Michael Stiefel

Master triathletes have not reached limits in their Ironman triathlon performance

The purpose of this study was to analyze the participation and performance trends of male triathletes in the “Ironman Switzerland” from 1995 to 2010. Participation trends of all finishers aged between 18 and 64 years were analyzed over the 16‐year period by considering four 4‐year periods 1995–1998, 1999–2002, 2003–2006, and 2007–2010, respectively. The 3.8‐km swimming, 180‐km cycling, 42‐km running times, and total race times were analyzed for the top 10 triathletes in each age group from 18 to 64 years. The participation of master triathletes (≥40 years old) increased over the years, representing on average 23%, 28%, 37%, and 48% of total male finishers during the four 4‐year periods, respectively. Over the 1995–2010 period, triathletes older than 40 years significantly improved their performance in swimming, cycling, running, and in the total time taken to complete the race. The question whether master Ironman triathletes have yet reached limits in their performance during Ironman triathlon should be raised. Further studies investigating training regimes, competition experience, or socio‐demographic factors are needed to gain better insights into the phenomenon of the relative improvement in ultra‐endurance performance with advancing age.

The age of peak performance in Ironman triathlon: a cross-sectional and longitudinal data analysis

BackgroundThe aims of the present study were, firstly, to investigate in a cross-sectional analysis the age of peak Ironman performance within one calendar year in all qualifiers for Ironman Hawaii and Ironman Hawaii; secondly, to determine in a longitudinal analysis on a qualifier for Ironman Hawaii whether the age of peak Ironman performance and Ironman performance itself change across years; and thirdly, to determine the gender difference in performance.MethodsIn a cross-sectional analysis, the age of the top ten finishers for all qualifier races for Ironman Hawaii and Ironman Hawaii was determined in 2010. For a longitudinal analysis, the age and the performance of the annual top ten female and male finishers in a qualifier for Ironman Hawaii was determined in Ironman Switzerland between 1995 and 2010.ResultsIn 19 of the 20 analyzed triathlons held in 2010, there was no difference in the age of peak Ironman performance between women and men (p > 0.05). The only difference in the age of peak Ironman performance between genders was in ‘Ironman Canada’ where men were older than women (p = 0.023). For all 20 races, the age of peak Ironman performance was 32.2 ± 1.5 years for men and 33.0 ± 1.6 years for women (p > 0.05). In Ironman Switzerland, there was no difference in the age of peak Ironman performance between genders for top ten women and men from 1995 to 2010 (F = 0.06, p = 0.8). The mean age of top ten women and men was 31.4 ± 1.7 and 31.5 ± 1.7 years (Cohens d = 0.06), respectively. The gender difference in performance in the three disciplines and for overall race time decreased significantly across years. Men and women improved overall race times by approximately 1.2 and 4.2 min/year, respectively.ConclusionsWomen and men peak at a similar age of 32–33 years in an Ironman triathlon with no gender difference. In a qualifier for Ironman Hawaii, the age of peak Ironman performance remained unchanged across years. In contrast, gender differences in performance in Ironman Switzerland decreased during the studied period, suggesting that elite female Ironman triathletes might still narrow the gender gap in the future.

A comparison of participation and performance in age-group finishers competing in and qualifying for Ironman Hawaii

Background Athletes intending to compete in Ironman Hawaii need to qualify in an age-group based qualification system. We compared participation and top ten performances of athletes in various age groups between Ironman Hawaii and its qualifier races. Methods Finishes in Ironman Hawaii and in its qualifier races in 2010 were analyzed in terms of performance, age, and sex. Athletes were categorized into age groups from 18–24 to 75–79 years and split and race times were determined for the top ten athletes in each age group. Results A higher proportion of athletes aged 25–49 years finished in the qualifier races than in Ironman Hawaii. In athletes aged 18–24 and 50–79 years, the percentage of finishes was higher in Ironman Hawaii than in the qualifier races. For women, the fastest race times were slower in Ironman Hawaii than in the qualifier races for those aged 18–24 (P<0.001), 25–29 (P<0.05), and 60–64 (P<0.05) years. Swim split times were slower in Ironman Hawaii than in the qualifier races for all age groups (P<0.05). Cycling times were slower in Ironman Hawaii for 18–24, 25–29, 40–44, 50–54, and 60–64 years (P<0.05) in age groups. For men, finishers aged 18–24 (P<0.001), 40–44 (P<0.001), 50–54 (P<0.01), 55–59 (P<0.001), 60–64 (P<0.01), and 65–69 (P<0.001) years were slower in Ironman Hawaii than in the qualifier races. Swim split times were slower in Ironman Hawaii than in the qualifier races for all age groups (P<0.05). Cycling times were slower in Ironman Hawaii for those aged 18–24 and those aged 40 years and older (P<0.05). Conclusion There are differences in terms of participation and performance for athletes in different age groups between Ironman Hawaii and its qualifier races. Triathletes aged 25–49 years and men generally were underrepresented in Ironman Hawaii compared with in its Ironman qualifier races. These athletes may have had less chance to qualify for Ironman Hawaii than female athletes or younger (<25 years) and older (>50 years) athletes.

