ReviewSports medicine (Auckland, N.Z.)2022
An Active Inference Account of Skilled Anticipation in Sport: Using Computational Models to Formalise Theory and Generate New Hypotheses.
Review in Sports medicine (Auckland, N.Z.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Team Cognizant Action: Insights into Developing Team Synergies in Sports.Sports medicine - open · 2026Article
- How game score shapes anticipatory swing decisions in baseball players: a functional MRI study.Scientific reports · 2026Article
- Active inference as a model of collision avoidance behavior in human drivers.Nature communications · 2026Article
- 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
- Imitation performance biases are moderated by perceived accuracy in golf putting.Scientific reports · 2025Article
- The information gain of explicitly provided over self-generated contextual knowledge for behavioral control.PloS one · 2025Article
- Action imagery as active inference: a commentary on Rieger et al. (2023).Psychological research · 2024Review
- 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
- Visual search strategies of performance monitoring used in action anticipation of basketball players.Brain and behavior · 2023Article
- Expert goalkeepers' and coaches' views on anticipation and cue utilisation facing backcourt throws in handball goalkeeping.Frontiers in sports and active living · 2023Article
- Contemporary pedagogy? The use of theory in practice: An evidence-informed perspective.Frontiers in sports and active living · 2023Article
- Task-evoked pupillary responses track precision-weighted prediction errors and learning rate during interceptive visuomotor actions.Scientific reports · 2022Article
- Egocentric Chunking in the Predictive Brain: A Cognitive Basis of Expert Performance in High-Speed Sports.Frontiers in human neuroscience · 2022Article
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Authors and funding
6 authors.
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Abstract
Optimal performance in time-constrained and dynamically changing environments depends on making reliable predictions about future outcomes. In sporting tasks, performers have been found to employ multiple information sources to maximise the accuracy of their predictions, but questions remain about how different information sources are weighted and integrated to guide anticipation. In this paper, we outline how predictive processing approaches, and active inference in particular, provide a unifying account of perception and action that explains many of the prominent findings in the sports anticipation literature. Active inference proposes that perception and action are underpinned by the organism's need to remain within certain stable states. To this end, decision making approximates Bayesian inference and actions are used to minimise future prediction errors during brain-body-environment interactions. Using a series of Bayesian neurocomputational models based on a partially observable Markov process, we demonstrate that key findings from the literature can be recreated from the first principles of active inference. In doing so, we formulate a number of novel and empirically falsifiable hypotheses about human anticipation capabilities that could guide future investigations in the field.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.