A multilevel hypernetworks approach to capture properties of team synergies at higher complexity levels.

RIBEIRO, João, SILVA, Pedro, DAVIDS, Keith, ARAÚJO, Duarte, RAMOS, João, J LOPES, Rui and GARGANTA, Júlio (2020). A multilevel hypernetworks approach to capture properties of team synergies at higher complexity levels. European Journal of Sport Science, 1-11.

[img]
Preview
PDF
Davids_A_Multilevel_Hypernetworks(AM).pdf - Accepted Version
All rights reserved.

Download (262kB) | Preview
Official URL: https://www.tandfonline.com/doi/full/10.1080/17461...
Link to published version:: https://doi.org/10.1080/17461391.2020.1718214

Abstract

Previous work has sought to explain team coordination using insights from theories of synergy formation in collective systems. Under this theoretical rationale, players are conceptualised as independent degrees of freedom, whose interactions can become coupled to produce team synergies, guided by shared affordances. Previous conceptualisation from this perspective has identified key properties of synergies, the measurement of which can reveal important aspects of team dynamics. However, some team properties have been measured through implementation of a variety of methods, while others have only been loosely addressed. Here, we show how multilevel hypernetworks comprise an innovative methodological framework that can successfully capture key properties of synergies, clarifying conceptual issues concerning team collective behaviours based on team synergy formation. Therefore, this study investigated whether different synergy properties could be operationally related utilising hypernetworks. Thus, we constructed a multilevel model composed of three levels of analysis. Level N captured changes in tactical configurations of teams during competitive performance. While Team A changed from an initial 1-4-3-3 to a 1-4-4-2 tactical configuration, Team B altered the dynamics of the midfielders. At Level N + 1, the 2 vs. 1 (1 vs. 2) and 1 vs. 1 were the most frequently emerging simplices, both behind and ahead of the ball line for both competing teams. Level N + 2 allowed us to identify the prominent players (a6, a8, a12, a13) and their interactions, within and between simplices, before a goal was scored. These findings showed that different synergy properties can be assessed through hypernetworks, which can provide a coherent theoretical understanding of competitive team performance.

Item Type: Article
Uncontrolled Keywords: Multilevel hypernetworks; association football; dynamics; performance analysis; team collective behaviour; team synergies; 1106 Human Movement and Sports Sciences; 0913 Mechanical Engineering; Sport Sciences
Identification Number: https://doi.org/10.1080/17461391.2020.1718214
Page Range: 1-11
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 18 Feb 2020 15:58
Last Modified: 17 Mar 2021 15:32
URI: https://shura.shu.ac.uk/id/eprint/25820

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics