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Plos One|August 22, 2024
Using machine learning to determine the nationalities of the fastest 100-mile ultra-marathoners and identify top racing eventsBeat Knechtle, Katja Weiss, David Valero, et al.
Sports Medicine - Open|November 25, 2025
Modeling Pe2rformance in IRONMAN<sup>®</sup> 70.3 Age Group TriathletesMabliny Thuany, David Valero, Elias Villiger, et al.
EXCLI Journal|August 28, 2023
Where are the fastest master butterfly swimmers competing in the FINA World Masters Championships from?Katja Weiss, Aldo Seffrin, Marilia Santos Andrade, et al.
Scientific Reports|April 29, 2026
Pacing profiles and slowdown patterns in ultra-triathlon performanceSrđan Marković, Ivan Cuk, Sasa Duric, et al.
Plos One|September 3, 2025
Sex differences in performance and pacing in the greatest Quintuple Iron ultra-triathlon race in history: The IUTA World Championship 2024 in FranceBeat Knechtle, Luciano Bernardes Leite, Sasa Duric, et al.
International Journal of Environmental Research and Public Health|February 25, 2023
A Machine Learning Approach to Finding the Fastest Race Course for Professional Athletes Competing in Ironman<sup>®</sup> 70.3 Races between 2004 and 2020Mabliny Thuany, David Valero, Elias Villiger, et al.
Scientific Reports|July 11, 2025
Change in elevation predicts 100 km ultra marathon performanceBeat Knechtle, Katja Weiss, David Valero, et al.
Plos One|December 9, 2024
The influence of origin and race location on performance in IRONMAN® age group triathletesBeat Knechtle, David Valero, Elias Villiger, et al.
Sports Medicine and Health Science|February 25, 2026
Resilience against exercise-related coronary atherosclerosis: A case study in a master athlete participating in 500 marathonsBeat Knechtle, Sasa Duric, Volker Scheer, et al.
Scientific Reports|March 16, 2025
Analysis of the 50-mile ultramarathon distance using a predictive XGBoost modelJonas Turnwald, David Valero, Pedro Forte, et al.
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