Sleep is a key behavioural health factor which affects athletic performance, including ability to complete high training loads with appropriate intensity, concentration and vigor; nevertheless, few information is known about the effects of different training modalities on sleep outcomes in competing athletes. To the best of the authors’ knowledge, this is the first study to investigate objectively-measured sleep characteristics in hybrid athletes, including a comparison between two training modes (i.e., resistance training and endurance training). All Hyrox participants presented with generally ‘good’ sleep outcomes overall, according to both subjective and objective parameters. There were slight differences between training modes in terms of sleep outcomes, which depended on the training mode, affecting one’s ability to fall asleep and cardiac characteristics also differed between exercise modes.

In the present study, hybrid athletes were characterized by performing specific, repeatable exercise training bouts across the study period (see: Supplemental Table 1 for training details). Briefly, although this study applied an ecologically-valid design (i.e. did not impose specific training loads per se), each athlete was interviewed to determine what was their training routine, and whether stark differences were present between the participants; all athletes reported similar intensities and duration of trainings across the week in terms of %HR max (for the endurance training) and %1RM (for the resistance training). Of relevance, the endurance and strength training loads were identical within the two recording days.

According to a recent study conducted with 175 young adult élite athletes from 12 different sports (Sargent et al. 2021), researchers reported actigraphy-based habitual sleep duration was 6.7 ± 0.8 h, which was shorter in athletes from individual sports compared to those participating in team sports. Athletes self-reported sleep satisfaction scores of 6.8 ± 1.6/10.0. In another cross-sectional study on 313 athletes (aged between 18 and 60 years), and recruited from a variety of sport disciplines (Randell et al. 2021), self-reported sleep duration was 7.6 ± 1.0 h, with lower sleep durations found in runners compared to team sports athletes. For this sample, sleep onset latency was reported as ~ 22 min. A systematic review on 1830 athletes reported average sleep duration of 7.7 ± 1.1 h and 86.3 ± 6.8% sleep efficiency (Vlahoyiannis et al. 2021), whereas portable polysomnography was recently used to assess sleep parameters in 13 élite youth rowers (Hof zum Berge et al. 2021a), finding a total sleep time ~ 6.7 h, sleep onset latency ~ 18 min, WASO ~ 42 min and sleep efficiency ~ 82%.

Athletes reported a total sleep time of ~ 6.6 h, which is in line with the previous literature, in particular with the previous study in rowers (Hof zum Berge et al. 2021a). Other sleep parameters assessed sleep onset latency (~ 15 min), WASO (~ 39 min), and sleep efficiency (~ 86%), which were similar to those previously reported, although differences were found according to the type of training; resistance training was characterized by higher sleep onset latency, but lower WASO compared to endurance training. To date, the only study directly comparing the effects of strength and endurance acute exercise on sleep parameters did not report any significant differences between the two types of training; however, participants were healthy trained males who had not actively trained in hybrid disciplines. The training sessions also started at 10:00 (Roveda et al. 2011), potentially only minimally affecting subsequent sleep. The possible effect of resistance training on sleep latency may be supported by previous data suggesting that, according to the type of sport, sleep onset latency is longer in power/explosiveness disciplines compared to other sports (Vlahoyiannis et al. 2021). Moreover, impaired WASO and sleep onset latency have been found to be correlated with daily training load (de Blasiis et al. 2021), although the role of exercise-induced delayed onset muscle soreness is still debated (Hausswirth et al. 2014; de Blasiis et al. 2021).

Considering sleep architecture, our study found that deep sleep stage (N3) accounted for 18% (range: 17‒21) of sleep time, and a proportion of REM sleep of 20% (range: 19‒21); these values are consistent with a previous study on 20 élite athletes from five different sports disciplines (Hof zum Berge et al. 2021b), which found sleep architecture proportions of 5.73 ± 3.41% N1, 36.78 ± 7.67% N2, 26.4 ± 6.13% N3, and 8.02 ± 5.18% of RM sleep. Compared tonon-athletic adult populations who typically spending more time in non-REM sleep and less time in REM sleep, hybrid athletes spent ~ 5% less time in REM, but ~ 7% longer time in N1 + N2. No significant differences were found according to training mode, although in the literature the type of sport has been suggested to potentially affect sleep architecture, since anaerobic sports is characterized by slightly less REM sleep, whereas N3 sleep is reportedly longer in athletes in mixed sports than in athletes in aerobic and power sports (Vlahoyiannis et al. 2021). Finally, seminal works in sport literature have found that after endurance races, REM proportions can be reduced and N3 stage sleep durations may increase, thereby suggesting REM sleep as a sensitive indicator of exercise-induced stress (Shapiro et al. 1981; Driver et al. 1994), while N3 sleep increases in response to higher physiological restorative demand in athletes (Sekiguchi et al. 2019).

