Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis

Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis It is well known that the fastest elite marathon runners come from East African countries such as Ethiopia and Kenya. However, to date, there is no information available on the origin of the fastest age group (master) marathoners. This study aimed to determine the countries of origin of the fastest age group marathoners who have participated in the ‘New York City Marathon’ over the past several decades. Race data from 1,009,839 runners (626,183 male and 383,656 female finishers) who completed the ‘New York City Marathon’ between 1999 and 2024 were analyzed. Participants were categorized into five-year age groups: <20, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49, 50–54, 55–59, 60–64, 65–69, 70–74, and 75 + years. The data were stratified by sex (male and female) and country of origin. The dataset was organized into five performance-based subgroups: (i) the entire dataset, including all finishers by age group and nationality; (ii) the top 100 finishers per age group; (iii) the top 30 finishers per age group; (iv) the top 10 finishers per age group; and (v) the top individual from each country within each age group. Regression analyses were conducted to explore demographic predictors of marathon performance. Participation generally increased over the study period, with temporary declines during the COVID-19 pandemic; male participation consistently outnumbered female participation, the 40–44 years age group was the most represented for both sexes, and participation was lowest in the youngest (< 20 years) and oldest (75 + years) age groups. Crucially, analyses focusing on the fastest age-group marathoners revealed clear nationality-based performance patterns. In younger adult age groups (20–39 years), the fastest average race times were predominantly achieved by female and male runners from Kenya and Ethiopia. The < 20 years age category showed comparatively stronger performances from European runners, including those from Poland, Switzerland and Italy. In the 50 years and older age groups, the best average times were increasingly recorded by runners from the United States of America, Japan, Germany and Switzerland. This shift highlights a regional transition in peak marathon performance with increasing age, from East African to European, North American, and East Asian dominance. Athletes’ origin trends in participation and performance of master runners in the New York City marathon (1999–2024): a sex- and age-group analysis | Scientific Reports

Mittelland Marathon

On December 28, 2025, the fifth edition of the Mittelland Marathon, the so-called “winter edition,” took place in Wangen an der Aare.

With temperatures of 1 °C, strong winds, and little sunshine, the runners had to complete six laps.

It was a good idea to add another marathon to the tally at the end of the year.

Cannero 6 ore

The fourth edition of Cannero 6 ore took place on December 7. Beautifully situated on Lake Maggiore, the race consisted of laps of 2145 m in length and 10 m in elevation gain on granite slabs and cobblestones. For a €25 entry fee, participants enjoyed a perfectly organized competition, with the village priest sending the runners on their way, a large buffet, and, at the end, a large medal and a backpack full of natural products.

Beat Knechtle Scholar Profiles and Rankings ScholarGPS

ScholarGPS has updated Scholar Profiles and Rankings. Beat Knechtle is listed as a highly ranked scholar in the fields of anthropometry, life sciences, and physiology. His H-index is 60. He ranks first in half marathons and second in world championships and Ironman triathlons.

The full evaluation can be found at Beat Knechtle | Scholar Profiles and Rankings | ScholarGPS

Modeling Performance in IRONMAN® 70.3 Age Group Triathletes

Individual factors related to performance in age group triathletes competing in different race distances have been explored in scientific literature. However, only a few studies have been conducted using machine learning (ML) predictive models to explore the importance of those individual factors. This study intended to build and analyze machine learning regression models that predict the performance of IRONMAN® 70.3 age group triathletes, considering sex, age, country of origin, and event location as predictive factors. A total of 823,464 finishers´ records (625,398 men and 198,066 women) of IRONMAN® 70.3 age group triathletes participating in 197 different events in 183 different locations between 2004 and 2020 were analyzed. The triathletes’ sex, age, country of origin, event location and year, and race finish times were thus obtained and considered for the study. Four different ML regression models were built to predict the triathletes’ race times from their age, sex, country of origin, and race location. The model with the best performance was then selected and further analyzed using model-agnostic interpretability tools to understand which factors would contribute most to the model predictions. The Random Forest Regressor model obtained the best predictive score. This model’s partial dependence plots indicated that men under 30 years, from Switzerland or Denmark, competing in IRONMAN®70.3 Austria/St. Polten, IRONMAN® 70.3 Switzerland, IRONMAN® 70.3 Sunshine Coast, and IRONMAN® 70.3 Busselton presented the best performance. Our results prove that ML models can be used to examine the complex, non-linear interactions between the factors that influence performance and gain insights that can help IRONMAN® 70.3 age group triathletes better plan their races.

Frauenfelder Marathon 2025

The Frauenfeld Marathon is a challenging 42.2-kilometer run with an elevation gain of 640 meters from Frauenfeld to Wil (SG) and back to Frauenfeld.

Although the run is very demanding, unfortunately there is only a very small medal.

Lago Maggiore Marathon 2025

On November 9, the Lake Maggiore Marathon took place once again in beautiful weather.

With a pacemaker, I was about 10 minutes faster than last year. The 4-hour mark is within reach.

The association between screening questions of anxiety and depression symptoms among endurance athletes

Anxiety is an important transdiagnostic factor for depression. Our purpose was to investigate the association between anxiety and depression symptoms among endurance runners. We used a cross-sectional, cross-country, web-based research design. A web survey was used to gather information about the runners’ general profile (age, sex, civil status, main sport, performance level, sports-specific characteristics, and training characteristics), anxiety symptoms (Generalized Anxiety Disorder-7), and depression symptoms (Patient Health Questionnaire-9). Network analysis was performed using the software JASP (Version 19). We sampled a total of 382 endurance men athletes, competing in ultramarathon (n = 226), marathon (n = 89), half-marathon (n = 55) or others. ANX_Q4 and DEPRESS_Q8 showed the highest strength and expected influence, indicating that are key bridge between anxiety and depressive symptoms and the rest of the network. Interventions that target relaxation capacity, body awareness, and recovery regulation could potentially attenuate the activation of both anxiety and depressive symptoms simultaneously.

10th Mostindien Marathon

On November 2, 2025, the next Mostindien Marathon took place in the form of a double-decker event. Twenty-four hours after the 9th event, it was pouring rain.

And only one person started the marathon on both days.