1
Vol.:(0123456789)
Scientific Reports |         (2023) 13:3692  
| https://doi.org/10.1038/s41598-023-30932-1
www.nature.com/scientificreports
Changes in pacing variation 
with increasing race duration 
in ultra‑triathlon races
Mirko Stjepanovic 1, Beat Knechtle 1,2*, Katja Weiss 2, Pantelis Theodoros Nikolaidis 3, 
Ivan Cuk 4, Mabliny Thuany 5 & Caio Victor Sousa 6
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.
An ultra-endurance performance is defined as any endurance performance of six hours in duration or  longer1. 
A triathlon is characterized by the successive completion of three disciplines (e.g., swimming, cycling, and run-
ning). Therefore, an Ironman® triathlon with 3.8 km swimming, 180 km cycling, and 42.2 km running must 
be considered an ultra-endurance performance considering the men’s world record being at 7:21:12 h:min:s2.
In addition to the single Ironman® distance, ultra-triathlon races of x-times the Ironman® distance exist, 
such as the Double Iron ultra-triathlon (7.6 km swimming, 360 km cycling and 84 km running), the Triple Iron 
ultra-triathlon (11.4 km swimming, 540 km cycling and 126.6 km running), the Quintuple Iron ultra-triathlon 
(19 km swimming, 900 km cycling and 211 km running), and the Deca Iron ultra-triathlon (38 km swimming, 
1800 km cycling and 422 km running). The popularity of ultra-triathlons is increasing, indicated by a rising 
number of  participants3–7. For example, participation trends during 1985–2009 showed an increase in both 
Double and Triple Iron (i.e., 17–98 per year in Double and 7–41 per year in Triple Iron, respectively)8. Similar 
results were shown by Sigg et al., in which the number of triathletes from Europe has increased for both sexes, 
while the numbers for North America increased only for the woman  athletes9.
OPEN
1Institute of Primary Care, University of Zurich, Zurich, Switzerland. 2Medbase St. Gallen Am Vadianplatz, 
Vadianstrasse 26, 9001 St. Gallen, Switzerland. 3School of Health and Caring Sciences, University of West Attica, 
Athens, Greece. 4Faculty of Sport and Physical Education, University of Belgrade, Belgrade, Serbia. 5Faculty of 
Sports, University of Porto, CIFI2D Porto, Portugal. 6Health and Human Sciences, Loyola Marymount University, 
Los Angeles, CA, USA. *email: beat.knechtle@hispeed.ch
2
Vol:.(1234567890)
Scientific Reports |         (2023) 13:3692  | 
https://doi.org/10.1038/s41598-023-30932-1
www.nature.com/scientificreports/
An important aspect regarding performance in endurance events is the distribution of exercise intensity. 
Athletes need to distribute their metabolic energy as fuel for their activity to avoid premature fatigue by going too 
fast early  on10. This has been often termed as ‘pacing’11,12. There are six different pacing strategies such as positive 
pacing (i.e., slowing over time), negative pacing (i.e. increase in speed over time), all-out pacing (i.e., maximal 
speed possible), even pacing (i.e. same speed over time), variable pacing (i.e., pacing with multiple fluctuations) 
and parabolic-shaped pacing (i.e., positive and negative pacing in different segments of the race)13. Research 
regarding pacing has increased over the past  years10–12,14–20. Positive pacing has been shown as the adequate strat-
egy adapted in many races and disciplines (i.e., for elite Ironman® triathletes, ultra-cyclists, and swimmers)21–23.
Race distance should be considered a factor that influences pacing  strategy13. It has been shown that athletes 
pace positively in long and ultra-long  races22. Considering triathlon, in both an Olympic distance and an Iron-
man® 70.3 distance triathlon, pacing strategies were strongly influenced by both the distance and the  discipline17. 
Regarding longer triathlon distances, finishers of a one per day Deca Iron ultra-triathlon applied positive  pacing20. 
At the ‘Ultraman Hawaii’, women paced differently than men (i.e. applied a more even pace after increasing speed 
at the start of the race)16. However, no study systematically investigates the effect of race distances on pacing 
strategies applied in very long triathlon distances such as Double Iron-, Triple Iron-, Quintuple Iron- and Deca 
Iron ultra-triathlon.
Another aspect is the performance level, where faster finishers pace differently than slower finishers and 
elite athletes pace differently than recreational  athletes24–26. In ultra-endurance running such as 100-km ultra-
marathon running, faster runners had fewer changes in running speed and started at a higher running speed 
while maintaining running speed  longer27. Among marathoners, slower finishers showed a greater pace variability 
than faster  finishers26. To the best of our knowledge, there is no study investigating the influence of performance 
level on pacing in ultra-triathlon.
Several physiological and psychological factors can influence both performance and pacing during endur-
ance and an ultra-endurance performance, such as  age5,  sex16, race  distance11, performance  level28, mechanical 
damage to muscle  fibers29, increasing body  temperature30, reduction in neuromuscular  activity31 and muscle 
glycogen  depletion8.
Additionally, gender seems to influence pacing during a triathlon  race32,33. In elite Ironman® triathletes, 
women were significantly slower when applying the same positive pacing  strategy15. However, at the ‘Ultra-
man Hawaii’, a multistage event consisting of 10 km swimming, 165 km cycling (day 1), 261 km cycling (day 2) 
and 85 km running (day 3), women applied a more even pacing strategy compared to men. The fastest women 
decreased performance on day 1 and could then maintain on days 2 and 3, whereas the fastest men impaired 
performance on days 1 and 2 but improved on day  316. A comparison of top performers from the Ironman® to 
the Double Deca Iron ultra-triathlon distance showed that men were faster than women and that the sex differ-
ence increased for swimming, running, and overall race time but not for  cycling34. There is, however, no study 
investigating all finishers (i.e., not only the top athletes).
Age has an influence on endurance performance and pacing. Regarding triathlon, performance and age-
related trends in elite triathletes competing in age group classes have been investigated for an Ironman® triath-
lon such as ‘Ironman® Hawaii’16,35 and short distances such as the Olympic distance  triathlon36. An age-related 
performance decline has been shown for all investigated  distances37. In Ironman® triathletes, the age-related 
performance decline started at a higher age than in short distance  triathletes3.
Another important aspect is the age of peak performance. When Olympic, Ironman® 70.3 and Ironman® 
distance races were compared, the age of peak triathlon performance was higher in the longer triathlon race 
 distances38. For ultra-triathlon, Deca Iron ultra-triathletes were older than Triple Iron ultra-triathletes39. How-
ever, the age-related performance and the age of peak performance for the Double and Quintuple Iron ultra-
triathlon distance are unknown.
Based on the limited existing literature regarding the effect of the race distance, age, gender, and performance 
level on pacing in ultra-triathlon races we hypothesized, firstly, that a positive pacing strategy would be applied 
on the shorter distances (e.g., Double and Triple Iron ultra-triathlon) and an even pacing on the longer ones (e.g., 
Quintuple and Deca Iron ultra-triathlon). Secondly, we hypothesized that slower finishers apply more variable 
pacing. Thirdly, we hypothesized to find differences in pacing between men and women. We hypothesized that 
the age-related declines would occur later at the longer distances (e.g., Quintuple and Deca Iron ultra-triathlon) 
compared to the shorter distances (e.g., Double and Triple Iron ultra-triathlon).
Materials and methods
Ethical approval. 
The Institutional Review Board of Kanton St. Gallen, Switzerland approved all procedures 
used in the study with a waiver of the requirement for informed consent of the participants given the fact that 
the study involved the analysis of publicly available data (01/06/2010). The study was conducted in accordance 
with recognized ethical standards according to the Declaration of Helsinki adopted in 1964 and revised in 2013.
Subjects. 
We focused on distances longer than the original Ironman® distance, like the Double Iron, Tri-
ple Iron, Quintuple Iron and Deca Iron ultra-triathlon. Overall results are available on the International Ultra 
Triathlon Association homepage (IUTA, https:// www. iutas port. com/). We contacted all race directors directly 
for the lap times in running, cycling and for the contestants’ age. Lap times were provided electronically in 
in spreadsheets. Furthermore, the age of all finishers was provided. The athletes were sorted into age groups 
of 10-year age intervals. Lap distances were different for each race as every race has its course. Tables 1 and 2 
provide an overview of the number of finishers for each race. We excluded all non-finishers. The number of 
calculated laps for each race type was provided additionally.
3
Vol.:(0123456789)
Scientific Reports |         (2023) 13:3692  | 
https://doi.org/10.1038/s41598-023-30932-1
www.nature.com/scientificreports/
The final analysis included all finishers, in total 969 athletes (849 men, 120 women) competing in a Double 
Iron, Triple Iron, Quintuple Iron, and Deca Iron ultra-triathlon. We calculated the pacing speed from lap distance 
and time per lap for every cycling and running lap. We excluded swimming times for the analysis because no lap 
times were recorded. However, evidence suggests that variations of pacing during swimming are not  apparent11. 
One race had to be excluded because of missing split times (Triple Iron ultra-triathlon in Bad Blumau, Austria). 
We included only official finishers. Finishers with improbable speed values (i.e., cycling speed > 48 km/h and 
running speed > 20 km/h) were also excluded. The last races included were the Double and Triple Iron ultra- 
triathlon in Florida in 2020, as the other races had been canceled due to the COVID-19 pandemic.
Statistical analyses. 
Data normality and homogeneity were confirmed with Kolmogorov–Smirnov and 
Levene’s test, respectively. Pacing variation was calculated individually as the coefficient of variation (%) between 
the average speed of each lap in the close circuit the athletes performed their ultra-triathlons. Each cycling lap 
ranges from 4 to 16.4 km and the running lap ranges from 1.4 to 3.5 km. Total distance is standard for all athletes. 
The performance level was defined according to the 33.3 and 66.6 percentile of overall race time for women and 
men. The first percentile (≤ 33.3 percentile) was named as ‘fast’, the last percentile (≥ 66.6 percentile) was named 
as ‘slow’, and the intermediate was named as ‘moderate’26. A multivariate model with two factors (two-way 
ANOVA) was applied for race time performance (overall, swimming, cycling, running) as the dependent vari-
able with ‘sex’ and ‘age group’ as independent factors. Quintuple and Deca Iron ultra-triathlon were not included 
in the previous model because of the low number of participants across the age groups. Another multivariate 
model with two factors with ‘age’ and ‘sex’ as covariates (two-way ANCOVA) was applied with pacing variation 
(cycling and running) as dependent variable, ‘race’ and ‘performance level’ as independent factors. Partial eta 
squared (ηp
2) was calculated for the ANOVAs where the values of the effect size 0.01, 0.06, and above 0.14 were 
considered small, medium, and large,  respectively40. Statistical significance was defined as p < 0.05. All statistical 
analyses were carried out with Statistical Software for the Social Sciences (IBM® SPSS v.25, Chicago, Ill, USA).
Table 1.  Number of finishers for each race type and number of excluded finishers.
Races
Double
Triple
Quintuple
Deca
Excluded
Total
Male
346
499
23
23
42
849
Finishers
Female
58
52
6
6
2
120
Overall
404
551
29
29
44
969
Laps
Bike
22,184
38,334
3560
5745
69,823
Run
19,231
51,404
3311
9818
83,764
Table 2.  All races included in the statistical analysis sorted by race type and year.
Double
Triple
Quintuple
Deca
2014
Virginia (USA)
2004
Lehnsahn (GER)
2016
Virginia (USA)
2017
Buchs (CH)
2015
Emsdetten (GER)
2005
Lehnsahn (GER)
2017
Buchs (CH)
2018
Buchs (CH)
2015
Florida (USA)
2006
Lehnsahn (GER)
2018
Buchs (CH)
2015
Virginia (USA)
2007
Lehnsahn (GER)
2019
Virginia (USA)
2015
Oregon (USA)
2008
Lehnsahn (GER)
2016
Florida (USA)
2009
Lehnsahn (GER)
2016
Oregon (USA)
2010
Lehnsahn (GER)
2016
Virginia (USA)
2011
Lehnsahn (GER)
2017
Florida (USA)
2012
Lehnsahn (GER)
2017
Emsdetten (GER)
2013
Lehnsahn (GER)
2017
Oregon (USA)
2014
Lehnsahn (GER)
2017
Panevėžys (LT)
2015
Virginia (USA)
2017
Virginia (USA)
2015
Lehnsahn (GER)
2018
Florida (USA)
2016
Lehnsahn (GER)
2018
Oregon (USA)
2016
Virginia (USA)
2019
Florida (USA)
2017
Virginia (USA)
2019
Emsdetten (GER)
2018
Lehnsahn (GER)
2019
Virginia (USA)
2019
Lehnsahn (GER)
2020
Florida (USA)
2019
Lehnsahn (GER)
2019
Virginia (USA)
2020
Florida (USA)
4
Vol:.(1234567890)
Scientific Reports |         (2023) 13:3692  | 
https://doi.org/10.1038/s41598-023-30932-1
www.nature.com/scientificreports/
Results
The final analysis included 386 athletes competing in a Double Iron, 539 in a Triple Iron, 15 in a Quintuple Iron, 
and 29 in Deca Iron ultra-triathlon (n = 969). For all race distances, the majority of athletes were aged 40–49 years, 
followed by 30–39 years (Fig. 1).
The multivariate model for Double Iron ultra-triathlon with overall race time as the dependent variable 
showed that ‘age group’ was a significant factor for swimming (F = 2.48, p = 0.044, ηp
2 = 0.026), and running 
(F = 5.99, p < 0.001, ηp
2 = 0.060), but not for cycling or overall performance. ‘Sex’ showed significant effects for 
swimming (F = 4.17, p = 0.042, ηp
2 = 0.011), cycling (F = 6.36, p = 0.012, ηp
2 = 0.017), overall (F = 6.15, p = 0.014, 
ηp
2 = 0.016), and a borderline effect for running (F = 3.03, p = 0.082, ηp
2 = 0.008). There were no significant 
(p > 0.05) interactions for ‘age group × sex’. Pairwise comparisons showed that swimming performance for men 
was faster in age groups 30–39 and 40–49 years. The female age group 30–39 years was faster than older age 
groups, and the male age group ≥ 60 years was slower than age groups 40–49 and 50–59 years (Fig. 2A). Men’s 
cycling performance in age groups 30–39 and 40–49 years was faster than in the same age groups for women 
(Fig. 2B). Men in the age group 30–39 years ran faster than others, followed by 40–49 years (Fig. 2C). For women, 
athletes in the age group 30–39 years were faster than athletes in age groups ≤ 29 and 50–59 years (Fig. 2D). 
Women had a slower overall performance in age groups 30–39 and 40–49 years. Men in the age group 30–39 years 
were faster than all the others, except the age group 40–49 years (Fig. 2D).
For the Triple Iron ultra-triathlon, the multivariate model showed that ‘age group’ was a significant factor 
only for cycling (F = 2.66, p = 0.032, ηp
2 = 0.020). ‘Sex’ showed significant effects for cycling (F = 16.35, p < 0.001, 
ηp
2 = 0.030), running (F = 6.55, p = 0.011, ηp
2 = 0.012), overall (F = 13.03, p < 0.001, ηp
2 = 0.024), and a border-
line effect for swimming (F = 2.91, p = 0.089, ηp
2 = 0.005). There were no significant (p > 0.05) interactions ‘age-
group × sex’. Pairwise comparisons showed that swimming performance for men was faster in the age group 
40–49 years. Men aged 50 or older swam slower than men in other age groups (Fig. 2E). Women’s cycling perfor-
mance was slower than for men, and men aged 60 years or older were slower than all others (Fig. 2F). Similarly, 
running and overall performance were lower in women, and men aged ≥ 60 years were slower than all others, 
whereas athletes in the age group 30–39 were faster than in age groups 40–49 and 50–59 years (Fig. 2G and H).
The multivariate model with pacing variation as the dependent variable showed that ‘performance level’ 
was a significant factor for both cycling (F = 10.51, p < 0.001, ηp
2 = 0.022), and running (F = 63.63, p < 0.001, 
ηp
2 = 0.118). Similarly, ‘race’ was also significant for both cycling (F = 173.12, p < 0.001, ηp
2 = 0.352), and running 
(F = 62.97, p < 0.001, ηp
2 = 0.165). The interaction ‘performance level × race’ was significant for cycling (F = 2.31, 
p = 0.032, ηp
2 = 0.014) and running (F = 36.15, p < 0.001, ηp
2 = 0.185). Pairwise comparisons showed that pacing 
variation was lower for faster athletes cycling in Double and Triple Iron ultra-triathlon and running in Triple Iron 
ultra-triathlon. Cycling pacing variation in Double Iron ultra-triathlon was the lowest across all performance 
levels. It was lower in Triple Iron ultra-triathlon than in Quintuple and Deca Iron ultra-triathlon. For running, 
all performance levels of Double Iron ultra-triathlon showed a lower pacing variation than in the Triple Iron 
ultra-triathlon. Moderate and fast athletes were also different from the Quintuple Iron ultra-triathlon and slow 
and fast athletes were different from the Deca Iron ultra-triathlon (Fig. 3).
Discussion
This study intended to investigate the trends in pacing and the effects of performance level, sex and age in ultra-
triathlons with the primary hypothesis of a positive pacing strategy in Double and Triple ultra-triathlon and an 
even pacing strategy in Quintuple and Deca ultra-triathlon.
Figure 1.  Number of participants in each age-group for Double (A), Triple (B), Quintuple (C), and Deca (D) 
ultra-triathlon.
5
Vol.:(0123456789)
Scientific Reports |         (2023) 13:3692  | 
https://doi.org/10.1038/s41598-023-30932-1
www.nature.com/scientificreports/
Figure 2.  Race performance (minutes) by age groups of men and women competing in Double Iron (A–D) and 
Triple Iron (E–H) ultra-triathlon. *: different between sex, within the same age group, #: different from all the 
other age groups, a: different from age group ≤ 29 years, b: different from age group 30–39 years, c: different from 
age group 40–49 years, d: different from age group 50–59 years, e: different from age group ≥ 60 years.
Figure 3.  Cycling and running pacing variation in Double, Triple, Quintuple, and Deca Iron ultra-triathlon 
by different performance levels. *: different from all other performance levels within the same race, b: different 
from Triple within the same performance level, c: different from Quintuple within the same performance level, 
d: different from Deca within the same performance level.
6
Vol:.(1234567890)
Scientific Reports |         (2023) 13:3692  | 
https://doi.org/10.1038/s41598-023-30932-1
www.nature.com/scientificreports/
The first important finding was a positive pacing strategy applied in all distances confirming our hypothesis 
for Double and Triple ultra-triathlon. This is consistent with other studies, where positive pacing strategies were 
observed in long-distance events. In 2014, the top 100 Ironman® finishers adopted a positive pacing strategy in 
most  races15. Two studies investigating 6 and 23 finishers competing in Deca Iron ultra-triathlon showed that 
split and overall race times increased linearly across the ten  days20,41. However, several studies showed athletes 
adopting an even pacing  strategy41–43. Male Triple Deca Iron ultra-triathletes competing for 30 days finishing an 
Ironman® distance triathlon daily could maintain their  performance5. Additionally, a male triathlete competing 
for 33 days and finishing an Ironman® distance triathlon daily was able to maintain his performance in cycling, 
running, and overall race  times42. The best performing female in Quintuple and Deca Iron ultra-triathlon applied 
an even pacing strategy during her two world record  races43. A potential explanation for the consistent pacing 
could be her background as an elite cyclist and her previous  experience43. Another important aspect is that we 
compared continuous races instead of one per day races. In one-a-day events, the change between disciplines 
might give enough rest to allow a steady pace throughout the race.
A second important finding was the difference in pacing variation. We hypothesized that slower finishers 
would apply more variable pacing. Faster finishers showed a significantly lower variation in cycling pacing in 
Double and Triple Iron ultra-triathlon and running pacing in the Triple Iron ultra-triathlon, confirming our 
hypothesis. Although not significant, faster athletes running in a Double Iron ultra-triathlon also showed the low-
est pacing variation. This is most likely explained by more ‘moderate’ athletes being split into three even groups. 
A recent study regarding elite triathletes showed that a lower variability in race pacing during a10-km run also 
reflected more successful run  times44. Keeping a low pacing variation seems to be the appropriate strategy for 
most distances and disciplines up to a Triple Iron ultra-triathlon.
Pacing variation is also different within disciplines. The variation in pace was lower in cycling than in run-
ning. This result corroborates with data of the world’s best female ultra-triathlete in Quintuple and Deca Iron 
ultra-triathlon where she showed a higher pacing variation in running than in  cycling43. Drinking and eating 
in such events is often reported to be harder in running than in cycling, as a quick stop in running reduces the 
speed to zero, whereas in cycling the speed drops slowly even when one stops  pedaling43.
In the longer race distances, the pacing variation increased. There were no significant changes in pacing vari-
ation between the different performance levels in the Quintuple and Deca Iron ultra-triathlon. These contrasting 
findings might be due to the low participation number in Quintuple and Deca Iron ultra-triathlon. There is no 
systematic research comparing pacing variation in ultra-triathlon to this day. With increasing distance, exercise 
economy seems harder to maintain or limited (i.e., stops for sleeping and nutrition), resulting in a more signifi-
cant pacing variation in longer  distances45.
A further important finding was that men paced faster than women confirming our hypothesis of different 
pacing between men and women. Women in age groups 30–39 and 40–49 years were overall significantly slower 
than men. The difference between sexes increased with increasing race distance for swimming, running, and 
overall race time. However, there was no significant difference in swimming time between men and women in age 
group 30–39 years in Triple Iron ultra-triathlon. This finding is consistent with an analysis of open-water ultra-
distance swimmers from 5 to 25 km, where the difference between sexes was lowest in 10 km compared to 5 km 
and 25  km46. For ultra-swimming, women seemed to achieve a similar or even better performance than  men34,47.
The difference between sexes in endurance performance is primarily caused by physiological differences in 
 VO2  max48 and anthropometric characteristics such as skeletal muscle mass and body  fat49. It has been shown 
that female ultra-runners have lower skeletal muscle mass and a higher percentage of body fat than male ultra-
runners, which may disadvantage women in ultra-running  performance50.
Regarding age, most participants were in age group 40–49 years, followed by the age group 30–39 years for all 
race distances. We hypothesized that ultra-triathletes would reach peak performance at a higher age compared 
to Ironman® triathletes. We could confirm this in the Double Iron ultra-triathlon, where men achieved the best 
performances overall in age groups 30–39 and 40–49 years while in Ironman® triathlon, peak performance for 
men was reported to be at 32.2 ± 1.5  years51. Regarding running performance in Double Iron ultra-triathlon, 
athletes in the age group 30–39 years were the fastest. Several studies showed that endurance and ultra-endurance 
performance in disciplines such as Ironman® triathlon and ultra-marathon appeared to be maintained until the 
age of 35–40 years, followed by modest decreases until 50 years of age and a progressive decrease in performance 
 thereafter37,52,53.
Women in Double Iron ultra-triathlon showed no difference in overall performance across all age groups. 
In swimming, athletes in the age group 40–49 and 50–59 years were significantly faster than athletes in the age 
group 30–39 years. In a study regarding the age-related performance decline in Ironman® triathlon, the decline 
in swimming performance already started in the age group 25–29 years for both women and  men3. A possible 
explanation for our finding could be the low participation number of women in long endurance events such as 
Iron ultra-triathlon or ultra-marathons. A study investigating participation trends in Triple Iron ultra-triathlon 
from 1988 to 2011 showed a stable participation rate of ∼8%54. In other ultra-endurance distances such as 100-
km ultra-marathons, female participation was higher at ∼13% but still very  low50. Consequently, the athletes 
competing have a good estimation of the extent of their performance due to their accumulated experience and 
therefore applied a pacing strategy that was right and correct. In addition, athletes might stop competing after an 
injury, so older athletes result from a further selection process that could be described as ’survival of the  fittest3. 
Another factor for the increase in performance in women in older age groups could be that the motivation in 
achieving best times has more importance for women competing in these  races55.
In contrast to our hypothesis, in Triple Iron ultra-triathlon, athletes in the age group 30–39 years were 
faster than athletes in the age group 40–49 years, suggesting a similar age of peak performance as reported in 
Ironman® triathlon for  men51. A previous study investigating both Triple Iron ultra-triathletes and Deca Iron 
ultra-triathletes showed that athletes were able to maintain their best performances for ages comprised between 
7
Vol.:(0123456789)
Scientific Reports |         (2023) 13:3692  | 
https://doi.org/10.1038/s41598-023-30932-1
www.nature.com/scientificreports/
25 and 44 years, independent of the race  distance39. To summarize, athletes in only one age group (10-years 
interval) between 40 and 49 years might hide an age-related decline in the age group 44–49 years (e.g., sampling 
bias). Peak performance might still be achievable between 40 and 44 years. There were no significant differences 
between the age groups in women participating in the Triple Iron ultra-triathlon. This is primarily explained by 
the low participation number of women. Quintuple and Deca Iron ultra-triathletes were not included because 
of the low number of participants across the age groups.
Age-related declines in endurance and ultra-endurance performance have been well described in the literature 
for  running56,  cycling57,  swimming58 and for  triathlon37,59. The duration of a triathlon race exerts an important 
influence on the age-related changes in triathlon  performance60,61.
The age-related performance decline in Ironman® triathlon starts with 25–29 years in swimming for both 
women and men and in the age group 35–39 years for men respective age 30–34 years for women in cycling, 
running and overall  performance3. We hypothesized that the age-related declines would occur later in the longer 
distances (e.g., Quintuple and Deca Iron ultra-triathlon) compared to the shorter distances (e.g., Double and 
Triple Iron ultra-triathlon). We could confirm our hypothesis for overall performance as in Double Iron ultra-
triathlon the decline started with age group 50–59 years. However, our hypothesis could not be confirmed for 
the Triple Iron ultra-triathlon where the age group 40–49 years was significantly slower than 30–39 years. In 
swimming, there were no significant differences for men until an age-related decline in the age group 50–59 years 
in Double Iron ultra-triathlon and age > 60 years in Triple Iron ultra-triathlon. No significant differences were 
observed in cycling times for all age groups. The age-related decline for running started for both Double and 
Triple Iron ultra-triathletes in the age group 40–49 years. This is consistent with other studies, finding that the 
age-related decline in swimming and cycling was less  pronounced39,59,62. The decrease in running performance 
for men in Triple Iron ultra-triathlon seems to be much more impactful on overall performance than in Double 
Iron ultra-triathlon. Quintuple and Deca Iron ultra-triathlon were not included because of the low number of 
participants across the age groups.
Strength, weakness, limitations and implications for future research. 
The strength of this study 
is the large data set including all finishers of ultra-triathlon races held worldwide between 2004 and 2020, with 
a total of 849 male and 120 female finishers in 46 ultra-triathlons. However, some races might not have been 
documented on the official IUTA website. In earlier years, lap times were not recorded electronically. Another 
strength of this study is its novelty, as it is the first one containing a detailed analysis of the pacing variation 
within the laps of the races. A weakness is that we were not able to consider environmental  conditions63–65 
and individual factors such as  anthropometric49 and nutritional  characteristics66,67 and previous  experience49. 
Besides environmental conditions, other race characteristics can influence pacing, such as elevation in cycling 
and running, swimming in open water (sea, lake) or a pool. Another weakness is the low participation number 
of women and the low participation numbers in Quintuple and Deca Iron ultra-triathlon. This is due to the 
low number of races held for these distances. We did not include non-finishers, so including those might give 
further insight into which pacing strategies result in failure. Future studies would need to include more female 
participants and a higher number of participants across all age groups in Quintuple and Deca ultra-triathlon.
Conclusion
Ultra-triathletes adapted a positive pacing strategy, i.e., speed decreased over the duration of the race. In addition, 
faster athletes show less variation in pacing then moderate and slower athletes in Double and Triple Iron ultra-
triathlon. Pacing variation differed between the disciplines, with the lowest variation in cycling. Consequently, 
ultra-triathletes should be advised to adopt less variable pacing while maintaining a positive pacing strategy. For 
professional athletes, an even pacing strategy might be achievable. Men pace faster than women. The sex differ-
ence increased with increasing race distance for swimming, running, and overall race time. It seems unlikely 
that women will outperform men with increasing distance.
The best age for men in Double Iron ultra-triathlon is between 30 and 49 years and in Triple Iron ultra-
triathlon between 30 and 39 years. The age-related performance decline in the age group 40–49 years is due to 
the lower running performance. This leads to a significant decrease in overall performance in the Triple Iron 
ultra-triathlon. Training should emphasize that finding by focusing more on improvement in running times.
Data availability
The athletes’ data was downloaded from the official IUTA website (www. iutas port. com/).
Received: 16 April 2022; Accepted: 3 March 2023
References
 1. Zaryski, C. & Smith, D. J. Training principles and issues for ultra-endurance athletes. Curr. Sports Med. Rep. 4, 165–170 (2005).
 2. Guinness World Records, Official site, 2023.
 3. Käch, I. W., Rüst, C. A., Nikolaidis, P. T., Rosemann, T. & Knechtle, B. The age-related performance decline in ironman triathlon 
starts earlier in swimming than in cycling and running. J. Strength Cond. Res. 32, 379–395 (2018).
 4. Whyte, G. Age, sex and (the) race: Gender and geriatrics in the ultra-endurance age. Extrem. Physiol. Med. 3, 1 (2014).
 5. Knechtle, B., Zingg, M. A., Rosemann, T., Stiefel, M. & Rüst, C. A. What predicts performance in ultra-triathlon races? A com-
parison between Ironman distance triathlon and ultra-triathlon. Open Access J. Sports Med. 6, 149–159 (2015).
 6. Meili, D., Knechtle, B., Rüst, C. A., Rosemann, T. & Lepers, R. Participation and performance trends in “Ultraman Hawaii” from 
1983 to 2012. Extrem. Physiol. Med. 2, 25 (2013).
 7. Sigg, K. et al. Sex difference in Double Iron ultra-triathlon performance. Extrem. Physiol. Med. 2, 12 (2013).
8
Vol:.(1234567890)
Scientific Reports |         (2023) 13:3692  | 
https://doi.org/10.1038/s41598-023-30932-1
www.nature.com/scientificreports/
 8. Rauch, H. G., St Clair Gibson, A., Lambert, E. V. & Noakes, T. D. A signalling role for muscle glycogen in the regulation of pace 
during prolonged exercise. Br. J. Sports Med. 39, 34–38 (2005).
 9. Sigg, K. et al. Central European triathletes dominate Double Iron ultratriathlon - analysis of participation and performance 
1985–2011. Open Access J. Sports Med. 3, 159–168 (2012).
 10. Skorski, S. & Abbiss, C. R. The manipulation of pace within endurance sport. Front. Physiol. 8, 102 (2017).
 11. Wu, S. S., Peiffer, J. J., Brisswalter, J., Nosaka, K. & Abbiss, C. R. Factors influencing pacing in triathlon. Open Access J. Sports Med. 
5, 223–234 (2014).
 12. Le Meur, Y. et al. Relationships between triathlon performance and pacing strategy during the run in an international competition. 
Int. J. Sports Physiol. Perform. 6, 183–194 (2011).
 13. Abbiss, C. R. & Laursen, P. B. Describing and understanding pacing strategies during athletic competition. Sports Med. (Auckland, 
N.Z.) 38, 239–252 (2008).
 14. Nikolaidis, P. T. & Knechtle, B. Pacing strategies by age in marathon cross-country skiing. Phys. Sportsmed. 1–7 (2018).
 15. Angehrn, N., Rüst, C. A., Nikolaidis, P. T., Rosemann, T. & Knechtle, B. Positive pacing in elite IRONMAN triathletes. Chin. J. 
Physiol. 59, 305–314 (2016).
 16. Knechtle, B. & Nikolaidis, P. T. Sex differences in pacing during “Ultraman Hawaii”. PeerJ 4, e2509 (2016).
 17. Wu, S. S. et al. Pacing strategies during the swim, cycle and run disciplines of sprint, Olympic and half-Ironman triathlons. Eur. 
J. Appl. Physiol. 115, 1147–1154 (2015).
 18. Roelands, B., de Koning, J., Foster, C., Hettinga, F. & Meeusen, R. Neurophysiological determinants of theoretical concepts and 
mechanisms involved in pacing. Sports Med. (Auckland, N.Z.) 43, 301–311 (2013).
 19. Jones, H. S. et al. Physiological and psychological effects of deception on pacing strategy and performance: A review. Sports Med. 
(Auckland, N.Z.) 43, 1243–1257 (2013).
 20. Herbst, L. et al. Pacing strategy and change in body composition during a Deca Iron Triathlon. Chin. J. Physiol. 54, 255–263 (2011).
