Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Original article 177 ABSTRACT Elite athletes experience substantial psychological and physical stress that can undermine motivation and engagement in daily training and competition. Drawing on the Job Demands–Resources (JD-R) model, this study examines how daily sport-related stress affects sport engagement in elite athletes, focusing on the mediating role of attentional focus and the moderating role of REM sleep. Nineteen professional female handball players from Slovenia participated in a 60-day experience sampling study during the competitive season. Participants completed daily mobile surveys assessing stress, focus, and engagement, and wore validated Oura rings to track nightly REM sleep. In total, 1,020 daily observations were collected and analyzed using multilevel modeling. The results indicate that higher levels of perceived stress were associated with lower sport engagement the following day. This negative relationship was positively mediated by attentional focus: although stress tended to impair concentration, individuals who maintained higher attentional focus remained more engaged. Importantly, REM sleep moderated this relationship such that the negative impact of stress on engagement was slightly attenuated following nights with more REM sleep. The study extends JD-R theory by identifying REM sleep as a physiological buffer against stress. Practically, the results support interventions targeting stress management, attentional control, and sleep quantity to maintain sport engagement. We used a lagged daily design in which stress reported on Day 1 and REM sleep recorded during Night 1 predicted focus and engagement assessed on Day 2. The study demonstrates the value of combining self-reports with objective sleep tracking to understand within-athlete fluctuations in well-being and performance. Keywords: sport engagement, sport-related stress, attentional focus, REM sleep, job demands–resources model 1 University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia 2 Gimnazija Bežigrad, Ljubljana, Slovenia IZVLEČEK Vrhunski športniki doživljajo znatne psihološke in telesne obremenitve, ki lahko oslabijo motivacijo in zavzetost za vsakodnevne treninge in tekmovanja. Na podlagi Modela delovnih zahtev in virov (JD-R) v prispevku preučujemo, kako dnevni delovni stres vpliva na športno zavzetost vrhunskih športnikov, pri čemer je naš glavni cilj preučiti vlogo osredotočenosti kot mediatorja in REM spanja kot moderatorja. V raziskavi je sodelovalo devetnajst poklicnih rokometašic iz Slovenije, ki so v času tekmovalne sezone sodelovale v 60-dnevni študiji z metodo izkustvenega vzorčenja. Udeleženke so vsak dan izpolnjevale mobilne vprašalnike o stresu, osredotočenosti in zavzetosti ter ponoči nosile validirane prstane Oura, ki so beležili njihovo REM spanje. Skupno je bilo zbranih 1.020 dnevnih opazovanj, ki smo jih analizirali z uporabo večnivojskega modeliranja. Rezultati kažejo, da so bile višje ravni zaznanega stresa povezane z nižjo športno zavzetostjo naslednji dan. V tej negativni povezavi kot mediator nastopa osredotočenost. To pomeni, da kljub temu, da stres zmanjšuje koncentracijo, športnice z višjo ravnijo osredotočenosti ohranjajo večjo zavzetost pri športu. Ključna ugotovitev je tudi, da REM spanje omili negativni vpliv dnevnega delovnega stresa na zavzetost, ki je nekoliko manjši po nočeh z več REM spanja. Študija bogati teorijo JD-R z vključitvijo REM spanja kot fiziološkega blažilca stresa. S praktičnega vidika rezultati podpirajo aktivnosti za obvladovanje stresa, nadzor osredotočenosti in količino spanja za ohranjanje športne zavzetosti. Uporabili smo zamaknjen dnevni raziskovalni dizajn, v katerem smo stres merili zvečer, REM spanje ponoči, osredotočenost in zavzetost pa nato ocenili naslednji dan. Študija tudi poudarja pomen kombinacije samoocenjevanja in objektivnega spremljanja spanja za razumevanje dobrega počutja in uspešnosti športnikov. Ključne besede: zavzetost pri športu, s športom povezan stres, osredotočenost, REM spanje, model delovnih zahtev in virov * Corresponding author: Jure Andolšek University of Ljubljana, School of Economics and Business, Kardeljeva pl. 17, 1000 Ljubljana, Slovenia E-mail: jure.andolsek@ef.uni-lj.si https://doi.org/10.52165/kinsi.31.2.177-190 Jure Andolšek 1,* Rok Čater 2 STRESSED BUT STILL IN THE GAME: HOW FOCUS AND REM SLEEP SHAPE DAILY ENGAGEMENT IN ELITE ATHLETES POD STRESOM, A ŠE VEDNO V IGRI: KAKO OSREDOTOČENOST IN REM SPANJE OBLIKUJETA VSAKODNEVNO ZAVZETOST VRHUNSKIH ŠPORTNIKOV Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 178 INTRODUCTION Elite athletes face continual psychological and physical demands. Striving for excellence in high-pressure sporting environments requires extended training sessions, frequent competitions, rigorous travel schedules, and constant performance expectations – all contributing to elevated stress levels (Nicholls & Polman, 2007; Lundqvist & Sandin, 2014). While