If NBA games were only five minutes long, Acie Law may have been an all-time great. Well, they’re not, so he’s not. As a senior at Texas A&M, Law was named 1st Team All-American and won the Bob Cousy Award as the best point guard in the country after averaging 18 points and five assists per game. Despite being a clutch performer in college who elevated his game at the most critical moments, Law never elevated beyond backup duties in the NBA. During his four-year NBA career, he averaged less than four points and two assists per game while playing for five different teams. As previously established, any player taken after the first ten overall picks is exempt from being declared a Top 10 Bust. But for this restriction, Law would have been a prime candidate. Instead, he earned an Honorable Mention and an eponymous exemption.
NBA Draft Categories (Busts to Superstars)
In honor of the 20th anniversary of Dumb and Dumber (versus the new release of the far inferior Dumb and Dumber To), this post simplifies the previous one regarding the distribution of win shares for 1st round NBA draft picks. There still are a lot of numbers, but the takeaways should be easier to understand. Just to be sure, here they are.
1. Generally, draft order is a good predictor of future success in the NBA. As such, the higher the pick, the better the player should be to avoid being labeled a bust.
2. Starting with the 11th overall pick, the probability of being a flame-out exceeds the probability of becoming an All-Star by a margin of 2:1 (40% to 20%). For that reason, players taken outside of the first ten overall picks have been excluded as potential Top 10 Busts.
3. NBA legends are rare, but not as rare as you might think.
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Distribution of Win Shares
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.
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