Positional Relationships Between Various Sprint and Jump Abilities in Elite American Football Players
Bibliographic record
Abstract
The purpose of this study was to investigate positional relationships between sprint and jump abilities and body mass in elite college American football players (n = 1,136). Data from the annual National Football League combine over the years 2005-2009 were examined. The measures included for examination were the 9.1-, 18.3-, 36.6-, and flying 18.3-m sprints and the vertical and horizontal jumps. Pearson's correlation coefficients (r) were calculated to determine the relationships between the tests, and coefficients of determination (r2) were used to determine common variance. With the exception of the relationship between the 9.1-m and the flying 18.3-m sprints, the relationships between all sprints are very strong. Vertical jump ability is more strongly associated with maximum speed, as compared with acceleration. Horizontal jump ability is similarly associated with maximum speed and acceleration. The 9.1-, 18.3-, and flying 18.3-m sprints and the jump tests would appear to measure independent skills. Stationary start sprints up to 36.6 m appear to be heavily influenced by acceleration and may thus measure similar characteristics. The flying 18.3-m sprint is recommended as a measure of maximum speed. Body mass was most strongly associated with performance in the lineman group. When body mass was controlled for, correlations weakened across all the groups. The role of body mass remains unclear. Regardless of sport, the present research supports the notion that the relationships between various sprint and jump abilities warrant positional consideration. Coaches and practitioners will be able to use the findings of this research to better test and monitor athletes requiring different skills.
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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 | 0.003 | 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 | 0.001 |
| 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".