It is very interesting
Recent research suggests that “statistics and analysis” typically lead to better decisions than “intuition and human intellect” in diverse areas such as choosing which students to admit to college and assessing mortality risks among cancer patients. Sports economics, with its rich data and abundant decisions to analyze has provided a fertile laboratory for studies of the efficiency of decision-making. In fact, researchers of the National Basketball Association (NBA) have used statistical models of player productivity to make strong claims about the “rationality” of NBA decision-makers. Yet these statistical models have rarely been subjected to any rigorous examination of their ability to forecast the future. We examine how well several player productivity metrics, including (a) John Hollinger’s Player Efficiency Rating, (b) Wages of Wins Wins Produced, and (c) the NBA Efficiency metric, do in predicting future team wins and future player productivity (the latter as measured by plus/minus statistics). In addition to a comprehensive examination of the player productivity metrics used by NBA statistical analysts, this paper is the first academic presentation of plus/minus statistics. Our findings provide a counterweight to much of prevailing literature and suggest that models that assume simplistic NBA decision-making often outperform more sophisticated statistical models.
http://www.stumblingonwins.com/LewinRosenbaum2007.pdf