 21. Casado, A., Hanley, B., Jiménez-Reyes, P. & Renfree, A. Pacing profiles and tactical behaviors of elite runners. J. Sport Health Sci. 
10, 537–549 (2021).
 22. Heidenfelder, A., Rosemann, T., Rüst, C. A. & Knechtle, B. Pacing strategies of ultracyclists in the "Race Across AMerica". Int. J. 
Sports Physiol. Perform. 11 (2016).
 23. Wu, S. S., et al. Improvement of sprint triathlon performance in trained athletes with positive swim pacing. Int. J. Sports Physiol. 
Perform. 11 (2016).
 24. Thuany, M. et al. Discriminant analysis of anthropometric and training variables among runners of different competitive levels. 
Int. J. Environ. Res. Public Health 18, 4248 (2021).
 25. Lorenz, D. S., Reiman, M. P., Lehecka, B. J. & Naylor, A. What performance characteristics determine elite versus nonelite athletes 
in the same sport?. Sports Health 5, 542–547 (2013).
 26. Haney, T. A. & Mercer, J. A. A description of variability of pacing in marathon distance running. Int. J. Exerc. Sci. 4, 133–140 (2011).
 27. Lambert, M. I., Dugas, J. P., Kirkman, M. C., Mokone, G. G. & Waldeck, M. R. J. Sports Sci. Med. 3, 167–173 (2004).
 28. C. A. Rüst, R. Lepers, M. Stiefel, T. Rosemann, B. Knechtle, Performance in Olympic triathlon: Changes in performance of elite 
female and male triathletes in the ITU World Triathlon Series from 2009 to 2012. Springerplus 2, (2013).
 29. Del Coso, J. et al. Running pace decrease during a marathon is positively related to blood markers of muscle damage. PLoS ONE 
8, e57602 (2013).
 30. Tucker, R., Marle, T., Lambert, E. V. & Noakes, T. D. The rate of heat storage mediates an anticipatory reduction in exercise intensity 
during cycling at a fixed rating of perceived exertion. J. Physiol. 574, 905–915 (2006).
 31. St Clair Gibson, A., Schabort, E. J. & Noakes, T. D. Reduced neuromuscular activity and force generation during prolonged cycling. 
Am. J. Physiol. Regul. Integr. Comp. Physiol. 281, R187-196 (2001).
 32. Le Meur, Y. et al. Influence of gender on pacing adopted by elite triathletes during a competition. Eur. J. Appl. Physiol. 106, 535–545 
(2009).
 33. Vleck, V. E., Bentley, D. J., Millet, G. P. & Burgi, A. Pacing during an elite Olympic distance triathlon: Comparison between male 
and female competitors. J. Sci. Med. Sport 11, 424–432 (2008).
 34. Knechtle, B., Zingg, M. A., Rosemann, T. & Rüst, C. A. Sex difference in top performers from Ironman to double Deca iron ultra-
triathlon. Open Access J. Sports Med. 5, 159–172 (2014).
 35. Lepers, R. Analysis of Hawaii ironman performances in elite triathletes from 1981 to 2007. Med. Sci. Sports Exerc. 40, 1828–1834 
(2008).
 36. Wonerow, M., Rüst, C. A., Nikolaidis, P. T., Rosemann, T. & Knechtle, B. Performance trends in age group triathletes in the Olympic 
Distance Triathlon at the World Championships 2009–2014. Chin. J. Physiol. 60, 137–150 (2017).
 37. Lepers, R., Knechtle, B. & Stapley, P. J. Trends in triathlon performance: Effects of sex and age. Sports Med. 43, 851–863 (2013).
 38. Knechtle, R., Rüst, C. A., Rosemann, T. & Knechtle, B. The best triathletes are older in longer race distances—A comparison 
between Olympic, Half-Ironman and Ironman distance triathlon. Springerplus 3, 538 (2014).
 39. Knechtle, B., Rust, C. A., Knechtle, P., Rosemann, T. & Lepers, R. Age-related changes in ultra-triathlon performances. Extrem. 
Physiol. Med. 1, 5 (2012).
 40. Cohen, J. Statistical Power Analysis for the Behavioral Sciences (Lawrence Erlbaum Associates, 2nd, 1988).
 41. Knechtle, B., Rosemann, T., Lepers, R. & Rüst, C. A. A comparison of performance of Deca Iron and Triple Deca Iron ultra-
triathletes. Springerplus 3, 1–13 (2014).
 42. Knechtle, B., Rüst, C. A., Rosemann, T. & Martin, N. 33 Ironman triathlons in 33 days–a case study. Springerplus 3, 1–9 (2014).
 43. Sousa, C. V., Nikolaidis, P. T., Clemente-Suárez, V. J., Rosemann, T. & Knechtle, B. Pacing and performance analysis of the World’s 
Fastest Female Ultra-Triathlete in 5x and 10x Ironman. Int. J. Environ. Res. Public Health 17, 1543 (2020).
 44. Etxebarria, N., Wright, J., Jeacocke, H., Mesquida, D. & Pyne, B. Running your best triathlon race. Int. J. Sports Physiol. Perform. 
16, 744–747 (2022).
 45. Roecker, K., Schotte, O., Niess, A. M., Horstmann, T., Dickhuth, H. H. Predicting competition performance in long-distance run-
ning by means of a treadmill test. Med. Sci. Sports Exercise 30, (1998).
 46. M. A. Zingg, C. A. Rüst, T. Rosemann, R. Lepers, B. Knechtle, Analysis of sex differences in open-water ultra-distance swimming 
performances in the FINA World Cup races in 5 km, 10 km and 25 km from 2000 to 2012. BMC sports science, medicine & reha-
bilitation 6, (2014).
