Analyzing performance with the aim of revealing the dynamics and complexity of team sports is largely an unexplored area and will likely lead to new avenues with theoretical and practical implications [28], [29], [30].
Analyzing performance with the aim of revealing the dynamics and complexity of team sports is largely an unexplored area and will likely lead to new avenues with theoretical and practical implications [28], [29], [30]. The integrated use of positional data, for example, may make it possible to develop performance indicators capable of describing and understanding the mechanisms that underlie players’ collective movements [31,32] and to describe their coordination when performing different tasks together, or how their individual and collective behavior adapts to that of their opponents. The practical implications of applying this type of analysis may have an impact, for example, in the assessment of talent in a sports context, with the immediate consequences in the transfer of players between teams. It is public knowledge that each year players are being transferred between clubs for record-breaking fees. Nevertheless, it is especially surprising that the evaluation of talented players relies on very few performance indicators (such as the number of goals scored) and circumstantial, subjective impressions [33], and there is no indication of the existence of performance indicators that consider the way in which players cooperate and/or compete, considering their spatial movements during competitions.