A comparison of performance of Deca Iron and Triple Deca Iron ultra-triathletes

Changes in pacing variation with increasing race duration in ultra-triathlon races

Despite the increasing scientific interest in the relationship between pacing and performance in endurance sports, little information is available about pacing and pacing variation in ultra-endurance events such as ultra-triathlons. Therefore, we aimed to investigate the trends of pacing, pacing variation, the influence of age, sex, and performance level in ultra-triathlons of different distances. We analysed 969 finishers (849 men, 120 women) in 46 ultra-triathlons longer than the original Ironman® distance (e.g., Double-, Triple-, Quintuple- and Deca Iron ultra-triathlons) held from 2004 to 2015. Pacing speed was calculated for every cycling and running lap. Pacing variation was calculated as the coefficient of variation (%) between the average speed of each lap. Performance level (i.e., fast, moderate, slow) was defined according to the 33.3 and 66.6 percentile of the overall race time. A multivariate analysis (two-way ANOVA) was applied for the overall race time as the dependent variable with 'sex' and 'age group' as independent factors. Another multivariate model with 'age' and 'sex' as covariates (two-way ANCOVA) was applied with pacing variation (cycling and running) as the dependent variable with 'race' and 'performance level' as independent factors. Different pacing patterns were observed by event and performance level. The general pacing strategy applied was a positive pacing. In Double and Triple Iron ultra-triathlon, faster athletes paced more evenly with less variation than moderate or slower athletes. The variation in pacing speed increased with the length of the race. There was no significant difference in pacing variation between faster, moderate, and slower athletes in Quintuple and Deca Iron ultra-triathlon. Women had a slower overall performance than men. The best overall times were achieved at the age of 30-39 years. Successful ultra-triathlon athletes adapted a positive pacing strategy in all race distances. The variation in pacing speed increased with the length of the race. In shorter ultra-triathlon distances (i.e., Double and Triple Iron ultra-triathlon), faster athletes paced more evenly with less variation than moderate or slower athletes. In longer ultra-triathlon distances (i.e., Quintuple and Deca Iron ultra-triathlon), there was no significant difference in pacing variation between faster, moderate, and slower athletes.

Strength Training in Long-Distance Triathletes: Barriers and Characteristics

ABSTRACT

Luckin, KM, Badenhorst, CE, Cripps, AJ, Landers, GJ, Merrells, RJ, Bulsara, MK, and Hoyne, GF. Strength training in long-distance triathletes: Barriers and characteristics. J Strength Cond Res 35(2): 495-502, 2021-The purpose of this investigation was to identify perceived and physical barriers toward the completion of concurrent strength training and endurance training in long-distance triathletes. Three hundred ninety long-distance triathletes (224 women, 166 men; age [y]: 39 ± 10) completed a 68-question self-administered, semiquantitative survey that assessed endurance and strength training characteristics, experience in triathlon, and perceived barriers regarding the completion of strength training. Mean training hours per week was 14.92 ± 5.25, with 54.6% reporting participation in strength training. Heavy strength training was the most commonly reported (39.4%), with significantly more men completing this form of strength training (p < 0.001). Results from subjects who did not complete strength training indicated that perceived time constraints (53.1%) in addition to lack of knowledge on exercise progression and form (52.5%) are prominent perceived barriers to strength training completion. Identification of the barriers perceived by long-distance triathletes that prevent them from completing concurrent strength training and endurance training may be useful for coaches, athletes, and sports scientists who seek to incorporate strength training for injury prevention and performance improvement.

Pacing strategy of a wheelchair athlete in a 5x and 10x Ironman ultra triathlon: a case study

OBJECTIVE

For disabled athletes such as wheelchair athletes, there is no knowledge about competing and pacing during a long-distance triathlon such as an Ironman triathlon. This study aimed to investigate the pacing strategy of a paraplegic wheelchair athlete competing and finishing a Quintuple Iron ultra-triathlon (i.e., five times 3.8 km swimming, 180 km handbike cycling and 42.195 km wheelchair racing in five days) and a Deca Iron ultra-triathlon (10 times the same distance in 10 days).

