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复杂网络模型与谱分解在奥运会游泳运动员表现分析中的应用

Complex Networks Models and Spectral Decomposition in the Analysis of Swimming Athletes' Performance at Olympic Games.

作者信息

Pereira-Ferrero Vanessa Helena, Lewis Theodore Gyle, Ferrero Luciane Graziele Pereira, Duarte Leonardo Tomazeli

机构信息

School of Applied Sciences, University of Campinas, Limeira, Brazil.

Center for Homeland Defense and Security, Naval Postgraduate School, Monterey, CA, United States.

出版信息

Front Physiol. 2019 Sep 3;10:1134. doi: 10.3389/fphys.2019.01134. eCollection 2019.

DOI:10.3389/fphys.2019.01134
PMID:31551810
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6733958/
Abstract

This study aims to present complex network models which analyze professional swimmers of 50-m freestyle Olympic competitions, comparing characteristics and variables that are considered performance determinants. This comparative research includes Olympic medalists' versus non-medalists' behavior. Using data from 40 athletes with a mean age, weight and height of 26 ± 2.9 years, 87 ± 5.59 kg, 193 ± 3.85 cm, respectively, at the Olympics of 2000, 2004, 2008, 2012, and 2016 (16-year interval), we built two types of complex networks (graphs) for each edition, using mathematical correlations, metrics and the spectral decomposition analysis. It is possible to show that complex metrics behave differently between medalists and non-medalists. The spectral radius (SR) proved to be an important form of evaluation since in all 5 editions it was higher among medalists (SR results: 3.75, 3.5, 3.39, 2.91, and 3.66) compared to non-medalists (2.18, 2.51, 2.23, 2.07, and 2.04), with significantly differences between. This study introduces a remarkable tool in the evaluation of the performance of groups of swimming athletes by complex networks, and is relevant to athletes, coaches, and even amateurs, regarding how individual variables relate to competition results and are reflected in the SR for the best performance. In addition, this is a general method and may, in the future, be developed in the analysis of other competitive sports.

摘要

本研究旨在提出复杂网络模型,该模型用于分析50米自由泳奥运比赛的专业游泳运动员,比较被视为成绩决定因素的特征和变量。这项比较研究包括奥运奖牌获得者与非奖牌获得者的行为。利用2000年、2004年、2008年、2012年和2016年奥运会(间隔16年)上40名运动员的数据,他们的平均年龄、体重和身高分别为26±2.9岁、87±5.59千克、193±3.85厘米,我们针对每个比赛年份构建了两种类型的复杂网络(图表),采用数学相关性、度量和谱分解分析。结果表明,奖牌获得者和非奖牌获得者的复杂度量表现不同。谱半径(SR)被证明是一种重要的评估形式,因为在所有5个比赛年份中,奖牌获得者的谱半径(SR结果:3.75、3.5、3.39、2.91和3.66)均高于非奖牌获得者(2.18、2.51、2.23、2.07和2.04),且两者之间存在显著差异。本研究引入了一种通过复杂网络评估游泳运动员群体表现的卓越工具,对于运动员、教练乃至业余爱好者而言,它关乎个体变量如何与比赛成绩相关联以及如何在谱半径中体现以实现最佳表现。此外,这是一种通用方法,未来可能会在其他竞技体育项目的分析中得到发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1e8/6733958/e8fb41a06d7d/fphys-10-01134-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1e8/6733958/466289456879/fphys-10-01134-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1e8/6733958/d7b595f21616/fphys-10-01134-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1e8/6733958/bad2c1944494/fphys-10-01134-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1e8/6733958/e8fb41a06d7d/fphys-10-01134-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1e8/6733958/466289456879/fphys-10-01134-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1e8/6733958/d7b595f21616/fphys-10-01134-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1e8/6733958/bad2c1944494/fphys-10-01134-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1e8/6733958/e8fb41a06d7d/fphys-10-01134-g004.jpg

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2
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3
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4
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Front Physiol. 2020 Dec 11;11:611550. doi: 10.3389/fphys.2020.611550. eCollection 2020.
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New J Phys. 2016 Oct;18. doi: 10.1088/1367-2630/18/10/100201.
4
Financial market predictability with tensor decomposition and links forecast.基于张量分解和链接预测的金融市场可预测性
Appl Netw Sci. 2017;2(1):7. doi: 10.1007/s41109-017-0028-1. Epub 2017 May 5.
5
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6
100-m Breaststroke Swimming Performance in Youth Swimmers: The Predictive Value of Anthropometrics.青少年游泳运动员100米蛙泳成绩:人体测量学的预测价值。
Pediatr Exerc Sci. 2018 Aug 1;30(3):393-401. doi: 10.1123/pes.2017-0220. Epub 2018 Mar 16.
7
Dynamics of the Metabolic Response During a Competitive 100-m Freestyle in Elite Male Swimmers.优秀男子游泳运动员 100 米自由泳比赛中代谢反应的动态变化。
Int J Sports Physiol Perform. 2018 Sep 1;13(8):1011-1020. doi: 10.1123/ijspp.2017-0597. Epub 2018 Sep 10.
8
Scholarly Olympics: How the games have shaped research.学术奥林匹克:奥运会如何塑造了研究。
Nature. 2016 Aug 4;536(7614):18-9. doi: 10.1038/536018a.
9
[Dynamics of changes body composition of polish national swimming team during the one month of training camp prior the junior World Championship in Dubai in 2013].[2013年迪拜青少年世界锦标赛前波兰国家游泳队在为期一个月的训练营期间身体成分变化动态]
Pomeranian J Life Sci. 2015;61(2):232-6.
10
Delay-correlation landscape reveals characteristic time delays of brain rhythms and heart interactions.延迟相关景观揭示了脑节律与心脏相互作用的特征性时间延迟。
Philos Trans A Math Phys Eng Sci. 2016 May 13;374(2067). doi: 10.1098/rsta.2015.0182.