• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

开发预期占有值模型以分析橄榄球联盟中的球队进攻表现。

Development of an expected possession value model to analyse team attacking performances in rugby league.

机构信息

School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds, United Kingdom.

Carnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, United Kingdom.

出版信息

PLoS One. 2021 Nov 12;16(11):e0259536. doi: 10.1371/journal.pone.0259536. eCollection 2021.

DOI:10.1371/journal.pone.0259536
PMID:34767602
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8589207/
Abstract

This study aimed to evaluate team attacking performances in rugby league via expected possession value (EPV) models. Location data from 59,233 plays in 180 Super League matches across the 2019 Super League season were used. Six EPV models were generated using arbitrary zone sizes (EPV-308 and EPV-77) or aggregated according to the total zone value generated during a match (EPV-37, EPV-19, EPV-13 and EPV-9). Attacking sets were considered as Markov Chains, allowing the value of each zone visited to be estimated based on the outcome of the possession. The Kullback-Leibler Divergence was used to evaluate the reproducibility of the value generated from each zone (the reward distribution) by teams between matches. Decreasing the number of zones improved the reproducibility of reward distributions between matches but reduced the variation in zone values. After six previous matches, the subsequent match's zones had been visited on 95% or more occasions for EPV-19 (95±4%), EPV-13 (100±0%) and EPV-9 (100±0%). The KL Divergence values were infinity (EPV-308), 0.52±0.05 (EPV-77), 0.37±0.03 (EPV-37), 0.20±0.02 (EPV-19), 0.13±0.02 (EPV-13) and 0.10±0.02 (EPV-9). This study supports the use of EPV-19 and EPV-13, but not EPV-9 (too little variation in zone values), to evaluate team attacking performance in rugby league.

摘要

本研究旨在通过预期控球价值(EPV)模型评估橄榄球联赛中的团队进攻表现。使用了 2019 年超级联赛赛季 180 场超级联赛比赛中的 59233 次比赛的位置数据。使用任意区域大小(EPV-308 和 EPV-77)或根据比赛中产生的总区域值(EPV-37、EPV-19、EPV-13 和 EPV-9)进行聚合生成了六个 EPV 模型。进攻集被视为马尔可夫链,允许根据控球结果估计每个访问区域的价值。使用 KL 散度来评估团队在比赛之间从每个区域(奖励分布)生成的值的可重现性。减少区域数量可以提高比赛之间奖励分布的可重现性,但会降低区域值的变化。在前六场比赛之后,EPV-19(95±4%)、EPV-13(100±0%)和 EPV-9(100±0%)的后续比赛中,已经有 95%或更多的比赛访问了后续比赛的区域。KL 散度值为无穷大(EPV-308)、0.52±0.05(EPV-77)、0.37±0.03(EPV-37)、0.20±0.02(EPV-19)、0.13±0.02(EPV-13)和 0.10±0.02(EPV-9)。本研究支持使用 EPV-19 和 EPV-13,但不支持 EPV-9(区域值变化太小)来评估橄榄球联赛中的团队进攻表现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/795e23227167/pone.0259536.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/5c7edbf1218c/pone.0259536.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/b9558ac42b64/pone.0259536.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/1a2e5784f9cf/pone.0259536.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/037c5473e6d0/pone.0259536.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/795e23227167/pone.0259536.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/5c7edbf1218c/pone.0259536.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/b9558ac42b64/pone.0259536.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/1a2e5784f9cf/pone.0259536.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/037c5473e6d0/pone.0259536.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58dc/8589207/795e23227167/pone.0259536.g005.jpg