METHODS

Data from an ultra-distance triathlon race (Swissultra) covering 5x and 10x Ironman distance were collected. Official performance data were acquired from the race organizer's website and athlete's personal information from the athlete through online interviews. The athlete is a man born in 1962, the races analysed in this study were held in the summer of 2017 (5x) and 2019 (10x). The split times for swimming, cycling and running, the overall race times for each Ironman and the lap times in cycling (handbike) and running (wheelchair) were analysed.

RESULTS

The athlete finished the Quintuple Iron ultra-triathlon in an overall race time of 66:28:31 h:min:s and the Deca Iron ultra-triathlon in 137:03:20 h:min:s. He adopted an even pacing in both races in split disciplines and for overall race time.

CONCLUSION

The paraplegic wheelchair athlete was able to finish both a Quintuple and a Deca Iron ultra-triathlon by adopting an even pacing in all split disciplines and for overall race time.IMPLICATIONS FOR REHABILITATIONTriathlon is a growing sport among athletes with spinal cord injury.Ultra-triathlons are ultra-endurance events and pacing is a key aspect to a successful race regardless the athlete's category.An athlete with a spinal cord injury finished a 5x and 10x Ironman ultra-triathlon applying an even pacing strategy.

Self-Selected Pacing During a World Record Attempt in 40 Ironman-Distance Triathlons in 40 Days

The present case study analyzed performance, pacing, and potential predictors in a self-paced world record attempt of a professional triathlete to finish 40 Ironman-distance triathlons within 40 days. Split times (i.e., swimming, cycling, running) and overall times, body weight, daily highest temperature, wind speed, energy expenditure, mean heart rate, and sleeping time were recorded. Non-linear regressions were applied to investigate changes in split and overall times across days. Multivariate regression analyses were performed to test which variables showed the greatest influence on the dependent variables cycling, running and overall time. The athlete completed the 40×Ironman distances in a total time of 444:22 h:min. He spent 50:26 h:min in swimming, 245:37 h:min in cycling, 137:17 h:min in running and 11:02 h:min in transition times. Swimming and cycling times became slower across days, whereas running times got faster until the 20th day and, thereafter, became slower until the 40th day. Overall times got slower until the 15th day, became faster to 31st, and started then to get slower until the end. Wind speed, previous day’s race time and average heart race during cycling were significant independent variables influencing cycling time. Body weight and average heart rate during running were significant independent variables influencing running performance. Cycling performance, running performance, and body weight were significant independent variables influencing overall time. In summary, running time was influenced by body weight, cycling by wind speed, and overall time by both running and cycling performances.

Ultra-triathlon-Pacing, performance trends, the role of nationality, and sex differences in finishers and non-finishers

Ultra-triathlons are defined as triathlons longer than the traditional Ironman distance and became more popular in the last two decades; however, scarce scientific evidence of these events are available. Therefore, we aimed to investigate the trends of performance, pacing, nationality, sex differences, and rate of non-finishers in ultra-triathlons. Data from 1985 to 2018 were collected including Double Iron, Triple Iron, Quintuple Iron, and Deca Iron ultra-triathlons. Different pacing patterns by event and sex were observed (P < .05); athletes spent less %time in swimming and cycling, and more %time in running as the distance of event was longer; women spent more %time in cycling and less% time in running in Double and Triple. Performance analysis showed a negative trend over time for men and women since 1985. Switzerland, France, and Germany were the fastest nations in ultra-triathlons. The frequency of North Americans competing in Europe was very low (<5%), whereas Europeans often competed in North America (~25%). The rate of non-finishers between sexes was similar in all races with the exception of Deca Iron ultra-triathlon, which was much greater (~20%) for women. Non-finishers had slower race times in swimming and cycling splits than finishers. In conclusion, ultra-triathletes should redistribute their energy among swimming, cycling, and running depending on their sex and distance of race. Performance in ultra-triathlons has been decreasing in men and women over the years, but sex difference in performance remained. Europeans were the fastest ultra-triathletes and compete in Europe and North America. Additionally, non-finishers were slower swimmers and cyclists than finishers.

