Impact of Weekly Workload Distribution on Performance in Male Football Players Across Competitive Levels – Scientific Hypothesis or Empirical Evidence: A Systematic Review
Bibliographic record
Abstract
This systematic review aims to comprehensively analyse weekly workload distribution patterns in male football and investigate their effects on performance outcomes. The review addresses two main objectives: (1) characterising how training load is distributed within weekly microcycles across different competitive levels, and (2) examining the evidence linking these distribution strategies to performance outcomes. A systematic search was conducted using PubMed, ScienceDirect, and Web of Science databases until December 2025. Included studies involved male football players at any competitive level and reported workload data across multiple days within weekly microcycles. Methodological quality was assessed using the Newcastle-Ottawa Scale. Expected outcomes include a synthesis of current periodisation practices in football and an evaluation of whether these practices are supported by empirical evidence or remain largely theoretical. This review will provide evidence-based recommendations for practitioners regarding optimal workload management strategies.
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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 | 0.045 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.633 | 0.959 |
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; both teacher heads agree on what is shown here.
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".