*This post was originally intended as part of a series on the NBA draft for the Wages of Win Journal . It began life as **a long e-mail conversation between **Andres Alvarez, Prof.Berri and myself. It grew into multiple pieces in the Wages of Win Journal, a Wall street Journal Article and this blog. The companion pieces are:*

*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 Years*

*The WSJ Piece: Arturo Galletti Evaluates 30 Years of the NBA Draft for the Wall Street Journal*

*And without further ado here’s the piece.*

**Some quick background**

This article uses Wins Produced and WP48 [Wins Produced per 48 minutes] to evaluate player’s performance.* This measure uses three key components to evaluate a player:

- The player’s per minute box score statistics
- The player’s team’s per minute box score statistics
- The average performance at the player’s position (PG, SG, SF, PF or C)

A full explanation can be found here. To give a general scale, an average player has a WP48 score of 0.100. The very best players in the league usually have a WP48 over 0.300. To put this in perspective; an average player who plays a full season at 24 minutes a game would generate around four wins for their team. In contrast, a player posting a 0.300 WP48 would generate more than twelve wins in this time on the court.

**What makes a good draft Pick?**

In our previous post on the draft we focused a lot of attention on evaluating rookies based on their immediate impact to their teams. GM and fans can be notoriously shortsighted in their goals. The low probability of quick fixes in the draft combined with ill-advised impatience has been the end of the line for many a front office. When dealing with draft picks it is important to remember that you are getting a low cost player for four and not one year and any evaluation of draft picks should go beyond the rookie year.

When looking back at draft picks over history it is easy to get confused. We “know” or are told who the best players are and what the best draft classes are. For example, we are constantly reminded that the 2003 draft class is the best in recent memory. But we already know that public accolades and public perception do not correlate with performance and value. A constantly repeated theme of this blog, is that the wrong guys often are lauded, paid and played and good talent goes to waste . Rarely does the best rookie get selected for Rookie of the Year (In fact the Yay!Points! rule should states that scoring equals pub) . So when looking at draft picks we want to use statistics and analysis to come to our conclusions.

The first and most critical question is how do we measure a good draft pick. We should consider the following factors:

- The players contract is important so we will look at players over the first four years of his career (i.e his rookie contract)
- Overall productivity (i.e. Wins Produced) is important
- Per minute performance (i.e WP48 ) is important
- A small sample size is bad so any player playing less that 1600 minutes ( about 4.9 minutes a game) in 4 years will be excluded .
- Where the player is picked is important. His value should be compared to relative value at his position. So average Wins produced per pick and average WP48 per pick will be important.

**Ranking the Draft Picks**

With these factors in mind let’s work on ranking the draft picks. We will be looking at four factors:

- WP48
- Wins Produced
- WP48 -Average WP48 at Pick
- Wins Produced-Average Wins Produced at Pick

Wp48 and Wins produced have been worked out for all the players but we will need to work out average WP48 and Wins Produced by pick. For Wins Produced by pick we simply take the sum of all wins by the players drafted at that position and divide it by 30 drafts. For WP48 by Pick we take the previously calculated total wins by Pick multiply by 48 and divide it by total minutes played. For the first thirty picks this looks as follows:

Couple of interesting points jump out from this table :

- If we rank picks in terms of Wins Produced we get:

- Pick 1
- Pick 3
- Pick 5
- Pick 2
- Pick 4
- Pick 9
- Pick 7
- Pick 11
- Pick 6
- Pick 10

- If we rank picks in terms of WP48 we get:

- Pick 1
- Pick 3
- Pick 5
- Pick 9
- Pick 26
- Pick 2
- Pick 11
- Pick 4
- Pick 30
- Pick 24

So it seems like in general teams get good value from the number one pick. But the data points to a talent evaluation model for NBA teams that is not very efficient at delivering value.

