Study note • PMID 41303792
Week-by-Week Predictive Value of External Load Ratios on Injury Risk in Professional Soccer: A Logistic Regression and ROC Curve Analysis Approach.
Worth trying if it fits your goal and context.
ELI5
In plain language
This study aimed to assess the week-by-week predictive value of Acute:Chronic Workload Ratios (ACWRs) for non-contact injury risk in professional soccer players. (cohort study; elite participants).
The abstract doesn’t indicate a clear change in Injury risk 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: This study aimed to assess the week-by-week predictive value of Acute:Chronic Workload Ratios (ACWRs) for non-contact injury risk in professional soccer players.
- • The abstract doesn’t indicate a clear change in Injury risk under the tested conditions.
- • Population: elite participants.
- • Protocol cues (title/abstract): 20 km • 25 km.
Protocol
Protocol (as reported)
- • Intervention/exposure: injury, load.
- • Dose/time/duration cues in abstract/title: 20 km • 25 km.
- • Outcomes: Injury risk.
- • Replication note: abstracts often omit adherence and timing; confirm details before changing training or supplementation.
Fit
Who it helps, and who should skip it
Who it helps
- • Athletes similar to the study population (elite participants) working on injury risk.
- • Athletes who can measure Injury risk with a repeatable workout or time-trial effort.
Who should skip
- • 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: cohort study.
- • Population: elite participants.
- • Outcomes measured: Injury risk.
- • Protocol cues mentioned: 20 km • 25 km.
- • Source: PubMed PMID 41303792 (2025) — Medicina (Kaunas, Lithuania).
Results excerpt
What the abstract reports
“The ACWR for 15-20 km/h (DSR15-20) demonstrated the highest predictive accuracy, particularly in Week 3 (AUC = 0.811, p = 0.004).”
Note: excerpts are short; for full context, read the paper.
Limits
Limitations & 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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