Counting the Baskets

Celtics Drafted Players Data Viz

Below I have a pretty simple data visualization focused on the Celtics new draftees. The box plots are all by position to get a better sense of how the Celtics players rate with their fellow new drafted rookies.

 

Terry Rozier Acceptance Phase

It is probably a good thing for Celtics fans that free agency in the NBA follows so closely on the heels of the draft, if only to distract them from their palpable disappointment. The collective draft let down stems from both the inability of the front office to move up in the draft from the sixteen spot and the resulting pick of Terry "Who Now?" Rozier out of Louisville with that pick. 

Rozier was projected by most mock drafts to be selected around the end of the first round, closer to the Celtic's 28th pick than where he was ultimately taken. His numbers weren't well liked by most of the analytic models in the public domain either, prompting Nylon's Nicholas Restifo to give the Celtics' an F as an objective and subjective draft grade. Restifo calculated that the Celtics left a good amount of value on the table with their maverick choice. Not great, Danny.

  

Acceptance Phase

 

First, it's important for fans and writers to remember that this was the team's choice to draft Rozier higher than expected, not Rozier's. All of the additional expectations should be on Danny Ainge, not Rozier.

 

However, there are a couple of reasons to think Rozier might be a better pick than the initial fan reaction held or that initial draft grades might have been a bit overly pessimistic on Rozier. Part of that stems simply from faith in the Celtics as a competent NBA organization, not a super all knowing, can't go wrong set of basketball geniuses, just a typically competent NBA organization. 

 

I applied that idea in my Benefit of the Doubt draft models the other day at Nylon Calculus, captured below using just the Celtics draft selections. The table shows the initial model rank and the rank in the Benefit of the Doubt models.

 

 

To be sure, the model would have estimated a higher value for a player at that spot who performed better in the initial, non-draft informed version of the model. But, balancing the judgement of teams with the analytic models does give better estimates and the Celtics seemed to move on Rozier because they thought other organizations would grab him before the 28th pick came up, so perhaps they weren't the only ones interested in him.

 

In addition, Nic Oza at the Georgretown Sports Analysis Business Research, had some thoughts on potentially overrated and underrated prospects in this year's draft. While Oza didn't mention Rozier, he did note that defensive skills are likely an underrated in the draft. A point I tend to agree with. Rozier is, of course, viewed as a defensive specialist indicating a reason he could have been an under valued prospect

 

Lastly, Rozier wasn't evaluated poorly by all of the analytic models. New Hampshire Math Professor Steven Shea's CPR rating had Rozier as the thirteenth best prospect. That in and of itself is not necessarily that interesting, any NBA worthy prospect can come out as well rated in one public draft model given how many there are now. 

 

But, it does get more interesting for two reasons. First, Shea's model rated all of the Celtics' first three picks well; rating R.J. Hunter as 11th and Jordan Mickey as 14th overall. Second, Shea's methodology focuses on the ten max performances by a prospect using game log data, then adjusted for class, suggesting those max performances may be more indicative than average performance of potential. What makes that interesting is that the Celtic's Director of Analytics, David Sparks, developed a game log metric back when he was a writer for Hardwood Paroxysm, so there's reason to believe the Celtics might be looking more at peak game performance as part of their analytic evaluation. I think there are pluses and minuses to that approach, especially if only a subset of games is used, however, I feel more confident in the Celtics selections thinking there was more than Danny's gut involved in the process.

 

As I said in the Benefit of the Draft model, all of the new rookies will soon have a chance to start proving themselves as NBA players and update our estimates of their potential.

 

RSCI Business: Draft Model Update

This year I added the high school consensus recruiting index rating to my draft model, which I discussed here.  The prmary benefit of adding the rating is to add prior information to college performance especially for the highest rated prospects.

As mentioned in the introductory post, the RSCI rating is most closely related to the age that players enter the draft, as that's a self selection based on the player's expected draft position. Therefore the biggest effect on the model, other than to boost highly rated recruits, is to reduce the relative power of the age variable.

So, while I consider the version including RSCI to be the best estimate and plan to use it going forward, it is sometimes useful to compare different versions of a model in order to better understand how variables are being weighed and to take a closer look at any instances where there is a particular divergence between the versions.

First here is the top twenty or so players based on recent Draft Express rankings (may not be completely up to date with current rankings).

The top of the order of the two models is slightly different. Jahlil Okafor is rated as the top prospect when including the information about his recruiting rank, but switches places with Karl Towns when that info is dropped. D'Angelo Russell moves into a very close third without the recruiting information, but is a more distant fourth when the RSCI rating is included.

Further down Justise Winslow and Stanley Johnson also swap places in the eight and twelve spots, with Johnson rising to eighth when the recruiting info is included.

In terms of the bigger list, I wanted to pull out the biggest risers and fallers between model. As above the 'Diff' column shows how much the player was helped, or hurt, by the recruiting information. First the biggest risers:

Andrew Harrison goes from completely undraftable at 78, to almost draftable at 62, which is not a great place for a former top 5 recruit out of high school to be. Sam Dekker also goes up given that he is relatively old for a former 13th rated recruit to enter the draft. Cliff Alexander is another beneficiary.

Then there is those lowered in the model by adding the additional rating:

 

Devin Booker falls despite being a well regarded recruit, simply because he is such a young prospect getting less boost from his borderline out of sample age.

If you are interested in the entire list it's linked here on Google docs.