相似文献

1
Development of an expected possession value model to analyse team attacking performances in rugby league.开发预期占有值模型以分析橄榄球联盟中的球队进攻表现。
PLoS One. 2021 Nov 12;16(11):e0259536. doi: 10.1371/journal.pone.0259536. eCollection 2021.
2
The expected value of possession in professional rugby league match-play.
J Sports Sci. 2016;34(7):645-50. doi: 10.1080/02640414.2015.1066511. Epub 2015 Jul 20.
3
The Impact of 3 Different-Length Between-Matches Microcycles on Training Loads in Professional Rugby League Players.3种不同时长的比赛间隔微周期对职业橄榄球联盟球员训练负荷的影响
Int J Sports Physiol Perform. 2015 Sep;10(6):767-73. doi: 10.1123/ijspp.2015-0100. Epub 2015 May 26.
4
Changing gears: data-driven velocity zones to support monitoring and research in men's rugby league.变速:数据驱动的速度区,以支持男子橄榄球联盟的监测和研究。
Sci Med Footb. 2024 Feb;8(1):60-67. doi: 10.1080/24733938.2022.2152482. Epub 2022 Nov 30.
5
Factors affecting exercise intensity in professional rugby league match-play.影响职业橄榄球联盟比赛中运动强度的因素。
J Sci Med Sport. 2016 Jun;19(6):504-8. doi: 10.1016/j.jsams.2015.06.008. Epub 2015 Jun 15.
6
Influence of Physical Characteristics and Match Outcome on Technical Errors During Rugby League Match Play.橄榄球联赛比赛中身体特征和比赛结果对技术失误的影响。
Int J Sports Physiol Perform. 2019 Sep 1;14(8):1043-1049. doi: 10.1123/ijspp.2018-0354.
7
Influence of injuries on team playing performance in Rugby League.
J Sci Med Sport. 2004 Sep;7(3):340-6. doi: 10.1016/s1440-2440(04)80029-x.
8
How fast is fast? Defining velocity zones in women's rugby league.多快才算快?界定女子橄榄球联盟中的速度区域。
Sci Med Footb. 2023 May;7(2):165-170. doi: 10.1080/24733938.2022.2062438. Epub 2022 Apr 21.
9
Out of your zone? 21 years of travel and performance in Super Rugby.不在你的舒适区?21 年超级橄榄球的旅行和表现。
J Sports Sci. 2019 Sep;37(18):2051-2056. doi: 10.1080/02640414.2019.1620427. Epub 2019 May 19.
10
The effects of travel on performance: a 13-year analysis of the National Rugby League (NRL) competition.旅行对比赛表现的影响:对国家橄榄球联盟(NRL)赛事的13年分析
Sci Med Footb. 2022 Feb;6(1):60-65. doi: 10.1080/24733938.2021.1876243. Epub 2021 Feb 1.

引用本文的文献

1
A Bayesian Mixture Model approach to expected possession values in rugby league.贝叶斯混合模型在英式橄榄球中预期控球价值的应用。
PLoS One. 2024 Nov 21;19(11):e0308222. doi: 10.1371/journal.pone.0308222. eCollection 2024.

本文引用的文献

1
A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions.一种用于对足球控球瞬间期望值进行细粒度评估的框架。
Mach Learn. 2021;110(6):1389-1427. doi: 10.1007/s10994-021-05989-6. Epub 2021 May 24.
2
Supervised sequential pattern mining of event sequences in sport to identify important patterns of play: An application to rugby union.对体育事件序列进行有监督的序贯模式挖掘,以识别重要的比赛模式:以橄榄球为例。
PLoS One. 2021 Sep 23;16(9):e0256329. doi: 10.1371/journal.pone.0256329. eCollection 2021.
3
Examining the evolution and classification of player position using performance indicators in the National Rugby League during the 2015-2019 seasons.
审视 2015-2019 赛季国家橄榄球联盟(National Rugby League)中运用表现指标对球员位置演变与分类的研究。
J Sci Med Sport. 2020 Sep;23(9):891-896. doi: 10.1016/j.jsams.2020.02.013. Epub 2020 Feb 27.
4
Explaining match outcome and ladder position in the National Rugby League using team performance indicators.使用球队表现指标解释国家橄榄球联盟中的比赛结果和排名情况。
J Sci Med Sport. 2017 Dec;20(12):1107-1111. doi: 10.1016/j.jsams.2017.04.005. Epub 2017 Apr 21.
5
The expected value of possession in professional rugby league match-play.
J Sports Sci. 2016;34(7):645-50. doi: 10.1080/02640414.2015.1066511. Epub 2015 Jul 20.
6
Match analysis in football: a systematic review.足球比赛分析:一项系统综述。
J Sports Sci. 2014 Dec;32(20):1831-1843. doi: 10.1080/02640414.2014.898852. Epub 2014 May 1.
7
Performance consistency of international soccer teams in euro 2012: a time series analysis.2012 年欧洲杯国际足球队表现的一致性:时间序列分析。
J Hum Kinet. 2013 Oct 8;38:213-26. doi: 10.2478/hukin-2013-0061. eCollection 2013.