REF-836 · Barrero et al., 2014 · International Journal of Sports Medicine, Vol. · Paper · PubMed

Intensity Profile during an Ultra-endurance Triathlon in Relation to Testing and Performance

Blimited evidenceMeasured on trained to highly trained athletesWritten before October 2026, being re-checked

Nine male ultra-endurance triathletes did graded tests in cycling, treadmill running and free swimming before an Ironman-distance race, giving sport-specific heart rate (HR)-VO2 equations and HR at the ventilatory thresholds (VT). In the race, mean HR was higher in the swim (149.2 bpm) than on the bike (137.1 bpm) and the run (136.2 bpm), and bike and run HR sat below both VTs.

The larger the gap between swim and bike HR, the worse the times in the following stages. Weight-adjusted VO2max and the bike-swim HR difference were the best predictors of final race time (81%).

Participants

n=9 male ultra-endurance triathletes (abstract: "9 male ultra-endurance triathletes completed the study"). Age, experience and finishing times are not given in the abstract.

Protocol

Before racing: graded exercise tests in cycle ergometry (C), treadmill running (R) and free swimming (S) for peak VO2 and HR at the ventilatory thresholds.
Exercise-specific HR-VO2 regression equations developed for each athlete.
Race HR recorded through an ultra-endurance triathlon and converted to an intensity profile with those equations.
Race HR and HR differences between stages related to split and final times.

Key Results

StageMean race HR (SD)
Swim (S)149.2 (10.1) bpm
Cycle (C)137.1 (5.7) bpm
Run (R)136.2 (10.5) bpm
During the cycle and the run, HR was below both ventilatory thresholds (the abstract gives "11% and 27-28%").
HR differences between the swim and the cycle correlated with cycle, run and final times; the largest swim-cycle differences went with the worst times in the next stages.
The athletes performed the swim at a higher relative intensity, which was inversely correlated with performance in the following stages.
Best predictors of final race time (81%): weight-adjusted VO2max and the HR difference between cycle and swim.

Practical Application

Does a hard Ironman swim cost me later in the race? In nine male ultra-endurance triathletes, the swim was raced at the highest heart rate of the day (149.2 bpm vs 137.1 on the bike and 136.2 on the run), and the athletes with the biggest swim-to-bike heart-rate gap had the slowest bike and run splits. Swim the Ironman controlled; the swim was the relatively hardest leg for these athletes, and a relatively harder swim went with slower later stages.
Heart rate on the bike and the run sat below both ventilatory thresholds here, so the Ironman bike and run were raced below the first threshold by heart rate for these athletes; that fits the Ironman athletes of REF-784 racing mainly in zone 2.
Weight-adjusted VO2max plus the bike-swim heart-rate difference predicted 81% of final time — fitness first, then not overcooking the swim.
Inference, not tested here: a high swim heart rate may partly reflect the swim start, cold water and horizontal position rather than only effort; the correlation does not tell which. Whether easing the swim speeds up a given athlete's bike and run was not tested.
Not from this paper; the base's own practice: set swim, bike and run heart-rate zones separately for each sport, because the same HR does not mean the same intensity across sports (REF-537).

Limitations

n=9 men, one race; no women; competitive level not given in the abstract.
Intensity is inferred from HR through lab HR-VO2 equations; HR in open water and late in a long race (cardiovascular drift) may not track VO2 as it did in the lab.
The abstract's "11% and 27-28%" below the ventilatory thresholds is not fully specified (which threshold, which sport); cite the direction, not the percentages, without the full text.
The 81% prediction and the swim-bike correlations come from nine athletes and may not replicate.
Written from the abstract and record metadata only (full text not read).
How this entry was checked and changed
Why this level

small observational study, n=9, correlations only