Heart rate variability and recovery as predictors of elite, African, male badminton players’ performance levels

Christo A. Bisschoff, Ben Coetzee and Michael R. Esco

International Journal of Performance Analysis in Sport, 2018, vol. 18, issue 1, 1-16

Abstract: The aim of this study was to determine whether pre-match, in-match, resting and post-match heart rate variability (HRV) as well as resting and post-match heart rate recovery (HRR) can serve as significant predictors of male, elite, African, singles badminton players’ performance levels. Twenty-two male badminton players were categorised into successful and less successful player groups according to match results. Heart rates were recorded every second before (pre-match), during (in-match) and directly after (post-match) 46 matches to determine 14 HRV and 2 HRR indices. Binary, forward, stepwise logistic regression analyses’ results showed that log transformed low frequency to high frequency ratio (Ln-LFnu/Ln-HFnu ratio) and peak very low frequency power (VLF power (Hz)), were significantly (p < .05) related to group allocation of successful and less successful badminton players. Overall model fit was good and 75% of players could be classified into their original groups by making use of the HRV-based logistic regression formulas. Furthermore, all models had a large effect in predicting player classification, although only the pre- and in-match models emerged as being useful. In conclusion, short-term frequency domain-related HRV variables are related to badminton match performances and should be considered when measuring HRV in sport and exercise settings.

Date: 2018
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DOI: 10.1080/24748668.2018.1437868

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