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

Mabliny Thuany, David Valero, Elias Villiger, Pedro Forte, Katja Weiss, Pantelis T. Nikolaidis, Marília Santos Andrade, Ivan Cuk, Caio Victor Sousa and Beat Knechtle ()
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Mabliny Thuany: Faculty of Sports, University of Porto, 4200-450 Porto, Portugal
David Valero: Ultra Sports Science Foundation, 69310 Pierre-Benite, France
Elias Villiger: Klinik für Allgemeine Innere Medizin, Kantonsspital St. Gallen, 9000 St. Gallen, Switzerland
Pedro Forte: CI-ISCE, Higher Institute of Educational Sciences of the Douro, 4560-708 Penafiel, Portugal
Katja Weiss: Institute of Primary Care, University Hospital Zurich, 8091 Zurich, Switzerland
Pantelis T. Nikolaidis: School of Health and Caring Sciences, University of West Attica, 12243 Athens, Greece
Marília Santos Andrade: Department of Physiology, Federal University of São Paulo, São Paulo 04021-001, Brazil
Ivan Cuk: Faculty of Sport and Physical Education, University of Belgrade, 11000 Belgrade, Serbia
Caio Victor Sousa: Health and Human Sciences, Loyola Marymount University, Los Angeles, CA 90045, USA
Beat Knechtle: Institute of Primary Care, University Hospital Zurich, 8091 Zurich, Switzerland

IJERPH, 2023, vol. 20, issue 4, 1-12

Abstract: 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.

Keywords: endurance; cycling; half-distance Ironman; swimming; triathlon; running (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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