Study note • PMID 41295769
Real-Time Performance Prediction in Long-Distance Trail Running: A Practical Model Based on Terrain Difficulty and Pacing Variability.
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
Trail running is a demanding endurance sport where performance prediction models often rely on laboratory testing or pre-race data, limiting their practical application. (controlled study; n=947 runners).
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: Trail running is a demanding endurance sport where performance prediction models often rely on laboratory testing or pre-race data, limiting their practical application.
- • The abstract doesn’t indicate a clear change in Time-trial performance under the tested conditions.
- • Population: n=947 runners.
- • 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 (n=947 runners) 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: n=947 runners.
- • Outcomes measured: Time-trial performance.
- • Source: PubMed PMID 41295769 (2025) — Sports (Basel, Switzerland).
Results excerpt
What the abstract reports
“Further validation in similar endurance events is recommended to confirm its utility as a practical tool for training and competition planning.”
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.
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