I couldn’t quite wait for Summer League to be over officially, run the numbers to see what, if anything, we can take from the rookies’ performance. But with the Lakers sitting virtually everyone of note for the Vegas Championship, I figured it’s over enough. (Note to the NBA: Vegas Summer League is too long, this is why teams start sitting their lottery talent).

In the link here, I have the full run down of per 40 one number performances via Kevin Ferrigan’s Daily RAPM Estimate (DRE) and Alt WIn Score (AWS), a metric I use quite often in my draft models with data from RealGM. But, to me, the real focus of Summer League has to be the rookies.

Some of that is informed by a Kevin Pelton ESPN Insider article, indicating that Summer League adds a bit of predictive power to rookie performance but not to 2nd year players. It’s also plain that we just have less information on rookies, so new info relatively more valuable as is seeing them in a new team setting.

In order to get a quick and estimate on evaluating the stats out of SL, and maybe providing a bit of perspective, I re-calculated my Rookie performance draft model, first by substituting the SL stats for the college or European league stats and then used the SL stats to just update my original Rookie Model.

First the Summer League Only (SLO) run. The SLO model seems to match the buzz coming out of Vegas very well, with Lonzo Ball on top followed by Dennis Smith Jr, and Jayson Tatum, at two and three. Laker fans might want to frame this table with three Lakers prospects in the top 10.

Of course, for reference I should add that the scale of the projections line up so that a 5 is roughly equal to average production, or a 0 in plus/minus terms. Indicating that the SLO model projects every rookie but Ball to be below average next year.

For Celtics fans SLO is more mixed, Tatum comes out the third best, Zizic performed respectably, and uh, Semi Ojeleye was also there.

It is hugely unfair to project Markelle Fultz based on what amounted to about 64 minutes of playing time. Though he was actually helped by the the regression I applied, since he had performed below average in his brief court time.

So then, how much to actually adjust our expectations, if at all? Going again based on the Pelton article, I ran the rookie model with the SL numbers added, weighted at a 25% of the pre-NBA numbers. This gives a much more realistic evaluation to Summer League importance.

For example, in the tables below ordered by the SL Updated Rookie Model (appropriately, perhaps- SLURM) Fultz is still appropriately in the top 2. And the most any player has been adjusted up is three tenths, and down is five tenths (again the model results are scaled so that it’s roughly the same as being projected to be .3 better in a plus/minus model).

And below is the 2nd half of the summer league rookies by SLURM:

Maybe, we can hold off on the Kuzma Rookie Of the Year ceremony and wait to bury Fultz or Zach Collins. At least until the second game of Preseason.