A macro to micro analysis to understand performance in 100-mile ultra-marathons worldwide

Thuany, Mabliny; Weiss, Katja; Villiger, Elias; Scheer, Volker; Ouerghi, Nejmeddine; Gomes, Thayse Natacha; Knechtle, Beat

doi:10.1038/s41598-023-28398-2

Cited by 5 publications

(2 citation statements)

References 45 publications

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“…Participation of females in ultra-marathon is an important aspect since the percentage of female runners is generally low in these races 9 , 40 . Lower participation of female runners compared to male runners overestimates the decline in age-related performance, especially in very old females 41 .…”

Section: Discussionmentioning

confidence: 99%

Elderly female ultra-marathoners reduced the gap to male ultra-marathoners in Swiss running races

Knechtle

Witthöft

Valero³

et al. 2023

Sci Rep

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Recent studies showed that female runners reduced the performance gap to male runners in endurance running with increasing age and race distance. However, the investigated samples were generally small. To investigate this further, the present study examined sex differences by age across various race distances (5, 10 km, half-marathon, marathon, and ultra-marathon) using a large dataset of over 1,100,000 race records from Switzerland over two decades (1999–2019). The study explored performance and participation disparities between male and female runners by employing diverse methods, such as descriptive statistics, histograms, scatter and line plots, correlations, and a predictive machine learning model. The results showed that female runners were more prevalent in shorter races (5, 10 km, half-marathon) and outnumbered male runners in 5 km races. However, as the race distance increased, the male-to-female ratio declined. Notably, the performance gap between sexes reduced with age until 70 years, after which it varied depending on the race distance. Among participants over 75 years old, ultra-marathon running exhibited the smallest sex difference in performance. Elderly female ultra-marathoners (75 years and older) displayed a performance difference of less than 4% compared to male ultra-marathoners, which may be attributed to the presence of highly selected outstanding female performers.

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Section: Discussionmentioning

confidence: 99%

Elderly female ultra-marathoners reduced the gap to male ultra-marathoners in Swiss running races

Knechtle

Witthöft

Valero³

et al. 2023

Sci Rep

Self Cite

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“…Ironman ® ‘70.3’ refers to the total distance in miles (113.0 km) of the race, consisting of a 1.2 mile swim, a 56 mile bike ride, and a 13.1 mile run. Among different research topics involving endurance athletes, the interest in understanding the environmental characteristics related to the place of competition and country of origin of the athletes has increased over the last few years [ 3 , 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Approach to Finding the Fastest Race Course for Professional Athletes Competing in Ironman® 70.3 Races between 2004 and 2020

Thuany

Valero²,

Villiger

et al. 2023

IJERPH

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Our purpose was to find the fastest race courses for elite Ironman® 70.3 athletes, using machine learning (ML) algorithms. We collected the data of all professional triathletes competing between 2004 and 2020 in Ironman 70.3 races held worldwide. A sample of 16,611 professional athletes originating from 97 different countries and competing in 163 different races was thus obtained. Four different ML regression models were built, with gender, country of origin, and event location considered as independent variables to predict the final race time. For all the models, gender was the most important variable in predicting finish times. Attending to the single decision tree model, the fastest race times in the Ironman® 70.3 World Championship of around ~4 h 03 min would be achieved by men from Austria, Australia, Belgium, Brazil, Switzerland, Germany, France, the United Kingdom, South Africa, Canada, and New Zealand. Considering the World Championship is the target event for most professional athletes, it is expected that training is planned so that they attain their best performance in this event.

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Analysis of over 1 million race records shows runners from East African countries as the fastest in 50-km ultra-marathons

Weiss,

Valero,

Villiger

et al. 2024

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The 50-km ultra-marathon is a popular race distance, slightly longer than the classic marathon distance. However, little is known about the country of affiliation and age of the fastest 50-km ultra-marathon runners and where the fastest races are typically held. Therefore, this study aimed to investigate a large dataset of race records for the 50-km distance race to identify the country of affiliation and the age of the fastest runners as well as the locations of the fastest races. A total of 1,398,845 50-km race records (men, n = 1,026,546; women, n = 372,299) were analyzed using both descriptive statistics and advanced regression techniques. This study revealed significant trends in the performance of 50-km ultra-marathoners. The fastest 50-km runners came from African countries, while the fastest races were found to occur in Europe and the Middle East. Runners from Ethiopia, Lesotho, Malawi, and Kenya were the fastest in this race distance. The fastest 50-km racecourses, providing ideal conditions for faster race times, are in Europe (Luxembourg, Belarus, and Lithuania) and the Middle East (Qatar and Jordan). Surprisingly, the fastest ultra-marathoners in the 50-km distance were found to fall into the age group of 20–24 years, challenging the conventional belief that peak ultra-marathon performance comes in older age groups. These findings contribute to a better understanding of the performance models in 50-km ultra-marathons and can serve as valuable insights for runners, coaches, and race organizers in optimizing training strategies and racecourse selection.

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A macro to micro analysis to understand performance in 100-mile ultra-marathons worldwide

Cited by 5 publications

References 45 publications

Elderly female ultra-marathoners reduced the gap to male ultra-marathoners in Swiss running races

Elderly female ultra-marathoners reduced the gap to male ultra-marathoners in Swiss running races

A Machine Learning Approach to Finding the Fastest Race Course for Professional Athletes Competing in Ironman® 70.3 Races between 2004 and 2020

Analysis of over 1 million race records shows runners from East African countries as the fastest in 50-km ultra-marathons

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