Video Analysis of Elite American Football Athletes During Vertical Jump.

IF 1.3 Q3 SPORT SCIENCES
Open Access Journal of Sports Medicine Pub Date : 2024-12-03 eCollection Date: 2024-01-01 DOI:10.2147/OAJSM.S481805
John L Grace, Meghan E Hancock, Madison L Malone, Bahman Adlou, Jerad J Kosek, Hannah R Houde, Christopher M Wilburn, Wendi H Weimar
{"title":"Video Analysis of Elite American Football Athletes During Vertical Jump.","authors":"John L Grace, Meghan E Hancock, Madison L Malone, Bahman Adlou, Jerad J Kosek, Hannah R Houde, Christopher M Wilburn, Wendi H Weimar","doi":"10.2147/OAJSM.S481805","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>The National Football League (NFL) combine tests the athleticism of prospects competing for the draft. The vertical jump is included to test lower extremity power, yet the components which lead to the greatest performance remain elusive. Therefore, this study aimed to utilize a sample of elite athletes to analyze vertical jump components associated with increased performance and the relationship between vertical jump performance and rookie-year success.</p><p><strong>Methods: </strong>Videos of 50 NFL prospects performing the vertical jump task were analyzed for various countermovement jump components. Regression analyses examined the components in relation to normalized jump height and rookie Approximate Value (AV) using an alpha level of 0.05.</p><p><strong>Results: </strong>After analysis, only the overall model for normalized jump height was statistically significant (R^2^ = 0.69, p = 0.002).</p><p><strong>Discussion: </strong>While no single variable predicted jump height, distinct strategies were evident between the top and bottom 25% performers based on component correlations. The regression model approached significance in predicting rookie AV (R^2^ = 0.94, p = 0.052), with notable components like heel pauses for skilled positions and greater knee flexion for linemen. By creating models that can predict jump height or AV, variables can be identified that can be used to improve one's jump height or, in the case of AV, that can be used to predict which draft prospects will perform better in the NFL.</p>","PeriodicalId":51644,"journal":{"name":"Open Access Journal of Sports Medicine","volume":"15 ","pages":"197-208"},"PeriodicalIF":1.3000,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11624661/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Access Journal of Sports Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/OAJSM.S481805","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"SPORT SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: The National Football League (NFL) combine tests the athleticism of prospects competing for the draft. The vertical jump is included to test lower extremity power, yet the components which lead to the greatest performance remain elusive. Therefore, this study aimed to utilize a sample of elite athletes to analyze vertical jump components associated with increased performance and the relationship between vertical jump performance and rookie-year success.

Methods: Videos of 50 NFL prospects performing the vertical jump task were analyzed for various countermovement jump components. Regression analyses examined the components in relation to normalized jump height and rookie Approximate Value (AV) using an alpha level of 0.05.

Results: After analysis, only the overall model for normalized jump height was statistically significant (R^2^ = 0.69, p = 0.002).

Discussion: While no single variable predicted jump height, distinct strategies were evident between the top and bottom 25% performers based on component correlations. The regression model approached significance in predicting rookie AV (R^2^ = 0.94, p = 0.052), with notable components like heel pauses for skilled positions and greater knee flexion for linemen. By creating models that can predict jump height or AV, variables can be identified that can be used to improve one's jump height or, in the case of AV, that can be used to predict which draft prospects will perform better in the NFL.

求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.80
自引率
0.00%
发文量
13
审稿时长
16 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信