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极限飞盘运动中的状态转换建模:一种用于侵入性运动性能分析的有前景方法的适应性研究

State Transition Modeling in Ultimate Frisbee: Adaptation of a Promising Method for Performance Analysis in Invasion Sports.

作者信息

Lam Hilary, Kolbinger Otto, Lames Martin, Russomanno Tiago Guedes

机构信息

Chair of Performance Analysis and Sports Informatics, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany.

Laboratory for Teaching Computer Science Applied to Physical Education and Sport, Faculty of Physical Education, University of Brasilia, Brasília, Brazil.

出版信息

Front Psychol. 2021 May 25;12:664511. doi: 10.3389/fpsyg.2021.664511. eCollection 2021.

Abstract

Although the body of literature in sport science is growing rapidly, certain sports have yet to benefit from this increased interest by the scientific community. One such sport is Ultimate Frisbee, officially known as Ultimate. Thus, the goal of this study was to describe the nature of the sport by identifying differences between winning and losing teams in elite-level competition. To do so, a customized observational system and a state transition model were developed and applied to 14 games from the 2017 American Ultimate Disc League season. The results reveal that, on average, 262.2 passes were completed by a team per game and 5.5 passes per possession. More than two-thirds of these passes were played from the mid zone (39.4 ± 6.57%) and the rear zone (35.2 ± 5.09%), nearest the team's own end zone. Winning and losing teams do not differ in these general patterns, but winning teams played significantly fewer backward passes from the front zone to the mid zone, nearest the opponent's end zone than losing teams (mean difference of -4.73%, = -4.980, < 0.001, = -1.16). Furthermore, losing teams scored fewer points when they started on defense, called breakpoints (mean difference of -5.57, = -6.365, < 0.001, = 2.30), and committed significantly more turnovers per game (mean difference of 5.64, = 5.85, < 0.001, = -1.18). Overall, this study provides the first empirical description of Ultimate and identifies relevant performance indicators to discriminate between winning and losing teams. We hope this article sheds light on the unique, but so far overlooked sport of Ultimate, and offers performance analysts the basis for future studies using state transition modeling in Ultimate as well as other invasion sports.

摘要

尽管体育科学领域的文献数量在迅速增长,但某些运动尚未从科学界对其兴趣的增加中受益。极限飞盘运动就是其中之一,其官方名称为极限飞盘。因此,本研究的目的是通过识别精英级比赛中获胜队伍和失败队伍之间的差异来描述这项运动的本质。为此,开发了一个定制的观察系统和一个状态转换模型,并将其应用于2017年美国极限飞盘联赛赛季的14场比赛。结果显示,平均而言,一支球队每场比赛完成262.2次传球,每次控球5.5次传球。这些传球中超过三分之二是从中区(39.4±6.57%)和后区(35.2±5.09%)传出的,这两个区域离球队自己的端区最近。获胜队伍和失败队伍在这些总体模式上没有差异,但与失败队伍相比,获胜队伍从前区向离对手端区最近的中区传出的向后传球明显更少(平均差异为-4.73%,t=-4.980,p<0.001,d=-1.16)。此外,失败队伍在防守开始时得分较少,即所谓的破发点(平均差异为-5.57,t=-6.365,p<0.001,d=2.30),并且每场比赛的失误明显更多(平均差异为5.64,t=5.85,p<0.001,d=-1.18)。总体而言,本研究首次对极限飞盘运动进行了实证描述,并确定了区分获胜队伍和失败队伍的相关绩效指标。我们希望本文能揭示极限飞盘这项独特但迄今为止被忽视的运动,并为绩效分析师提供未来在极限飞盘运动以及其他侵入性运动中使用状态转换模型进行研究的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c03/8185146/41a93bfc5dc7/fpsyg-12-664511-g002.jpg

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