Cocić, D., Vaci, N. orcid.org/0000-0002-8094-0902, Prieger, R. et al. (1 more author) (2020) Reading the future from body movements – anticipation in handball. Journal of Motor Behavior, 53 (4). pp. 483-498. ISSN 0022-2895
Abstract
In speed-based sports that require fast reactions, the most accurate predictions are made once the players have seen the ball trajectory. However, waiting for the ball trajectory does not leave enough time for appropriate reactions. Expert athletes use kinematic information which they extract from the opponent’s movements to anticipate the ball trajectory. Temporal occlusion, where only a part of the full movement sequence is presented, has often been used to research anticipation in sports. Unlike many previous studies, we chose occlusion points in video-stimuli of penalty shooting in handball based on the domain-specific analysis of movement sequences. Instead of relying on randomly chosen occlusion points, each time point in our study revealed a specific chunk of information about the direction of the ball. The multivariate analysis showed that handball goalkeepers were not only more accurate and faster than novices overall when predicting where the ball will end up, but that experts and novices also made their decisions based on different kinds of movement sequences. These findings underline the importance of kinematic knowledge for anticipation, but they also demonstrate the significance of carefully chosen occlusion points.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Informa UK Ltd. This is an author-produced version of a paper subsequently published in Journal of Motor Behavior. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | expertise; anticipation; temporal occlusion; multilevel modeling; handball |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 04 Aug 2020 10:26 |
Last Modified: | 24 Jan 2022 14:48 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.1080/00222895.2020.1802216 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:163995 |