Drafting Errors and Decision Making Theory in the NBA Draft

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Abstract: Even with the recent influx of data regarding NCAA basketball players and professional teams investing more resources into scouting than ever before, NBA decision makers continue to struggle to consistently select productive players. In this study, I determine the NCAA statistics and pre-draft player characteristics that predict draft position and NBA performance for all NCAA players drafted between 2006-2013. Based on the factors that are under and overemphasized by NBA decision makers, I then examine how these choices relate to general decision making theory. Linear regression models are specified for both draft position and NBA performance, with percentage based metrics used in place of traditional box score counting statistics (i.e. assist percentage instead of assists per game). All factors are adjusted for the position of the player, classified as a Big, Wing, or Point Guard rather than into one of the five traditional positions. A Heckman (1971) sample selection correction is also applied to correct for the non-randomly selected NBA performance sample, which necessarily excludes players who have not played a sufficient (>=500) amount of NBA minutes. NBA decision makers continue to base their draft selections on statistics and characteristics that do not actually predict future NBA success. Overemphasized factors include scoring, size, and college conference, while ball control and offensive efficiency are generally underrated. NBA draft strategy at large can also be connected to certain decision making theories, such as Heath and Tversky’s (1991) competency hypothesis, Samuelson and Zeckhauser’s (1988) status quo bias, and Kahneman and Tversky’s (1979) theory of risk aversion when facing possible gains.

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