A Multi-Test Assessment of Anaerobic Power in Male Athletes
Bibliographic record
Abstract
1436 The assessment of sport specific anaerobic power using various field and laboratory tests is often used to chart training progress and identify talent. PURPOSE: To determine if an extensive battery of anaerobic tests could successfully identify differing components of athletic power, predict short sprint performance, and distinguish between worst, average, and best performances. METHODS: 18 male college athletes (23 ± 7 yrs, Height 179 ± 5 cm, Body mass 85 ± 12 kg) performed 8 subclasses of tests to assess specific components of anaerobic power (1RM tests: Smith machine back squat, supine bench press, and barbell power clean; Jump tests: CMVJ, CMVJ + 20kg, CMVJ +40 kg, CONJ, 30cm depth jump, plyometric push up, and standing long jump; 10M sprint, 35M sprint; 10 second Quebec cycle test; 7.2kg overhead shot throw, 3.5kg seated shot throw). RESULTS: T-tests were used to assess any statistical differences between jump variables (Height (cm), Ppower (W), Ppower/kg (W/kg)) for the different jump conditions (CMVJ, CMVJ +20kg, CMVJ + 40kg, CONJ, 30cm depth jump). Correlation coefficients (r) and coefficients of determination (R squared) values were calculated between all test variables to assess commonality between tests. Correlations ranged from r = −0.85 (CD 72.4%) to r = 0.91 (CD 83%) Power produced during the depth jump condition was statistically greater (p ≤ 0.05) compared to all other jump conditions. Measure's corrected for body mass (Ppower/kg) produced stronger correlations when body mass was the primary resistance, and when maximal speed (10 m, 35 m sprints (s)), and height (CMVJ, CONJ) were the performance objectives. Regression analysis highlighted statistically significant groupings of variables, which could in part predict performance (10m sprint, 35m sprint (s), height CMVJ, CONJ (cm), Overhead shot distance (m), Plyopush up power (W)) outcomes. The best three groupings accounted for 65% to 85% of the performance outcomes during the performance tests. CONCLUSIONS: A combined multi-test approach of anerobic power is needed to assess varying force/velocity components of short sprint, jumping, and throwing performance with a greater degree of specificity. Care needs to be taken so that tests do not measure the same components of anaerobic power.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 0.001 |
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".