用BasketballAnalyzeR分析篮球数据

A. Fox, Marica Manisera, Marco Sandri, P. Zuccolotto
{"title":"用BasketballAnalyzeR分析篮球数据","authors":"A. Fox, Marica Manisera, Marco Sandri, P. Zuccolotto","doi":"10.1080/09332480.2022.2123161","DOIUrl":null,"url":null,"abstract":"The R package BasketballAnalyzeR, described in the book “Basketball Data Science”, is designed to be a flexible tool for a great variety of aims. It is simple enough to eliminate barriers-to-entry for aspiring data scientists and sports analysts, but is also allows to perform more complex analyses for scientific research. It is appropriate for teaching, in both degree courses in Statistics and specific Masters and post-graduate courses in sports. In this article we show some of the statistical graphical tools made available by BasketballAnalyzeR: bubble plots, to assess relationships among several game variables; shot charts and heatmaps of the shots’ spatial density, to extract information about spatial performance; shot density charts, to analyze shot frequency with respect to some concurrent game variables; assist/shot networks, to highlight the relationships between teammates; nonparametric estimation of scoring probability and expected points with respect to some concurrent game variables, to investigate which are each player’s most efficient shots.","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"269 ","pages":"42 - 56"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analyzing Basketball Data with BasketballAnalyzeR\",\"authors\":\"A. Fox, Marica Manisera, Marco Sandri, P. Zuccolotto\",\"doi\":\"10.1080/09332480.2022.2123161\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The R package BasketballAnalyzeR, described in the book “Basketball Data Science”, is designed to be a flexible tool for a great variety of aims. It is simple enough to eliminate barriers-to-entry for aspiring data scientists and sports analysts, but is also allows to perform more complex analyses for scientific research. It is appropriate for teaching, in both degree courses in Statistics and specific Masters and post-graduate courses in sports. In this article we show some of the statistical graphical tools made available by BasketballAnalyzeR: bubble plots, to assess relationships among several game variables; shot charts and heatmaps of the shots’ spatial density, to extract information about spatial performance; shot density charts, to analyze shot frequency with respect to some concurrent game variables; assist/shot networks, to highlight the relationships between teammates; nonparametric estimation of scoring probability and expected points with respect to some concurrent game variables, to investigate which are each player’s most efficient shots.\",\"PeriodicalId\":88226,\"journal\":{\"name\":\"Chance (New York, N.Y.)\",\"volume\":\"269 \",\"pages\":\"42 - 56\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chance (New York, N.Y.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/09332480.2022.2123161\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chance (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09332480.2022.2123161","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在“篮球数据科学”一书中描述的R包basketanalyzer被设计成一个灵活的工具,用于各种各样的目标。它简单到足以消除有抱负的数据科学家和体育分析师的进入障碍,但它也允许为科学研究执行更复杂的分析。它适用于统计学学位课程和特定的体育硕士和研究生课程的教学。在本文中,我们将展示BasketballAnalyzeR提供的一些统计图形工具:泡泡图,用于评估几个游戏变量之间的关系;镜头图和镜头空间密度热图,提取空间表现信息;投篮密度图,分析一些并发游戏变量的投篮频率;助攻/投篮网络,突出队友之间的关系;对一些并发游戏变量的得分概率和期望得分进行非参数估计,以调查每个玩家最有效的射门。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Analyzing Basketball Data with BasketballAnalyzeR
The R package BasketballAnalyzeR, described in the book “Basketball Data Science”, is designed to be a flexible tool for a great variety of aims. It is simple enough to eliminate barriers-to-entry for aspiring data scientists and sports analysts, but is also allows to perform more complex analyses for scientific research. It is appropriate for teaching, in both degree courses in Statistics and specific Masters and post-graduate courses in sports. In this article we show some of the statistical graphical tools made available by BasketballAnalyzeR: bubble plots, to assess relationships among several game variables; shot charts and heatmaps of the shots’ spatial density, to extract information about spatial performance; shot density charts, to analyze shot frequency with respect to some concurrent game variables; assist/shot networks, to highlight the relationships between teammates; nonparametric estimation of scoring probability and expected points with respect to some concurrent game variables, to investigate which are each player’s most efficient shots.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Multiple discoveries in causal inference: LATE for the party. Bayes Factors for Forensic Decision Analyses with R Three Welcome Arrivals for 2023: 1. Florence Nightingale Bayesian Probability for Babies Fresh Perspective
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1