Sex-based performance analysis in Olympic triathlon: swimming, cycling, and running at Paris 2024

This study aimed to analyze sex differences in performance across the disciplines of the Olympic triathlon at the 2024 Paris Olympic Games. Performance times in swimming, cycling, running and transitions (T1 and T2) were compared between male (n = 50) and female (n = 51) athletes. Data were extracted from the official Olympic website and analyzed using the Mann–Whitney U test with effect size (Cohen’s d). Quantile regression was applied to examine the relationship between total race time and performance in each discipline of the Olympic triathlon. Male athletes outperformed females across all segments, including swimming, cycling, running, and transitions (p < 0.001). Cycling accounted for the largest proportion of total race time in both sexes (49.4% for females, 48.2% for males), while the contribution of running was slightly higher in males (29.8%) than in females (29.5%). Quantile regression revealed that cycling was the most influential predictor of total time among males, whereas running had greater impact among females, particularly in slower athletes (q = 0.75). Swimming was a consistent but less prominent predictor in both sexes, especially among faster athletes (q = 0.25). Transitions had limited influence in males but showed significant associations with performance among females at specific quantiles, notably in T2. These findings underscore the need for sex-specific training strategies, emphasizing running development in female triathletes and cycling optimization in males, while also considering the role of transitions, especially in draft-legal events.

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Women in the triathlon—the differences between female and male triathletes: a narrative review

Triathlon events have gained popularity in recent years. With the increasing participation of women, aspects that influence performance and physiology, as well as differences between women and men, are of interest to athletes and coaches. A review of the existing literature concerning differences between women and men in triathlon is lacking. Therefore, this narrative review aimed to compare female and male triathletes in terms of participation, performance, and the different influences on performance (e.g., physiology, age, pacing, motivation). A literature search was conducted in PubMed and Scopus using the search terms “female triathletes”, “women in triathlon”, “triathlon AND gender difference”, and “triathlon AND sex difference”. 662 articles were found using this search strategy, of which 147 were relevant for this review. All distances from sprint to ultra-triathlon (e.g., x-times IRONMAN® distance) were analyzed. The results showed that the participation of female triathletes, especially female master triathletes increased over time. An improvement in the performance of female and older triathletes was observed at the different distances in the last decades. Sex differences in performance varied across distances and in the three disciplines. Female triathletes showed a significantly lower VO2max and higher lactate thresholds compared to men. They also had a higher body fat percentage and lower body mass. The age for peak performance in the IRONMAN® triathlons is achieved between 25 and 39 years for both women and men. Strong predictors of IRONMAN® race performance in both female and male triathletes include achieving a personal best time in a marathon and a previous best time in triathlon races. Further studies need to balance the representation of female and male athletes in study cohorts to ensure that findings are relevant to both sexes. Another research gap that should be addressed by future studies is the effect of menstruation and female hormones, the presence of premenstrual syndrome, and the impact of pregnancy and childbirth on the triathlon performance to better understand the differences with men and to account for hormonal fluctuations in training.

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Marathons

After Beat Knechtle broke Frenchman Guy Rossi’s record for the most long-distance triathlons worldwide, the next record chase awaits. Now it’s all about the most marathons ever run by a Swiss.

Christian Marti’s record of 600 marathons is the next target.

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Congratulations on being named a 2024 Highly Ranked Scholar by ScholarGPS

ScholarGPS® is the world’s most comprehensive scholarly analytics platform, built by scholars but accessible to all. ScholarGPS® is comprised of powerful computational systems and processes such as novel data mining, artificial intelligence, machine learning, statistical analysis, as well as data distillation, interpretation, and presentation. ScholarGPS provides detailed profiles for each of over 30 million scholars and 120,000 research institutions, including over 24,000 academic institutions in more than 200 countries.

Beat Knechtle is among the highly ranked scholars with position 384 for Life Sciences, position 10 for Physiology and position 8 for Running Beat Knechtle | Scholar Profiles and Rankings | ScholarGPS

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No hyponatremia despite continuous plasma sodium decline in female runners during a seven stage ultramarathon

The role of sodium supplements and sex in the occurrence of exercise-associated hyponatremia (EAH) remains controversial. This study investigated hydration status in ultrarunners (19 males and 9 females) who completed seven marathons over seven consecutive days. Due to the limited number of female participants, no statistical comparison between sexes was performed. Plasma sodium concentration ([Na+]) and multiple hydration markers were assessed before, during, and after the race. Reported sodium supplement consumption showed no association with plasma [Na+]. An overall decline in plasma [Na+] was observed in females (regression slope = -1.278, p = 0.02) across the event, whereas no significant change was detected in males (slope = -0.325, p = 0.57). Additionally, no significant associations were found between plasma [Na+] and other monitored variables, including sodium supplement intake, pre-race hydration strategy, body mass, total body water, plasma osmolality, hematocrit, hemoglobin, urine specific gravity, urinary [Na+], thirst rating, or fluid intake reported pre-, during, and post-stage. No cases of symptomatic or asymptomatic hyponatremia were identified, suggesting that total fluid and sodium intake were adequate to maintain fluid-electrolyte balance and prevent EAH in both sexes.

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Race course characteristics are the most important predictors in 48 h ultramarathon running

Ultra-marathon running - where races are held in distance-limited (50 km, 50 miles, 100 km, 100 miles, etc.), time-limited (6 h, 12 h, 24 h, 48 h, 72 h, etc.), and multi-stage races - is gaining in popularity. However, we have no knowledge of where the fastest 48-hour runners originate and where the fastest 48-hour races are held. This study tried to determine the origin of the fastest 48-hour runners and the predictor factors associated with 48-hour ultra-marathon performance, such as age, gender, event country, country of origin and race course specific characteristics. A machine learning (ML) model based on the XG Boost algorithm was built to predict running speed from the athlete´s age, gender, country of origin, where the race occurs and race course characteristic such as elevation (flat or hilly) and surface (asphalt, cement, granite, grass, gravel, sand, track, or trail). Model explainability tools were then used to investigate how each independent variable would influence the predicted result. A sample of 16,233 race records from 7,075 unique runners originating from 60 different countries and participating in races held in 36 different countries between 1980 and 2022 was analyzed. Participation was spread across many countries, with USA, France, Germany, and Australia at the top of the participants’ rankings. Athletes from Japan, Israel, and Iceland achieved the fastest average running speed. The fastest races were held in Japan, France, Great Britain, Netherlands, and Egypt. The XG Boost model showed that elevation of the course (flat course) and the running surface (track) were the variables that had a larger influence on the running speed. The country of origin of the athlete and the country where the event was hold were the most important features by the SHAP analysis, yielding the broader range of model outputs. Men were ~ 0.5 km/h faster than women. Most finishers were 45–49 years old, and runners in this age group achieved the fastest running speeds. In summary, elevation of the course (flat course) and the running surface (track) were the most important variables for fast 48-hour races, whilst the country of origin of the athlete and the country where the event was hold would lead to the broadest difference in the predicted running speed range. Athletes from Japan, Israel, and Iceland achieved the fastest average running speed. The fastest races were held in Japan, France, Great Britain, Netherlands, and Egypt. Any athlete intending to achieve a personal best performance in this race format can benefit from these findings by selecting the most appropriate race course.

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