Variables that influence Ironman triathlon performance - what changed in the last 35 years?

Objective This narrative review summarizes findings for Ironman triathlon performance and intends to determine potential predictor variables for Ironman race performance in female and male triathletes. Methods A literature search was performed in PubMed using the terms “Ironman”, “triathlon”, and “performance”. All resulting articles were searched for related citations. Results Age, previous experience, sex, training, origin, anthropometric and physiological characteristics, pacing, and performance in split disciplines were predictive. Differences exist between the sexes for anthropometric characteristics. The most important predictive variables for a fast Ironman race time were age of 30–35 years (women and men), a fast personal best time in Olympic distance triathlon (women and men), a fast personal best time in marathon (women and men), high volume and high speed in training where high volume was more important than high speed (women and men), low body fat, low skin-fold thicknesses and low circumference of upper arm (only men), and origin from the United States of America (women and men). Conclusion These findings may help athletes and coaches to plan an Ironman triathlon career. Age and previous experience are important to find the right point in the life of a triathlete to switch from the shorter triathlon distances to the Ironman distance. Future studies need to correlate physiological characteristics such as maximum oxygen uptake with Ironman race time to investigate their potential predictive value and to investigate socio-economic aspects in Ironman triathlon.

Pacing strategy in male elite and age group 100 km ultra-marathoners

Pacing strategy has been investigated in elite 100 km and elite 161 km (100 mile) ultra-marathoners, but not in age group ultra-marathoners. This study investigated changes in running speed over segments in male elite and age group 100 km ultra-marathoners with the assumption that running speed would decrease over segments with increasing age of the athlete. Running speed during segments in male elite and age group finishers for 5-year age groups (ie, 18–24 to 65–69 years) in the 100 km Lauf Biel in Switzerland was investigated during the 2000–2009 period. Average running speed over segment time station (TS) TS1–TS2 (56.1 km) was compared with running speed Start–TS1 (38 km) and Start–TS3 (76.7 km) and running speed TS2–TS3 was compared with running speed Start–Finish. For the top ten athletes in each edition, running speed decreased from 2000 to 2009 for TS1–TS2 and TS2–TS3 (P<0.0001) but not in TS3–Finish (P>0.05). During TS1–TS2, athletes were running at 98.0%±2.1% of the running speed of Start–TS1. In TS2–TS3, they were running at 94.6%±3.4% of the running speed of TS1–TS2. In TS3–Finish, they were running at 95.5%±3.8% of running speed in TS2–TS3. For age group athletes, running speed decreased in TS1–TS2 and TS2–TS3. In TS3–Finish, running speed remained unchanged with the exception of the age group 40–44 years for which running speed increased. Running speed showed the largest decrease in the age group 18–24 years. To summarize, the top ten athletes in each edition maintained their running speed in the last segment (TS3–Finish) although running speed decreased over the first two segments (TS1–TS2 and TS2–TS3). The best pacers were athletes in the age group 40–44 years, who were able to achieve negative pacing in the last segment (TS3–Finish) of the race. The negative pacing in the last segment (TS3–Finish) was likely due to environmental conditions, such as early dawn and the flat circuit in segment TS3–Finish of the race.

What predicts performance in ultra-triathlon races? - a comparison between Ironman distance triathlon and ultra-triathlon.

