Comportamento tático coletivo em Pequenos Jogos no Futebol: influência de jogadores adicionais

Abstract

-The aim of this study was to compare the collective tactical behavior between numerically balanced and unbalanced small-sided soccer games. Eighteen male soccer players (mean age 16.4 years) participated in the study. Polar coordinate analysis was performed using positional data obtained with a 15-Hz GPS device. Collective variables including length, width, centroid distance (average point between teammates), and length per width ratio (LPWratio) were collected. Data were analyzed using Friedman's test. The results showed greater length and width values in 4vs.3 games, while a higher LPWratio was observed in 3vs.3+2 games compared to the other configurations. In games with an additional player (4vs.3), ball circulation and the increase in effective game space were alternatives to overcome the more concentrated defensive systems near the goal. On the other hand, 3vs.3+2 games allowed more actions in the length axis and a fast reach of the opponent's goal.

Effect of Game Format on the Intensity of Soccer Training

“…Therefore, it is important to emphasize that besides the rules, the team's game model and the configuration of the games directly influence the movement of players during training and official matches. 29,30 The rules laid down by the technical commission should not be drawn merely to obtain the physical results, but also in the development of technical aspects and operational or tactical principles. 23 They must be designed according to the game model desired by the coach.…”

Reliability of spatial-temporal metrics used to assess collective behaviours in football: an in-silico experiment

“…Statistical analyses are then frequently performed by comparing samples across independent variables that may indicate expertise such as age (Olthof et al 2015;Barnabé et al 2016;Aquino et al 2016a;Menuchi et al 2018). The most common metrics analysed using this approach include those describing behaviour at the team level such as team centroid (Frencken et al 2011;Moura et al 2012;Barnabé et al 2016;Castellano et al 2016;Praça et al 2016;Olthof et al 2019), surface area (Baptista et al, 2020;Frencken et al 2011Frencken et al , 2013Travassos et al 2014;Aquino et al 2016b;Castellano et al 2017) and stretch index (Bartlett et al 2012;Frias 2014;Silva et al 2014a;Olthof et al 2019). Alternative approaches have included calculation of samples across discrete sequences within games such as attacks.…”