Over 1 million race information present East Africans as quickest in 50-km ultra-marathons

In a current examine printed within the journal Scientific Experiences, researchers investigated the age and race places of elite ultra-marathon runners, in addition to the nation they had been affiliated with.

Their outcomes point out that the quickest runners are from nations in Africa, like Ethiopia and Kenya, with the quickest races occurring in Center Jap nations and Europe, and the height efficiency age is between 20 and 24 years.

Examine: Evaluation of over 1 million race information reveals runners from East African nations because the quickest in 50-km ultra-marathons. Picture Credit score: lzf / Shutterstock


Extremely-marathons, outlined as races exceeding the usual marathon distance (42.2 km) or lasting longer than six hours, embody each distance-limited and time-limited codecs. Amongst these, the 50 km race is a well-liked and accessible entry level for marathoners searching for higher challenges.

Prior analysis on ultra-marathons has examined efficiency developments, efficiency variations linked to age, intercourse variations, inflammatory responses, dietary wants, cardiovascular impacts, and operating biomechanics.

Regardless of intensive exploration, the nationwide origins of the quickest 50 km runners remained unstudied. Identified for his or her dominance in conventional marathons, East African runners’ efficiency in ultra-marathons, notably on the 50 km distance, lacked comparable investigation.

Research on longer races, just like the 100-km and 100-mile races, recognized high performers from Japan, Russia, Brazil, Sweden, and Hungary, with potential influences from doping scandals.

Contrarily, youthful runners (these between 18 and 24 years) had been discovered to be slower in 100-km occasions, elevating questions on peak efficiency ages in shorter ultra-marathons.

In regards to the examine

This examine addressed current analysis gaps by analyzing the age and nation of affiliation of the quickest 50-km ultra-marathoners and figuring out the place the quickest races had been situated.

The examine analyzed a dataset comprising 1,398,845 race information from 549,154 distinctive runners throughout 122 nations. Every file included contributors’ affiliated nation, gender, age, occasion location, 12 months, and imply race pace.

Knowledge was cleaned to take away incomplete information and duplicates and categorized into age teams of 5 years. Information from nations with fewer than ten entries had been excluded to attenuate noise.

The evaluation concerned visualizing histograms for age teams and race speeds and rating nations by their imply race pace. To foretell race pace, a regression mannequin was developed utilizing encoded variables, comparable to athlete gender, age group, athlete nation, and occasion nation.

The mannequin’s efficiency was evaluated and validated utilizing imply absolute error (MAE) and R² metrics, prediction distribution plots, and have significance.


The examine analyzed 1,398,845 race information from 549,154 distinctive runners, together with 1,026,546 males and 372,299 girls, from 122 nations competing in 50-km races held in 86 places between 1894 and 2022.

The variety of feminine racers taking part elevated over time, decreasing the male-to-female ratio. Males averaged sooner speeds (8.2 km/h) than girls (7.4 km/h), with the 20-24 age group being the quickest (8.3 km/h).

The quickest runners had been from Ethiopia (14.1 km/h), Lesotho (13.1 km/h), Malawi (12.4 km/h), and Kenya (12.3 km/h). Compared, the quickest races occurred in Luxembourg (11.4 km/h), Belarus (11.3 km/h), Lithuania (11.2 km/h), Qatar (11.2 km/h), and Jordan (10.7 km/h).

The regression mannequin indicated that the occasion nation was the strongest predictor of race pace (66%), with athlete gender (23%), age group (7%), and athlete nation (5%) following. The mannequin achieved an R² of 0.36 and an MAE of 1.4 km/h.

A multivariate linear regression (MLR) mannequin yielded an analogous R² of 0.325, with all predictors being statistically vital. Univariate fashions confirmed occasion and athlete nation as vital predictors individually (R² = 0.279 and R² = 0.260, respectively), indicating a excessive stage of correlation.


The examine aimed to establish elite ultra-marathoners within the 50 km class by nation, the places of the quickest races, and their age.

It discovered that the quickest racers had been from African nations (Malawi, Lesotho, Kenya, and Ethiopia), the quickest racecourses had been in Europe and Center Jap nations, and the quickest age group was between 20 and 24 years, opposite to expectations of older peak efficiency.

The examine’s findings spotlight the affect of geographic and demographic components on ultra-marathon efficiency. They align with earlier analysis highlighting East African dominance in distance operating, attributed to genetic predispositions, high-altitude coaching, conventional diets, and sociocultural components.

Nonetheless, in contrast to prior research that usually targeted on marathon efficiency peaking round 35 years or older, this examine discovered that youthful athletes (20-24 years) excelled within the 50-km races.

The examine’s strengths embody a big dataset and a complete evaluation of predictors influencing race efficiency. Nonetheless, it has limitations, comparable to potential pattern bias as a consequence of socioeconomic components and the exclusion of environmental variables like temperature and humidity.

Future analysis ought to delve into the precise physiological and psychological traits that permit younger runners to excel in 50-km races and take into account a extra granular evaluation of participant demographics to account for socioeconomic influences.

Understanding these components can higher inform coaching and improvement applications for ultra-marathon runners.

Journal reference:

  • Evaluation of over 1 million race information reveals runners from East African nations because the quickest in 50-km ultra-marathons. Weiss, Okay., Valero, D., Villiger, E., Thuany, M., Forte, P., Gajda, R., Scheer, V., Sreckovic, S., Cuk, I., Nikolaidis, P.T., Andrade, M.S., Knechtle, B. Scientific Experiences (2024). DOI: 10.1038/s41598-024-58571-0, https://www.nature.com/articles/s41598-024-58571-0

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