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Knechtle B, Cuk I, Andrade MS, Nikolaidis PT, Weiss K, Forte P, Thuany M. Case Report: Differences in self-selected pacing in 20, 40, and 60 ironman-distance triathlons: a case study. Front Sports Act Living 2024; 6:1155844. [PMID: 39351144 PMCID: PMC11439664 DOI: 10.3389/fspor.2024.1155844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 09/03/2024] [Indexed: 10/04/2024] Open
Abstract
Background Triathletes are pushing their limits in multi-stage Ironman-distance triathlons. In the present case study, we investigated the pacing during 20, 40, and 60 Ironman-distance triathlons in 20, 40, and 60 days, respectively, of one professional IRONMAN® triathlete. Case study Event 1 (20 Ironman-distance triathlons in 20 days), Event 2 (40 Ironman-distance triathlons in 40 days), and Event 3 (60 Ironman-distance triathlons in 60 days) were analyzed by discipline (swimming, cycling, running, and overall event time), by Deca intervals (10 days of consecutive Ironman-distance triathlons) and additional data (sleep duration, body mass, heart rate in cycling and running). To test differences between Events and Deca intervals within the same discipline, T-tests (2 groups) or one-way ANOVAs (3 or more groups) were used. Results Swimming splits were fastest in Event 1, (ii) cycling and running splits were fastest in both Event 2 and 3, (iii) overall speed was fastest in Event 3, (iv) sleep duration increased during Event 2 but decreased in Event 3, (v) body mass decreased in Event 2, but increased in Event 3 and (vi) heart rate during cycling was similar in both Event 2 and 3. In contrast, heart rate during running was greater in Event 3. Conclusion In a professional IRONMAN® triathlete finishing 20, 40, and 60 Ironman-distance triathlons in 20, 40, and 60 days, respectively, split performances and both anthropometrical and physiological changes such as body mass and heart rate differed depending upon the duration of the events.
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Affiliation(s)
- Beat Knechtle
- Medbase St. Gallen Am Vadianplatz, St. Gallen, Switzerland
- Institute of Primary Care, University Hospital Zurich, Zurich, Switzerland
| | - Ivan Cuk
- Faculty of Sport and Physical Education, University of Belgrade, Belgrade, Serbia
| | | | | | - Katja Weiss
- Institute of Primary Care, University Hospital Zurich, Zurich, Switzerland
| | - Pedro Forte
- Research Center for Active Living and Wellbeing, Instituto Politécnico de Bragança, Bragança, Portugal
- Research Center in Sports, Health and Human Development, Covilhã, Portugal
- Department of Sports Sciences, Instituto Politécnico de Bragança, Bragança, Portugal
| | - Mabliny Thuany
- Centre of Research, Education, Innovation and Intervention in Sport, Faculty of Sports, University of Porto, Porto, Portugal
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Cuk I, Markovic S, Weiss K, Knechtle B. Running Variability in Marathon-Evaluation of the Pacing Variables. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:218. [PMID: 38399506 PMCID: PMC10890654 DOI: 10.3390/medicina60020218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 01/21/2024] [Accepted: 01/24/2024] [Indexed: 02/25/2024]
Abstract
Background and Objectives: Pacing analyses for increasingly popular long-distance running disciplines have been in researchers' spotlight for several years. In particular, assessing pacing variability in long-distance running was hardly achievable since runners must repeat long-running trials for several days. Potential solutions for these problems could be multi-stage long-distance running disciplines. Therefore, this study aimed to assess the long-distance running variability as well as the reliability, validity, and sensitivity of the variables often used for pacing analyses. Materials and Methods: This study collected the split times and finish times for 20 participants (17 men and three women; mean age 55.5 years ± 9.5 years) who completed the multiday marathon running race (five marathons in 5 days), held as part of the Bretzel Ultra Tri in Colmar, France, in 2021. Seven commonly used pacing variables were subsequently calculated: Coefficient of variation (CV), Change in mean speed (CS), Change in first lap speed (CSF), Absolute change in mean speed (ACS), Pace range (PR), Mid-race split (MRS), and First 32 km-10 km split (32-10). Results: Multi-stage marathon running showed low variability between days (Intraclass correlation coefficient (ICC) > 0.920), while only the CV, ACS, and PR variables proved to have moderate to good reliability (0.732 < ICC < 0.785). The same variables were also valid (r > 0.908), and sensitive enough to discern between runners of different performance levels (p < 0.05). Conclusions: Researchers and practitioners who aim to explore pacing in long-distance running should routinely utilize ACS, CV, and PR variables in their analyses. Other examined variables, CS, CSF, MRS, and 32-10, should be used cautiously. Future studies might try to confirm these results using different multi-stage event's data as well as by expanding sensitivity analysis to age and gender differences.
