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.
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