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职业橄榄球联盟球员踢球成功的生物力学决定因素。

Biomechanical determinants of placekicking success in professional Rugby Union players.

机构信息

Division of Health, Engineering, Computing and Science, Te Huataki Waiora School of Health, University of Waikato, Tauranga, New Zealand.

School of Physical Education, Sport and Exercise Sciences, University of Otago, Dunedin, New Zealand.

出版信息

Sports Biomech. 2022 Aug;21(7):861-876. doi: 10.1080/14763141.2020.1728368. Epub 2020 Mar 5.

Abstract

The ability to score from placekicks discriminates winning from losing Rugby Union teams. We aimed to identify which biomechanical variables related to successful placekicking in professional Rugby Union players, and use self-organising maps (SOM) to determine whether meaningful sub-groups existed. Three professional placekickers performed 10 kicks outdoors. Placekicks were categorised into , , and performances based on outcomes and coach and player perceptions. Seven 3D biomechanical variables consistently and meaningfully (moderate Cohen's effect size) discriminated from placekicks in all players. The three-cluster solution from SOM on these seven variables highlighted differences between players rather than , and attempts. Within-clusters, however, the and placekicks tended to be represented in separate map regions. The seven variables identified using standardised effect sizes can be useful for group-level coaching of placekicking skills in absence of individual data, and translated in an applied setting using verbal and visual cues to promote overall placekicking performance. However, players' idiosyncrasies formed the main SOM boundaries, indicating that optimising placekicking success would benefit from an individualised approach and numerous effective movement templates may exist.

摘要

踢定位球的能力可以区分英式橄榄球联合会(Rugby Union)比赛中球队的胜负。我们旨在确定哪些与职业英式橄榄球联合会球员踢定位球成功相关的生物力学变量,并使用自组织映射(SOM)来确定是否存在有意义的亚组。三名职业定位球球员在户外进行了 10 次踢腿。根据结果和教练及球员的感知,将定位球分为成功和失败两类。在所有球员中,7 个 3D 生物力学变量始终且有意义(中等 Cohen 效应量)地将 与 区分开来。SOM 对这 7 个变量的三聚类解决方案突出了球员之间的差异,而不是 与 之间的差异。然而,在聚类内, 和 尝试通常代表不同的地图区域。使用标准化效应量确定的这 7 个变量可用于在没有个人数据的情况下进行定位球技能的群体级教练,并且可以在应用环境中使用口头和视觉提示来提高整体定位球表现。然而,球员的特质构成了 SOM 的主要边界,这表明优化定位球成功率将受益于个性化方法,并且可能存在许多有效的运动模板。

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