## 4 Discussion
### Limits and Strengths  
The exclusion of athletes with irregular menstrual cycles or incomplete data may have limited the generalizability of our results to a wider population of female athletes. However, exclusions are evenly distributed. The requirement to follow at least two uninterrupted cycles ensures that athletes can continue to be monitored on a daily basis in real-life conditions. While our study benefits from a large and diverse cohort of elite athletes representing various sports, it is important to note that providing the exact timing of follow-up for each participant is not feasible. This is because training schedules, competition periods, and rest phases vary significantly, not only between sports but also among individual athletes, even within the same team. However, this diversity represents a strength of our methodology, as it ensures that the data captured reflects the athletes' real-life schedules. By incorporating participants from a wide range of sports, our findings are more broadly applicable to elite athletes in diverse contexts. Interaction tests between menstrual, weekly, and seasonal cycles were not statistically significant, but several factors may explain this result. Firstly, the variability of individual responses to these cycles could introduce heterogeneity, potentially masking significant interactions. Then, external factors such as variations in training programs, environmental influences, or unmeasured confounders may have diluted potential interaction effects. We recognize that the results may not be fully generalizable to amateur athletes or women of different age groups, as their experiences may vary due to factors such as training intensity, hormonal fluctuations, or other lifestyle factors. However, many of the patterns observed in our study, such as the impact of menstrual and seasonal cycles on mood and physical readiness, align with findings in the general population [3]. For instance, individuals in non-athletic contexts might also experience lower energy levels and mood disturbances during the premenstrual phase or improved overall wellness during summer months, which could influence daily life, such as workplace productivity or social engagement. At the same time, elite athletes differ from non-athletes in several respects. Their higher levels of physical activity and structured lifestyles--characterized by intense training schedules, precise recovery strategies, and careful monitoring of physiological metrics--may amplify or stabilize certain cyclical patterns. For example, regular physical activity is known to mitigate mood swings and improve sleep quality, which could buffer some of the fluctuations typically seen in non-athletic populations. The wellness data collected in this study relied on self-reported measures, which were inherently subjective. However, this subjectivity aligned with the aim of capturing the athletes' personal perceptions [36; 37] of their mood, sleep quality, and fitness levels. These variables were best assessed through self-report, as they reflected the athletes' lived experiences [38]. Daily reporting through a familiar application further ensured the reliability and consistency of the data. Fewer data points were collected during the summer due to the off-season for many athletes resulting in an uneven distribution of data across seasons. However, while some athletes had reduced training periods, many maintained a consistent training load. Conducting comprehensive daily monitoring for high-level athletes is challenging due to competitions and international travel. For the same reasons, only 35.0% of the included athletes performed accurate hormonal measurements, which may raise questions about the accuracy of our phase division. We acknowledge that a phase estimation may include anovulatory cycles and potential luteal phase deficiencies, comprising heterogenous hormonal profiles. Hence, the results cannot be attributed to hormonal fluctuations but rather to the moment in the cycle the athletes are in.