Sport is complex and dynamic, comprising numerous interacting and interdependent components (Balague et al., Citation2013; Salmon and McLean, Citation20219). For example, the interactions of physiological, psychological, and technical components of athletes to the social, economic, and political influences that shape the sports industry more broadly (Mclean et al., Citation2021; Salmon et al., Citation2021). In any complex system, the interactions between these components are not linear or straightforward, and they can produce emergent behaviours that are difficult to anticipate or manage (Cilliers, Citation1998; Skyttner, Citation2001). This complexity is at odds with the deterministic methods typically applied in sport research. Deterministic approaches focus on reducing systems down to their component parts on the assumption that if individual components can be understood and improved, then these improvements will enhance the overall system. Deterministic methods have driven scientific research for decades (Dekker, Citation2011) and in many contexts they have enhanced the understanding of sport system components and helped optimise performance in many areas, such as equipment and technology design, technique/skill development, to name a few. It is our contention that deterministic methods may have taken us as far as they can in terms of understanding and optimising sport. We are now left with a set of complex, longstanding, and intractable issues that cannot be resolved with such approaches. As a result, there is a growing body of sports research in which models and methods from the complexity sciences are being applied to understand optimised sport system performance. The purpose of this special issue was to invite authors to showcase their work on complexity and systems thinking in sport, to gauge the current state of complex systems approaches in sport research and to inspire new applications across sporting domains.
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