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Affiliation(s)
- Ivan Cuk
- Faculty of Sport and Physical Education, University of Belgrade, 11000 Belgrade, Serbia
| | - Srdjan Markovic
- Faculty of Physical Education and Sports Management, Singidunum University, 11000 Belgrade, Serbia;
| | - Katja Weiss
- Institute of Primary Care, University of Zurich, 8006 Zurich, Switzerland;
| | - Beat Knechtle
- Institute of Primary Care, University of Zurich, 8006 Zurich, Switzerland;
- Medbase St. Gallen Am Vadianplatz, 9000 St. Gallen, Switzerland
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Ristanović L, Cuk I, Villiger E, Stojiljković S, Nikolaidis PT, Weiss K, Knechtle B. The pacing differences in performance levels of marathon and half-marathon runners. Front Psychol 2023; 14:1273451. [PMID: 38187410 PMCID: PMC10771621 DOI: 10.3389/fpsyg.2023.1273451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 11/21/2023] [Indexed: 01/09/2024] Open
Abstract
Introduction Many studies indicate a considerable impact of optimal pacing on long-distance running performance. Given that the amount of carbohydrates in metabolic processes increases supralinearly with the running intensity, we may observe differences between the pacing strategies of two long-distance races and different performance levels of runners. Accordingly, the present study aimed to examine the differences in pacing strategies between marathon and half-marathon races regarding the performance levels of runners. Methods The official results and split times from a total of 208,760 (marathon, N = 75,492; half-marathon, N = 133,268) finishers in the "Vienna City Marathon" between 2006 and 2018 were analyzed. The percentage of the average change of speed for each of the five segments (CS 1-5), as well as the absolute change of speed (ACS) were calculated. The CS 1-5 for the marathon are as follows: up to the 10th km, 10th - 20th km, 20th - 30th km, 30th - 40th km, and from the 40th km to the 42.195 km. For the half-marathon, the CS 1-5 are half of the marathon values. Four performance groups were created as quartiles of placement separately for sexes and races: high-level (HL), moderate to high-level (MHL), moderate to low-level (MLL), and low-level (LL). Results Positive pacing strategies (i.e., decrease of speed) were observed in all performance groups of both sex and race. Across CS 1-5, significant main effects (p < 0.001) were observed for the segment, performance level, and their interaction in both sex and race groups. All LL groups demonstrated higher ACS (men 7.9 and 6.05%, as well as women 5.83 and 5.49%, in marathon and half-marathon, respectively), while the HL performance group showed significantly lower ACS (men 4.14 and 2.97%, as well as women 3.16 and 2.77%, in marathon and half-marathon, respectively). Significant main effects (p < 0.001) for the race were observed but with a low effect size in women (ŋ2 = 0.001). Discussion Better runners showed more even pacing than slower runners. The half-marathoners showed more even pacing than the marathoners across all performance groups but with a trivial practical significance in women.
