Europe has the fastest Ironman race courses and the fastest Ironman age group triathletes

The majority of participants in Ironman triathlon races are age group athletes. We have extensive knowledge about recreational athletes’ training and competition participation. Nonetheless, Ironman age group triathletes must achieve fast race times to qualify for the Ironman World Championship in Hawaii. They can, therefore, benefit from knowing where the fastest Ironman racecourses in the world are. The aim of the present study was to investigate where the fastest Ironman racecourses for age group triathletes are located in the world. Data from 677,702 Ironman age group finishers’ records (544,963 from men and 132,739 from women) originating from 228 countries and participating in 444 events across 66 different Ironman race locations between 2002 and 2022 were analyzed. Data was analyzed through traditional descriptive statistics and with machine learning regression models. Four algorithms were tested (Random Forest Regressor, XG Boost Regressor, Cat Boot Regressor, and Decision Tree Regressor). The models used gender, age group, country of origin, environmental factors (average air and water temperatures), and the event location as independent variables to predict the final overall race time. Despite the majority of successful Ironman age group triathletes originating from the USA (274,553), followed by athletes from the United Kingdom (55,410) and Canada (38,264), these countries exhibited average overall race times that were significantly slower compared to the fastest countries. Most of the triathletes competed in Ironman Wisconsin (38,545), followed by Ironman Florida (38,157) and Ironman Lake Placid (34,341). The fastest overall race times were achieved in Ironman Copenhagen (11.68 ± 1.38 h), followed by Ironman Hawaii (11.72 ± 1.86 h), Ironman Barcelona (11.78 ± 1.43 h), Ironman Florianópolis (11.80 ± 1.52 h), Ironman Frankfurt (12.03 ± 1.38 h) and Ironman Kalmar (12.08 ± 1.47 h). The fastest athletes originated from Belgium (11.48 ± 1.47 h), followed by athletes from Denmark (11.59 ± 1.40 h), Switzerland (11.62 ± 1.49 h), Austria (11.68 ± 1.50), Finland (11.68 ± 1.40 h) and Germany (11.74 ± 15.1 h). Flat running and cycling courses were associated with faster overall race times. Three of the predictive models identified the ‘country’ and ‘age group’ variables as the most important predictors. Environmental characteristics showed the lowest influence regarding the other variables. The origin of the athlete was the most predictive variable whereas environmental characteristics showed the lowest influence. Flat cycling and flat running courses were associated with faster overall race times. The fastest overall race times were achieved mainly in European races such as Ironman Copenhagen, Ironman Hawaii, Ironman Barcelona, Ironman Florianópolis, Ironman Frankfurt and Ironman Kalmar. The fastest triathletes originated from European countries such as Belgium, Denmark, Switzerland, Austria, Finland, and Germany.

Analysis of the 72‑h ultramarathon using a predictive XG Boost model

Ultramarathon running enjoys unwavering popularity. This includes the 72-h run, the longest time-limited ultramarathon based on hours and not days, yet this specific race format remains understudied. In particular, we are still determining where the fastest 72-h ultra-marathoners originate or where the fastest races are held. The aim of the present study was to investigate the origins of the best performers and the locations of the fastest races. A machine learning model based on the XG Boost algorithm was built to predict running speed based on the athlete´s gender, age group, country of origin, the country where the race was held, the kind of race course (road, trail, track), and the elevation (flat, hilly). Model explainability tools were then used to investigate how each independent variable would influence the predicted running speed. A total of 2,857 race records from 1,870 unique runners from 36 different countries participating in 55 races held in 22 countries between 1989 and 2022 were analyzed. Athletes from the USA account for more than 2/3 of the sample size. Also, more than 3/4 of the participants competed in USA-based races. Athletes from Ireland, Japan, and Ukraine were the fastest. In respect of the fastest races, they were held in Ukraine, The Netherlands, and Japan. The model rated the country of event as the most important predictor followed by the race characteristics of elevation and race course, athlete country of origin, age group, and gender. On average, men were 0.33 km/h faster than women. The fastest running speeds were achieved by runners in age group 45–49 years. The country of the event was found to be the most important predictor in the 72-h run. Despite the dominance of runners from USA and the predominance of courses in the USA in terms of participation, athletes from Ireland, Japan, and Ukraine achieved the fastest times, while Ukraine, The Netherlands, and Japan were found to host the fastest courses.