short-term stress can be motivating, prolonged or excessive stress impairs emotional well-being, reduces motivation, and undermines athletic performance (Fletcher & Sarkar, 2012). Recent reviews confirm that stress is a pervasive and multifaceted issue for elite athletes, encompassing both competitive and organizational dimensions (Nuetzel, 2023; Halson et al., 2021). These effects are not only cumulative but also fluctuate significantly from day to day, highlighting the need for research that captures within-person processes in real time (Tenenbaum et al., 2013; McCormick et al., 2015). A particularly vulnerable domain in this regard is sport engagement; a state marked by high vigor, dedication, and absorption in sport-related tasks (Lonsdale et al., 2007). Engaged athletes tend to be more committed, focused, and emotionally invested in their performance, which predicts greater achievement and lower burnout risk (Hodge et al., 2009). However, elevated stress may compromise athletes’ ability to sustain engagement. In occupational contexts, stress consistently reduces daily work engagement (Sonnentag, 2003; Bakker & Demerouti, 2007), raising the question of whether the same holds true for elite athletes. In this study, we conceptualize work stress as perceived sport-related stress; that is, the psychological pressure and strain athletes experience in relation to their daily training, performance demands, recovery expectations, and sport-related responsibilities. We therefore hypothesize: H1: Sport-related stress negatively affects sport engagement of elite athletes. Evidence points to attentional focus as a possible central mechanism in this relationship. By attentional focus, we refer to the athlete’s capacity to maintain concentration on task-relevant cues while resisting internal or external distractions during training or competition (Wulf, 2013). Stress often leads to intrusive thoughts, emotional distraction, or cognitive overload, impairing concentration (Laborde et al., 2014; Wilson et al., 2009). In sport, reduced focus is linked to poor decision-making, increased performance errors, and lower task involvement (Janelle, 2002; Nideffer, 1990). Athletes who struggle to concentrate may find it harder to immerse themselves in training or competition, even when physically prepared. Studies using the Test of Attentional and Interpersonal Style (TAIS) highlight that maintaining focus under Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 179 pressure is critical for elite performance (Nideffer, 2002). day-to-day changes in focus explain how stress leads to disengagement. However, few studies have explored whether day-to-day changes in focus explain how stress leads to disengagement. One notable exception is Van Yperen et al. (2015), who found that attentional states fluctuate meaningfully and relate to daily motivation in athletes. Similarly, McCormick et al. (2018) emphasized the dynamic nature of focus under pressure, but did not test it as a mediator between stress and engagement. To address this gap, we propose: H2: Attentional focus mediates the relationship between sport-related stress and sport engagement of elite athletes. Beyond cognitive mechanisms, REM sleep (Rapid Eye Movement sleep) is emerging as a vital yet underexplored personal resource in elite sport. REM sleep is the stage of sleep associated with vivid dreaming and emotional processing (Blumberg et al., 2020). REM sleep supports emotional processing, neural plasticity, and stress regulation (Walker & van der Helm, 2009; Goldstein & Walker, 2014). Neurophysiological evidence shows that REM sleep dampens noradrenergic activity linked to arousal and fear responses, enabling emotional recovery (van der Helm et al., 2011). Psychologically, REM sleep may enhance stress resilience by facilitating overnight emotional recalibration (Suchecki et al., 2012). While general sleep quality is associated with engagement and performance in both workplace (Litwiller et al., 2017) and athletic contexts (Samuels, 2008), the moderating role of REM sleep in daily sport engagement remains largely unexplored. Accordingly, we hypothesize: H3: REM sleep moderates the relationship between sport-related stress and sport engagement of elite athletes. Our conceptual model (Figure 1) is grounded in the Job Demands–Resources (JD-R) framework (Bakker & Demerouti, 2007), which posits that stress, as a demand, depletes personal energy and reduces engagement unless counterbalanced by resources – whether external or internal. Applied to elite sport, we conceptualize REM sleep as a replenishable personal resource that may buffer the negative effects of daily stress. We also examine attentional focus as a key pathway through which stress undermines athletes’ capacity to stay buffered and committed to sport tasks. To test this model in real time, we used a lagged day- level design, in which perceived stress was assessed on Day 1, REM sleep recorded during the following night (Night 1), and focus and engagement measured on Day 2. Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 180 Figure 1. The hypothesized model. METHODS Participants Nineteen female professional handball players from RK Krim Mercator (Ljubljana, Slovenia) took part in the study. The club competes at the highest national level and regularly in the European Champions League, making these athletes highly experienced and accustomed to intense training and competitive pressure. The sample represented nearly the entire first-team roster for the 2022/2023 season. Participants had a mean age of 24.3 years (SD = 3.2, range 19– 30) and averaged 12.3 years of playing experience. All were full-time athletes training daily. Inclusion criteria were team membership and being healthy enough to train and compete during the study period. While players with sleep-related conditions were not efouxplicitly excluded, none reported such issues during pre-study screening. All participants provided written informed consent. The study was approved by the Institutional Ethics Committee of the University of Ljubljana. Data were treated confidentially. To encourage daily compliance, players received personalized feedback on their sleep and wellness data post-study. Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 181 Design and procedure We used an experience sampling method (ESM) with daily diary surveys over a two-month mid-season period (December 2022 to January 2023), which included regular training, league matches, and a brief winter break. Each participant wore an Oura Ring (Gen2), a validated wearable device that tracks physiological signals and estimates nightly REM sleep duration. The Oura Ring has shown high agreement with gold-standard polysomnography for sleep detection and good accuracy in identifying sleep stages (de Zambotti et al., 2019), making it suitable for research use. Participants received a mobile survey link each evening at 9:00 PM and were asked to complete it before bedtime, reflecting on that day’s training or competition. The survey took approximately 3–5 minutes and measured perceived stress, attentional focus, and sport engagement. Responses were time-stamped, and adherence was monitored. Compliance was high, with participants completing surveys on 89% of study days (range: 80–100%), resulting in 1,020 of 1,140 possible daily observations (19 athletes × 60 days). At the end of the study, sleep data were exported from participants’ Oura profiles – accessed via the app’s sharing feature – and matched to their daily survey responses. The analysis focused on REM sleep duration. To examine the interaction between sleep and stress on next-day outcomes, we temporally aligned data so that stress was assessed on Day 1, REM sleep during the following night (Night 1), and focus and engagement on Day 2. This lagged design allowed us to explore how prior-day stress and sleep jointly influence next-day cognitive and motivational states. Measures All psychological measures in the daily survey were adapted from validated instruments to capture state-level (daily) experiences. Unless otherwise noted, responses were recorded on 5- point Likert scales (1 = very low/strongly disagree, 5 = very high/strongly agree), referencing “today” or “today’s training/match”. The model includes four key variables: • Perceived stress (independent variable): Daily stress was assessed using a shortened version of the Perceived Stress Scale – PSS (Chiu et al., 2016), adapted for day-level reporting. Four items were selected and reworded to reflect daily experience. The items were: “Today, how often did you feel that difficulties were piling up so high you could not overcome them?”, “Today, how often did you feel unable to control the important things in your life?”, “Today, how often did you feel confident about your ability to handle personal problems?” (reverse Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 182 coded), and “Today, how often did you feel that things were going your way?” (reverse coded). Athletes rated the extent to which they felt stressed or overwhelmed that day. A mean score of the four items (two reverse-coded per PSS guidelines) represented daily stress, with higher values indicating greater perceived stress. • Sport engagement (dependent variable): Engagement was measured using a brief version of the Athlete Engagement Questionnaire – AEQ (Lonsdale et al., 2007), capturing daily expressions of confidence, vigor, dedication, and enthusiasm. To keep the survey brief, we used one item for each dimension. Specifically, athletes rated: “Today, I felt energetic and vigorous in my sport activities”, “Today, I was enthusiastic about playing/training”, “Today, I felt confident in my sport capabilities”, and “Today, I was dedicated to giving my best in my sport”. The mean of these four items indexed daily sport engagement (higher scores reflect stronger engagement). • Attentional focus (mediator): Focus was measured using two items based