Cardiac autonomic activity is potentially affected by the type of exercise training. In the present study, cardiac arousals were more frequent and longer before sleep onset after completing a bout of resistance training exercise, whereas more frequent and longer cardiac arousals were found to occur after sleep onset when endurance training was performed. These findings seem to provide an autonomic rationale of differential effects of the training modality on sleep latency (i.e., longer after resistance training) and WASO (longer after endurance training), although the causative nature of this relationship cannot be confirmed by correlation analysis alone. Despite its possible relation to sleep onset and maintenance (Nano et al. 2020), the role of cardiac autonomic response during sleep has been scarcely investigated after performing exercise. It has been found that with late exercise timing and high exercise strain, there are potential associations with higher nocturnal resting heart rate and lower nocturnal heart rate variability (i.e., higher sympathetic drive) (Leota et al. 2025). These responses may be exacerbated, or more evident after vigorous late-night exercise during the first sleeping hours (Myllymäki et al. 2011). As such, this study confirms previous works which have suggested an association between cardiac autonomic activity and sleep quality, and may be of interest to the athletic population due to this modulation based on exercise-mode. Taken together, the findings communicated in this work suggest that hybrid athletes present with sleep characteristics that are in line with those found in other “classical” sport disciplines, although the type of training (resistance training vs. endurance training) appears to influence sleep quality, with a possible effect on cardiac autonomic activity observed both before and after sleep onset.

This study encompassed an ecologically valid design, which included athletes who had similar training characteristics, and without imposing specific regimens that might have affected their normal training routine or normal sleep function. The study therefore employed a cross-over design in random training order to minimize any potential bias depending on the days of the week, or order effect on sleep function. However, due to the participants’ tight training schedule, it was not possible to compare sleep outcomes after training days to sleep outcomes after full rest days, without influencing the athlete’s training schedule and periodization plans directly. Since this study has attempted to examine differences based on exercise mode, we did require somewhat comparable ‘workloads’ or ‘work completed’ bouts, which were generally compatible, although it remains that direct comparison between exercise modes could not take into account all real-world training complexities (e.g. nutritional loading, hydration status, energetics). Every effort was made to ensure a fair comparison was possible, and this effort was done by minimizing external factors researchers could control, e.g. requesting athletes to complete comparable overall bout durations, completing two-days with identical training and nutrition logs for a given mode, and ensuring all exercise was completed several hours before bedtime. Further, to reduce the influence of different chronotypes on sleep quality, “definitely evening” types were not included in this study, which might limit the generalizability of the results to athletes with such a chronotype. In the current study, only male participants volunteered for the study and were included in the final data analysis, therefore limiting the generalizability of these findings to female athletes. The researchers recognize far more studies are needed to clearly identify the influence of menstrual cycle and female-specific physiology on sleep and performance outcomes in female athletes (Hrozanova et al. 2021; Kullik et al. 2025). The use of a validated wearable medical device for objective sleep measurements allowed us to collect several data about sleep quality, quantity and architecture, with a minimally invasive protocol. Finally, the focus on hybrid athletes not only provided novel data in an understudied trained population, but also provided an insight into the influence of the type of training on sleep in athletes used to both training modalities. The findings presented herein suggest i) typical training routines in hybrid athletes do not impair sleep quality or quantity per se, at least when trainings are completed more than 3–4 hours before going to bed, however ii) cardiac arousals ( a sign of sympathetic activation) might affect sleep latency and “wake after sleep onset” parameters, so promoting relaxation practices, and good sleep hygiene techniques, are critical for athletes to encourage or improve sleep quality when training vigorously.