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Record W4416168844 · doi:10.70252/erin2946

Perceived Recovery and Muscle Fatigue in Professional Soccer Players During Preseason

2025· article· en· W4416168844 on OpenAlexaff
Josip Maleš, Frane Žuvela, Nicola Luigi Bragazzi, Andrea De Giorgio, Goran Kuvačić

Bibliographic record

VenueInternational journal of exercise science · 2025
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsYork University
Fundersnot available
KeywordsAthletesMuscle fatigueTeam sportIntensity (physics)LeagueMuscle massFootballBody mass index

Abstract

fetched live from OpenAlex

This study aimed to examine weekly variations and within-subject relationships between internal training intensity (ITI), perceived recovery (TQR), neuromuscular performance (CMJ), and perceived muscle soreness (PMS) during a four-week preseason period in professional soccer players. Twenty-three soccer players (age 24.8 ± 4.4 years; height 182 ± 7 cm; body mass 74.6 ± 6.7 kg) classified as Tier 3 athletes from the Croatian Second Soccer League were monitored using session rating of perceived exertion, TQR scales, countermovement jump tests, and PMS questionnaires. A significant reduction in ITI and concurrent improvement in TQR scores were observed across the preseason, with the highest intensity in week 1 and the lowest recovery in week 2. CMJ height performance declined during peak fatigue but rebounded as training intensity tapered. Repeated-measures correlations revealed negative associations between weekly ITI and TQR of the following week (rrm = −0.72), and between ITI and CMJ (rrm = −0.55), indicating that greater training intensities may impair both perceptual and neuromuscular recovery. The training stimulus–recovery difference index was positively associated with next-day TQR, suggesting it may serve as a sensitive marker of session-level readiness. These findings highlight the interplay between intensity, recovery, and fatigue, emphasizing the utility of low-cost subjective and objective tools for monitoring preseason responses and guiding individualized training strategies in elite soccer settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.345
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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