Browsing by Author "Cuk, Ivan"
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- Analysis of over 1 million race records shows runners from East African countries as the fastest in 50-km ultra-marathonsPublication . Weiss, Katja; Valero, David; Villiger, Elias; Thuany, Mabliny; Forte, Pedro; Gajda, Robert; Scheer, Volker; Sreckovic, Sreten; Cuk, Ivan; Nikolaidis, Pantelis Theo; Andrade, Marilia Santos; Knechtle, BeatThe 50-km ultra-marathon is a popular race distance, slightly longer than the classic marathon distance. However, little is known about the country of affiliation and age of the fastest 50-km ultra-marathon runners and where the fastest races are typically held. Therefore, this study aimed to investigate a large dataset of race records for the 50-km distance race to identify the country of affiliation and the age of the fastest runners as well as the locations of the fastest races. A total of 1,398,845 50-km race records (men, n = 1,026,546; women, n = 372,299) were analyzed using both descriptive statistics and advanced regression techniques. This study revealed significant trends in the performance of 50-km ultra-marathoners. The fastest 50-km runners came from African countries, while the fastest races were found to occur in Europe and the Middle East. Runners from Ethiopia, Lesotho, Malawi, and Kenya were the fastest in this race distance. The fastest 50-km racecourses, providing ideal conditions for faster race times, are in Europe (Luxembourg, Belarus, and Lithuania) and the Middle East (Qatar and Jordan). Surprisingly, the fastest ultra-marathoners in the 50-km distance were found to fall into the age group of 20–24 years, challenging the conventional belief that peak ultra-marathon performance comes in older age groups. These findings contribute to a better understanding of the performance models in 50-km ultra-marathons and can serve as valuable insights for runners, coaches, and race organizers in optimizing training strategies and racecourse selection.
- Biophysical characterization of the first ultra-cyclist in the world to break the 1,000 km barrier in 24-h non-stop road cycling: a case reportPublication . Knechtle, Beat; Forte, Pedro; Weiss, Katja; Cuk, Ivan; Nikolaidis, Pantelis Theo; Sousa, Caio Victor; Andrade, Marilia Santos; Thuany, MablinyA plethora of factors determine elite cycling performance. Those include training characteristics, pacing strategy, aerodynamics, nutritional habits, psychological traits, physical fitness level, body mass composition, and contextual features; even the slightest changes in any of these factors can be associated with performance improvement or deterioration. The aim of the present case report is to compare the performances of the same ultra-cyclist in achieving two world records (WR) in 24 h cycling. We have analyzed and compared the distance covered and speed for each WR. The 24 h period was split into four-time intervals (0-6 h; > 6-12 h; > 12-18 h; > 18-24 h), and we compared the differences in the distance covered and speed between the two WRs. For both WRs, a strong negative correlation between distance and speed was confirmed (r = -0.85; r = -0.89, for old and new WR, respectively). Differences in speed (km/h) were shown between the two WRs, with the most significant differences in 12-18 h (Delta = 6.50 km/h). For the covered distance in each block, the most significant differences were observed in the last part of the cycling (Delta = 38.54 km). The cyclist effective surface area (ACd) was 0.25 m(2) less and 20% more drag in the new WR. Additionally, the mechanical power was 8%, the power to overcome drag was 31%, and the power-weight ratio was 8% higher in the new WR. The mechanical efficiency of the cyclist was 1% higher in the new WR. Finally, the heart rate (HR) presented significant differences for the first 6 h (Old WR: 145.80 +/- 5.88 bpm; New WR: 139.45 +/- 5.82 bpm) and between the 12 and 18 h time interval (Old WR: 133.19 +/- 3.53 bpm; New WR: 137.63 +/- 2.80 bpm). The marginal gains concept can explain the performance improvement in the new WR, given that the athlete made some improvements in technical specifications after the old WR.
- Case Report: Differences in self-selected pacing in 20, 40, and 60 ironman-distance triathlons: a case studyPublication . Knechtle, Beat; Cuk, Ivan; Andrade, Marilia Santos; Nikolaidis, Pantelis Theo; Weiss, Katja; Forte, Pedro; Thuany, MablinyTriathletes 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.
