Abstract

PurposeTo describe individual sleep habits and nocturnal heart rate variability (HRV) responses, and to explore intra-individual associations of workload with sleep and nocturnal HRV indices in high-level female soccer players throughout a 2-week competitive period.Materials and methodsThe study followed a descriptive, observational design. Thirty-four high-level female soccer players (aged 20.6 ± 2.3 years) wore wrist actigraph units and heart rate (HR) monitors during night-sleep to record objective sleep and HRV data throughout 14 days [six evening-time training sessions (ET), six rest-days (RD), and two match-days (MD)]. During each ET and MD, exercise HR (HRexe), %HRpeak, training impulse (TRIMP), session rating of perceived exertion (s-RPE) and perceived ratings of wellbeing were monitored.ResultsAfter ET, a higher number of players (17–22) slept less than 7 h/night, in contrast to the remaining days (i.e., MD and RD), but only 1–6 players had a sleep efficiency < 75%. The coefficient of variation (CV) for sleep duration and sleep efficiency ranged between 9–22% and 2–11%, respectively. A small negative within-subject correlation was found between TRIMP and sleep duration [r = −0.25 (−0.36; −0.12); P < 0.001] and sleep efficiency [r = −0.20 (−0.32; −0.08); P = 0.004]. A moderate and small negative within-subject correlation was found between s-RPE and sleep duration [r = −0.43 (−0.53; −0.32); P < 0.001] and sleep efficiency [r = −0.17 (−0.30; −0.05); P = 0.02]. Nocturnal HRV for the time-domain analyses ranged from 4.1 (3.9; 4.3) to 4.4 (4.1; 4.6) ln[ms], and for the frequency-domain analyses ranged from 6.3 (5.9; 6.7) to 7.5 (7.1; 7.9) ln[ms2]. CV for time-domain HRV ranged from 3 to 23%, and from 4 to 46% for the frequency-domain. Higher CV fluctuations in time- and frequency-domain HRV were particularly observed in four players.ConclusionOverall, this study highlights the individual variability of sleep and nocturnal HRV indices, indicating that sleep duration may be affected by training and match schedules and workloads. Training and matches workload were not associated with nocturnal HRV in high-level female soccer players.

Highlights

  • Athletes, coaches, and health and performance supporting staff should adopt an evidence-based approach to design and monitor training programs

  • It is currently accepted that overnight sleep measurements over several days are appropriate for tracking recovery of heart rate variability (HRV) following exercise (Al Haddad et al, 2009; Costa et al, 2018c)

  • The fourth evening-time training session (ET4) had the lowest average training impulse (TRIMP) and session rating of perceived exertion (s-RPE), while the highest TRIMP and s-RPE were recorded in MD1

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Summary

Introduction

Coaches, and health and performance supporting staff should adopt an evidence-based approach to design and monitor training programs. Attention has been given to the evaluation of monitoring tools that may indicate general signs of fatigue and/or health status of athletes (Peake et al, 2018). These indicators include heart-rate (HR) derived indices (Buchheit, 2014) and sleep (Walsh et al, 2020) monitoring. Non-invasive time-efficient devices such as wearable actigraphy, to assess sleep duration and quality, and HR monitors, to record heart rate variability (HRV) indices, can provide detailed information about positive and negative adaptions over short and/or long periods throughout the competitive season in athletes (Sargent et al, 2016; Plews et al, 2017). It is currently accepted that overnight sleep measurements (free of external disruptive events) over several days are appropriate for tracking recovery of HRV following exercise (Al Haddad et al, 2009; Costa et al, 2018c)

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