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The Stats Say: Some young Rockets are likely to have a very successful NBA career (and some are not)

How successful of an NBA career can we expect from newbies like Donatas Motiejunas, Terrence Jones, and Greg Smith? Will they become stars, or will they at least be productive contributors? Will they be middling journeymen? Or will they be dropped from the league within a couple of years? And what about the more established young players like Patrick Beverley, Chandler Parsons, Jeremy Lin, and Omer Asik?

If you were Leslie Alexander, you might answer these difficult and important questions by hiring several Ivy League PhDs and/or a traveling contingent of professional scouts. But you are not Leslie Alexander, and so you are stuck with me and my spreadsheet. I looked at all NBA players in the past 50 years who started their career similarly to the young/inexperienced Rockets (where “similarly” is based on age and performance [as measured mostly by RAPM but also by PER and WS/48]) and used that information to estimate how successful of a career each of the young Rockets may have. Results are below. If interested, see the footnote for more detail on the methods.*

career prospective for rockets young players

Quick hits:

  • I threw in Thomas Robinson just for fun. A lot of people are still high on him, but I think both Sacramento and Houston were smart to sell high. While it’s still possible that he will end up being a good NBA player, it’s pretty unusual that a 21-to-23-year-old rookie who performs that poorly ends up being any good, so a team is probably better off rolling the dice on another rookie, especially if that team’s front office has a recent streak of Parsons-, Beverley-, and Smith-like gems.
  • Unfortunately what I just said about Thomas Robinson can also be said of Donatas Motiejunas.
  • Motiejunas and Terrence Jones are often spoken of as if it’s a toss up as to who is better, but, statistically, Terrence Jones wins by a mile. If you go only by his box score statistics (PER and WS/48), then you would not be out of line to predict that Jones’s future includes All-Star appearances or Hall of Fame inductions since so few rookies post a PER above 17 or a WS/48 above .125. His RAPM, however, tells a different story. This conflict may mean nothing other than that we’ve got a small-sample-size problem (Jones played only 276 minutes). I will be very curious to see how he performs this season.
  • Greg Smith is rarely thought of as having career prospects on the level of Jeremy Lin and Chandler Parsons, but RAPM, PER, and WS/48 suggest that’s where he belongs.
  • Why does Patrick Beverley’s contract not get mentioned alongside Chandler Parsons’s as one of the best-value contracts in the league? And why does Patrick Beverley not get mentioned alongside Alaska as one of the best thefts from Russia?
  • Based on the estimates shown above, there is a 58% chance that at least one of the seven young Rockets will have a Hall-of-Fame-level career (38% if you exclude Asik).
  • I’m extremely impressed by Morey et al.’s ability to find good, young players from a haystack of really bad ones. The chart above would look even more impressive if I compared each player’s expectations to the expectations for the draft pick they were selected with (where applicable).

performance expectations by draft pick


*Here’s a brief example of how the results were calculated: Based on a weighted average of RAPM, WS/48, and PER (where RAPM is weighted highest), Donatas Motiejunas’s rookie season was about 1 standard deviation below NBA historical average, so I looked at all NBA players since the 1962-63 season who performed similarly badly in their rookie season (between 0.75 and 1.25 standard deviations below average) at around the same age (21-23) and then counted how many ended up having a “successful” career. The numbers in the chart are the percentage of these players who fell into one of four categories of career success. I defined the categories based on career RAPM, career PER, and total number of seasons played. Rather than explaining the convoluted definitions, it will be easier just to show summary statistics for each of the four categories:

description of career success categories

I don’t want to bore you (or me) with the details of all the little analytical decisions I made along the way, but if you have questions feel free to ask.

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