Acceleration, Deceleration and Dynamic Stress Load in Elite Hurling: A Between-Quarter and Between-Position Comparison
Bibliographic record
Abstract
This study described the decrement in accelerations, decelerations and dynamic stress load (DSL) between quarters in elite hurling. GPS (10-Hz) were used to record data from 42 players over 22 games (2018-2020 season). The number of accelerations and decelerations and DSL between quarters were assessed. Accelerations and decelerations were greater in Q1 than Q2 (ES = 0.28 and ES = 0.44, respectively), and Q4 (ES = 0.57 and ES = 0.60, respectively), and in Q3 compared to Q4 (ES = 0.50 and ES = 0.44, respectively). The DSL was 56 ± 21 AU in Q1, 56 ± 20 AU in Q2, 52 ± 20 AU in Q3 and 56 ± 24 AU in Q4. There was a decrease in DSL in Q3 compared to Q1 (ES = -0.20) and Q2 (ES = -0.20). Each position experienced a temporal decrease in at least one quarter (ES = 0.43-1.46) in all metrics except full-backs', half-backs' and full forwards' accelerations, midfielders' decelerations and midfielders' and half forwards' DSL. Current data show temporal decrements in running performance in Q2 and Q4 and DSL in Q3. Players should be conditioned to minimize the drop-off in running performances following the third quarter.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".