Modeling Performance in IRONMAN® 70.3 Age Group Triathletes
Our results prove that ML models can be used to examine the complex, non-linear interactions between the factors that influence performance and gain insights that can help IRONMAN<sup>®</sup> 70.3 age group triathletes better plan their races.
Authors
- Katja Weiss (ORCID: https://orcid.org/0000-0003-1247-6754)
- Beat Knechtle (ORCID: https://orcid.org/0000-0002-2412-9103)
- Marília Santos Andrade (ORCID: https://orcid.org/0000-0002-7004-4565)
- Pantelis Τ. Nikolaidis (ORCID: https://orcid.org/0000-0001-8030-7122)
- Mabliny Thuany (ORCID: https://orcid.org/0000-0002-6858-1871)
- Pedro Miguel Forte (ORCID: https://orcid.org/0000-0003-0184-6780)
- Elias Villiger (ORCID: https://orcid.org/0000-0001-8371-1390)
- Ivan Čuk (ORCID: https://orcid.org/0000-0001-7819-4384)
- David Valero (ORCID: https://orcid.org/0000-0003-4133-4843)
- Thomas Johannes Rosemann (ORCID: https://orcid.org/0000-0002-6436-6306)
Institutions
- University of St.Gallen (CH)
- Universidade do Estado do Pará (BR)
- University of Belgrade (RS)
- Universidade Politécnica de Bragança (PT)
- University of West Attica (GR)
- Medbase (CH)
- Tech Foundation (US)
- Universidade Federal de São Paulo (BR)
Publication Details
- Journal
- Sports Medicine - Open
- Published
- 2025-11-25
- DOI
- https://doi.org/10.1186/s40798-025-00948-0
- Primary Topic
- Sports Performance and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00