Strength Level of Professional Elite Soccer Players after the COVID-19 Lockdown Period: A Retrospective Double-Arm Cohort Study
Bibliographic record
Abstract
Background. It is well known that periods of inactivity generate a loss of muscle strength, a fundamental component of sports performance in soccer. However, little information is available on the decrease in strength levels in professional soccer players after the quarantine lockdown that occurred during the COVID-19 pandemic. Aim. To compare the isokinetic peak torque profiles of professional soccer players from different teams before and after the quarantine period generated by COVID-19. Methods. A retrospective observational study was performed using data collected from two different professional elite-level soccer teams just before and immediately after the COVID-19 quarantine period. One team gave individual instructions to its players for conditioning maintenance at home during the quarantine period, while the other team used regular video calls to maintain the player’s conditioning status on home training. The main outcomes were the mean peak torque of knee extensors and flexors, from concentric and eccentric contractions of each playing position. Analysis. A two-way ANOVA analysis was used to compare peak torque before and after the quarantine period and between both teams’ strategies, showing a statistically significant reduction in eccentric knee flexor peak torque from the team that did not have remote monitoring. Conclusions. Remote monitoring programs are recommended so that athletes are less affected by the deleterious effects of confinement.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.007 | 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".