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Pursuing Collective Synchrony in Teams: A Regime-Switching Dynamic Factor Model of Speed Similarity in Soccer

Published online by Cambridge University Press:  01 January 2025

Daniel M. Smith Open the ORCID record for Daniel M. Smith [Opens in a new window]  and
Theodore A. Walls
Daniel M. Smith*
Affiliation:
Springfield College
Theodore A. Walls
Affiliation:
University of Rhode Island
*
Correspondence should be made to Daniel M. Smith, Department of Physical Education and Health Education, Springfield College, 263 Alden Street, Springfield, MA01109, USA. Email: [email protected]
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Abstract

Collective synchrony refers to the simultaneous occurrence of behavior, cognition, emotion, and/or physiology within teams of three or more persons. It has been suggested that collective synchrony may emanate from the copresence of team members, from their engagement in a shared task, and from coordination enacted in pursuit of a collective goal. In this paper, a regime-switching dynamic factor analytical approach is used to examine interindividual similarities in a particular behavioral measure (i.e., speed) in a collegiate soccer team. First, the analytical approach is presented didactically, including the state space modeling framework in general, followed by the regime-switching dynamic factor model in particular. Next, an empirical application of the approach is presented. Speed similarity (covariation in speed, operationalized in two ways: running cadence and distance covered) during competitive women’s soccer games is examined. A key methodological aspect of the approach is that the collective is the unit of analysis, and individuals vary about collective dynamics and their evolution. Reporting on the results of this study, we show how features of substantive interest, such as the magnitude and prevalence of behavioral similarity, can be parameterized, interpreted, and aggregated. Finally, we highlight several key findings, as well as opportunities for future research, in terms of methodological and substantive aims for advancing the study of collective synchrony.

Keywords

intensive longitudinal datastate space modelstime series
Type
Application Reviews and Case Studies
Information
Psychometrika , Volume 86 , Issue 4: Special Section: Revisiting Cronbach’s Alpha , December 2021 , pp. 1016 - 1038
Copyright
Copyright © 2021 The Psychometric Society

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