- Cycling and Running are More Predictive of Overall Race Finish Time than Swimming in IRONMAN® Age Group TriathletesPublication . Knechtle, Beat; Valero, David; Villiger, Elias; Thuany, Mabliny; Cuk, Ivan; Forte, Pedro; Andrade, Marilia Santos; Nikolaidis, Pantelis T.; Rosemann, Thomas; Weiss, KatjaSeveral studies have evaluated the most predictive discipline (swimming, cycling, and running) of performance in elite IRONMAN® triathletes. However, no study has ever determined the most decisive discipline for IRONMAN® age group triathletes. The present study analyzed the importance of the three disciplines on the overall race times in IRONMAN® age group triathletes, in order to try and determine the most predictive discipline in IRONMAN® for age group triathletes, and whether the importance of the split disciplines changes with increasing age. This cross-sectional study used 687,696 IRONMAN® age group triathletes race records (553,608 from males and 134,088 from females). Age group athletes were divided in 5-year age groups (i.e., 18–24, 25–29, 30–34,…,70–74, and last 75 + years). The relationships between split disciplines (i.e., swimming, cycling, and running) and overall race times were evaluated using Spearman and Pearson correlations. A multi-linear regression model was used to calculate their prediction strength. The overall finish time correlated more with cycling and running times than with swimming times for both male and female IRONMAN® age group triathletes (r = 0.88 and r = 0.89 for females; r = 0.89 and r = 0.90 for males, respectively). All correlation coefficients decreased with increasing age, which was more noticeable for the swimming discipline. Both cycling and running are more predictive than swimming in IRONMAN® age group triathletes, where the correlation between the overall race times and the split times decreased with increasing age more in swimming than in cycling and running. These insights are useful for IRONMAN® age group triathletes and their coaches in planning their IRONMAN® race preparation and concentrating training on the more predictive disciplines.
- A machine learning approach to finding the fastest race course for professional athletes competing in Ironman® 70.3 races between 2004 and 2020Publication . Thuany, Mabliny; Valero, David; Villiger, Elias; Forte, Pedro; Weiss, Katja; Nikolaidis, Pantelis Theo; Andrade, Marília S.; Cuk, Ivan; Sousa, Caio Victor; Knechtle, BeatOur purpose was to find the fastest race courses for elite Ironman® 70.3 athletes, using machine learning (ML) algorithms. We collected the data of all professional triathletes competing between 2004 and 2020 in Ironman 70.3 races held worldwide. A sample of 16,611 professional athletes originating from 97 different countries and competing in 163 different races was thus obtained. Four different ML regression models were built, with gender, country of origin, and event location considered as independent variables to predict the final race time. For all the models, gender was the most important variable in predicting finish times. Attending to the single decision tree model, the fastest race times in the Ironman® 70.3 World Championship of around ~4 h 03 min would be achieved by men from Austria, Australia, Belgium, Brazil, Switzerland, Germany, France, the United Kingdom, South Africa, Canada, and New Zealand. Considering the World Championship is the target event for most professional athletes, it is expected that training is planned so that they attain their best performance in this event.
- Performance and pacing of professional IRONMAN triathletes: the fastest IRONMAN World Championship ever - IRONMAN Hawaii 2022Publication . Knechtle, Beat; Cuk, Ivan; Villiger, Elias; Forte, Pedro; Thuany, Mabliny; Andrade, Marilia Santos; Nikolaidis, Pantelis Theo; Weiss, KatjaPacing during cycling and running in an IRONMAN triathlon has been investigated in only one study with elite IRONMAN triathletes. We have, however, no knowledge of how professional triathletes pace during an IRONMAN World Championship. To investigate the split-by-split speed, pacing strategies and pacing variability in professional female and male IRONMAN World Championship participants in the fastest IRONMAN World Championship ever in IRONMAN Hawaii 2022. For both cycling and running, 25 specific split times were recorded in each discipline. The best 30 men and 30 women overall were chosen from the official IRONMAN website database for further analysis. They were divided into three performance groups: Top 10, 11–20th place, and 21st–30th place. Mean speed, individual linear regressions with the corresponding correlation coefficients, and coefficient of variation were calculated to assess split-by-split speed, pacing strategies, and pacing variability, respectively. In both men’s and women’s cycling and running segments, the top ten participants exhibited faster split times compared to the slower performance groups. Notably, no discernible differences existed between the 11–20th and 21st–30th place in men’s cycling and women’s running times. Conversely, in men’s running and women’s cycling segments, those in the 11–20th place displayed quicker times than those in the 21st–30th place. In the cycling segment across all groups, men demonstrated a more negative pacing pattern (indicating an increase in speed), whereas women exhibited more consistent pacing. In the running segment, the top 10 men and all women’s groups showcased relatively similar slightly positive pacing profiles. However, men ranking 11–20th and 21st–30th displayed more pronounced positive pacing strategies, implying a more significant decline in speed over time. In terms of cycling, the variability in pacing remained relatively consistent across the three performance groups. Conversely, during the running segment, the top ten male triathletes and those in the 11–20th place displayed lower pacing variability than their counterparts in the 21st–30th position place and all women’s groups. In summary, performance and pacing were examined in professional male and female IRONMAN World Championship participants during IRONMAN Hawaii 2022. Top performers showed faster cycling and running split times, with differences in pacing strategies between sexes. The pacing was more consistent in cycling, while running pacing varied more, particularly among male triathletes in different performance groups.
