Effects of emphasising opposition and cooperation on collective movement behaviour during football small-sided games

Abstract

Optimizing collective behaviour helps to increase performance in mutual tasks. In team sports settings, the small-sided games (SSG) have been used as key context tools to stress out the players' awareness about their in-game required behaviours. Research has mostly described these behaviours when confronting teams have the same number of players, disregarding the frequent situations of low and high inequality. This study compared the players' positioning dynamics when manipulating the number of opponents and teammates during professional and amateur football SSG. The participants played 4v3, 4v5 and 4v7 games, where one team was confronted with low-superiority, low- and high-inferiority situations, and their opponents with low-, medium- and high-cooperation situations. Positional data were used to calculate effective playing space and distances from each player to team centroid, opponent team centroid and nearest opponent. Outcomes suggested that increasing the number of opponents in professional teams resulted in moderate/large decrease in approximate entropy (ApEn) values to both distance to team and opponent team centroid (i.e., the variables present higher regularity/predictability pattern). In low-cooperation game scenarios, the ApEn in amateurs' tactical variables presented a moderate/large increase. The professional teams presented an increase in the distance to nearest opponent with the increase of the cooperation level. Increasing the number of opponents was effective to overemphasise the need to use local information in the positioning decision-making process from professionals. Conversely, amateur still rely on external informational feedback. Increasing the cooperation promoted more regularity in spatial organisation in amateurs and emphasise their players' local perceptions.

Emergence of Exploratory, Technical and Tactical Behavior in Small-Sided Soccer Games when Manipulating the Number of Teammates and Opponents

“…Nevertheless, extreme difficult scenarios probably will produce the contrary effect, and players would not be able to cope with the situation. These results may also be related to that obtained when studying the positioning dynamics of small-sided games [60], as an increase in the number of teammates seemed to promote regularity in spatial organization in AMA teams, although in PRO teams the variation in players’ irregularity ranged from trivial to small. PRO players probably anticipate better the need to optimize collective decision-making.…”

Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science

“…Sampaio et al (2014) further showed that during an inferiority situation during a 5-a-side small sided game the regularity of the distance to the team centroid increased. Goncalves et al (2016) investigated the influence of numerical imbalances between attacking and defending team in small sided games in professional and amateur players. Player numbers varied between 4 versus 3, 4 versus 5, and 4 versus 7.…”

Exploring match performance of elite tennis players : the multifactorial game-related effects in Grand Slams

“…First of all, results were in agreement with O'Donoghue and Cullinane (2011) The quality of opposition is one of the contextual variables that have been widely considered in team sports to evaluate and explain the performance of interested teams against different level of opponents (Gómez, Silva, Lorenzo, Kreivyte, & Sampaio, 2017;Gómez, Lago, et al, 2013;Gonçalves, Marcelino, Torres-Ronda, Torrents, & Sampaio, 2016;Liu et al, 2016) but there is a paucity of investigation in tennis over this topic (Goossens, Kempeneers, Koning, & Spieksma, 2015;O'Donoghue & Cullinane, 2011;Reid et al, 2010). Gosseens et al (2015) grouped the tennis players into 7 categories according to their world ranking and tried to predict the winning probability of male and female players in Grand Slams; Reid et al (2010) used the match statistics of male tennis player tournament from Association of Tennis ( The results of two-step cluster analysis supported the last statement as well in that not all variables in the stronger correlation group were the same ones in every slam, and some of their strengths of correlation varied from one to another.…”