ECSS Paris 2023: OP-AP36
INTRODUCTION: While sleep quantity and quality are well-established indicators of sleep health, sleep variability is increasingly recognized as an additional key dimension, commonly assessed using the Coefficients of Variation (CV) or recently evaluated with the Sleep Regularity Index (SRI).1 However, these metrics capture distinct aspects of variability,2 with CV reflecting overall night-to-night variability (values >10% indicating high variability) and SRI quantifying the consistency of sleep-wake patterns across nights, with a mean score of 81.0 reported in the general population.3 Athletes, particularly those involved in team sports with collectively scheduled training sessions, are frequently exposed to irregular sleep patterns,4,5 and differences in sleep variability according to sex and competitive level remain insufficiently characterized. Given the central role of sleep in recovery, sleep education promoting stable sleep behaviours may be essential to enhance sleep regularity. Therefore, this study aimed to compare sleep variability in male and female team-sport athletes competing at professional and recreational levels and evaluate the effects of sleep education including recommendations to maintain regular sleep-wake schedule on CV and SRI. METHODS: Sixty-five team-sport athletes (36 professional males [Tier 3], 29 recreational females [Tier 2]) practicing rugby and handball were monitored over two weeks (PRE/POST), separated by one month, using actigraphy and daily subjective sleep questionnaires. Before the POST week, athletes received individualized sleep recommendations to align sleep schedules with their own chronotype by establishing consistent bed and wake-up times. Comparisons between male and female metrics were conducted with Mann-Whitney U tests. As residuals did not follow normality, nonparametric ANOVA-Type Statistic models were applied to assess the main effects of sex and phase. RESULTS: While CVwake-up time was 17.7 ± 5.6 for females, 13.2 ± 4.9 for males and decreased for both sexes following the intervention (13.3 ± 6.2, 10.5 ± 3.6 respectively; p < 0.001, η2 = 0.20), no other variables exhibited significant changes. Median SRI was 72.0 in PRE and 73.4 in POST, but no statistical difference was observed. Whatever the week, SRI was positively correlated with sleep efficiency. Compared to males, females showed higher variability in CVbedtime and CVwake-up time (p = 0.04, η2 = 0.09 for both) in both weeks. CONCLUSION: Athletes showed high overall and consecutive sleep variability, confirming previous studies,4,5 and for the first time, sleep education improved sleep timing consistency in both sexes. While CV offer a useful and accessible overview of sleep timing, the SRI gives a validated score capturing night-to-night consistency. CV and SRI provide complementary insights into sleep variability and may inform future sleep strategies to improve athletes sleep health. 1Kemp et al., 2023 2Fischer al., 2021 3Windred et al., 2021 4Wilson et al., 2025 5Halson et al., 2022
Read CV Mathias GoldbergECSS Paris 2023: OP-AP36
INTRODUCTION: Perceived Recovery Status (PRS) and Rating of Physical Freshness (RPF) provide a low-cost and time-efficient feedback on recovery and readiness in relation to training. Since sleep is a key modifiable determinant of recovery, athletes may complement these self-reported measures with indicators of sleep quality and disturbances over the previous month (such as the Pittsburgh Sleep Quality Index (PSQI)). In sub-elite volleyball, congested training–match schedules may compromise athletes’ recovery, and monitoring is often limited. Hence, this study aimed to monitor in-season short-term patterns in perceived recovery and freshness, also in relation to the sleep quality in sub-elite volleyball players. METHODS: Eleven female volleyball players competing in the Italian National Serie B2 (age: 24.0 ± 6.4 years; height: 1.77 ± 0.05 m; weight: 69.75 ± 7.58 kg) were monitored in-season across three consecutive weeks including four training sessions and one match/week. Prior to the study, athletes’ chronotype and sleeping habits and quality were assessed through the Morningness-Eveningness Questionnaire (MEQ) and PSQI, respectively. For each session and match, training load was evaluated through the Session Rating of Perceived Exertion (s-RPE) method (Borg scale CR-10). Furthermore, for each week, PRS (0-10), and RPF (1-7) were collected before the first training session. Linear mixed models with random intercepts were applied to assess week