Comparison of the Technique of the Football Quarterback Pass Between High School and University Athletes
Notice bibliographique
Résumé
Toffan, A, Alexander, MJL, and Peeler, J. Comparison of the technique of the football quarterback pass between high school and university athletes. J Strength Cond Res 32(9): 2474-2497, 2018-The purpose of the study was to compare the most effective joint movements, segment velocities, and body positions to perform the fastest and most accurate pass of high school and university football quarterbacks. Secondary purposes were to develop a quarterback throwing test to assess skill level, to determine which kinematic variables were different between high school and university athletes, and to determine which variables were significant predictors of quarterback throwing test performance. Ten high school and 10 university athletes were filmed for the study, performing 9 passes at a target and 2 passes for maximum distance. Thirty variables were measured using Dartfish Team Pro 4.5.2 video analysis system, and Microsoft Excel was used for statistical analyses. University athletes scored slightly higher than the high school athletes on the throwing test; however, this result was not statistically significant. Correlation analysis and forward stepwise multiple regression analysis were performed on both the high school players and the university players to determine which variables were significant predictors of throwing test score. Ball velocity was determined to have the strongest predictive effect on throwing test score (r = 0.900) for the high school athletes; however, position of the back foot at release was also determined to be important (r = 0.661) for the university group. Several significant differences in throwing technique between groups were noted during the pass; however, body position at release showed the greatest differences between the 2 groups. High school players could benefit from more complete weight transfer and decreased throw time to increase throwing test score. University athletes could benefit from increased throw time and greater range of motion in external shoulder rotation and trunk rotation to increase their throwing test score. Coaches and practitioners will be able to use the findings of this research to help improve these and related throwing variables in their high school and university quarterbacks.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».