Beneficial Performance Effects of Training Load Intensification Can Be Abolished by Functional Overreaching: Lessons From a Water Polo Study in Female Athletes
Bibliographic record
Abstract
ABSTRACT: Brisola, GMP, Dutra, YM, Murias, JM, and Zagatto, AM. Beneficial performance effects of training load intensification can be abolished by functional overreaching: Lessons from a water polo study in female athletes. J Strength Cond Res 37(6): e391-e402, 2023-The purpose of this study was to compare the outcomes from 2 weeks of training load intensification strategy in female water polo players diagnosed with functional overreaching (F-OR) with no F-OR players (acute fatigue) on the performance outcomes and hormonal, immunological, and cardiac autonomic nervous system responses. Twenty-two female water polo players were allocated into control and intensification group during 7 weeks. The swimming performance, biochemical parameters, heart rate variability, profile of mood states, and upper respiratory tract infection symptoms were assessed twice before and twice after 2 weeks of intensification period. F-OR showed a worsening in total time of the repeated sprint ability (RSA) test compared with the control group and the acute fatigue group after intensification ( p ≤ 0.035). Furthermore, after the tapering period, the F-OR group maintained worse total time of the RSA test than the acute fatigue group ( p = 0.029). In addition, the acute fatigue group showed improvement in total time of the RSA test after intensification compared with the control group ( p < 0.001). No significant interactions were found for the other parameters. Therefore, periods of intensification without the F-OR development can promote higher gains in the total time of the RSA test after intensification and tapering period.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".