ISCTE-Instituto Universitário de Lisboa, Lisbon, Portugal.
Universidade Europeia, Laureate International Universities, Lisbon, Portugal.
Sports Med. 2018 Jan;48(1):17-28. doi: 10.1007/s40279-017-0786-z.
The evolution of performance analysis within sports sciences is tied to technology development and practitioner demands. However, how individual and collective patterns self-organize and interact in invasive team sports remains elusive. Social network analysis has been recently proposed to resolve some aspects of this problem, and has proven successful in capturing collective features resulting from the interactions between team members as well as a powerful communication tool. Despite these advances, some fundamental team sports concepts such as an attacking play have not been properly captured by the more common applications of social network analysis to team sports performance. In this article, we propose a novel approach to team sports performance centered on sport concepts, namely that of an attacking play. Network theory and tools including temporal and bipartite or multilayered networks were used to capture this concept. We put forward eight questions directly related to team performance to discuss how common pitfalls in the use of network tools for capturing sports concepts can be avoided. Some answers are advanced in an attempt to be more precise in the description of team dynamics and to uncover other metrics directly applied to sport concepts, such as the structure and dynamics of attacking plays. Finally, we propose that, at this stage of knowledge, it may be advantageous to build up from fundamental sport concepts toward complex network theory and tools, and not the other way around.
运动科学中表现分析的发展与技术的发展和从业者的需求密切相关。然而,个体和集体模式如何自组织和相互作用在具有侵入性的团队运动中仍然难以捉摸。社会网络分析最近被提出以解决这个问题的某些方面,并且已经证明在捕捉团队成员之间的相互作用产生的集体特征以及作为强大的沟通工具方面是成功的。尽管取得了这些进展,但一些基本的团队运动概念,如进攻性比赛,并没有被社会网络分析在团队运动表现中的更常见应用所正确捕捉。在本文中,我们提出了一种基于运动概念的团队运动表现的新方法,即进攻性比赛。网络理论和工具,包括时间和二分或多层网络,被用于捕捉这个概念。我们提出了八个直接与团队表现相关的问题,讨论如何避免在使用网络工具捕捉运动概念时常见的陷阱。一些答案被提出来,试图更准确地描述团队的动态,并揭示其他直接适用于运动概念的指标,例如进攻性比赛的结构和动态。最后,我们提出,在这个知识阶段,从基本的运动概念向复杂的网络理论和工具发展可能是有利的,而不是相反。