基于多元回归的NBA球员薪金与技术数据分析  

Analysis of NBA Players Salaries and Technical Data Based on Multiple Regression

作　　者：罗舜 LUO Shun(School of Economics and Management Fuzhou University,Fuzhou,Fujian Province,350108 China)

机构地区：[1]福州大学经济与管理学院,福建福州350108

出　　处：《当代体育科技》2021年第4期229-232,共4页Contemporary Sports Technology

摘　　要：该文运用文献资料法、数理统计法、比较研究法,对2018—2019赛季美国男子职业篮球联赛常规赛场均得分前50名的球员的赛季薪金与各项技术数据进行分析与比对,将球员数据进行分类,对球员各类技术数据进行相关分析,并将得出的结果可视化,最后得出每个因素对球员工资的影响程度,为中国职业篮球联赛球员的挑选提供理论性的参考。结果表明:2018—2019赛季美国男子职业篮球联赛常规赛顶尖球员的技术数据中,在满足t检验的显著性水平Sig<0.05的情况下,场均篮板、场均助攻和场均得分对球员赛季薪金有显著性影响并且呈正相关,其中场均助攻的影响程度最高;场均失误对球员赛季薪金有显著性影响并且呈负相关。This paper uses the methods of literature,mathematical statistics and comparative research to analyze and compare the season salary and various technical data of the top 50 players with average score in each game in the regular field of the 2018—2019 NBA,classify the player data,make relevant analysis on all kinds of technical data of the players,and visualize the results,and finally get each of them.The inf luence of the factors on the player's salary can provide theoretical reference for the selection of players in the CBA.The results show that:in the technical data of the top players in the regular season of the 2018—2019 NBA,under the condition of meeting the significance level sig<0.05 of the t-test,the average rebounds,assists and scores have a significant and positive impact on the players'season salary,of which the average assists have the highest impact.The average mistakes have a significant impact on the players'season salary.It also has negative correlation.

关 键 词：美国职业篮球联赛 篮球技术数据 多元回归分析 薪金 

分 类 号：G841[文化科学—体育训练]