An investigation of data-driven player positional roles within the Australian Football League Women's competition using technical skill match-play data

IF 1.5 4区 教育学 Q3 HOSPITALITY, LEISURE, SPORT & TOURISM
Braedan van der Vegt, Adrian Gepp, Justin Keogh, Jessica B. Farley
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Abstract

Understanding player positional roles are important for match-play tactics, player recruitment, talent identification, and development by providing a greater understanding of what each positional role constitutes. Currently, no analysis of competition technical skill data exists by player position in the Australian Football League Women's (AFLW) competition. The primary aim of the research was to use data-driven techniques to observe what positions and roles characterise AFLW match-play using detailed technical skill action data of players. A secondary aim was to comment on the application of clustering methods to achieve more interpretable, reflective positional clustering. A two-stage, unsupervised clustering approach was applied to meet these aims. Data cleaning resulted in 165 variables across 1296 player seasons in the 2019–2022 AFLW seasons which was used for clustering. First-stage clustering found four positions following a common convention (forwards, midfielders, defenders, and rucks). Second-stage clustering found roles within positions, resulting in a further 13 clusters with three forwards, three midfielders, four defenders, and three ruck positional roles. Key variables across all positions and roles included the field location of actions, number of contested possessions, clearances, interceptions, hitouts, inside 50s, and rebound 50s. Unsupervised clustering allowed the discovery of new roles rather than being constrained to pre-defined existing classifications of previous literature. This research assists coaches and practitioners by identifying key game actions players need to perform in match-play by position, which can assist in player recruitment, player development, and identifying appropriate match-play styles and tactics, while also defining new roles and suggestions of how to best use available data.
利用技术比赛数据对澳大利亚女子足球联赛中数据驱动的球员位置角色进行调查
理解球员的位置角色对于比赛战术、球员招募、人才识别和发展都很重要,这可以让我们更好地理解每个位置角色的构成。目前,澳大利亚女子足球联赛(AFLW)比赛中还没有对球员位置的比赛技术数据进行分析。本研究的主要目的是使用数据驱动技术,通过详细的球员技术动作数据来观察AFLW比赛中的位置和角色特征。第二个目的是评论聚类方法的应用,以实现更可解释的,反射的位置聚类。采用两阶段无监督聚类方法来实现这些目标。数据清理产生了2019-2022年AFLW赛季1296个球员赛季的165个变量,用于聚类。第一阶段集群发现了四个位置,遵循一个共同的惯例(前锋、中场、后卫和后卫)。第二阶段的集群在位置上找到了角色,形成了13个集群,其中有3个前锋,3个中场,4个后卫和3个后卫位置角色。所有位置和角色的关键变量包括动作的场地位置、有争议的回合数、解围、拦截、安打、内线50分和篮板50分。无监督聚类允许发现新的角色,而不是局限于先前文献的预定义现有分类。这项研究通过确定球员在比赛中需要采取的关键动作来帮助教练和实践者,这可以帮助球员招募,球员发展,确定合适的比赛风格和战术,同时也定义了新的角色和如何最好地利用现有数据的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.50
自引率
15.80%
发文量
208
期刊介绍: The International Journal of Sports Science & Coaching is a peer-reviewed, international, academic/professional journal, which aims to bridge the gap between coaching and sports science. The journal will integrate theory and practice in sports science, promote critical reflection of coaching practice, and evaluate commonly accepted beliefs about coaching effectiveness and performance enhancement. Open learning systems will be promoted in which: (a) sports science is made accessible to coaches, translating knowledge into working practice; and (b) the challenges faced by coaches are communicated to sports scientists. The vision of the journal is to support the development of a community in which: (i) sports scientists and coaches respect and learn from each other as they assist athletes to acquire skills by training safely and effectively, thereby enhancing their performance, maximizing their enjoyment of the sporting experience and facilitating character development; and (ii) scientific research is embraced in the quest to uncover, understand and develop the processes involved in sports coaching and elite performance.
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