Last week I revealed that thanks to Andres Alvarez, the Wins Produced calculation has been automated. Consequently – as I noted last Friday – it is now possible for more people to take these numbers and tell stories. So far, 34 people have volunteered to start writing these stories. And that means the number of voices you are about to hear in this forum is going to expand dramatically (we will work out the details of all this sometime this week).
The numbers – as Andres noted yesterday in the comments – will not be available until next Saturday. So this week we are still stuck with just my voice. And that voice is going to spend today talking about the All-NBA team.
Reviewing the All-NBA Team
Each year the media makes its selections. Some of these choices are quite obvious. LeBron James and Kevin Durant — by almost any measure — rank among the very best players in the game in 2009-10. Some of the other choices, though, seem to reflect a very common theme. Yes, let’s all say it together: Scorers are overvalued.
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Here are the top five players in the NBA in points scored per game (PPG) in 2009-10:
Kevin Durant: 30.1 PPG
LeBron James: 29.7 PPG
Carmelo Anthony: 28.2 PPG
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Kobe Bryant: 27.0 PPG
Dwyane Wade: 26.6 PPG
Each of these players – with the exception of Melo – was named to the All-NBA first team. And Melo was named to the All-NBA second team.
Now scoring is not the only factor the media considers. Playing for a winning team also helps. The productivity of an individual player, though, is not captured by simply noting how many points the player scores and whether or not his team tends to win. It helps to separate the player from his teammates by focusing on how all the player’s individual actions impact team wins. In other words, it helps to look at Wins Produced (at least, that is the argument in this forum).
Such a look is provided in Table One, where the Top 15 players at each position is listed.
As one can see, the media’s evaluations and Wins Produced are not entirely consistent. A list of the top six guards does include Wade, Steve Nash and Deron Williams. Jason Kidd, Rajon Rondo, and Manu Ginobili, though, did not receive enough consideration to displace Kobe, Joe Johnson, or Brandon Roy.
Turning to the forwards, again a person who believed Wins Produced (like me) can’t quibble with the selections of LeBron and Durant. And Tim Duncan was also a good choice; although I think Duncan spent quite a bit of time at center this year (more on position assignment in a moment). Anthony, Stoudemire (who I think spent more time at forward, although as I note, one can disagree with this notion), and Nowitzki, though, could have been replaced by Gerald Wallace, Marcus Camby, Carlos Boozer, and Lamar Odom.
At center the media and Wins Produced agree on Dwight Howard. David Lee, though, could have received more consideration than Andrew Bogut. Of course, it is possible that Lee was considered a forward by the media.
When we look at minutes played, though, it does appear that Lee was a center. But as I have noted in the past, position assignments are somewhat arbitrary. Yes, power forwards and centers are clearly different from point guards and shooting guards. Hence there is a need to consider position in evaluating a player. Whether or not a player is a center or power forward, though, may be in the eye of the beholder (or best left to the designation of the team).
Calculating Wins Produced
And that returns me to the subject of Wins Produced. This model was explained in The Wages of Wins. It was also explained in an article I published in 2008 (with details reviewed in other articles, some published much earlier) as well as in Stumbling on Wins. And back in 2007 I created a website to illustrate this measurement (a website linked to at stumblingonwins.com).
This website reviews the steps one follows in calculating WP48 [steps initially reviewed in the above publications]. As people who have reviewed these steps know, at the step just prior to reaching WP48 one calculates Adjusted Production per 48 minutes [ADJ P48]. This number considers all the player’s box score statistics (weighted in terms of wins), as well as the adjustments for team defensive variables and the teammates’ production of blocked shots and assists. In other words, ADJ P48 is everything except the position adjustment.
The position adjustment involves subtracting the average ADJ P48 at a player’s position from the player’s ADJ P48. And then 0.099 – the average player’s production of wins per 48 minutes – is added back in.
For example, Rajon Rondo posted a 0.439 ADJ P48. An average point guard posts a 0.263 mark. Given these two figures, Rondo’s WP48 is calculated as follows:
Rondo’s WP48 = 0.439 – 0.263 + 0.099 = 0.275
To repeat the same calculation for any player all one needs is the player’s ADJ P48 and the average ADJ P48 at each position. Given how I allocate players across positions, here are my position averages for 2009-10.
Power Forward: 0.371
Small Forward: 0.280
Shooting Guards: 0.228
Point Guards: 0.263
With these values in hand – and the corresponding ADJ P48 for each player – anyone can see what a player’s WP48 would be at any position.