Effects of The Performance Level and Race Distance on Pacing in Ultra-Triathlons

The aim of this study was to examine the effects of the performance level and race distance on pacing in ultra-triathlons (Double, Triple, Quintuple and Deca), wherein pacing is defined as the relative time (%) spent in each discipline (swimming, cycling and running). All finishers (n = 3,622) of Double, Triple, Quintuple and Deca Iron ultra-triathlons between 1985 and 2016 were analysed and classified into quartile groups (Q1, Q2, Q3 and Q4) with Q1 being the fastest and Q4 the slowest. Performance of all non-finishers (n = 1,000) during the same period was also examined. Triple and Quintuple triathlons (24.4%) produced the highest rate of non-finishers, and Deca Iron ultra-triathlons produced the lowest rate (18.0%) (χ² = 12.1, p = 0.007, φC = 0.05). For the relative swimming and cycling times (%), Deca triathletes (6.7 ± 1.5% and 48.8 ± 4.9%, respectively) proved the fastest and Double (9.2 ± 1.6% and 49.6 ± 3.6%) Iron ultra-triathletes were the slowest (p < 0.008) with Q4 being the fastest group (8.3 ± 1.6% and 48.8 ± 4.3%) and Q1 the slowest one (9.5 ± 1.5% and 50.9 ± 3.0%) (p < 0.001). In running, Double triathletes were relatively the fastest (41.2 ± 4.0%) and Deca (44.5 ± 5.4%) Iron ultra-triathletes the slowest (p < 0.001) with Q1 being the fastest (39.6 ± 3.3%) and Q4 the slowest group (42.9 ± 4.7%) (p < 0.001). Based on these findings, it was concluded that the fastest ultra-triathletes spent relatively more time swimming and cycling and less time running, highlighting the importance of the role of the latter discipline for the overall ultra-triathlon performance. Furthermore, coaches and ultra-triathletes should be aware of differences in pacing between Double, Triple, Quintuple and Deca Iron triathlons.

Sex differences in pacing during 'Ultraman Hawaii'

Background

To date, little is known for pacing in ultra-endurance athletes competing in a non-stop event and in a multi-stage event, and especially, about pacing in a multi-stage event with different disciplines during the stages. Therefore, the aim of the present study was to examine the effect of age, sex and calendar year on triathlon performance and variation of performance by events (i.e., swimming, cycling 1, cycling 2 and running) in ‘Ultraman Hawaii’ held between 1983 and 2015.

Methods

Within each sex, participants were grouped in quartiles (i.e., Q1, Q2, Q3 and Q4) with Q1 being the fastest (i.e., lowest overall time) and Q4 the slowest (i.e., highest overall time). To compare performance among events (i.e., swimming, cycling 1, cycling 2 and running), race time in each event was converted in z score and this value was used for further analysis.

Results

A between-within subjects ANOVA showed a large sex × event (p = 0.015, η² = 0.014) and a medium performance group × event interaction (p = 0.001, η² = 0.012). No main effect of event on performance was observed (p = 0.174, η² = 0.007). With regard to the sex × event interaction, three female performance groups (i.e., Q2, Q3 and Q4) increased race time from swimming to cycling 1, whereas only one male performance group (Q4) revealed a similar trend. From cycling 1 to cycling 2, the two slower female groups (Q3 and Q4) and the slowest male group (Q4) increased raced time. In women, the fastest group decreased (i.e., improved) race time from swimming to cycling 1 and thereafter, maintained performance, whereas in men, the fastest group decreased race time till cycling 2 and increased it in the running.

Conclusion

In summary, women pace differently than men during ‘Ultraman Hawaii’ where the fastest women decreased performance on day 1 and could then maintain on day 2 and 3, whereas the fastest men worsened performance on day 1 and 2 but improved on day 3.

Pacing in a self-paced world record attempt in 24-h road cycling

Background

Pacing strategy plays a major role in sport performance. However, there is a dearth of knowledge concerning pacing during ultra-endurance sport events. The present case study investigated the pacing of an ultra-cyclist in a self-paced attempt to break the world record in 24-h road cycling and, with all the caveats and the limitations affecting a case report, could be useful in generating hypotheses and further studies about pacing dynamics during prolonged sport performances.

Case description

A well experienced ultra-cyclist completed laps of 11.731 km during 24 h and the support crew recorded for each lap time and power output in Watt. The trend in cycling speed and power output across laps was investigated using regression analyses. A mixed-effects regression model including lap, ambient air temperature, air pressure, air humidity and wind speed as fixed variables was used to investigate a relationship of environmental factors with cycling speed.

