It was easier to know it than to explain why I know it. If you were asked to prove that two and two made four, you might find some difficulty, and yet you are quite sure of the fact.
-Sherlock Holmes “A Study in Scarlet”
You may have heard that a draft is coming.
No. A draft not The Draft.
And you already know I’m fascinated by the NBA draft and of course I’m going to say some words about it.
But before we get to this year’s draft, let’s talk last year and review some of the historical work.
We are going to woolgather a bit
Let’s talk origins and background people.
Specifically we are going to get you nice and caught up with all the pertinent draft work and do a nice early review of the the draft picks made in this space last year.
Before we start sling tables and numbers, if you’re a rookie here yourself go read the Basics. Let’s give some background:
Background(in green, fell free to skip)
With this series I will rank and review rookie performances during this NBA season. This will be one of the lynchpins of my blog for this season (and however long we continue to inhabit this space). As longtime readers of this blog know, nothing inspires me like the NBA draft and rookies. To illustrate and provide some background, here are a few of my pieces.
The Draft:
Part 1: Finding Elite Rookies in the NBA Draft or How the NBA Draft is a Lottery
Part1a: The Top 33 Rookies in the Past 33 Y ears
The WSJ Piece: Arturo Galletti Evaluates 30 Years of the NBA Draft for the Wall Street Journal
Part 2: Ranking 30 Years of Draft Picks
Part 3 :A Sunday Kind of Piece: Return of The Draft
Where I ask How good are GMs at finding talent?
(The answer: Not Very)
Part 3a: The Draft,The Draft,The Draft………
Where I concluded that:
- Talent is always available in late in the first round.
- The trick is finding it with some accuracy (which I postulate we can do).
- Given that the identification is risky a later,cheaper pick is better.
This lead to a lengthy draft strategy segment in my guide to running an NBA franchise (Build me a winner rev.2). Which you can go read for detail (it’s really good I swear 
)
Based on my findings I wanted to see if I could build a model to predict rookie performance. So I did.
The Rookie Models:
I built two models (go here for the model build parts 1 & part 2 ). I called them : Yogi and Booboo.
This is a totally legit picture
To give you an idea of the value of the models I decided to look at:
- The probability of landing a better than average player (>.090 WP48) for his first four seasons
- The probability of landing a good player (>.150 WP48) for his first four seasons
I also decided to show this for:
- Any qualifying pick (>400 MP in his rookie Year)
- Any Top 5 pick
- Any Top 10 pick
- Any 1st Round Pick
- And Both models.
And this was done for 1995 to 2009. The table is here:
The best performing scenario is both models calling for you to draft the player, followed by Yogi then Boo Boo then having the Top five picks. Yogi is more picky, Boo Boo casts a broader net and is more accurate.
So with a good model in hand, I got to work on evaluating the incoming rookie class.
The Rookie Projections for 2010-2011:
The full rookie projection is here
For the reader’s digest version, It took all the player data, fed it into the models and got this (ranked by projected wins):
Only Griffin projected out as a difference maker for his team based on the model and his college numbers.
At reader’s requests, I then added some of the undrafted players:
The final component in this recap is rookie performance for the preseason:
One final note (and it’s been previously noted here). I miss assigned the Talented Mr. Fields position to SF and not SG. The corrected model is the one that will be shown.
Still here? Good. Now that you’re all caught up on all my silly little stats about rookies and the draft from the preseason we can talk about how the rookies actually performed for their rookie season
2010 NBA Rookies
How I do? Much like the playoff model, we did pretty darn well. Let’s summarize:
| Greater than .080 WP48? | |||
| Picked by | Outside Top 10 | Top 10 Pick | All Players |
| All Players | 24% | 55% | 31% |
| No Models | 17% | 43% | 22% |
| One Model | 50% | 50% | 50% |
| Both Models | 100% | 100% | 100% |
If we compare the top 10 picks versus model selection and set our benchmark for success at .080 WP48 for rookies, one model picks performed identically to top 10 picks and two model picks were can’t miss prospects in this draft. Only 30% of all picks were successful contributing rookies and the models clearly outperformed that mark.
The GM’s and scouting thus get fairly trounced by the math.
The takeaway? Math always wins and it’s worth doing this again.
And I will for 2011.
In Part 2 of course.
Ain’t I a stinker?
RandomStrring
06/21/2011
Can’t wait for part II The Culling
Rex
06/21/2011
I can’t tell what to look at when comparing performance of GMs vs. the Model(s). I suspect it’s because I don’t understand how to read the summary table. Please advise.
Also, the category, Don’t Draft is baffling. Same for Draft Score=0. Most players end up there. So # of picks greatly exceeds players categorized as Draft-worthy. How is that practical?
arturogalletti
06/21/2011
Rex,
Top 10 Picks hit 55% of the time. 2 Model picks hit 100%. Single model picks outside top 10 hit at 50% (so far).
There were ten players out of sixty picked by the model. Of the ten, seven were available after pick 10 and 4 after pick twenty. You will have a shot at them.
Rex
06/21/2011
Thanks AG, that totally clears it up. I missed the Pick column on the Early Returns table. Will be interesting to see how the model does down the road for the “Draft” guys who didn’t play, or were injured (Xavier Henry).
Ransom Hollister
06/21/2011
Chad Ford just mentioned that Minnesota could get #13 and Marcin Gortat for the #2 pick. Sounds like an incredible franchise changing trade. Gortat, Love, then use your models to select someone at 13. Sounds like a contender.
winniepoo
06/22/2011
Hey Arturo,
Just wondering why you used .080 for the model success cut-off when your basic premise at the outset was for above average i.e. above .090 for the first four years. It is inconsistent whilst a bit nitpicking on my behalf. I understand there is likely an assumption in play that any given player will improve until the age of 25-26 thus taking their four year average to greater than .090 from a set starting point but that isn’t clearly set out.
winniepoo
06/22/2011
Hi Arturo,
The question I was trying to ask in the previous post but not clearly is that Evan Turner’s actual WP48 results fall below 0.90 and I don’t understand how that constitutes a success.
On the flipside though, I can see from the build v2 that for the first model a projected 0.95WP48 is the hit rate cut-off likely to a generate a 0.90WP48 average over 4 years while a projected 0.67 for the separate model is the similar hit rate cut-off for the second model.
Based on these cut-offs wouldn’t that make Ed Davis a Yes for the 1st model expanding the number of two model inclusions to 4 and hitting on 3. 1 of 2 top 10′s and 2 of 2 outside top 10′s. Which reinforces the model’s success at predicting quality players drafted outside the top 10.
arturogalletti
06/22/2011
WP,
The thing to remember is that I’m looking at the 1st year only. Typically, I would evaluate results over a four year period (and I would expect rookies to improve).
I will do a correction just for you later in the day.
winniepoo
06/24/2011
I figured as much Arturo
You haven’t commented on my thoughts that Ed Davis is a hit on both Yogi and Boo boo and another successful 2 model pick?
arturogalletti
06/24/2011
I will. I was on a deadline yesterday!
Chicago Tim
06/23/2011
I hope we are getting the goods today before the draft.
arturogalletti
06/23/2011
CT,
What 3 posts in 24 hours not good enough?
No worries.
Neerav Vyas
06/23/2011
As lifelong NY resident and a dismayed Knicks fan I’m amazed that Dolan didn’t throw away Fields with the Melo trade.. he must be loosing his touch