 47. C. A. Rüst, B. Knechtle, T. Rosemann, R. Lepers, Women reduced the sex difference in open-water ultra-distance swimming [For-
mula: see text] La Traversée Internationale du Lac St-Jean, 1955–2012. Applied physiology, nutrition, and metabolism = Physiologie 
appliquee, nutrition et metabolisme 39, (2014).
 48. B. Knechtle et al., Fat oxidation in men and women endurance athletes in running and cycling. International journal of sports 
medicine 25, (2004).
 49. Knechtle, B., Wirth, A., Baumann, B., Knechtle, P. & Rosemann, T. Personal best time, percent body fat, and training are differently 
associated with race time for male and female ironman triathletes. Res. Q. Exerc. Sport 81, 62–68 (2010).
 50. B. Knechtle, C. A. Rüst, T. Rosemann, R. Lepers, Age-related changes in 100-km ultra-marathon running performance. Age 
(Dordrecht, Netherlands) 34, (2012).
 51. Stiefel, M., Knechtle, B., Rüst, C. A., Rosemann, T. & Lepers, R. The age of peak performance in Ironman triathlon: A cross-sectional 
and longitudinal data analysis. Extrem. Physiol. Med. 2, 27 (2013).
9
Vol.:(0123456789)
Scientific Reports |         (2023) 13:3692  | 
https://doi.org/10.1038/s41598-023-30932-1
www.nature.com/scientificreports/
 52. Reaburn, P. & Dascombe, B. Endurance performance in Masters athletes. Eur. Rev. Aging Phys. Activ. 5, 31–42 (2008).
 53. M. Zingg, C. A. Rüst, R. Lepers, T. Rosemann, B. Knechtle, Master runners dominate 24-h ultramarathons worldwide-a retrospec-
tive data analysis from 1998 to 2011. Extreme Physiol. Med. 2, (2013).
 54. Rüst, C. A., Knechtle, B., Knechtle, P., Rosemann, T. & Lepers, R. Participation and performance trends in triple iron ultra-
triathlon—A cross-sectional and longitudinal data analysis. Asian J. Sports Med. 3(3), 145–152 (2012).
 55. Krouse, R. Z., Ransdell, L. B., Lucas, S. M. & Pritchard, M. E. Motivation, goal orientation, coaching, and training habits. J. Strength 
Cond. Res. 25, 2835–2842 (2011).
 56. N. PT, A.-C. JR, V. E, R. T, K. B, The Age-Related Performance Decline in Marathon Running: The Paradigm of the Berlin Marathon. 
International journal of environmental research and public health 16, (2019).
 57. B. J, P. CR, B. SR, D. RC, Age-related changes in maximal power and maximal heart rate recorded during a ramped test in 114 
cyclists age 15–73 years. Journal of aging and physical activity 13, (2005).
 58. T. H, S. DR, Endurance exercise performance in Masters athletes: age-associated changes and underlying physiological mechanisms. 
The Journal of physiology 586, (2008).
 59. Lepers, R., Sultana, F., Bernard, T., Hausswirth, C. & Brisswalter, J. Age-related changes in triathlon performances. Int J Sports Med 
31, 251–256 (2010).
 60. E. F et al., Age and gender interactions in short distance triathlon performance. Journal of sports sciences 31, (2013).
 61. E. F, K. B, R. CA, R. T, L. R, The age-related decline in Olympic distance triathlon performance differs between males and females. 
The Journal of sports medicine and physical fitness 53, (2013).
 62. T. Bernard, F. Sultana, R. Lepers, C. Hausswirth, J. Brisswalter, Age-related decline in olympic triathlon performance: effect of 
locomotion mode. Experimental aging research 36, (2010).
 63. J. A. Wegelin, M. D. Hoffman, Variables associated with odds of finishing and finish time in a 161-km ultramarathon. European 
journal of applied physiology 111, (2011).
 64.  Dallam, G. M., Jonas, S., Miller, T. K. Medical considerations in triathlon competition: recommendations for triathlon organisers, 
competitors and coaches. Sports Med. 35 (2005).
 65.  Vihma, T. Effects of weather on the performance of marathon runners. Int. J. Biometeoroll 54 (2010).
 66. Applegate, E. Nutritional concerns of the ultraendurance triathlete. Med. Sci. Sports Exercise 21 (1989).
 67. Bentley, D. J., Cox, G. R., Green, D. & Laursen, P. B. Maximising performance in triathlon: applied physiological and nutritional 
aspects of elite and non-elite competitions. J. Sci. Med. Sport 11, 407–416 (2008).
Author contributions
Conceptualization: M.S., B.K. Data curation: M.S. Formal analysis: C.V.S. Writing- original draft: M.S., B.K. All 
authors have read and agreed to the published version of the manuscript. All authors consent to the publication 
of this manuscript.
Competing interests 
The authors declare no competing interests.
Additional information
Correspondence and requests for materials should be addressed to B.K.
Reprints and permissions information is available at www.nature.com/reprints.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and 
institutional affiliations.
Open Access  This article is licensed under a Creative Commons Attribution 4.0 International 
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or 
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the 
Creative Commons licence, and indicate if changes were made. The images or other third party material in this 
article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the 
material. If material is not included in the article’s Creative Commons licence and your intended use is not 
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from 
the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
© The Author(s) 2023

Changes in pacing variation with increasing race duration in ultra-triathlon races.
Stjepanovic, Mirko,Knechtle, Beat,Weiss, Katja,Nikolaidis, Pantelis Theodoros,Cuk, Ivan,Thuany, Mabliny,Sousa, Caio Victor