Loeys Tom, De Clerck Tom, Haerens Leen
Department of Data-analysis, Ghent University, Belgium.
Department of Movement & Sport Sciences, Ghent University, Belgium.
Psychol Sport Exerc. 2025 Jan;76:102752. doi: 10.1016/j.psychsport.2024.102752. Epub 2024 Sep 27.
Interpersonal behavior in sports teams are inherently intricate. The Social Relations Model (SRM) presents a compelling framework to conceptualize and dissect these complexities, enabling the empirical testing of theories concerning relationships within group settings. The SRM decomposes dyadic measurements obtained from a round-robin design into components at the individual (actor and partner) level, relationship level, and team level. Leveraging data on need satisfaction, as experienced by the coach, team captain and two other athletes in relation to each other across 96 sports teams, we showcase the application of the SRM. A step-by-step introduction to the implementation of the model in R is provided. We elucidate how the SRM facilitates the investigation of research questions that deepen our understanding of team dynamics. Our illustration reveals that while the team effect exhibits minimal explanatory power over variability, substantial variability in need satisfaction is accounted for by both individual factors (actor and partner) and relationship effects. Notably, considerable differences are observed between sports teams in the extent to which coaches elicited need satisfaction in their team members. On average, coaches elicit lower levels of need satisfaction compared to other team members. Reciprocal relationships are evident in the team captain-athlete dyad and the athlete-athlete dyad, but not in dyadic relationships with the coach. In sum, this tutorial illustrates how analyzing dyadic data from a round-robin design using the SRM can enhance our understanding of dyadic relationship data within sports teams.
运动队中的人际行为本质上错综复杂。社会关系模型（SRM）提供了一个引人注目的框架，用于概念化和剖析这些复杂性，从而能够对有关群体环境中人际关系的理论进行实证检验。SRM将从循环赛设计中获得的二元测量分解为个体（行为者和伙伴）层面、关系层面和团队层面的组成部分。利用96个运动队中教练、队长和其他两名运动员相互之间体验到的需求满足数据，我们展示了SRM的应用。提供了在R中实施该模型的逐步介绍。我们阐明了SRM如何促进对研究问题的调查，这些问题加深了我们对团队动态的理解。我们的例证表明，虽然团队效应对变异性的解释力最小，但需求满足的大量变异性是由个体因素（行为者和伙伴）和关系效应共同造成的。值得注意的是，在教练激发团队成员需求满足的程度方面，运动队之间存在相当大的差异。平均而言，与其他团队成员相比，教练激发的需求满足水平较低。队长与运动员二元组以及运动员与运动员二元组中存在互惠关系，但与教练的二元关系中不存在。总之，本教程说明了如何使用SRM分析循环赛设计中的二元数据，可以增强我们对运动队中二元关系数据的理解。
