Developing Performance in Sports Teams Through a Collective Homeostasis Model Supports Regulation, Adaptation, and Evolution in Competition

The collective homeostasis model, grounded in ecological dynamics, has recently been proposed to explain the self-regulating individual-environment interactions that are necessary to conceptualizing sports teams as collective homeostatic systems. Based on these insights and given the capacity of humans to construct and adapt their ecological niches, this article explores the creation of enriching sporting contexts for the development of adaptive player-environment interactions in competitive team sports. This model of adaptation emphasizes the importance of creating a sports niche rich in shared affordances to enable team coordination through the development of individual and collective homeostasis in different sub-phases of competitive performance. In a homeostatic sports system, principles of play advocated by coaches allow players to intentionally coordinate and adapt their actions to shape the collective identity of the team. The team’s identity is shaped by the synergetic development of collective attractors (stable system states) emerging at specific scales of complexity. This is facilitated through the manipulation of constraints by the coaching and support staff. These ideas have important implications for implementing team sports training and performance preparation, helping to transform the self-regulating tendencies of players through adapting their behaviors to dynamic performance contexts.

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Publication Details

Journal
Adaptive Behavior
Published
2024-12-24
DOI
https://doi.org/10.1177/10597123241309980
Citations
3
Primary Topic
Sport Psychology and Performance
Type
article
Field-Weighted Citation Impact
2.37
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article

Developing Performance in Sports Teams Through a Collective Homeostasis Model Supports Regulation, Adaptation, and Evolution in Competition

Júlio Garganta, João Ribeiro, Keith Davids, Ricardo Santos
3 citations
Adaptive Behavior
Sport Psychology and Performance
2.37
article

Developing Performance in Sports Teams Through a Collective Homeostasis Model Supports Regulation, Adaptation, and Evolution in Competition

Júlio Garganta, João Ribeiro, Keith Davids, Ricardo Santos
article en
3 citations

Abstract

The collective homeostasis model, grounded in ecological dynamics, has recently been proposed to explain the self-regulating individual-environment interactions that are necessary to conceptualizing sports teams as collective homeostatic systems. Based on these insights and given the capacity of humans to construct and adapt their ecological niches, this article explores the creation of enriching sporting contexts for the development of adaptive player-environment interactions in competitive team sports. This model of adaptation emphasizes the importance of creating a sports niche rich in shared affordances to enable team coordination through the development of individual and collective homeostasis in different sub-phases of competitive performance. In a homeostatic sports system, principles of play advocated by coaches allow players to intentionally coordinate and adapt their actions to shape the collective identity of the team. The team’s identity is shaped by the synergetic development of collective attractors (stable system states) emerging at specific scales of complexity. This is facilitated through the manipulation of constraints by the coaching and support staff. These ideas have important implications for implementing team sports training and performance preparation, helping to transform the self-regulating tendencies of players through adapting their behaviors to dynamic performance contexts.

Adaptive BehaviorVol. 33(2)
Universidade do Porto (PT), Sheffield Hallam University (GB)
Life in Land
Openalex Percentile: Top 10%
Sport Psychology and Performance
2.37
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Developing Performance in Sports Teams Through a Collective Homeostasis Model Supports Regulation, Adaptation, and Evolution in Competition — Júlio Garganta, João Ribeiro, et al. · Adaptive Behavior (2024) | TGRS Research Map | TGRS