- A study of the fastest courses for professional triathletes competing in IRONMAN® triathlonsPublication . Thuany, Mabliny; Valero, David; Villiger, Elias; Fernandes, Matheus Santos Sousa; Forte, Pedro; Weiss, Katja; Nikolaidis, Pantelis Theo; Cuk, Ivan; Knechtle, BeatPurpose. The IRONMAN® triathlon is an endurance multisport discipline of high popularity. Professional IRONMAN® triathletes need to qualify for the IRONMAN® World Championships and, therefore, would benefit from identifying the fastest race courses. Our purpose was to identify the fastest races held for professional IRONMAN® triathletes competing from 2002 to 2022. Methods. This was an observational study, sampling 7,078 race records (380 different events in 55 different event locations) of professional IRONMAN® triathletes of both sexes (4,235 males and 2,843 females). We downloaded information about sex, nationality, both split (swimming, cycling, and running) and overall race times, the event location, and the year. Information about race course characteristics, water temperatures, and air temperatures was obtained. Descriptive statistics were calculated for each event location, and factorial ANOVA tests were used to explore the statistical significance of the results. A confidence interval of 95% was adopted. Results. The fastest overall IRONMAN® average race times were achieved during the IRONMAN® Tallinn, IRONMAN® Switzerland held in Thun, and IRONMAN® Des Moines. A lake for the swim split characterized the first five courses, while the bike split featured rolling or hilly terrain. For the run split, most of the courses were characterized as flat. For environmental characteristics, lower water and air temperatures also added time to the average finish time. Conclusions. Understanding the fastest race courses and their characteristics would assist professional IRONMAN® triathletes in selecting races that offer the optimal conditions for their competition. Fast IRONMAN® race courses typically feature a lakeside swim course, a rolling or hilly bike course, and a flat run course.
- The influence of origin and race location on performance in IRONMAN® age group triathletesPublication . Knechtle, Beat; Valero, David; Villiger, Elias; Thuany, Mabliny; Nikolaidis, Pantelis Theo; Cuk, Ivan; Andrade, Marilia Santos; Forte, Pedro; Braschler, Lorin; Rosemann, Thomas; Weiss, KatjaThe 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.
- There are the fastest master butterfly swimmers competing in the fina world masters championships from?Publication . Weiss, Katja; Seffrin, Aldo; Andrade, Marilia Santos; Ahmad, Wais; Forte, Pedro; Moreitz, Sascha; Stanula, Arkadiusz; Cuk, Ivan; Nikolaidis, Pantelis Theo; Knechtle, BeatWhile the butterfly stroke has received considerable attention in sports science, the origin of the fastest master butterfly swimmers remains unknown. The present study investigated which geographical locations produce the top-performing master butterfly swimmers within their age groups and gender. A total of 26,512 master butterfly swimmers (11,288 women and 15,224 men) competed in 50 m, 100 m and 200 m races in World Masters Championships held between 1986 and 2019. From each swimmer, the year of competition, first name, last name, age group and distance were recorded. Descriptive data were presented using mean, standard deviation, maximum and minimum values, and/or confidence intervals. The top 10 race times for master butterfly swimming and gender were identified for descriptive purposes. Nationalities were then grouped into six categories: the top five nationalities with the most appearances in the top 10 fastest times in butterfly swimming by distance each year and one group consisting of all other nationalities. In the event of a tie, the nationality with the most participants overall was selected. Generalized linear models (GLMs) with a gamma probability distribution and log link function were used to assess the effect of age groups and gender on swimming time. In summary, Germany had the fastest women butterfly master swimmers across all distances, while the USA had the fastest men butterfly master swimmers for all distances. Men covered all distances faster than women and younger swimmers were quicker than older swimmers. The results of this study can be utilized to determine the countries that produce the most successful master butterfly swimmers, providing a foundation for further research to explore the factors that lead to their success.
- Where are the fastest master butterfly swimmers competing in the fina world masters championships from?Publication . Weiss, Katja; Seffrin, Aldo; Andrade, Marilia Santos; Ahmad, Wais; Forte, Pedro; Moreitz, Sascha; Stanula, Arkadiusz; Cuk, Ivan; Nikolaidis, Pantelis Theo; Knechtle, BeatWhile the butterfly stroke has received considerable attention in sports science, the origin of the fastest master butterfly swimmers remains unknown. The present study investigated which geographical locations produce the top-performing master butterfly swimmers within their age groups and gender. A total of 26,512 master butterfly swimmers (11,288 women and 15,224 men) competed in 50 m, 100 m and 200 m races in World Masters Cham-pionships held between 1986 and 2019. From each swimmer, the year of competition, first name, last name, age group and distance were recorded. Descriptive data were presented using mean, standard deviation, maximum and minimum values, and/or confidence intervals. The top 10 race times for master butterfly swimming and gender were identified for descriptive purposes. Nationalities were then grouped into six categories: the top five nation-alities with the most appearances in the top 10 fastest times in butterfly swimming by distance each year and one group consisting of all other nationalities. In the event of a tie, the nationality with the most participants overall was selected. Generalized linear models (GLMs) with a gamma probability distribution and log link function were used to assess the effect of age groups and gender on swimming time. In summary, Germany had the fastest women butterfly master swimmers across all distances, while the USA had the fastest men butterfly master swimmers for all distances. Men covered all distances faster than women and younger swimmers were quicker than older swim-mers. The results of this study can be utilized to determine the countries that produce the most successful master butterfly swimmers, providing a foundation for further research to explore the factors that lead to their success.