Evidence map›Paper›PMID 39652572›Full record

ArticlePloS one2024

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

Beat Knechtle, David Valero, Elias Villiger, Mabliny Thuany, Pantelis T Nikolaidis, Ivan Cuk, Marilia Santos Andrade, Pedro Forte, Lorin Braschler, Thomas Rosemann and 1 more

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Beat KnechtleMedbase St. Gallen Am Vadianplatz, St. Gallen, Switzerland.ORCID 0000-0002-2412-9103
David ValeroUltra Sports Science Foundation, Pierre-Benite, France.
Elias VilligerInstitute of Primary Care, University of Zurich, Zurich, Switzerland.ORCID 0000-0001-8371-1390
Mabliny ThuanyDepartment of Physical Education, State University of Para, Pará, Brazil.
Pantelis T NikolaidisSchool of Health and Caring Sciences, University of West Attica, Athens, Greece.
Ivan CukFaculty of Sport and Physical Education, University of Belgrade, Belgrade, Serbia.
Marilia Santos AndradeDepartment of Physiology, Federal University of Sao Paulo, Sao Paulo, Brazil.
Pedro ForteCI-ISCE, Higher Institute of Educational Sciences of the Douro, Penafiel, Portugal.ORCID 0000-0003-0184-6780
Lorin BraschlerFaculty of Medicine, University of Bern, Bern, Switzerland.
Thomas RosemannInstitute of Primary Care, University of Zurich, Zurich, Switzerland.
Katja WeissInstitute of Primary Care, University of Zurich, Zurich, Switzerland.ORCID 0000-0003-1247-6754

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

objectiveTo determine the fastest IM racecourse for age group IM triathletes using descriptive and predictive statistical methods.

methodsWe 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.

resultsThe 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.

conclusionsIM 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.

Indexed as

AthletesAthletic PerformanceBicyclingAdolescentAdultAgedAge FactorsFemaleHawaiiHumansMaleMiddle AgedRunningSwimmingYoung Adult

Identifiers

PMID39652572
PMCPMC11627357

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.