Objective This narrative review summarizes recent intentions to find potential predictor variables for ultra-triathlon race performance (ie, triathlon races longer than the Ironman distance covering 3.8 km swimming, 180 km cycling, and 42.195 km running). Results from studies on ultra-triathletes were compared to results on studies on Ironman triathletes. Methods A literature search was performed in PubMed using the terms “ultra”, “triathlon”, and “performance” for the aspects of “ultra-triathlon”, and “Ironman”, “triathlon”, and “performance” for the aspects of “Ironman triathlon”. All resulting papers were searched for related citations. Results for ultra-triathlons were compared to results for Ironman-distance triathlons to find potential differences. Results Athletes competing in Ironman and ultra-triathlon differed in anthropometric and training characteristics, where both Ironmen and ultra-triathletes profited from low body fat, but ultra-triathletes relied more on training volume, whereas speed during training was related to Ironman race time. The most important predictive variables for a fast race time in an ultra-triathlon from Double Iron (ie, 7.6 km swimming, 360 km cycling, and 84.4 km running) and longer were male sex, low body fat, age of 35–40 years, extensive previous experience, a fast time in cycling and running but not in swimming, and origins in Central Europe. Conclusion Any athlete intending to compete in an ultra-triathlon should be aware that low body fat and high training volumes are highly predictive for overall race time. Little is known about the physiological characteristics of these athletes and about female ultra-triathletes. Future studies need to investigate anthropometric and training characteristics of female ultra-triathletes and what motivates women to compete in these races. Future studies need to correlate physiological characteristics such as maximum oxygen uptake (VO2max) with ultra-triathlon race performance in order to investigate whether these characteristics are also predictive for ultra-triathlon race performance.

Running and the association with anthropometric and training characteristics

Running can be performed as a sprint discipline on the track over a few meters up to 10 km to the marathon and ultramarathon running distances over hundreds to thousands of kilometers. Running performance is influenced by a variety of anthropometric and training factors. Morphological features such as skin fold thickness, body fat percentage, circumferences and length of limbs, body weight, body height and body mass index (BMI) seem to have an influence on the running performance. The training volume and running speed during training are also correlated with running performance. When all variables were investigated comparatively, body fat and running speed during training were usually the most important influencing factors. For longer running performances (over 6 hours or 100 km, respectively), the aspects of experience (number of successfully finished races) and personal best times were, however, far more important than training volume or morphological characteristics such as body fat. It was also shown that ultra runners prepare differently (lower running speed and higher running volume) as runners competing over shorter distances such as half-marathon and marathon.

Laufsport und der Zusammenhang zwischen Training und Körperbau: Running and the association with anthropometric and training characteristics

Running can be performed as a sprint discipline on the track over a few meters up to 10 km to the marathon and ultramarathon running distances over hundreds to thousands of kilometers. Running performance is influenced by a variety of anthropometric and training factors. Morphological features such as skin fold thickness, body fat percentage, circumferences and length of limbs, body weight, body height and body mass index (BMI) seem to have an influence on the running performance. The training volume and running speed during training are also correlated with running performance. When all variables were investigated comparatively, body fat and running speed during training were usually the most important influencing factors. For longer running performances (over 6 hours or 100 km, respectively), the aspects of experience (number of successfully finished races) and personal best times were, however, far more important than training volume or morphological characteristics such as body fat. It was also shown that ultra runners prepare differently (lower running speed and higher running volume) as runners competing over shorter distances such as half-marathon and marathon.

Laufsport und der Zusammenhang zwischen Training und Körperbau

Running can be performed as a sprint discipline on the track over a few meters up to 10 km to the marathon and ultramarathon running distances over hundreds to thousands of kilometers. Running performance is influenced by a variety of anthropometric and training factors. Morphological features such as skin fold thickness, body fat percentage, circumferences and length of limbs, body weight, body height and body mass index (BMI) seem to have an influence on the running performance. The training volume and running speed during training are also correlated with running performance. When all variables were investigated comparatively, body fat and running speed during training were usually the most important influencing factors. For longer running performances (over 6 hours or 100 km, respectively), the aspects of experience (number of successfully finished races) and personal best times were, however, far more important than training volume or morphological characteristics such as body fat. It was also shown that ultra runners prepare differently (lower running speed and higher running volume) as runners competing over shorter distances such as half-marathon and marathon.