The synergistic interaction between teammates in association football has properties that can be captured by Social Network Analysis (SNA). The analysis of networks formed by team players passing a ball in a match shows that team success is correlated with high network density and clustering coefficient, as well as with reduced network centralization. However, oversimplification needs to be avoided, as network metrics events associated with success should not be considered equally to those that are not. In the present study, we investigated whether network density, clustering coefficient and centralization can predict successful or unsuccessful team performance. We analyzed 12 games of the Group Stage of UEFA Champions League 2015/2016 Group C by using public records from TV broadcasts. Notational analyses were performed to categorize attacking sequences as successful or unsuccessful, and to collect data on the ball-passing networks. The network metrics were then computed. A hierarchical logistic-regression model was used to predict the successfulness of the offensive plays from network density, clustering coefficient and centralization, after controlling for the effect of total passes on successfulness of offensive plays. Results confirmed the independent effect of network metrics. Density, but not clustering coefficient or centralization, was a significant predictor of the successfulness of offensive plays. We found a negative relation between density and successfulness of offensive plays. However, reduced density was associated with a higher number of offensive plays, albeit mostly unsuccessful. Conversely, high density was associated with a lower number of successful offensive plays (SOPs), but also with overall fewer offensive plays and “ball possession losses” before the attacking team entered the finishing zone. Independent SNA of team performance is important to minimize the limitations of oversimplifying effective team synergies.

Serve and serve-reception performance have predicted success in volleyball. Given the impact of serve-reception on the game, we aimed at understanding what it is in the serve and receiver's actions that determines the selection of the type of pass used in serve-reception and its efficacy. Four high-level volleyball players received jump-float serves from four servers in two reception zones—zone 1 and 5. The ball and the receiver's head were tracked with two video cameras, allowing 3D world-coordinates reconstruction. Logistic-regression models were used to predict the type of pass used (overhand or underhand) and serve-reception efficacy (error, out, or effective) from variables related with the serve kinematics and related with the receiver's on-court positioning and movement. Receivers' initial position was different when in zone 1 and 5. This influenced the serve-related variables as well as the type of pass used. Strong predictors of using an underhand rather than overhand pass were higher ball contact of the server, reception in zone 1, receiver's initial position more to the back of the court and backward receiver movement. Receiver's larger longitudinal displacements and an initial position more to the back of the court had a strong relationship with the decreasing of the serve-reception efficacy. Receivers' positioning and movement were the factors with the largest impact on the type of pass used and the efficacy of the reception. Reception zone affected the variance in the ball's kinematics (with the exception of the ball's lateral displacement), as well as in the receivers' positioning (distances from the net and from the target). Also the reception zone was associated with the type of pass used by the receiver but not with reception efficacy. Given volleyball's rotation rule, the receiver needs to master receiving in the different reception zones; he/she needs to adapt to the diverse constraints of each zone to maintain performance efficacy. Thus, being able to flexibly vary positioning and passing, given local (zone) constraints, can yield an advantage in high-level volleyball serve-reception. Further, research needs to consider other serve modes (e.g., power-jump serve) and a full-court context of performance to support the present study's findings.

In a group-serve-reception task, how does serve-reception become effective? We addressed "who" receives/passes the ball, what task-related variables predict action mode selection and whether the action mode selected was associated with reception efficacy. In 182 serve-receptions we tracked the ball and the receivers' heads with two video-cameras to generate 3D world-coordinates reconstructions. We defined receivers' reception-areas based on Voronoi diagrams (VD). Our analyses of the data showed that this approach was accurate in describing "who" receives the serve in 95.05% of the times. To predict action mode selection, we used variables related to: serve kinematics, receiver's movement and on-court positioning, the relation between receiver and his closest partner, and interactions between receiver-ball and receiver-target. Serve's higher initial velocities together with higher maximum height, as well as smaller longitudinal distances between receiver and target increased the chances for the use of the overhand pass. Conversely, decreasing alignment of the receiver with the ball and the target increased the chances of using the underhand-lateral pass. Finally, the use of the underhand-lateral pass was associated with lower quality receptions. Behavioural variability's relevance for serve-reception training is discussed.

Collective behaviors in sports teams emerge from the coordination between players formed from their perception of shared affordances. Recent studies based on the theoretical framework of ecological dynamics reported new analytical tools to capture collective behavior variables that describe team synergies. Here, we introduce a novel hypothesis based on the principles of tensegrity to describe collective behavior. Tensegrity principles operate in the human body at different size scales, from molecular to organism levels, in structures connected physically (biotensegrity). Thus, we propose that a group of individuals connected by information can exhibit synergies based on the same principles (group-tensegrity), and we provide an empirical example based on the dynamics of a volleyball team sub-phase of defense.

How impactful is volleyball's 'serve-reception game'? Its efficacy has been found to discriminate between winning and losing a match. But how does reception become (in)effective? Based on the theoretical rationale of ecological dynamics, we e hypothesized that skilled receivers in volleyball would not display ready-made responses, but rather would co-adapt action modes during serve-reception to deal with the specific, emergent constraints of service to achieve ttask goals. In order to examine this issue we investigated whether the coadaptation of serve and reception action modes was a significant predictor of set outcome in elite volleyball performance (win or loss), analysing the first and last sets of the 2014 World League Finals matches (897 game-sequences). The power-jump and jump-float were the serving modes observed and the overhand, underhand-lateral and underhand-frontal passes were the reception modes categorized. We found that the coadaptation of serve and reception action modes predicted set outcome in the final set of a match. Receiving the jump-float serve with an overhand pass or underhand-lateral pass increased the odds of winning the final set by 200 per cent. Results suggested that, at an expert level, mastering the overhand pass and the underhandlateral pass gives teams a competitive edge. Receivers showing flexibility in action mode selection improved a team's odds of successfully winning the final set of a match.