Relation Between Scouting Combine and Game Performance Among Defensive National Players in the Canadian Football League
Bibliographic record
Abstract
ABSTRACT: Pincivero, DM and Vandeweerd, J. Relation between scouting combine and game performance among defensive national players in the Canadian Football League. J Strength Cond Res 35(12S): S5-S10, 2021-The objective of this study was to examine the relation between fitness testing and draft order on professional performance of defensive national players in the Canadian Football League. A retrospective analysis (2006-2019) was completed for all subjects at the National Scouting Combine (NSC) and included height, body mass, 40 yard (38 m) dash, bench press, vertical jump, broad jump, and the shuttle run. A compiled variable for all NSC results was derived by calculating averaged Z-scores (Zavg). Multiple regression analyses revealed that the draft order was significantly predicted by the 40 yard dash and Zavg for the defensive linemen, Zavg for the linebackers, and the broad jump for the defensive backs. The broad jump and the 40 yard dash were significant predictors of total and special teams tackles per game for the defensive linemen. The draft order significantly predicted games played and defensive tackles per game, whereas the broad jump predicted total tackles per game for the linebackers. None of the NSC results or draft order significantly predicted defensive back league performance. The findings suggest that NSC testing can provide low-to-moderate levels of predictability for future performance in national-categorized defensive linemen and linebackers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".