Physiology and Pathophysiology of Marathon Running: A narrative Review

Marathon training and running have many beneficial effects on human health and physical fitness; however, they also pose risks. To date, no comprehensive review regarding both the benefits and risks of marathon running on different organ systems has been published. The aim of this review was to provide a comprehensive review of the benefits and risks of marathon training and racing on different organ systems. A predefined search strategy including keywords (e.g., marathon, cardiovascular system, etc.) and free text search was used. Articles covering running regardless of sex, age, performance level, and event type (e.g., road races, mountain marathons) were considered, whereas articles examining only cycling, triathlon, stress-tests or other sports were excluded. In total, we found 1021 articles in PubMed, Scopus, and Google Scholar, of which 329 studies were included in this review. Overall, marathon training offers several benefits for different organ systems and reduces all-cause mortality. As such, it improves cardiovascular risk factors, leads to favorable cardiac adaptations, enhances lung function, and improves quality of life in chronic kidney disease patients. It also enhances gastrointestinal mobility and reduces the risk of specific tumors such as colorectal cancer and hepatocellular carcinoma. Marathon training enhances bone health and skeletal muscle metabolism. It further positively affects hematopoiesis and cytotoxic abilities of natural killer cells, and may act neuroprotective on a long-term basis. After a marathon, changes in biomarkers suggesting pathological events in certain organ systems such as cardiovascular, renal, gastrointestinal, liver, hematological, immune, musculoskeletal, central nervous, and endocrine systems can often be observed. Mostly, these changes are limited to 1–3 days post-race and usually normalize within a week. Moreover, marathon running poses the risk of serious adverse events such as sudden cardiac death or acute liver failure. Concerning lung function, a decrease after a marathon race was observed. Acute kidney injury, as well as electrolyte imbalances, are relatively common amongst marathon finishers. Many runners complain of gastrointestinal symptoms during or after long-distance running. Many runners suffer from running-related musculoskeletal injuries often impairing performance. A marathon is often accompanied by an acute inflammatory response with transient immunosuppression, making runners susceptible to infections. Also, hormonal alterations such as increased cortisol levels or decreased testosterone levels immediately after a race are observed. Disturbances in sleep patterns are commonly found in marathon runners leading up to or directly after the race. All in all, marathon training is generally safe for human health and individual organ systems. Considering the high popularity of marathon running, these findings supply athletes, coaches, sports scientists, and sports medicine practitioners with practical applications. Further large-scale studies examining long-term effects on the cardiovascular, renal, and other system are needed.

The association of origin and environmental conditions with performance in professional IRONMAN triathletes

We have little knowledge about where the fastest professional IRONMAN triathletes originate from and where the fastest races take place and we have no knowledge of the optimal weather conditions for an IRONMAN triathlon. The aims of the present study were, therefore, to investigate the origin and the fastest IRONMAN race courses for professional triathletes and to evaluate the best environmental conditions (i.e. water and air temperatures and type of race course) for the fastest IRONMAN race times in professional IRONMAN triathletes. Data of all professional female and male IRONMAN triathletes competing between 2002 and 2022 in all IRONMAN races held worldwide were collected. A total of 6,943 finishers´ records (4,162 from men and 2,781 from women) from 58 different countries participating in 54 different event locations between 2002 and 2022 were considered. Data was analyzed using descriptive statistics and machine learning (ML) regression models. The models considered gender, country of origin, event location, water, and air temperature as independent variables to predict the final race time. Three different ML models were built and evaluated, based on three algorithms, in order of growing complexity and predictive power: Decision Tree Regressor, Random Forest Regressor, and XG Boost Regressor. Most of the athletes originated from the USA (1786), followed by athletes from Germany (674), Canada (426), Australia (396), United Kingdom (342), France (325), and Switzerland (276). Most of the athletes competed in IRONMAN Hawaii (925), IRONMAN Florida (563), IRONMAN Austria (452), IRONMAN France (354), IRONMAN Wisconsin (330), IRONMAN Lanzarote (322) and IRONMAN Texas (313). The Decision Tree and the XG Boost models were the best performing models (r2 = 0.48) and rated the relative feature importances in the order gender, country of origin, water temperature, air temperature and event location. Men were on average ~ 0.8 h faster than women. Switzerland had the fastest and Japan and Slovakia the slowest athletes. IRONMAN Brazil Florianopolis, IRONMAN Barcelona, and IRONMAN Louisville hold the fastest races. Optimal water temperature was over 22 °C and optimal air temperature between 19 and 26 °C. Between 2002 and 2022, most professional IRONMAN triathletes originated from the USA, and most professional IRONMAN triathletes competed in IRONMAN Hawaii. The fastest athletes originated from Switzerland, the fastest race courses were IRONMAN Brazil Florianopolis, IRONMAN Barcelona, and IRONMAN Louisville. The fastest race times were achieved in water temperature warmer than 22 °C and air temperature between 19 and 26 °C.

