ABSTRACT
Complexity sciences have been used to study and explain the rich patterns formed in complex systems such as animal collectives, weather systems, the human brain and movements in team sports, where patterns emerge from seemingly random component trajectories (Bak and Chialvo 2001; Kauffman 1993; Sumpter 2006). From this description, it is clear that an emerging expert performance can be viewed as a complex system, composed of many degrees of freedom on many system levels. The potential for interaction between system components provides the platform for rich patterns of behaviour to emerge as individuals interact with dynamically changing environments. This new perspective reveals that compensatory adaptation in performance achievement occurs as the result of system trade-offs between specificity and diversity of behaviours (Edelman and Gally 2001). These ideas are harmonious with a dynamical systems theoretical perspective on the influence of interacting constraints. This overarching theoretical framework proposes that expert levels of performance can be achieved in diverse ways as individual performers attempt to satisfy the unique constraints on them (Davids et al. 2003).