on the Test of Attentional and Interpersonal Style – TAIS (Nideffer, 1990), targeting two key aspects of sport-relevant attention: narrowing focus on task-relevant cues and resisting distraction. The items were: “Today, I was able to stay focused on my training/competition tasks without getting distracted”, and “I concentrated well on what was important during practice or the game today”. Responses were averaged, with higher scores indicating better attentional focus. While these items were derived from an established instrument, they have not been formally validated for daily (state-level) use, and results should be interpreted with this limitation in mind. • REM sleep duration (moderator): Measured in minutes, REM sleep was tracked nightly using the Oura ring. Given existing validation studies supporting its accuracy in detecting REM sleep, we used the recorded values as an objective indicator of REM sleep quantity. To account for individual differences that could influence engagement or stress reactivity, we measured three baseline (once, at the start of the study) control variables using single-item indicators for brevity. Resilience (Smith et al. 2008) was assessed with “I tend to bounce back quickly after difficulties”, adapted from the Brief Resilience Scale. Motivational climate (Newton et al., 2000) was captured by “Our team environment motivates me to improve and do my best”, reflecting perceptions of a supportive vs. pressuring environment. Emotional stability (John & Srivastava, 1999) was measured with “I see myself as emotionally stable (not easily upset or anxious)”, indexing general emotional resilience. All items were rated on a 1–5 scale. Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 183 Statistical analysis Given the nested structure of our data (daily observations within individuals), we employed multilevel modeling (hierarchical linear modeling) to test our hypotheses. A two-level model was specified, with daily measures at Level 1 and person-level variables at Level 2. Analyses were conducted using the MLmed macro in SPSS. The analytic procedure included the following steps: • Data preparation: Daily stress (Day 1), REM sleep (Night 1), and next-day attentional focus and engagement (Day 2) were temporally aligned to assess how stress and sleep affect subsequent cognitive–motivational states. Level-1 predictors (stress, focus, REM) were person-mean centered to reflect within-person variation, while Level-2 controls (resilience, motivational climate, emotional stability) were grand-mean centered. • Descriptive statistics: Means, standard deviations, and intercorrelations among study variables were calculated to assess distribution and relationships. • Hypotheses testing: We used multilevel models to test three key effects. Significance of the indirect effect was determined using bootstrapped confidence intervals. RESULTS Descriptive statistics Descriptive statistics, including means, standard deviations, and within-/between-person correlations, are presented in Table 1. Table 1. Descriptive statistics (means, standard deviations, and pairwise correlations). Variables Mean SD Sport- related stress Attention al focus Sport engage- ment REM sleep duration Resilience Motiva- tional climate Emotio- nal stability Sport-related stress 2.05 1.01 - Attentional focus 4.11 0.54 .036 - Sport engagement 4.13 0.56 .018 .653** - REM sleep duration 70.78 35.81 .109 -.108 .027 - Resilience 3.54 0.62 .099 .049 .169* .211** - Motivational climate 3.89 0.49 .074 .149* .162* -.063 .215** - Emotional stability 3.54 0.52 .110 .124 -.105 -.307** .018** .164** - Notes: **p < .01; *p < .05; †p < .10. Hypotheses testing Table 2 presents the hypothesis testing results. For H1 (X → Y), daily stress was found to significantly predict lower next-day engagement (−0.7402, p = 0.0044). For H2 (X → M → Y), Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 184 attentional focus was found to significantly and positively mediate the negative relationship between stress and engagement (0.2029, p = 0.0271). Finally, H3 (X × W → Y) was supported, showing that REM sleep moderates the link between stress and engagement. Table 2. Results of longitudinal analyses using MLmed Moderated-mediation model Predicting Focus as mediating variable Predicting Sport engagement as outcome variable Within-effects (across time) Constant 4.05 (2.29) 2.98 (1.98) Sport-related stress 0.271 (0.120) -0.740** (-0.257) Attentional focus 0.750** (0.065) Indirect effect of Focus 0.203** (0.092) Interaction effect: REM sleep duration × Stress 0.000** (0.000) Between-effects (between individuals) REM sleep duration 0.000 (0.000) Sport-related stress -0.160 (0.239) 0.017 (0.270) Attentional focus 0.701* (0.242) Resilience 0.069 (0.309) 0.247 (0.236) Motivational climate 0.635 (0.437) 0.025 (0.361) Emotional stability 0.029 (0.016) -0.024 (0.013) Indirect effect of Focus -0.113 (0.183) Interaction effect: REM sleep duration × Stress 0.000 (0.000) Moderated