Evaluating the effectiveness of different network flow motifs in association football

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS
Else Marie Håland, Astrid Salte Wiig, L. M. Hvattum, M. Stålhane
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引用次数: 3

Abstract

Abstract In association football, a network flow motif describes how distinct players from a team are involved in a passing sequence. The flow motif encodes whether the same players appear several times in a passing sequence, and in which order the players make passes. This information has previously been used to classify the passing style of different teams. In this work, flow motifs are analyzed in terms of their effectiveness in terms of generating shots. Data from four seasons of the Norwegian top division are analyzed, using flow motifs representing subsequences of three passes. The analysis is performed with a generalized additive model (GAM), with a range of explanatory variables included. Findings include that motifs with fewer distinct players are less effective, and that motifs are more likely to lead to shots if the passes in the motif utilize a bigger area of the pitch.
评价不同网络流动机在足协足球运动中的有效性
在英式足球中,网络流基序描述了球队中不同球员在传球序列中的表现。流母题编码相同的玩家是否在一个传递序列中出现多次,以及玩家的传递顺序。这些信息以前被用来对不同球队的传球风格进行分类。在这项工作中,流母题分析了它们在生成镜头方面的有效性。来自挪威顶级联赛的四个赛季的数据进行了分析,使用流图案表示三个通道的子序列。分析是用广义加性模型(GAM)进行的,其中包括一系列解释变量。研究结果包括,球员特征较少的主题更不有效,如果主题中的传球利用了更大的球场面积,那么主题更有可能导致射门。
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来源期刊
Journal of Quantitative Analysis in Sports
Journal of Quantitative Analysis in Sports SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
2.00
自引率
12.50%
发文量
15
期刊介绍: The Journal of Quantitative Analysis in Sports (JQAS), an official journal of the American Statistical Association, publishes timely, high-quality peer-reviewed research on the quantitative aspects of professional and amateur sports, including collegiate and Olympic competition. The scope of application reflects the increasing demand for novel methods to analyze and understand data in the growing field of sports analytics. Articles come from a wide variety of sports and diverse perspectives, and address topics such as game outcome models, measurement and evaluation of player performance, tournament structure, analysis of rules and adjudication, within-game strategy, analysis of sporting technologies, and player and team ranking methods. JQAS seeks to publish manuscripts that demonstrate original ways of approaching problems, develop cutting edge methods, and apply innovative thinking to solve difficult challenges in sports contexts. JQAS brings together researchers from various disciplines, including statistics, operations research, machine learning, scientific computing, econometrics, and sports management.
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