So now that we have our base data set for the players and the picks what’s next? Simple, we will now rank our players based on the four factors (WP48,Wins Produced,WP48 -Average WP48 at Pick,Wins Produced-Average Wins Produced at Pick). Once we have his ranks for these four number we will average them and proceed to rank the players based on their composite rank (or **Draft Rank). **Draft Rank should give us an effective tool for measuring the value and “goodness” or “badness “ of a pick.

So to work an example, let’s pick a player . We’ll call him Player K . Player K’s numbers are as follows:

You’ve done it again. Great post Arturo.

Thank You. Satisfaction guaranteed or your money back 🙂

This doesn’t seem to take into account the time sometimes needed for a 17, 18, or 19-year-old rookie to grow into a superstar. On the other hand, besides the risk that it won’t happen, there’s also the risk that the young rookie will leave the team before that growth takes place.

Tim,

You got it. This is geared to the fact that a team is guaranteed the player’s services for four years. If you’re the Wizards and you draft 20 year old John Wall you’re not necessarily getting the 24 year old Wall.

And if you do resign a 24-year-old player, you may do so by signing a good-but-not-great player to the market price, which means you don’t get the discount for rookies and superstars built into the cap system.

Hey, Prof. Berri says he won’t go on twitter, but have you considered doing so? I would follow you.

I already am on twitter. Check out the sidebar. I typically tweet when a piece is up.

Beautiful work, Arturo. Is it possible to get a margin of error on those WP48 averages? That might be more telling regarding the level of risk associated with each pick. Thanks and keep up the good work!

That really should not be too hard. I can do it as a short post in the future.

Maybe I’m missing something obvious, but the per-pick Wins Produced and WP48 in the by year ‘draft-1.png’ table do not match the numbers in the player K and Draft-Score tables.

For example in the per year table the per player total wins and WP48 for pick #13 are 9.7 wins and .080 WP48; I get the same numbers doing the math myself. However in the player K table they are 0.9 wins and .039 WP48 respectively.

I cannot figure out how to reproduce those latter numbers, where did they come from?

BPS,

You’re right , I goofed. The tables are an older version reflecting 1 Year not 4 Year Averages. Fixed it now.

You sir get a no-prize. Give me a topic and I shall write a post about it. For Free.

The thought I had when looking at this chart was to try and figure out the monetary value of a draft pick. Since the pay scale is fixed, and we have a rough idea of the expected production of each pick, and a value of a win per year…

BPS,

That’s actually close to what the followup piece (for which the data crunching is already done) would be. I can get a post on monetary value and risk done.

Arturo – love the work of wages of wins and the network. I was a little suprised to see my favourite player Manu Ginobili so low on the list, and I think I’ve figured out why – the “average” WP scores for the 57th pick are the 2nd highest in the table (ie only the no. 1 pick has higher average WP scores). I’m guessing this is because not many of the 57th picks actually play enought to be included, and Manu is distorting the average to the high end.

Could you re-run Manu’s numbers against the lowest average WP scores for any of the draft picks ahead of no. 57, and see where that puts him ?

I realise it’s probably a lot of work, but he’s being ranked far too low in my opinion.

Thanks, James.

Fresh post just for You.

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This is fascinating and very valuable (and entertaining!).

Your table ranks Roy Tarpley a little better pick than Manu Ginobili. Do you think that’s accurate?

Tom,

The Tarpley -Ginobli thing is why we did the fix with a hard minute cap. Ginobli is better than Tarpley once I account for the minute warping in WP48.

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The WP and WP/48 discrepancy can be partially explained by something you’ve discussed in previous entries. Top picks are likely to get more playing time and more opportunities than later picks. Thus, while WP are likely to be highest for higher picks, as they get the most playing time, this tends to have an adverse effect on WP/48 because the bad players are getting those extra minutes too.

Contrast that with the later picks, such as the #26 pick in the draft. All it takes is a great player or two drafted out of that 26 spot to skew the WP/48 of that pick because the best players earn top minutes while the bad players continue to get minimal playing time.

[…] written this piece before.Long-time readers know that the draft is old and fertile ground for me (see here for a good example). Now, typically I need no prompting to start writing about the draft but in this particular case […]

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