Abstract
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.
Highlights
The evolution of performance analysis (PA) as a sub-discipline of sports sciences has seen significant advances in team sports
We reviewed how PA emerged as a sub-discipline of sports sciences by building on notational analysis and biomechanics approaches and with further contributions from dynamical systems theory (DST)
We discussed what new directions, tools and potential methods network theory and complex networks can further contribute to PA
Summary
The evolution of performance analysis (PA) as a sub-discipline of sports sciences has seen significant advances in team sports. Dynamic relations in team sports games have other basic dimensions, in addition to passes, that have not yet been fully captured in sports settings: i) relational space (i.e. interactions considered in a geographical space); ii) their time structure (i.e., rate change, order or sequence, or simultaneity of interactions); and iii) their relations with types of nodes (i.e. colleagues or adversaries), meaning cooperation or competition interactions [18], as we discuss This is a possible approach for handling complex adaptive systems including team sports analyses in competition. This means aggregating all the passes between players in a single directed network for which measures are taken and related to success indicators (e.g. reaching a competition stage, goals scored) [12, 14, 15, 19]. The outcomes of these dynamic interactions are naturally represented by different layers in bipartite networks
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