Motor competence is related to a large number of correlates of different natures, forming together a system with flexible parts that are synergically and cooperatively connected to produce a wide range of motor outcomes that cannot be explained from a predetermined linear view or a unique mechanism. The diversity of interacting correlates, the various connections between them, and the fast changes between assessments at different time points are clear barriers to the study of motor competence. In this manuscript, we present a multilayer framework that accounts for the theoretical background and the potential mathematical procedures necessary to represent the non-linear, complex, and dynamic relationships between several underlying correlates that emerge as a motor competence network. Exploring motor competence from a new perspective that could be operationalized through multilayer networks seems promising, and allows more accurate inspection and representation of its topology and dynamics. This new perspective might also improve the understanding of motor competence structure and functionality over the developmental course. The use of the proposed approach could open up new horizons for the broad literature comprising motor competence.

运动能力与大量不同性质的相关性有关，共同形成一个系统，这些柔性部分协同协作地连接在一起，以产生无法从预定的线性视图或独特机制来解释的广泛运动结果。相互作用的相关性的多样性、它们之间的各种联系以及不同时间点评估之间的快速变化是运动能力研究的明显障碍。在这份手稿中，我们提出了一个多层框架，该框架解释了理论背景和潜在的数学程序，以表示作为运动能力网络出现的几个基本相关性之间的非线性、复杂和动态关系。从可以通过多层网络操作的新角度探索电机能力似乎很有前途，并且可以更准确地检查和表示其拓扑和动力学。这种新视角也可能提高对发展过程中运动能力结构和功能的理解。使用所提出的方法可以为包含运动能力的广泛文献开辟新的视野。