{"title":"篮球比赛成功驱动因素的检测：机器学习算法的探索性研究","authors":"M. Migliorati","doi":"10.1285/I20705948V13N2P454","DOIUrl":null,"url":null,"abstract":"This paper aims to detect which are the drivers leading to victory for basketball matches in NBA, the American National Basketball Association. First games for regular seasons from 2004-2005 to 2017-2018 have been summarized in terms of box scores and Dean's four factors. Then box scores and four factors have been used as classication independent variables to identify victory drivers, focusing on Golden StateWarriors matches. Both CART and Random Forests machine learning techniques have been applied, and results are compared to assess the more suitable approach.","PeriodicalId":44770,"journal":{"name":"Electronic Journal of Applied Statistical Analysis","volume":"13 1","pages":"454-473"},"PeriodicalIF":0.6000,"publicationDate":"2020-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1285/I20705948V13N2P454","citationCount":"8","resultStr":"{\"title\":\"Detecting drivers of basketball successful games: an exploratory study with machine learning algorithms\",\"authors\":\"M. Migliorati\",\"doi\":\"10.1285/I20705948V13N2P454\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper aims to detect which are the drivers leading to victory for basketball matches in NBA, the American National Basketball Association. First games for regular seasons from 2004-2005 to 2017-2018 have been summarized in terms of box scores and Dean's four factors. Then box scores and four factors have been used as classication independent variables to identify victory drivers, focusing on Golden StateWarriors matches. Both CART and Random Forests machine learning techniques have been applied, and results are compared to assess the more suitable approach.\",\"PeriodicalId\":44770,\"journal\":{\"name\":\"Electronic Journal of Applied Statistical Analysis\",\"volume\":\"13 1\",\"pages\":\"454-473\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2020-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1285/I20705948V13N2P454\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Journal of Applied Statistical Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1285/I20705948V13N2P454\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Journal of Applied Statistical Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1285/I20705948V13N2P454","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Detecting drivers of basketball successful games: an exploratory study with machine learning algorithms
This paper aims to detect which are the drivers leading to victory for basketball matches in NBA, the American National Basketball Association. First games for regular seasons from 2004-2005 to 2017-2018 have been summarized in terms of box scores and Dean's four factors. Then box scores and four factors have been used as classication independent variables to identify victory drivers, focusing on Golden StateWarriors matches. Both CART and Random Forests machine learning techniques have been applied, and results are compared to assess the more suitable approach.
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