effects and associations between PSQI and PRS/RPF and s-RPE. Furthermore, the predictive relationship between PRS and RPF was investigated. Statistical significance was set at p<0.05. RESULTS: Across the considered weeks, RPE_ POST30 showed no significant changes (3.67 ± 0.09 AU, p > 0.05). No significant differences emerged also in weekly s-RPE (trainings: 658.75 ± 212.14 AU; matches: 298.06 ± 194.02 AU, all p > 0.05). Athletes classified in intermediate (63.5%) and moderately serotine (36.4%) chronotype for MEQ and reported a poor sleep quality (45.5%) for PSQI. No significant week effects were observed for PRS and RPF (p ≥ 0.74). PSQI was not associated with PRS (b = −0.159 ± 0.090, F(1,9) = 3.11, p = 0.112) nor with RPF (b = −0.026 ± 0.060, F(1,9) = 0.19, p = 0.672). In contrast, PRS was a strong positive predictor of RPF when controlling for PSQI and week (b = 0.361 ± 0.088, F(1,26.06) =16.89, p = 0.00035), suggesting that higher perceived recovery translated into meaningfully greater freshness. CONCLUSION: Across three competitive weeks, group-level recovery/readiness ratings remained stable, but perceived recovery emerged as a key determinant of next-day freshness. PSQI did not explain short-term variation in readiness in this sample, supporting the practical value of simple self-reported monitoring measures in sub-elite volleyball players. Future work should include larger samples and objective measures of sleeping patterns to clarify the role of chronobiological and sleep-related factors in relation to perceived recovery.
Read CV Francesca Di RoccoECSS Paris 2023: OP-AP36
INTRODUCTION: Academy soccer players are exposed to unique and interacting performance, developmental and psychological demands which can increase energy requirements. Inadequate energy intake relative to exercise energy expenditure may result in low energy availability (LEA), characterised, in part, by changes in physiological function and psychological wellbeing. Despite these recognised contributing factors to LEA, data describing energy availability and associated physiological and psychological markers in male academy team sport athletes are limited. METHODS: Using a cross-sectional design, 33 elite male academy soccer players (age=19±2 y) completed a three-day food and activity diary to estimate energy intake, macronutrient intake and exercise energy expenditure. A 22% correction factor was applied to energy intake to account for underreporting. Resting metabolic rate (RMR) was measured via pulmonary gas exchange and estimated (Hannon et al., 2023) to calculate RMRratio. Whole-body fat free mass (FFM) was estimated from skinfold thickness. Participants completed validated questionnaires assessing wellbeing, training distress, burnout and eating disorder risk. RESULTS: Mean energy intake, exercise energy expenditure and energy availability over three days were 2445±493 kcal·d-1, 757±266 kcal·d-1 and 26±9 kcal·kgFFM·d-1, respectively. Twenty participants (63%) reported average energy availability below commonly used thresholds (<30 kcal·kgFFM·d-1), with three demonstrating an RMRratio below 0.90. Mean carbohydrate, protein and fat intake were 3.1±1.1 g/kg, 1.5±0.7 g/kg and 29.4±7.5% of total energy intake, respectively. Mean RMR and RMRratio were 2183±306 kcal·d-1 and 1.10±0.15, respectively. Mean wellbeing score was 22±7 AU, training distress 9±7 AU, physical and emotional exhaustion 11±3 AU, personal accomplishment 9±3 AU, sport devaluation 7±2 AU, total burnout 27±6 AU, and BEDA-Q 12.8±14.7%. Energy availability was moderately correlated with physical and emotional exhaustion (r=-0.412, p=0.019) and total burnout (r=-0.548, p=0.001). Small correlations were observed for personal accomplishment (rs=-0.395, p=0.025) and sport devaluation (rs=-0.350, p=0.050). A moderate positive correlation was found between energy availability and RMRratio (r=0.436, p=0.013). Trivial associations were observed with overall wellbeing (r=-0.121, p=0.508), training distress (rs=0.195, p=0.284) and eating disorder risk (rs=0.100, p=0.586). CONCLUSION: A substantial proportion of players demonstrated a mean energy availability below commonly used thresholds, with some indications of metabolic suppression. Lower energy availability was associated with greater physical and emotional exhaustion and overall burnout. These findings support routine monitoring of energy availability within academy soccer environments, particularly during periods of heightened performance, developmental and psychological demand.
Read CV Tom MullenECSS Paris 2023: OP-AP36