Discussion and evaluation

The athlete achieved 896.173 km within the 24 h. He set a new world record by breaking the old record (Jure Robic, 2004, 834.77 km) by 61.403 km. He cycled at an average speed of 37.34 km/h with an average power output of 250.2 W. The decrease in cycling speed and power output across laps could be modelled linearly. Temperature and wind speed were related to cycling speed during the whole event. There was a significant interaction air temperature × relative humidity for the whole event.

Conclusions

The athlete adopted a positive pacing (i.e. speed gradually declined throughout the event) and environmental factors (i.e. temperature and wind speed) influenced cycling speed during the event.

The aspect of experience in ultra-triathlon races

Previous experience seems to be an important predictor for endurance and ultra-endurance performance. The present study investigated whether the number of previously completed races and/or the personal best times in shorter races is more predictive for performance in longer non-stop ultra-triathlons such as a Deca Iron ultra-triathlon. All female and male ultra-triathletes who had finished between 1985 and 2014 at least one Double Iron ultra-triathlon (i.e. 7.6 km swimming, 360 km cycling and 84.4 km running), one Triple Iron ultra-triathlon (i.e. 11.4 km swimming, 540 km cycling and 126.6 km running), one Quintuple Iron ultra-triathlon (i.e. 19 km swimming, 900 km cycling and 221 km running) and one Deca Iron ultra-triathlon (i.e. 38 km swimming, 1,800 km cycling and 422 km running) were identified and their best race times for each distance were recorded. Multiple regression analysis (stepwise, forward selection, p of F for inclusion <0.05, p of F for exclusion >0.1, listwise deletion) was used to determine all variables correlating to overall race time and performance in split disciplines for both Quintuple and Deca Iron ultra-triathlon. The number of finished shorter races (i.e. Double and Triple Iron ultra-triathlon) was not associated with the number of finished longer races (i.e. Quintuple and Deca Iron ultra-triathlon) whereas both split and overall race times correlated to split and overall race times of the longer races with the exception of the swimming split times in Double Iron ultra-triathlon showing no correlation with swimming split times in both Quintuple and Deca Iron ultra-triathlon. In summary, previous experience seemed of importance in performance for longer ultra-triathlon races (i.e. Quintuple and Deca Iron ultra-triathlon) where the personal best times of shorter races (i.e. Double and Triple Iron ultra-triathlon) were important, but not the number of previously finished races. For athletes and coaches, fast race times in shorter ultra-triathlon races (i.e. Double and Triple Iron ultra-triathlon) are more important than a large of number finished races in order to achieve a fast race time in a longer ultra-triathlon (i.e. Quintuple and Deca Iron ultra-triathlon).

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 (VO_2max) with ultra-triathlon race performance in order to investigate whether these characteristics are also predictive for ultra-triathlon race performance.

What is the age for the fastest ultra-marathon performance in time-limited races from 6 h to 10 days?

Recent findings suggested that the age of peak ultra-marathon performance seemed to increase with increasing race distance. The present study investigated the age of peak ultra-marathon performance for runners competing in time-limited ultra-marathons held from 6 to 240 h (i.e. 10 days) during 1975-2013. Age and running performance in 20,238 (21%) female and 76,888 (79%) male finishes (6,863 women and 24,725 men, 22 and 78%, respectively) were analysed using mixed-effects regression analyses. The annual number of finishes increased for both women and men in all races. About one half of the finishers completed at least one race and the other half completed more than one race. Most of the finishes were achieved in the fourth decade of life. The age of the best ultra-marathon performance increased with increasing race duration, also when only one or at least five successful finishes were considered. The lowest age of peak ultra-marathon performance was in 6 h (33.7 years, 95% CI 32.5-34.9 years) and the highest in 48 h (46.8 years, 95% CI 46.1-47.5). With increasing number of finishes, the athletes improved performance. Across years, performance decreased, the age of peak performance increased, and the age of peak ultra-marathon performance increased with increasing number of finishes. In summary, the age of peak ultra-marathon performance increased and performance decreased in time-limited ultra-marathons. The age of peak ultra-marathon performance increased with increasing race duration and with increasing number of finishes. These athletes improved race performance with increasing number of finishes.