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Standardised computer-based reaction tests predict the sport-specific visuomotor speed and performance of young elite table tennis athletes

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  • Thorben Hülsdünker
  • Martin Ostermann
  • Andreas Mierau

Abstract

The importance of visuomotor reactions in sports is inevitable; however, its assessment using computer-based tests raises the question, if results are transferable to sport-specific situations. Since computer-based simple reaction tests are widely used by sport scientists and practioners, this study examined their relation to sport-specific visuomotor reaction speed and performance. Seventeen international young elite table tennis players performed a simple visuomotor reaction test in response to stimuli presented on a computer screen (laboratory experiment) as well as table tennis balls played by a ball robot (sport-specific experiment). A sport-specific cued choice reaction task served as a control condition. The visuomotor reaction time (VMRT) was determined for all tasks. In addition, neurophysiological correlates of visual perception/processing speed (N2/N2-r) were measured in the laboratory experiment. The VMRT and neurophysiological parameters measured in the laboratory experiment predicted the sport-specific reaction speed (VMRT: r = 0.62; N2: r = 0.51; N2-r: r = −0.47) as well as sport-specific visuomotor performance reflected by the number of successfully hit balls (VMRT: r = −0.68; N2: r = −0.65; N2-r: r = 0.50). This did not apply to the choice reaction task. This study suggests computer-based behavioural and neurophysiological indices of visuomotor reaction time are directly related to the sport-specific visuomotor speed and performance in a more ecologically valid setting.

Suggested Citation

  • Thorben Hülsdünker & Martin Ostermann & Andreas Mierau, 2019. "Standardised computer-based reaction tests predict the sport-specific visuomotor speed and performance of young elite table tennis athletes," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 19(6), pages 953-970, November.
  • Handle: RePEc:taf:rpanxx:v:19:y:2019:i:6:p:953-970
    DOI: 10.1080/24748668.2019.1688071
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    Cited by:

    1. Song, Honglin & Li, Yutao & Fu, Chenyi & Xue, Feng & Zhao, Qiyue & Zheng, Xingyu & Jiang, Kunkun & Liu, Tianbiao, 2024. "Using complex networks and multiple artificial intelligence algorithms for table tennis match action recognition and technical-tactical analysis," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).

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