model fit (BIC) 1177.306 Notes: **p < .01; *p < .05; †p < .10. DISCUSSION Theoretical implications This study explored how daily stress affects sport engagement in elite athletes, focusing on the roles of attentional focus and REM sleep. Using intensive longitudinal data from professional female handball players, we found that daily stress undermined athletes’ engagement by disrupting their ability to stay mentally focused (H1), consequently highlighting attentional focus as a key mediating mechanism in this process (H2). However, when athletes had sufficient REM sleep the night before, this negative effect of stress was significantly reduced (H3). Together, these findings confirm that daily engagement in sport is shaped not only by psychological demands like stress, but also by the athlete’s cognitive resources and physiological recovery. Our results align with recent evidence showing that psychological stress is one of the most significant predictors of well-being and performance variability in elite athletes (Nuetzel, 2023; Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 185 Halson et al., 2021). While most studies have emphasized cumulative or chronic effects, our day-level approach complements this by revealing short-term fluctuations in engagement as a function of daily stress and recovery. For example, Savage and Torgler (2011) showed that stress impacts performance under pressure, consistent with our finding that stress impairs engagement unless buffered by sleep and attentional control. To our knowledge, this is among the first studies to combine experience sampling with objective sleep tracking in elite sport and apply the JD-R model to within-person variation in sport engagement. Our findings highlight the intertwined roles of psychological and physiological processes in athletes’ daily motivation and well-being. Our results extend JD-R theory into elite sport. Within this framework, daily stress functions as a demand that drains personal energy, reducing engagement unless buffered by sufficient resources. We demonstrated the demand–strain pathway at the individual level by showing that, even within the same athlete, higher stress was associated with lower engagement. This pattern is consistent with findings from workplace research (Demerouti et al., 2001), where elevated stress has been linked to reduced work engagement. Crucially, we identified attentional focus as a mediating mechanism. Sport and cognitive psychology suggest that stress taxes attentional and working memory resources – through worry, distraction, or self-monitoring – limiting the ability to stay task-focused. By measuring focus daily, we showed that stress impaired concentration, which in turn lowered engagement. This bridges JD-R with attentional control theory, indicating that stress weakens top-down focus, likely diminishing the intrinsic rewards of sport activity. Future models of athlete burnout and motivation would benefit from including cognitive mediators like focus as part of the daily loss cycle driven by demands. We also contribute to JD-R research by identifying sleep – specifically REM sleep – as a key personal resource in sport. While JD-R includes personal resources like self-efficacy, sleep remains underexplored in this context. Our data show that athletes who had more REM sleep the previous night were less vulnerable to the disengaging effects of stress. REM sleep supports emotional processing and physiological recovery (Walker & van der Helm, 2009), and our results suggest it bolsters resilience against daily stressors. Put simply, better REM sleep seemed to buffer the effects of stress, helping athletes maintain stable engagement. Schleupner and Kühnel (2021) similarly found that good sleep promotes work engagement via improved mental health. Our study complements this by demonstrating a direct moderating effect of REM Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 186 sleep on a daily timescale. These findings integrate physiological recovery into the JD-R framework and reinforce the role of the mind–body connection in sustaining athlete motivation. Practical implications Our findings have clear practical implications. First, the robust negative impact of stress on engagement suggests that stress management is essential for maintaining athlete motivation. Coaches and organizations should monitor stress levels – whether sport-related or stemming from life events – and offer appropriate support such as counseling, rest, or coping skills training. Proactive stress management may help prevent engagement dips that could evolve into poor training quality or burnout. Second, since focus plays a mediating role, it is important to support athletes in maintaining attentional control under pressure. Mindfulness exercises, pre-performance routines, and attentional refocusing techniques are already common in sport psychology. Our findings offer additional support for these approaches, showing that staying focused not only