Again, all of this has been detailed in the above books, articles, and websites. But I thought it might be useful to remind everyone of these steps as they start to think about writing about NBA players from the perspective of Wins Produced.
Once Again, jbrett’s Coded Responses
Such writings – as we have seen across the past few years – can generate some negative reactions. Last year – in discussing the 2009 All-NBA teams – I repeated something originally noted by jbrett in the comments section. As jbrett observed, it appears that a number of comments offered in this forum are repetitive. Consequently, we might see a gain in efficiency by assigning letters to the comments that most frequently appear.
Hopefully everyone will once again find jbrett’s observation as funny as I did (and if what he posted last year isn’t funny enough, jbrett and I have added to this list for this year).
Again, here is what jbrett said last year (with a bit of updating):
It seems to me your blog could benefit from posting, at the beginning of each Comments section, a list of time-saving conventions for the new or un-industrious poster. I only found it a few months ago; I spent a long time reading the older articles, and eventually I bought the book. This seemed the sensible approach, though, judging from the tone of many of the comments left, not the favored one. For the benefit of the many posters who consider this site homework-optional, I submit the following list of generic positions that NEED NOT EVER BE ELABORATED UPON EVEN ONE MORE TIME:
A. I have little or no training in statistics (me, for one)
B. Obviously, any metric that says Player A (let’s say, oh, Jermaine O’Neal) is not as good as Player B (how about, um, David Lee) is clearly flawed
C. Anyone who’s ever watched a game can see that Superstar A (Allen Iverson, anyone?) is ten times the player that Serviceable Role Player B (Chauncey Billups, maybe–or how about Andre Miller?) will ever be
D. Superstar A and his ilk cannot be quantified in the same way as mortal players can; they only shoot 42 percent from the field and 28 percent from 3-point range because their teammates DEMAND they do so, by leaving them with the tough shots at the end of the 24-second clock
(See how much space that one will save, when all you have to type is ‘D’?)
E. My friend/ brother-in-law’s boss/ opinionated alter-ego hasn’t read or studied your work, but I told him the results say Mike Miller is way better the Richard Jefferson OR Rip Hamilton, and he says you’re clearly deluded
F. I haven’t read THE WAGES OF WINS or STUMBLING ON WINS, nor am I likely to, and as a result I will begin by gainsaying basic tenets of the book
G. I read your books, and I say “Nunh-unh.”
Okay, here are some new comments for this year:
H.“Marcus Camby?!!!! Sure–go ahead and put 5 Cambys on the floor, and see how many games you win.”
I. “It’s just preposterous to try to define the value of any player’s contributions with a single statistic; therefore, anyone who attempts to do so (or anyone who enables that misguided wretch thru positive feedback or affirmation) is by definition not worthy of a scathing criticism, or even a haughty dismissal. I can’t believe I visit this blog ten times a week, I hold it in such disdain.”
(OK, that one might be a bit long-winded even for me.)
J. “These measurements are largely irrelevant because they measure only what a player has actually DONE, and not what he WOULD be able to do if he had better coaching and were playing a different position on a different team in a universe with different laws of physics where I, ZOD, were the UNDISPUTED MASTER OF ALL!”
And here are some new – more geeky – comments (one of these from DJ).
K. I saw that someone regressed their model (i.e. adjusted plus-minus or APM) on your model and this devastating and damning test (it is important you use the words “devastating” and “damning”) proves that your model is wrong. I hold this belief because 1) I am able to ignore the fact it is not clear which model is being tested, 2) I am able to ignore the obvious shortcomings APM (very inconsistent over time, most player evaluations are statistically insignificant), 3) I really have no idea how one would actually evaluate an empirical model.
L. All you’re doing is arbitrarily dividing up the team’s wins amongst the players, then making a team adjustment to hide any discrepancies. I can say this because I never read the books or the underlying empirical articles. I have read many “experts” on the Internet (and you know they are “experts” because they said so).
M. “A correlation of 0.94? Clearly that isn’t possible; therefore, you must not really be measuring anything new or unique.”
N. “Unless and until we are able to tabulate every single act that can conceivably occur on the court, and calculate their relative value in terms of wins, the metric you present here is either so incomplete as to be completely useless or hopelessly skewed and misleading.”
I’ll stop there–but, obviously, as other arguments become hackneyed, they can be assigned the next letter. Think how much easier it will be to find the genuinely interesting discussion when the endless repetitive jabber is distilled to a handful of letters one can note and skip past. It seems like an idea whose time has come. Any thoughts?
The WoW Journal Comments Policy
Our research on the NBA was summarized HERE.
Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:
Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.