Abstract
ABSTRACTExpert performance across a range of domains is underpinned by superior perceptual-cognitive skills. Over the last five decades, researchers have provided evidence that experts can identify and interpret opponent kinematics more effectively than their less experienced counterparts. More recently, researchers have demonstrated that experts also use non-kinematic information, in this paper termed contextual priors, to inform their predictive judgments. While the body of literature in this area continues to grow exponentially, researchers have yet to develop an overarching theoretical framework that can predict and explain anticipatory behaviour and provide empirically testable hypotheses to guide future work. In this paper, we propose that researchers interested in anticipation in sport could adopt a Bayesian model for probabilistic inference as an overarching framework. We argue that athletes employ Bayesian reliability-based strategies in order to integrate contextual priors with evolving kinematic information during anticipation. We offer an insight into Bayesian theory and demonstrate how contemporary literature in sport psychology fits within this framework. We hope that the paper encourages researchers to engage with the Bayesian literature in order to provide greater insight into expert athletes’ assimilation of various sources of information when anticipating the actions of others in complex and dynamic environments.
Highlights
We are frequently required to make accurate estimates about the state of an uncertain world, often with only probabilistic information to hand (Brunswik, 1952)
We provide the reader with an overview of key empirical research and models focusing on the use of kinematic information and contextual priors in the domain of sport
In keeping with Bayesian theory, to reduce the uncertainty of the decision, athletes integrate contextual priors with kinematic information according to the comparative reliabilities of available information sources
Summary
We are frequently required to make accurate estimates about the state of an uncertain world, often with only probabilistic information to hand (Brunswik, 1952). In the quest for an overarching framework, it has been suggested that athletes may employ Bayesian reliability-based strategies in order to integrate contextual priors with evolving kinematic information during anticipation (Loffing & Cañal-Bruland, 2017).
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More From: International Review of Sport and Exercise Psychology
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