ArticlePsychological research2023
A Bayesian computational model to investigate expert anticipation of a seemingly unpredictable ball bounce.
Article in Psychological research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Predictive Processing in Sport and Exercise Science: A Scoping Review and Theoretical Overview.Sports medicine - open · 2026Review
- Badminton expertise shapes cue extraction and evidence accumulation during perceptual prediction.Frontiers in psychology · 2026Article
- Decision-Making in Repeated Games: Insights from Active Inference.Behavioral sciences (Basel, Switzerland) · 2025Review
- Beyond performance: A POMDP-based machine learning framework for expert cognition.Behavior research methods · 2025Article
- Preserved use of prior information under time constraints: an EEG study of action anticipation in expert athletes.Cognitive research: principles and implications · 2025Article
- Context modulates evidence accumulation in split-second handball penalty decisions.Cognitive research: principles and implications · 2025Article
- The Impact of Skill Level on the Integration of Information and Post-Error Adjustment during Action Anticipation in Basketball.Behavioral sciences (Basel, Switzerland) · 2024Article
- The effect of task load, information reliability and interdependency on anticipation performance.Cognitive research: principles and implications · 2024Article
- Perception-action coupling in anticipation research: a classification and its application to racket sports.Frontiers in psychology · 2024Article
- Optimal integration of kinematic and ball-flight information when perceiving the speed of a moving ball.Frontiers in sports and active living · 2022Article
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3 authors.
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Abstract
During dynamic and time-constrained sporting tasks performers rely on both online perceptual information and prior contextual knowledge to make effective anticipatory judgments. It has been suggested that performers may integrate these sources of information in an approximately Bayesian fashion, by weighting available information sources according to their expected precision. In the present work, we extended Bayesian brain approaches to anticipation by using formal computational models to estimate how performers weighted different information sources when anticipating the bounce direction of a rugby ball. Both recreational (novice) and professional (expert) rugby players (n = 58) were asked to predict the bounce height of an oncoming rugby ball in a temporal occlusion paradigm. A computational model, based on a partially observable Markov decision process, was fitted to observed responses to estimate participants' weighting of online sensory cues and prior beliefs about ball bounce height. The results showed that experts were more sensitive to online sensory information, but that neither experts nor novices relied heavily on prior beliefs about ball trajectories in this task. Experts, but not novices, were observed to down-weight priors in their anticipatory decisions as later and more precise visual cues emerged, as predicted by Bayesian and active inference accounts of perception.
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