The DOI matches its Crossref record.
Accumulated workloads and the acute:chronic workload ratio relate to injury risk in elite youth football players
Open accessAbstract
Aim: The purpose of this study was to investigate the relationship between physical workload and injury risk in elite youth football players. Methods: The workload data and injury incidence of 32 players were monitored throughout 2 seasons. Multiple regression was used to compare cumulative (1, 2, 3 and 4-weekly) loads and acute:chronic (A:C) workload ratios (acute workload divided by chronic workload) between injured and non-injured players for specific GPS and accelerometer-derived variables:total distance (TD), high-speed distance (HSD), accelerations (ACC) and total load. Workloads were classified into discrete ranges by z-scores and the relative risk was determined. Results: A very high number of ACC (≥9254) over 3 weeks was associated with the highest significant overall (relative risk (RR)=3.84) and non-contact injury risk (RR=5.11). Non-contact injury risk was significantly increased when a high acute HSD was combined with low chronic HSD (RR=2.55), but not with high chronic HSD (RR=0.47). Contact injury risk was greatest when A:C TD and ACC ratios were very high (1.76 and 1.77, respectively) (RR=4.98). Conclusions: In general, higher accumulated and acute workloads were associated with a greater injury risk. However, progressive increases in chronic workload may develop the players' physical tolerance to higher acute loads and resilience to injury risk.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Soligard, T., Schwellnus, M., Alonso, J.-M., Bahr, R., Clarsen, B., Dijkstra, H. P., Gabbett, T., Gleeson, M., Hägglund, M., Hutchinson, M. R., et al. (2016) · British Journal of Sports Medicine · doi:10.1136/bjsports-2016-096581 · Cited by 1,041
Schwellnus, M., Soligard, T., Alonso, J.-M., Bahr, R., Clarsen, B., Dijkstra, H. P., Gabbett, T. J., Gleeson, M., Hägglund, M., Hutchinson, M. R., et al. (2016) · British Journal of Sports Medicine · doi:10.1136/bjsports-2016-096572 · Cited by 836
Metadata
- Authors
- Bowen, L., Gross, A. S., Gimpel, M., & Li, F.-X.
- Venue
- British Journal of Sports Medicine
- Publisher
- BMJ
- Published
- 2016-07-22
- Volume
- 51
- Issue
- 5
- Pages
- 452-459
- ISSN
- 0306-3674 (ISSN-L)
- 1473-0480
- OpenAlex
- W2489330634
- Cited by
- 351
- References
- 0
- FWCI
- 28.50
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.