improves performance but also helps athletes remain engaged and enjoy their sport. Coaches might incorporate drills that simulate pressure and train athletes to redirect attention using cue words or routines. Enhancing this cognitive buffer could reduce athletes’ susceptibility to everyday stress. Third, our results emphasize the protective value of quality, particularly REM-rich, sleep for recovery and mental resilience. While it is well known that poor sleep impairs performance, we show that even within normal variation, more REM sleep helps insulate athletes from the effects of stress. Teams should promote sleep hygiene and consider tracking sleep (e.g., using wearables like Oura rings) to ensure athletes are not just getting enough sleep but enough REM sleep. Adjusting training schedules, improving sleep environments, and teaching relaxation techniques could enhance REM duration. The finding that stress had minimal impact on engagement after nights of high REM sleep offers a powerful message: better sleep may help athletes stay motivated under pressure. This is especially important during intense competition periods, when stress peaks and recovery is crucial. Sports organizations may even consider adjusting early training times post-travel to allow full REM sleep cycles. Limitations and suggestions for future research This study has several limitations. First, the small and homogeneous sample – 19 elite female handball players from one team in Slovenia – helped control for extraneous variation but limits Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 187 generalizability. Results may differ in male athletes, other sports, or non-elite populations. Replication in larger and more diverse samples is needed to assess broader applicability. Future studies could also explore how these dynamics unfold in different types of sports (e.g., endurance vs. power-based disciplines), in mixed-gender or male teams, and in settings where interpersonal dynamics may influence engagement. Investigating how team-level processes interact with individual-level stress and recovery would offer a valuable extension of the present model. Second, we relied on self-reported measures of stress, focus, and engagement. Although we used validated instruments (adapted PSS, TAIS, AEQ), self-reports are susceptible to mood and social desirability bias. Still, the within-person daily design – where participants serve as their own controls – helps reduce some of these concerns. Future studies could benefit from adding objective indicators such as coach ratings or training data to triangulate engagement. Third, causal interpretation is constrained by the observational design, as stress, focus, and engagement were measured around the same time each day. While our model assumes stress affects focus, which in turn shapes engagement, these processes likely unfold dynamically and may influence each other reciprocally. We attempted to structure the timing so that perceived daily stress could precede training focus and end-of-day engagement. Nonetheless, future studies could apply lagged analyses (e.g., prior-day stress predicting next-day engagement) or experimental manipulation (e.g., stress induction) to strengthen causal inference. Fourth, while the moderated mediation model fit the data well, unmeasured day-level factors (e.g., training intensity, coach behavior) may also affect engagement. We included baseline resilience, team climate, and training stability to account for some stable third variables, but daily confounds remain possible. Finally, although the Oura ring offers a practical way to estimate REM sleep, it does not directly measure brain activity, and sleep staging errors may occur. We assume such errors are random. Validation studies for Oura Gen2 support the reliability of our REM estimates, yet future research should consider polysomnography or complementary measures (e.g., subjective sleep quality, daytime fatigue) for a more comprehensive view. While we focused on REM sleep due to its theorized role in stress and emotional regulation, other dimensions – such as total sleep time, deep sleep, and sleep consistency – may also influence stress-related outcomes. Our findings offer a starting point for deeper exploration of sleep’s role in athletic recovery. Kinesiologia Slovenica, 31, 2, 177-190 (2025), ISSN 1318-2269 Focus, Sleep and Engagement in Elite Athletes 188 CONCLUSION Despite its limitations, this study offers novel insights into the daily mechanisms that shape sport engagement. Our findings highlight how stress, cognitive focus, and sleep quality interact dynamically to influence motivation and involvement in sport. Elevated perceived stress can undermine engagement, primarily by impairing the athlete’s ability to maintain focused attention. However, sufficient REM sleep appears to buffer against these negative effects, helping athletes remain engaged even under pressure. 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