The Relationship between Training Load and Injury Risk in Basketball: A Systematic Review
Bibliographic record
Abstract
The relationship between training load and injury risk in basketball is an important area in sports injury prevention and performance enhancement; however, there is limited conclusive evidence of their associations. The aim of this systematic review was to examine the evidence of the relationship between training load and injury risk in basketball, which is one of the most common sports worldwide. This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A comprehensive literature search was conducted on the PubMed, SCOPUS, and Web of Science databases up until March 2024. The search aimed to identify studies that prospectively and/or retrospectively examined the relationship between training load and injury risk in basketball. Inclusion criteria were limited to studies published before February 2024. The quality of each study was assessed using the Newcastle-Ottawa Quality Assessment Scale and Oxford Centre for Evidence-Based Medicine levels of evidence. A narrative synthesis of the findings was performed. A total of 14 articles met the inclusion criteria and were included in the review. Of these, 11 studies reported at least partially statistically significant results, providing evidence of a relationship between training load and injury risk. In conclusion, the findings of this review suggest a clear relationship between training load and injury risk in basketball.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".