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  • Title: New predictive model of the touchdown times in a high level 110 m hurdles.
    Author: Iwasaki R, Nunome H, Nozawa K.
    Journal: PLoS One; 2022; 17(12):e0278651. PubMed ID: 36459532.
    Abstract:
    The present study aimed to establish a more robust, reliable statistical model of touchdown times based on the data of elite 110 m hurdlers to precisely predict performance based on touchdown times. We obtained 151 data (race time: 13.65 ± 0.33 s, range of race time: 12.91 s- 14.47 s) from several previous studies. Regression equations were developed to predict each touchdown time (times from the start signal to the instants of the leading leg landing after clearing 1st to 10th hurdles) from the race time. To avoid overtraining for each regression equation, data were split into training and testing data sets in accordance with a leave-one-out cross-validation. From the results of cross-validation, the agreement and generalization were compared between the present study model and the existing model. As a result, the proposed predictive equations showed a good agreement and generalization (R2 = 0.527-0.981, MSE = 0.0015-0.0028, MAE = 0.019-0.033) compared to that of existing equations (R2 = 0.481-0.979, MSE = 0.0017-0.0039, MAE = 0.034-0.063). Therefore, it can be assumed that the proposed predictive equations are a more robust, reliable model than the existing model. The touchdown times needed for coaches and elite hurdlers to set their target records will be accurately understood using the model of this study. Therefore, this study model would help to improve training interventions and race evaluations.
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