Ironman performance: How age, climate, and geography make or break success

From climate to age, this study reveals the factors that can take Ironman athletes from finishers to top performers.

Ironman performance: How age, climate, and geography make or break success

Running trends in Switzerland from 1999 to 2019: An exploratory observational study

Several single race events (5 km, 10 km, half-marathon, marathon, ultra-marathon) in different countries and different years have been analyzed in multiple studies, representing the rising interest in endurance-based activity and thus physical health. With focus on participation numbers, performance or sex difference, many single study results were obtained. The running trends in a whole country covering a longer period of time and several race distances are missing so far. The aim of this study is therefore to examine 5 km, 10 km, half-marathon, marathon and ultra-marathon races by age, sex, participation numbers and performance during two decades (1999–2019) for one country (Switzerland). In this exploratory observational study, we analyzed 1,172,836 finishers (370,517 women and 802,319 men) competing between 1999 and 2019 in 5 different race distances in Switzerland. We used publicly available data about the athletes and examined total finishing numbers, sex, age and performances (measured in m/s) via descriptive analyses and linear mixed models. Do-not-finishers were excluded. The most frequented race was the half-marathon (33.1% of finishers), the less frequented was the ultra-marathon distance (8.5% of finishers). In most recent years, only the number of finishers in ultra-marathon, especially in trail runs increased. In total, there were more male finishers (68.4%) than female finishers (31.6%) and only in 5 km races, more women finished than men (55.3%). Men were faster than women and both sexes were running slower in all race distances across years. Athletes in 10 km races had the best performance within the five analyzed race distances. Median age increased with longer race distance and decreased in ultra-marathon in recent years. In summary, finishing numbers especially in ultra-marathons increased with a focus on trail runs, female and male athletes had a declining performance across years in all race distances and men ran faster than women. Median age increased with longer race distance leading to more aged endurance-trained athletes. A downtrend in median age is found only in ultra-marathon in recent years. The results are important for athletes, race directors and coaches with regard to training schedules and the trend towards long distance races as well as for the medical attendance especially of older athletes, being more and more interested in endurance running.

The fastest nonprofessional age group IRONMAN triathletes in the world originate from Europe

It is well known that elite athletes of specific ethnicities and/or nationalities dominate certain sports disciplines (e.g., East Africans in marathon running). However, we do not know the nationalities of the fastest non-professional IRONMAN triathletes. Therefore, this study intended to identify the fastest athletes by country of origin competing in IRONMAN triathlon events, focusing on non-professional age group triathletes. Data from all IRONMAN age group athletes competing worldwide between 2002 and 2022 in all official IRONMAN races were collected. Sex, age group, country of origin of the athletes, location and year of the event, split times, overall race times, and transition times were obtained. Additionally, the dataset was augmented with specific data (i.e. event characteristics such as temperatures for water and air and course characteristics for all three split disciplines) related to the different race locations. We limited the analysis to the top 150 countries by participation (i.e. countries with at least 13 successful finishers records in the sample). A total of 677,320 records of IRONMAN age group triathletes originating from 150 different countries and participating in 443 races over 65 different locations were analyzed. European countries such as Germany, Austria, Denmark, Belgium, Switzerland, Norway, Czechia, Estonia, and Slovenia have the fastest IRONMAN age group athletes. IRONMAN Hawaii, IRONMAN Vitoria-Gasteiz and IRONMAN Hamburg are the fastest races. Hilly running and cycling race courses led to slower race times, while flat surfaces, rolling cycling and ocean swimming led to faster race times. Optimal water temperatures were found at 23–25 °C and optimal air temperature ranged between 19–21 and 25–28 °C. The fastest IRONMAN age group triathletes from European countries such as Germany, Austria, Denmark, Belgium, Switzerland, Norway, Czechia, Estonia, and Slovenia. With the presented results for optimal air and water temperatures and description of the optimal cycling and running course characteristics, IRONMAN age group athletes might be able to select an IRONMAN race with the best conditions in order to achieve a fast IRONMAN race time.

Comeback 2025

I’ll be back

60 Marathons

For the 60 marathons in 1 year, there was a special medal and a special gift.

In May 2025, the 2nd Eastern Switzerland Marathon Days will take place again in the Arbon area, this time 11 marathons in 11 days are planned.