当前位置: X-MOL 学术Journal of Quantitative Analysis in Sports › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
The relative wages of offense and defense in the NBA: a setting for win-maximization arbitrage?
Journal of Quantitative Analysis in Sports ( IF 1.1 ) Pub Date : 2019-08-27 , DOI: 10.1515/jqas-2018-0095
Justin Ehrlich 1 , Shane Sanders 2 , Christopher J. Boudreaux 3
Affiliation  

Abstract In basketball, a point scored on offense carries a nearly identical on-court (win) value as a point denied on defense (e.g. within the Pythagorean expected wins model). Both outcomes bear the same score margin implication. As such, a win-maximizing team is expected to value the two outcomes equally. We ask whether the salaries of NBA players reveal such an equality among NBA teams. If not, a win-maximizing team would enjoy a disequilibrium arbitrage opportunity, whereby the team could improve, in expectation, even while reducing roster payroll. We considered the 322 National Basketball Association (NBA) players during the 2016–2017 season who were on a full-season contract for which the salary was not stipulated under the NBA Collective Bargaining Agreement. We estimated the implied marginal wage of an additional point created on offense (denied on defense) per 100 possessions. Namely, we constructed a set of fixed effects, ordinary least squares regression models that specify a player’s pre-assigned 2016–2017 player salary as a function of primary team fixed effects, offensive adjusted plus minus, defensive adjusted plus minus, position-of-play, and control variables such as age. We conclude that a win-maximizing NBA team currently faces a substantial arbitrage opportunity. Namely, one unit of offense carries the same estimated implicit salary as approximately two and a half to four units of defense. We also find moderate between-team variation in adjusted plus minus return on payroll allocations.

中文翻译:

NBA进攻和防守的相对工资:最大化获胜套利的环境吗?

摘要在篮球比赛中,在进攻端得到的得分与在防守端得到的得分(例如在毕达哥拉斯的预期胜利模型中)几乎一样。两种结果都具有相同的得分余量含义。因此,希望获得最大胜利的团队将平等地评价这两个结果。我们问NBA球员的薪水是否体现了NBA球队之间的平等。如果没有,最大化胜利的团队将享受不平衡套利的机会,即使在减少名册工资的同时,该团队也可以期望地提高。我们考虑了2016-2017赛季期间的322个国家篮球协会(NBA)球员,他们的合同没有按照《 NBA集体谈判协议》的规定进行全赛季合同。我们估算了每100个回合在进攻上创造的额外积分(被拒绝防守)的隐含边际工资。也就是说,我们构建了一套固定效应,即普通最小二乘回归模型,该模型指定了一名球员预先分配的2016-2017年球员薪水与一线球队固定效应,进攻性调整后的正负值,防守性调整后的正负值,播放和控制年龄等变量。我们得出的结论是,要使胜利最大化的NBA球队目前面临大量套利机会。即,一个进攻单位的隐含估计工资与大约两个半到四个防御单位相同。我们还发现调整后的工资减去分配的报酬率之间存在适度的团队间差异。普通最小二乘回归模型,该模型指定球员的预分配球员2016-2017年球员薪水,取决于主要球队的固定效应,进攻调整后的正负值,防守调整后的正负值,比赛位置以及年龄等控制变量。我们得出的结论是,要使胜利最大化的NBA球队目前面临大量套利机会。即,一个进攻单位的隐含估计工资与大约两个半到四个防御单位相同。我们还发现调整后的工资减去分配的报酬率之间存在适度的团队间差异。普通最小二乘回归模型,该模型指定球员的预分配球员2016-2017年球员薪水,作为主要球队固定效应,进攻调整后的正负值,防守调整后的正负值,比赛位置以及年龄等控制变量的函数。我们得出的结论是,要使胜利最大化的NBA球队目前面临大量套利机会。即,一个进攻单位的隐含估计工资与大约两个半到四个防御单位相同。我们还发现调整后的工资减去分配的报酬率之间存在适度的团队间差异。我们得出的结论是,要使胜利最大化的NBA球队目前面临大量套利机会。即,一个进攻单位的隐含估计工资与大约两个半到四个防御单位相同。我们还发现调整后的工资减去分配的报酬率之间存在适度的团队间差异。我们得出的结论是,要使胜利最大化的NBA球队目前面临大量套利机会。即,一个进攻单位的隐含估计工资与大约两个半到四个防御单位相同。我们还发现调整后的工资减去分配的报酬率之间存在适度的团队间差异。
更新日期:2019-08-27
down
wechat
bug