To achieve performance goals in competitive sport there is a need to strike a delicate balance between movement pattern stability and variability because, although athletes need to achieve consistent outcomes, they also need to be able to successfully adapt their movements to changes in the performance environment. To achieve these aims, the theory of ecological dynamics advocates that there is an intertwined relationship between the specific intentions, perceptions, and actions of individual athletes that constrains this relationship between movement pattern stability and variability in each individual performer. This intertwined relation between an individual’s intentions, perception, and action processes needs to be carefully understood because of the insights it provides on expert performance in sport.
Traditionally, a high level of expertise in sport has been associated with the capacity to be able to reproduce a specific movement pattern consistently and to reduce attention demands during performance by increasing the automaticity of movement. It was assumed that the central nervous system (CNS) functioned as an executive organizer and prescriber of motor programs and action plans charged with the task of producing stable movement patterns from an individual’s effector system. From that viewpoint, expertise in sport was associated with a reduction in deviations in task performance from an ideal standard or movement template which was represented in the CNS. By harnessing integrated feedback systems, athletes were considered to modify the motor program entry parameters until expert behavior was eventually achieved after many hours of practice. Traditionally, therefore, movement variability was considered as noise in performance and learning which should be minimized or eradicated to enable the production of highly functional movement programs (movement variability was considered to be an artifact limiting an individual system’s processing of information from input to output).
However, research in ecological dynamics has shown that movement system variability should not necessarily be construed as noise, detrimental to performance. Nor should it always be viewed as error or a deviation from a putative expert model, which should be constantly corrected in learners. Inspired by insights from the Russian physiologist Nicolai Bernstein, movement system variability instead is now considered to exemplify the functional flexibility of a skilled athlete to respond to changes in dynamic performance constraints. For this and other reasons, the concept of functional variability has gained a significant amount of empirical support in the sport psychology field. A key idea is that movement pattern variability can be viewed as a functional property of skilled performers to help them adapt their movement behaviors to changing task constraints (see entry on “Task Constraints”). Traditional research has typically focused on the amount of movement variability exhibited by an athlete during performance, assessed by statistical measures such as the standard deviation or variance around a distribution mean. According to Karl Newell’s (1986) Constraints on the Development of Coordination, these statistics indicate the amount of noise in a single measurement—that is, the standard deviation only indicates the magnitude of variability recorded during task performance (the amplitude, the spatial aspect of the scores in a performance distribution. It provides little information on the structure of movement variability exhibited by an athlete, which is needed to understand whether it is functional or not. For this reason, Newell and his co-investigators recommended studying the temporal structure of movement pattern variability by analyzing the spectral range of noise, which provides information on the deterministic (preplanned) or stochastic (emergent) nature of movement variability. Also pointed out was that it would be wrong to consider that deterministic processes specify the invariance of a movement pattern and that stochastic processes specify its variance. Given these theoretical advances in understanding movement pattern variability, ecological dynamicists have argued that there is no ideal motor coordination solution (a classical technique) that all athletes should aspire to during learning. Rather, functional patterns of coordination emerge during practice from the interaction of constraints on each individual athlete (task, environmental, and organismic), leading to intraindividual and interindividual movement pattern variability as consistent performance outcomes are achieved.
Recently, the functional role of movement pattern variability has also been supported by research highlighting the property of neurobiological system degeneracy, technically defined by Gerald Edelman and Joseph Gally as the capacity of system components that differ in structure to achieve the same function or performance output. This structural property in humans indicates the availability of an abundance of motor system degrees of freedom—that is, the many components of the movement system (alluded to by Bernstein), which can take on different roles when assembling functional actions during sport performance (captured by system degeneracy).
Allied to these ideas on neurobiological degeneracy, research on sport performance has begun to explain why expert performers often display higher levels of intraindividual movement pattern variability than novices in sport, data traditionally viewed as counterintuitive. The movement variability exhibited by skilled individuals can play a functional role. For instance, it highlights an expert athlete’s capacity to perform several types of movement or to adopt one of a number of coexisting modes of coordination, that is, exploit system multistability (the many functional states of system organization) and metastability (the capacity to switch between functional states), in order to achieve the same functional performance outcomes. In the past years, empirical research on sport performance has clearly exemplified how intraindividual and interindividual movement variability can play a functional role in the performance of team-based and a range of individual physical activities, such as a cyclical movement task in an aquatic environment (breaststroke swimming) and a continuous discrete task in the wilderness (ice climbing) (see studies by Duarte Araújo, Keith Davids, and Ludovic Seifert and coworkers). These key ideas on functional variability have now been integrated into a motor learning theory by Wolfgang Schöllhorn et al., known as Differential Learning, which advocates adding noise to initial performance conditions to provoke learning by forcing the individual to adapt unexpectedly.
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