Dataset Information

Soccer goalkeeper expertise identification based on eye movements.

ABSTRACT: By focusing on high experimental control and realistic presentation, the latest research in expertise assessment of soccer players demonstrates the importance of perceptual skills, especially in decision making. Our work captured omnidirectional in-field scenes displayed through virtual reality glasses to 12 expert players (picked by DFB), 10 regional league intermediate players, and13 novice soccer goalkeepers in order to assess the perceptual skills of athletes in an optimized manner. All scenes were shown from the perspective of the same natural goalkeeper and ended after the return pass to that goalkeeper. Based on the gaze behavior of each player, we classified their expertise with common machine learning techniques. Our results show that eye movements contain highly informative features and thus enable a classification of goalkeepers between three stages of expertise, namely elite youth player, regional league player, and novice, at a high accuracy of 78.2%. This research underscores the importance of eye tracking and machine learning in perceptual expertise research and paves the way for perceptual-cognitive diagnosis as well as future training systems.

SUBMITTER: Hosp BW

PROVIDER: S-EPMC8133470 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Soccer goalkeeper expertise identification based on eye movements.

Hosp Benedikt W BW Schultz Florian F Höner Oliver O Kasneci Enkelejda E

PloS one 20210519 5

By focusing on high experimental control and realistic presentation, the latest research in expertise assessment of soccer players demonstrates the importance of perceptual skills, especially in decision making. Our work captured omnidirectional in-field scenes displayed through virtual reality glasses to 12 expert players (picked by DFB), 10 regional league intermediate players, and13 novice soccer goalkeepers in order to assess the perceptual skills of athletes in an optimized manner. All scen ...[more]

PMID: 34010305

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Project description:The aim of this study was to define a method for evaluating a player's decisions during a game based on the success probability of his actions and for analyzing the player strategy inferred from game actions. There were developed formal definitions of i) the stochastic process of player decisions in game situations and ii) the inference process of player strategy based on his game decisions. The method was applied to the context of soccer goalkeepers. A model of goalkeeper positioning, with geometric parameters and solutions to optimize his position based on the ball position and trajectory, was developed. The model was tested with a sample of 65 professional goalkeepers (28.8 ± 4.1 years old) playing for their national teams in 2010 and 2014 World Cups. The goalkeeper's decisions were compared to decisions from a large dataset of other goalkeepers, defining the probability of success in each game circumstance. There were assessed i) performance in a defined set of classes of game plays; ii) entropy of goalkeepers' decisions; and iii) the effect of goalkeepers' positioning updates on the outcome (save or goal). Goalkeepers' decisions were similar to the ones with the lowest probability of goal on the dataset. Goalkeepers' entropy varied between 24% and 71% of the maximum possible entropy. Positioning dynamics in the instants that preceded the shot indicated that, in goals and saves, goalkeepers optimized their position before the shot in 21.87% and 83.33% of the situations, respectively. These results validate a method to discriminate successful performance. In conclusion, this method enables a more precise assessment of a player's decision-making ability by consulting a representative dataset of equivalent actions to define the probability of his success. Therefore, it supports the evaluation of the player's decision separately from his technical skill execution, which overcomes the scientific challenge of discriminating the evaluation of a player's decision performance from the action result.

Project description:IntroductionVisuocognitive performance is closely related to expertise in chess and has been scrutinized by several investigations in the last decades. The results indicate that experts' decision-making benefits from the chunking process, perception and visual strategies. Despite numerous studies which link these concepts, most of these investigations have employed common research designs that do not use real chess play, but create artificial laboratory conditions via screen-based chess stimuli and obtrusive stationary eye tracking with or without capturing of decision-making or virtual reality settings.MethodsThe present study assessed the visuocognitive performance of chess novices, intermediates and experts in a real chess setting. Instead of check detection, find-the-best-move tasks or to distinguish between regions of a chessboard that were relevant or irrelevant to the best move in previous studies, we introduced n-mate tasks and sequentially manipulated their difficulty. Due to the complexity of the tasks, we monitored players' visual strategies in a fine-graded initial phase (different time intervals instead of analysing a fixed number of first fixations) of task-solving and for complete trials, employing non-obtrusive mobile eye tracking, multi-sensor observation and full-automatic annotation of decision-making.ResultsThe results revealed significant expertise-dependent differences in visuocognitive performance based on a circumstantial spatial and temporal analysis. In order to provide more detailed results, for the first time the analyses were performed under the special consideration of different time intervals and spatial scalings. In summary, experts showed a significantly higher number of fixations on areas of interest and empty squares between pieces in the task processing than less-skilled players. However, they had a strikingly low total number of fixations on the whole board and in complete trials.DiscussionAs a conclusion, experts apply different visual search strategies in problem-solving. Moreover, experts' visuocognitive processing benefits from stored chunks of mating constellations.

Dataset Information

Soccer goalkeeper expertise identification based on eye movements.

Publications

Soccer goalkeeper expertise identification based on eye movements.

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