Comparing Tactical Analysis Methods in Women's Soccer Using Positioning Data from Electronic Performance and Tracking Systems

Although, in recent years, it has been common to monitor players in team sports using EPTSs (Electronic Performance and Tracking Systems) devices, most of the studies have focused on the optimization of individual performance rather than collective work or tactical analysis. Moreover, almost all these studies focus on men's teams with little focus on women's teams. In this work, data from women's soccer teams at different levels (competition and grassroots) have been collected using both a low-cost personally developed EPTS and a commercial EPTS. With these systems, we have built a dataset consisting of more than 16 million records, paying special attention to spatio-temporal variables collected in the form of geographical coordinates. Different methods have been applied to the collected dataset to solve the problem of determining the position (individual role) of each player on the field based solely on spatio-temporal variables. The methods include algorithms based on clustering, centroid calculation, and computer vision. We have verified the effectiveness of these methods and propose an alternative method based on image recognition algorithms applied to heat maps generated from the position of the players monitored during the matches. As shown in this paper, the validity of the proposed method has been verified, exceeding the performance of existing methods and extending the range of application of these techniques.