A correction to the source editorial exists (BJSM 2019;53(18):e6) but its text was not retrievable. "A correction to the sweet-spot paper" is materially different from "a correction to that paper", and this card contradicts a widely-taught metric. The grade is withheld until that is settled.
The verdict below is shown because withholding it silently would be worse than showing it with its caveat. It must not be cited until resolved.
The random-denominator test. Researchers re-analysed published injury data replacing the chronic-load denominator with fixed and randomly generated numbers. Original ACWR: OR 2.45 (1.28–4.71). Divided by a constant: OR 1.95. Random denominators: OR 1.16–2.07. Discrimination was 0.574 for ACWR versus 0.544 for acute load alone — against 0.5 for chance. Independently replicated in a Bayesian analysis of 35 first-division footballers.
Mathematical coupling. The acute week sits inside the four-week chronic denominator in roughly 95% of studies. Correlating a quantity with a function of itself generates correlation from the algebra alone.
Analytic irreproducibility. One dataset (86 players, 6,250 athlete-days, 196 health problems) was analysed 108 different ways. Only 21% of those analyses were statistically significant. The finding is a function of the analyst's choices.
Provenance of the 'sweet spot'. The 0.8–1.3 band comes from a 2016 editorial that fitted a polynomial to binned points (R²=0.53) — not a validated model. It was subsequently reproduced in a consensus statement, which is how it acquired institutional authority.
The intervention test. A cluster RCT of 34 teams and 482 elite youth footballers of both sexes, over a full 10-month season, had coaches plan all training using published ACWR principles delivered through a commercial athlete-management system. Result: RR 1.01 (95% CI 0.91–1.12, p=0.84). No effect. The authors flag high dropout and imperfect adherence.
Two cohorts found injuries concentrated inside the sweet spot. 27.5% of soccer and 83.3% of pentathlon injuries occurred within 0.8–1.3, and the most severe soccer injuries occurred there. In 1,660 children, injury risk was essentially flat at ~3% from a 60% decrease to a 30% increase in activity.
- The text of the correction to the source editorial could not be retrieved (403, no abstract). This is the blocker.
- The formal retraction request for the sweet-spot figure exists as a preprint; no peer-reviewed venue was located.
- No post-2016 consensus statement revising the recommendation was located — but absence of location is not proof of absence.
- Impellizzeri FM, et al. (2021). Sports Med 51(3):581–592 — random-denominator test ↗
- Dalen-Lorentsen T, et al. (2021). Br J Sports Med 55(2):108–114 — cluster RCT, n=482 ↗
- Dalen-Lorentsen T, et al. (2021). JOSPT 51(4):162–173 — 108 analyses ↗
- Lolli L, et al. (2019). Br J Sports Med 53(15):921–922 — mathematical coupling ↗
- Carbone L, et al. (2022). J Clin Med 11(19):5945 — Bayesian replication ↗
- Sedeaud A, et al. (2020). Front Physiol 11:1034 — injuries inside the sweet spot ↗
- Wang C, et al. (2022). Am J Epidemiol 191(4):665–673 — n=1,660 children ↗
- Blanch P, Gabbett TJ (2016). Br J Sports Med 50(8):471–475 — source of the sweet spot ↗
- v1 · 2026-07-26 · Initial grade — withheld pending correction verification.
SSMT. "The acute:chronic workload ratio predicts injury risk, and keeping athletes within a target ACWR range reduces injuries." Claim SSMT-2026-0005 v1, graded 2026-07-26. https://sportssciencetech.com/c/SSMT-2026-0005