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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/80881

    Title: NBA球員薪資探討
    Authors: 鄭秉軒;Cheng, Ping-Hsuan
    Contributors: 產業經濟研究所
    Keywords: 球員薪資;最小平方法
    Date: 2019-07-16
    Issue Date: 2019-09-03 15:13:59 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 中文摘要
    美國國家籃球協會(National Basketball Association,簡稱NBA)是世界職業籃球最頂尖的組織,而它也是推廣程度以及市場化優秀的職業運動聯盟之一,多數球員薪資令人羨慕。
    本研究主要是探討2009年到2018年共十年的時間,NBA球員們的薪資隨著年齡增長、比賽績效等因素,是否與球員薪資呈現正相關性。根據美國籃球數據網站Basketball Reference所整理的相關數據顯示,在聯盟實力備受球迷、媒體高度關注的球員,獲得比他人優渥的薪資待遇;例如洛杉磯湖人隊Kobe Bryant、金州勇士隊Stephen Curry等;這2位球員確有隨著年齡增加,取得愈多年薪情況。此類情況發生原因有球員自己在賽場上的績效數據排名在聯盟前段班,對球隊的貢獻程度等,確實是讓球隊老闆為了維持球隊競爭力願意提高薪資留住球員絕對考量因素。

    關鍵字: 球員薪資、最小平方法
    NBA(National Basketball Association) is the best professional basketball organization in the world. It is also one of professional sport league with more population and well marketing condition.
    The purpose of this article is mainly investigating the salary difference between basketball players in NBA. What we want to figure out is a player can earn more yearly with aging,performance and other factors. According to Basketball Reference,one of US basketball data website,players who get high attention by fans and media can earn more munificent payroll than others. For instance,Kobe Bryant(Los Angeles Lakers), Stephen Curry( Golden State Warriors),and so on. These two players are satisfied with what we previously mention. The reason why they can get a great deal of money is that their performances are on top rank in the league,and they have big impact on their team. So the owner of the franchise is willing to pay more on players like them so as to maintain its competition in the league.
    This essay uses a data which contains thirty teams in recent ten years. Combined with OLS statistic method,it shows that salary high or low is related with players′ situation or not;moreover,different positions should take in consideration yearly. Last,other factors(race、all star game selection,etc) put in the model to proof players′ salary is affected directly by these variables via a fit statistic model.
    Finally,the empirical results show that nationality,all star selection,performance,and field goal percentage have a big impact on players′ salary. But race does not have an influence on it. Among all the independent variables,ASG has the most influence on the model,which points out a player becomes an all star in the league,he can earn more payroll than that does not have a chance to participate all star game.
    Keywords: player salary;OLS statistic method
    Appears in Collections:[產業經濟研究所] 博碩士論文

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