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Affiliation(s)
- Ljubica Ristanović
- Faculty of Sport and Physical Education, University of Belgrade, Belgrade, Serbia
| | - Ivan Cuk
- Faculty of Sport and Physical Education, University of Belgrade, Belgrade, Serbia
| | - Elias Villiger
- Klinik für Allgemeine Innere Medizin, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | | | - Pantelis T. Nikolaidis
- Exercise Physiology Laboratory, Nikaia, Greece
- School of Health and Caring Sciences, University of West Attica, Athens, Greece
| | - Katja Weiss
- Institute of Primary Care, University of Zurich, Zurich, Switzerland
| | - Beat Knechtle
- Institute of Primary Care, University of Zurich, Zurich, Switzerland
- Medbase St. Gallen Am Vadianplatz, St. Gallen, Switzerland
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Fariod M, Olher RR, Sousa CV, Scheer V, Cuk I, Nikolaidis PT, Thuany M, Weiss K, Knechtle B. Pacing Variation in Multistage Ultramarathons: Internet-Based Cross-Sectional Study. JMIR Form Res 2023; 7:e46650. [PMID: 37610796 PMCID: PMC10483293 DOI: 10.2196/46650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 05/14/2023] [Accepted: 05/15/2023] [Indexed: 08/24/2023] Open
Abstract
BACKGROUND Ultramarathon running is the most popular ultraendurance competition in terms of the number of races and runners competing annually worldwide; however, no study has compared pacing and performance over a long period. OBJECTIVE This study analyzes the pacing of successful finishers and nonfinishers in multistage ultramarathons worldwide. METHODS A total of 4079 athletes (men=3288; women=791) competing in 99 multistage ultramarathon events from 1983 to 2021 were analyzed, including the number of participants, age, gender, rank, and running speed of successful finishers. RESULTS The results showed a significant increase in the number of events (n=338) and a significant increase in the number of finishers and nonfinishers (n=5575) in the ultramarathons worldwide during this period. The general linear models (GLMs) of pacing variation showed nonsignificant effects for gender (F1,36.2=2.5; P=.127; ηp2=0.063) and age group (F10,10=0.6; P=.798; ηp2=0.367), but it showed a significant interaction (gender × age) effect (F10,2689=2.3; P=.008; ηp2=0.009). Post hoc analyses showed that men have a higher pacing variation than women in the under 30 years (U30), U35, U45, and U50 groups. Additionally, the fastest women's age group (U35) had the lowest pacing variation. The GLM of pacing variation by gender and event distance showed significant effects for both gender (F1,3=18.5; P<.001; ηp2=0.007) and distance (F2,3=20.1; P<.001; ηp2=0.015). Post hoc analyses showed a growing pacing variation with increasing race distance for both men and women. In addition, men had a higher variation in long events. Furthermore, there was a significant main effect for both genders (F1,3=33.7; P<.001; ηp2=0.012) and rank (F1,3=136.6; P<.001; ηp2=0.048) on performance, with men being faster than women. Pacing varied greatly due to gender (F1,3=4.0; P=.047; ηp2=0.001), with a lower (ie, more even) pacing variation for male athletes in the top 3 finishers. Male nonfinishers showed a higher performance than female nonfinishers (F1,1340=25.6; P<.001), and no difference was identified for pacing variation (F1,789=1.5; P=.228) based on gender. In addition, a weak but significant correlation (r=-0.130; P<.001) was identified between the average running speed and pacing variation for both female and male nonfinishers. CONCLUSIONS In summary, multistage ultramarathon competitions showed an increasing number of competitors and a higher performance challenge. Men have a higher pacing (ie, less even) variation than women, especially observed in longer events. A higher pacing variation was associated with lower performance for men, women, and nonfinishers.
