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. 2020 Oct 14;10(1):17288.
doi: 10.1038/s41598-020-74487-x.

Decision-making and dynamics of eye movements in volleyball experts

Daniel Fortin-Guichard  1 , Vincent Laflamme  2 , Anne-Sophie Julien  3 , Christiane Trottier  4 , Simon Grondin  2
Affiliations

Decision-making and dynamics of eye movements in volleyball experts

Daniel Fortin-Guichard et al. Sci Rep. .

Abstract

Key decision-makers among experts in a given field can sometimes be identified based on their role and responsibilities. The aim of the study is to compare perceptual-cognitive skills of experts with decisional responsibilities (setters in volleyball) with that of other volleyball experts. Eighty-two participants (26 setters, 36 other players and 20 controls) viewed 50 volleyball video sequences. Sequences stopped 120 ms before ball contact and participants, whose eye movements were recorded, had to predict the ball direction. Generalized Estimating Equations analysis revealed that setters and controls made more but shorter fixations than other players. However, both expert groups made better predictions than controls. Dynamics analyses of eye movements over time show that, right before ball contact, opposing players' upper body is a most relevant attentional cue in all game situations. Results are discussed in terms of decision-making responsibilities to identify key decision-makers in volleyball and in general. They point towards specific perceptual-cognitive abilities found in setters and support the idea that they constitute a subgroup of experts, but that they are not "better" than other players in anticipating the game.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Mean number of fixations per sequence as a function of group and sequence types. Error bars represent the standard error of the means. Lines between data points are meant to facilitate the distinction between sequence types across groups, and not to presume of any quantitative link between groups.
Figure 2
Figure 2
Average fixation duration as a function of groups and sequence types. Error bars represent the standard error of the means. Lines between data points are meant to facilitate the distinction between sequence types across groups, and not to presume of any quantitative link between groups.
Figure 3
Figure 3
Mean number of AOIs fixated per sequence as a function of group and sequence types. Error bars represent the standard error of the mean. Lines between data points are meant to facilitate the distinction between sequence types across groups, and not to presume of any quantitative link between groups.
Figure 4
Figure 4
Mean correct predictions as a function of group and sequence types. Error bars represent the standard error of the mean. Lines between data points are meant to facilitate the distinction between sequence types across groups, and not to presume of any quantitative link between groups.
Figure 5
Figure 5
Predicted probability that an AOI is fixated as a function of time for each group and for and each type of sequence.
See this image and copyright information in PMC

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