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The influence of origin and race location on performance in IRONMAN® age group triathletes

2024Journal article Open access
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dc.contributor.authorKnechtle, Beat
dc.contributor.authorValero, David
dc.contributor.authorVilliger, Elias
dc.contributor.authorThuany, Mabliny
dc.contributor.authorNikolaidis, Pantelis Theo
dc.contributor.authorCuk, Ivan
dc.contributor.authorAndrade, Marilia Santos
dc.contributor.authorForte, Pedro
dc.contributor.authorBraschler, Lorin
dc.contributor.authorRosemann, Thomas
dc.contributor.authorWeiss, Katja
dc.date.accessioned2025-01-13T10:52:07Z
dc.date.available2025-01-13T10:52:07Z
dc.date.issued2024
dc.description.abstractThe IRONMAN® (IM) triathlon is a popular multi-sport, where age group athletes often strive to qualify for the IM World Championship in Hawaii. The aim of the present study was to investigate the location of the fastest IM racecourses for age group IM triathletes. This knowledge will help IM age group triathletes find the best racecourse, considering their strengths and weaknesses, to qualify. To determine the fastest IM racecourse for age group IM triathletes using descriptive and predictive statistical methods. We collected and analyzed 677,702 age group IM finishers’ records from 228 countries participating in 444 IM competitions held between 2002 and 2022 across 66 event locations. Locations were ranked by average race speed (performance), and countries were sorted by number of records in the sample (participation). A predictive model was built with race finish time as the predicted variable and the triathlete’s gender, age group, country of origin, event location, average air, and water temperatures in each location as predictors. The model was trained with 75% of the available data and was validated against the remaining 25%. Several model interpretability tools were used to explore how each predictor contributed to the model’s predictive power, from which we intended to infer whether one or more predictors were more important than the others. The average race speed ranking showed IM Vitoria-Gasteiz (1 race only), IM Copenhagen (8 races), IM Hawaii (18 races), IM Tallinn (4 races) and IM Regensburg (2 races) in the first five positions. The XG Boost Regressor model analysis indicated that the IM Hawaii course was the fastest race course and that male athletes aged 35 years and younger were the fastest. Most of the finishers were competing in IM triathlons held in the US, such as IM Wisconsin, IM Florida, IM Lake Placid, IM Arizona, and IM Hawaii, where the IM World Championship took place. However, the fastest average times were achieved in IM Vitoria-Gasteiz, IM Copenhagen, IM Hawaii, IM Tallin, IM Regensburg, IM Brazil Florianopolis, IM Barcelona, or IM Austria with the absolutely fastest race time in IM Hawaii. Most of the successful IM finishers originated from the US, followed by athletes from the UK, Canada, Australia, Germany, and France. The best mean IM race times were achieved by athletes from Austria, Germany, Belgium, Switzerland, Finland, and Denmark. Regarding environmental conditions, the best IM race times were achieved at an air temperature of ∼27°C and a water temperature of ∼24°C. IM age group athletes who intend to qualify for IM World Championship in IM Hawaii are encouraged to participate in IM Austria, IM Copenhagen, IM Brazil Florianopolis, and/or IM Barcelona in order to achieve a fast race time to qualify for the IM World Championship in IM Hawaii where the top race times were achieved. Most likely these races offer the best ambient temperatures for a fast race time.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationKnechtle, Beat; Valero, David; Villiger, Elias; Thuany, Mabliny; Nikolaidis, Pantelis T.; Cuk, Ivan; Andrade, Marilia Santos; Forte, Pedro; Braschler, Lorin; Rosemann, Thomas; Weiss, Katja (2024). The influence of origin and race location on performance in IRONMAN® age group triathletes. PLOS One. ISSN 1932-6203. 19:12, p. 1-23pt_PT
dc.identifier.doi10.1371/journal.pone.0315064pt_PT
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/10198/30936
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherPLOSpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectTriathlonpt_PT
dc.subjectMulti-sportpt_PT
dc.subjectPerformancept_PT
dc.subjectRace speedpt_PT
dc.subjectResearch Subject Categories::INTERDISCIPLINARY RESEARCH AREAS::Sportspt_PT
dc.titleThe influence of origin and race location on performance in IRONMAN® age group triathletespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage23pt_PT
oaire.citation.issue12pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titlePLOS ONEpt_PT
oaire.citation.volume19pt_PT
person.familyNameForte
person.givenNamePedro
person.identifier.ciencia-id351B-B16B-79C7
person.identifier.orcid0000-0003-0184-6780
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication3ecc6d1b-07a4-40d7-81f4-df6fd7b3d5b0
relation.isAuthorOfPublication.latestForDiscovery3ecc6d1b-07a4-40d7-81f4-df6fd7b3d5b0

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