With the 4th overall pick in the 2016 NBA Draft, the Phoenix Suns selected Croatian phenom Dragan Bender. Unlike the first three picks, Bender played exclusively overseas. As such, most of us have no basis to compare him with the other top prospects. Regardless, the “experts” believe he has the talent to become a star. In contrast, I believe he’s more likely to become a bust. I’ll admit that I undervalued 2015 #4 overall pick Kristaps Porzingis. However, I’ll double down and bet that Bender is not another “unicorn.”
Throughout its history, the NBA has relied on an assortment of gimmicks to determine how teams could select new players. Well before the use of lotteries and coin flips, the league gave teams a preferential right to select local players who presumably offered a built-in following. This type of draft exemption ended by the mid-1960s, but not before the rule was applied inconsistently for one player. Wanna take a guess?
To be fair, the following post is geared towards “quant jocks” (ok, nerds) who have a reasonable knowledge of statistical distributions. In particular, I have used Weibull distributions to model different subsets of 1st round picks from over 40 NBA drafts. With different shape and scale parameters for each subset, the expected value of a draft pick can be estimated with statistical probability. Based on my analysis, I developed a methodology to define a bust objectively in order to overcome the bias which seems to be apparent in existing lists of all-time busts. If you work for an NBA team and came across this site, you should read this post.