、创新的方法来量化足球战术表现。
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