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Validating Tackle Mechanics in American Football: Improving Safety and Performance
Annals of Biomedical Engineering ( IF 3.8 ) Pub Date : 2020-09-30 , DOI: 10.1007/s10439-020-02625-7
Arthur Maerlender 1 , Caitlin J Masterson 2, 3 , Rex Norris 4 , Adam Hinthorne 4
Affiliation  

Research has helped to understand the risks of injuries of tackling in American football and rugby; however, approaches to teaching and analysis are not well-documented. Shoulder-led tackling has been proposed as a safer approach to tackling even though data on the effectiveness for safety and defensive performance is limited. Additionally, some have argued that safety and effectiveness are incompatible. The purpose of the study was to validate a specific sequence of tackling actions as a tool for teaching safer and more effective tackling skills. Results suggested tackle scores help predict presence of head contact, and that higher tackle scores were associated with reductions in Yards After Contact (YAC). Eight hundred and thirty-two (832) American high school football tackles were rated using a 12-element rating system. Estimated Structural Equation Modeling (ESEM) was employed to identify the factor structure of the elements with three factors identified: Track, Engage, and Finish. ANOVA, along with logistic and linear equation models were run to determine relationships between tackle scores and outcomes. Tackle scores predicted head-contact category (binary logistic regression accuracy = .76). Yards after contact (YAC) were significantly reduced [Finish factor: MANOVA F(3, 828) = 105.825, p < .001]. Construct and predictive validity were demonstrated and show that these tackle elements provide valid foci for teaching better tackling as well as analyzing both teaching effectiveness and performance.



中文翻译:

验证美式足球中的铲球力学:提高安全性和表现

研究有助于了解美式橄榄球和橄榄球中铲球受伤的风险;然而,教学和分析的方法没有很好的记录。尽管有关安全和防守性能有效性的数据有限,但肩扛式铲球已被提议作为一种更安全的铲球方法。此外,有些人认为安全性和有效性是不相容的。该研究的目的是验证特定的铲球动作序列作为教授更安全和更有效的铲球技能的工具。结果表明铲球得分有助于预测头部接触的存在,并且更高的铲球得分与接触后码数 (YAC) 的减少有关。八百三十二 (832) 次美国高中橄榄球铲球使用 12 要素评级系统进行评级。采用估计结构方程模型 (ESEM) 来确定元素的因素结构,其中确定了三个因素:跟踪、参与和完成。运行方差分析以及逻辑和线性方程模型以确定铲球得分和结果之间的关系。解决得分预测头部接触类别(二元逻辑回归准确度 = .76)。接触后码数 (YAC) 显着减少 [完成系数:MANOVAF (3, 828) = 105.825, p < .001]。结构和预测有效性得到证明,并表明这些铲球元素为教学更好的铲球以及分析教学效果和表现提供了有效的焦点。

更新日期:2020-10-02
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