The association of origin and environmental conditions with performance in professional IRONMAN triathletes
Abstract We have (i) little knowledge about where the fastest professional IRONMAN triathletes originate from and where the fastest races take place and (ii) we have no knowledge of the optimal weather conditions for an IRONMAN triathlon. The aims of the present study were, therefore, (i) to investi...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-025-86033-8 |
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| author | Beat Knechtle Mabliny Thuany David Valero Elias Villiger Pantelis T. Nikolaidis Marilia S. Andrade Ivan Cuk Thomas Rosemann Katja Weiss |
| author_facet | Beat Knechtle Mabliny Thuany David Valero Elias Villiger Pantelis T. Nikolaidis Marilia S. Andrade Ivan Cuk Thomas Rosemann Katja Weiss |
| author_sort | Beat Knechtle |
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| description | Abstract We have (i) little knowledge about where the fastest professional IRONMAN triathletes originate from and where the fastest races take place and (ii) we have no knowledge of the optimal weather conditions for an IRONMAN triathlon. The aims of the present study were, therefore, (i) to investigate the origin and the fastest IRONMAN race courses for professional triathletes and (ii) 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. |
| format | Article |
| id | doaj-art-1a7de50242c547908737d74afc640b09 |
| institution | Kabale University |
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| spelling | doaj-art-1a7de50242c547908737d74afc640b092025-01-26T12:27:49ZengNature PortfolioScientific Reports2045-23222025-01-0115111710.1038/s41598-025-86033-8The association of origin and environmental conditions with performance in professional IRONMAN triathletesBeat Knechtle0Mabliny Thuany1David Valero2Elias Villiger3Pantelis T. Nikolaidis4Marilia S. Andrade5Ivan Cuk6Thomas Rosemann7Katja Weiss8Medbase St. Gallen Am VadianplatzDepartment of Physical Education, State University of ParaUltra Sports Science FoundationInstitute of Primary Care, University Hospital ZurichSchool of Health and Caring Sciences, University of West AtticaDepartment of Physiology, Federal University of Sao PauloFaculty of Sport and Physical Education, University of BelgradeInstitute of Primary Care, University Hospital ZurichInstitute of Primary Care, University Hospital ZurichAbstract We have (i) little knowledge about where the fastest professional IRONMAN triathletes originate from and where the fastest races take place and (ii) we have no knowledge of the optimal weather conditions for an IRONMAN triathlon. The aims of the present study were, therefore, (i) to investigate the origin and the fastest IRONMAN race courses for professional triathletes and (ii) 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.https://doi.org/10.1038/s41598-025-86033-8TriathlonIronmanSwimmingCyclingRunningRace prediction |
| spellingShingle | Beat Knechtle Mabliny Thuany David Valero Elias Villiger Pantelis T. Nikolaidis Marilia S. Andrade Ivan Cuk Thomas Rosemann Katja Weiss The association of origin and environmental conditions with performance in professional IRONMAN triathletes Scientific Reports Triathlon Ironman Swimming Cycling Running Race prediction |
| title | The association of origin and environmental conditions with performance in professional IRONMAN triathletes |
| title_full | The association of origin and environmental conditions with performance in professional IRONMAN triathletes |
| title_fullStr | The association of origin and environmental conditions with performance in professional IRONMAN triathletes |
| title_full_unstemmed | The association of origin and environmental conditions with performance in professional IRONMAN triathletes |
| title_short | The association of origin and environmental conditions with performance in professional IRONMAN triathletes |
| title_sort | association of origin and environmental conditions with performance in professional ironman triathletes |
| topic | Triathlon Ironman Swimming Cycling Running Race prediction |
| url | https://doi.org/10.1038/s41598-025-86033-8 |
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