Study note • PMID 26034882
The influence of performance level, age and gender on pacing strategy during a 100-km ultramarathon.
How to use this page
This note summarizes one study record. Check the participants, methods, results, and limitations before applying it to training.
- • Design signal: controlled study.
- • Population relevance: athlete/trained context.
- • Consistency: single-study evidence.
- • Practical recommendation depends on tolerance, context, and whether it protects training consistency.
ELI5
In plain language
The aim of this study is to analyse the influence of performance level, age and gender on pacing during a 100-km ultramarathon. (controlled study; athletes).
The abstract doesn’t indicate a clear change in Time-trial performance under the tested conditions. Treat this as a signal, not a guarantee; confirm methods and context in the full paper.
Takeaways
What the abstract suggests
- • Study question: The aim of this study is to analyse the influence of performance level, age and gender on pacing during a 100-km ultramarathon.
- • The abstract doesn’t indicate a clear change in Time-trial performance under the tested conditions.
- • Population: athletes.
- • Protocol cues: abstract may omit dose/timing; use the full paper to replicate accurately.
Protocol
Protocol (as reported)
- • Intervention/exposure: pacing.
- • Dose/time/duration: abstract doesn’t include enough detail; use the full paper’s methods section.
- • Outcomes: Time-trial performance.
- • Replication note: abstracts often omit adherence and timing; confirm details before changing training or supplementation.
Fit
Who it may help, and who should be cautious
Who it helps
- • Athletes similar to the study population (athletes) working on pacing.
- • Athletes who can measure Time-trial performance with a repeatable workout or time-trial effort.
Who should be cautious
- • If you have symptoms or conditions that make the intervention risky, get professional guidance.
- • If you’re near race day and can’t safely test, defer the experiment.
Methods
What the study actually did
- • Design: controlled study.
- • Population: athletes.
- • Outcomes measured: Time-trial performance.
- • Source: PubMed PMID 26034882 (2016) — European journal of sport science.
Results excerpt
What the abstract reports
“Overall strategies remained consistent across age categories, although a similar phenomenon was observed within each category whereby 'top' competitors displayed lower relative speeds than 'bottom' competitors in the early stages, but higher relative speeds in the later stages.”
Note: excerpts are short; for full context, read the paper.
Limits
Limitations and bias
- • Abstract-only summaries can miss critical details (population, protocol, adherence, and context).
- • Single studies often don’t generalize to your event, history, and training load; treat results as a starting point.
- • If your context differs (elite vs recreational; cycling vs running), adjust expectations and be conservative.
- • This is performance information, not medical advice.
Adaptive AI coach for iPhone
Meet your adaptive AI coach.
Tell your coach what you are training for. It builds the plan, follows the work you complete, and adapts upcoming training when recovery, your schedule, or real life changes.
Keep going
Performance Science Lab
Research summaries for endurance athletes, with study context, practical protocols, and clear limitations.
Pacing performance research
Pacing is applied physiology: the best plan fails if you spend your budget early.
Caffeine for endurance performance: a practical protocol
Evidence-informed protocol: Caffeine for endurance performance: a practical protocol. Practical steps, who it helps, and what to watch out for.