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Affiliation(s)
- Mielad Fariod
- Department of Orthopedic, Traumatology and Reconstructive Surgery, Klinikum Frankfurt-Höchst, Frankfurt, Germany
| | - Rafael Reis Olher
- Department of Physical Education, University Center of Central Plateau Apparecido dos Santos, Brasilia, Brazil
| | - Caio Victor Sousa
- Health and Human Sciences, Loyola Marymount University, Los Angeles, CA, United States
| | - Volker Scheer
- Ultra Sports Science Foundation, Pierre-Benite, France
| | - Ivan Cuk
- Faculty of Sport and Physical Education, University of Belgrade, Belgrade,
| | | | | | - Katja Weiss
- Institute of Primary Care, University Hospital Zurich, Zurich, Switzerland
| | - Beat Knechtle
- Medbase St Gallen Am Vadianplatz, St Gallen, Switzerland
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Wirnitzer K, Tanous D, Motevalli M, Wagner KH, Raschner C, Wirnitzer G, Leitzmann C, Rosemann T, Knechtle B. Racing Experiences of Recreational Distance Runners following Omnivorous, Vegetarian, and Vegan Diets (Part B)-Results from the NURMI Study (Step 2). Nutrients 2023; 15:nu15102243. [PMID: 37242128 DOI: 10.3390/nu15102243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/03/2023] [Accepted: 05/06/2023] [Indexed: 05/28/2023] Open
Abstract
The potential running or endurance performance difference based on following different general types of diets, such as omnivorous, vegetarian, or vegan, remains questionable. Several underlying modifiable factors of long-distance running performance, especially runner training behaviors and experience, diminish the clarity of results when analyzing dietary subgroups. Based on the cross-sectional design (survey), the NURMI Study Step 2 aimed to investigate a plethora of training behaviors among recreational long-distance running athletes and the relationship of general diet types with best time race performance. The statistical analysis was based on Chi-squared and Wilcoxon tests. The final sample (n = 245) included fit recreational long-distance runners following an omnivorous diet (n = 109), a vegetarian diet (n = 45), or a vegan diet (n = 91). Significant differences were found between the dietary subgroups in body mass index (p = 0.001), sex (p = 0.004), marital status (p = 0.029), and running-related motivations for well-being (p < 0.05) but not in age (p = 0.054). No significant difference was found for best time half-marathon, marathon, and/or ultra-marathon race performance based on diet type (p > 0.05). Whether the vegan diet is associated with enhanced endurance performance remains unclear. Although, the present results are suggestive that 100% plant-based (vegan) nutrition is compatible with distance running performance at the least.
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Affiliation(s)
- Katharina Wirnitzer
- Department of Research and Development in Teacher Education, University College of Teacher Education Tyrol (PH Tirol), 6010 Innsbruck, Austria
- Department of Sport Science, University of Innsbruck, 6020 Innsbruck, Austria
- Research Center Medical Humanities, University of Innsbruck, 6020 Innsbruck, Austria
| | - Derrick Tanous
- Department of Research and Development in Teacher Education, University College of Teacher Education Tyrol (PH Tirol), 6010 Innsbruck, Austria
- Department of Sport Science, University of Innsbruck, 6020 Innsbruck, Austria
| | - Mohamad Motevalli
- Department of Research and Development in Teacher Education, University College of Teacher Education Tyrol (PH Tirol), 6010 Innsbruck, Austria
- Department of Sport Science, University of Innsbruck, 6020 Innsbruck, Austria
| | - Karl-Heinz Wagner
- Department of Nutritional Sciences, University of Vienna, 1090 Vienna, Austria
| | - Christian Raschner
- Department of Sport Science, University of Innsbruck, 6020 Innsbruck, Austria
| | | | - Claus Leitzmann
- Institute of Nutrition, University of Gießen, 35390 Gießen, Germany
| | - Thomas Rosemann
- Institute of Primary Care, University of Zurich, 8091 Zurich, Switzerland
| | - Beat Knechtle
- Institute of Primary Care, University of Zurich, 8091 Zurich, Switzerland
- Medbase St. Gallen, Am Vadianplatz, 9001 St. Gallen, Switzerland
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