Identification of Sensitive Measures of Recovery After External Load From Football Match Play
Bibliographic record
Abstract
Objective measures of recovery from football match play could be useful for assessing athletes' readiness to train, if sensitive to preceding match load. PURPOSE: To identify the sensitivity of countermovement-jump (CMJ) performance and concentration of salivary testosterone and cortisol relative to elite football match load. METHODS: CMJ performance and salivary hormones were measured in 18 elite football players before (27, 1 h) and after (0.5, 18, 42, 66, 90 h) 3 consecutive matches. Match load was determined via accelerometer-derived PlayerLoad and divided into tertiles. Sensitivity of CMJ performance and hormone concentrations to match load was quantified with t statistics and magnitude-based inferences (change in mean as % ± 90% confidence interval) derived with a linear mixed model. RESULTS: Jump height was reduced in medium and high load at 0.5 h (10% ± 7% and 16% ± 8%) and 18 h (7% ± 4% and 9% ± 5%) postmatch. There was a 12% ± 7% reduction in ratio of flight time to contraction time (FT:CT) in high load at 0.5 h post, with reductions in medium and high load at 18 h. Reductions in FT:CT persisted at later postmatch time points than changes in jump height. Increased cortisol (range 55-165%) and testosterone (range 17-20%) were observed in all match loads at 0.5 h post, with individual variability thereafter. CONCLUSIONS: Measures of CMJ performance and hormonal concentrations were sensitive to levels of A League football match load. Although jump height was reduced immediately postmatch, FT:CT provided a more sensitive measure of recovery. Football match play induces an acute hormonal response with substantial individual variability thereafter.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".