NBA球員薪資與場上效率分析: 以2018-19賽季為例

The purpose of this study is to evaluate efficiency of teams and players in National Basketball Association by using data envelopment analysis (DEA) during 2018-2019 season. For the section of teams, we implemented the sum of player salaries as an input and the number of wins in regular season, averaged plus-minus per game as well as averaged fans attendance per game as outputs. The analysis indicated that only 5 teams of 30 have operating efficiency and the other 25 over invested on their player roster which is hence inefficient. Moreover, the team which are having more high-paid player does not have higher efficiency. For the section of players, we implemented player’s salary, averaged minutes played per game as inputs and averaged points, assists, rebounds, steals, blocks, turnovers and fouls per game as outputs. The empirical findings show that there are about 40-50% of players are efficient in the league. The BCG-like matrix analysis is applied to categorize players in order to compare the players more specifically. As the general manager of the team, high-salary and high efficiency player came to the first priority of picking. Besides, managers should also keep eyes on potential players who are categorized in the low-salary but high-efficiency quadrant. These players have higher chance to be next stars and also constitute the foundation of the team.