We will describe how soccer players` dynamic positional match data can be used to assess tactical performance by measuring interplayer synchronization and coordination. The data will be used to calculate overall, sectorial and position-specific centroids and, afterwards, the players` and dyads distances, angles and coupling to these collective attractors will be presented in covariation with several situational variables. Data analysis will be processed with non-linear statistical procedures, such as approximate entropy, to identify the amount of randomness in each time series; and relative phase, to identify different modes of coordination (in-phase, anti-phase and transitions) during the matches dynamics`. The results will be complemented with visual analysis tools to improve the understanding of emergent self-organization behaviours and the dynamic functional constraints at the scale of the environment.
© Copyright 2014 19th Annual Congress of the European College of Sport Science (ECSS), Amsterdam, 2. - 5. July 2014. Published by VU University Amsterdam. All rights reserved.