Today I want to post my Wins Produced numbers for the 2009-10 season (yes I know, I should have done this some time ago). But before I get to these, let me just re-post the WP story (as posted last week in an interview I gave to Raptors HQ).
RaptorsHQ – So let’s kick things off with a biggie – how on earth did you get interested in not only the field of sports economics, but in developing the metric you’re most well-known for, “wins-produced?”
David Berri: My interest in the economics of sports began as a graduate student at Colorado State. And it began somewhat by accident. In the process of looking for a research topic I came across a reference to a paper measuring the economic value of a baseball player. Prior to seeing this reference I did not know someone could use economics to study sports. Once I found this paper – and others in the same area – I decided to write a paper on the economics of the labor market in baseball. From there, I began my own research program in the economics of sports.
Because most economists had focused on baseball, I decided to start examining the economics of professional basketball. That research, though, had a significant road block. In baseball, productivity can easily be measured with OPS, Runs Created, etc… These measures have already been established, generally capture accurately a hitter’s contribution to wins, and are fairly easy to explain in an academic article. When I started research in the NBA – around 1994 or 1995 – the only measures that were generally available were something akin to NBA Efficiency. The NBA Efficiency measure (which is similar to Dave Heeran’s TENDEX measure and Robert Bellotti’s Points Created model) is quite easy to calculate and explain. But it is not highly correlated with team wins. So it is not a particularly good measure of player performance.
A better approach is to determine how the statistics tabulated for NBA players statistically relate to wins. But this is easier said and done. As I recall, Stacey Brook (my co-author on The Wages of Wins) came up with somewhat convoluted four equation system back in 1996 (for a paper we presented at the University of Colorado). Upon seeing the model a person in the audience said, “I take it this is not your first guess.” And I think I replied, “And it won’t be our last.”
These four equations were eventually reduced to two equations for a paper Stacey and I published in 1999. And these two equations were further refined for a paper I also published in 1999.
Dean Oliver and I had many discussions concerning this two equation system. Dean had also developed a measure of player performance, a measure that I questioned on theoretical and practical grounds (the issues raised were briefly discussed in The Wages of Wins). But although I was not willing to fully accept Win Shares (by the way…. Win Shares is a model that I prefer – as a forthcoming paper I have written argues – to the Player Efficiency Rating and Adjusted Plus-Minus), that doesn’t mean that what I had done so far couldn’t be improved upon. And with Dean’s urging me along, the model I had published was made better.
In 2006, Tony Krautmann and I published a paper (a paper originally presented in 2004) that offered a simple one equation model that connected much of what a player did on the court to team wins. This approach was improved upon – and labeled Wins Produced — for The Wages of Wins.
So the Wins Produced model began back in the mid-1990s. After much discussion (with various academics — including Dean Oliver), it was gradually transformed into what people can see today (in Stumbling on Wins and other publications).
Let me close by noting the basic lessons the Wins Produced model teaches.
Wins in the NBA are determined by the ability of a team to gain and keep possession of the ball (so rebounds and turnovers are important) and the ability to turn possession of the ball into points (so shooting efficiency is also important). Players who are not particularly efficient scorers and/or have problems gaining and maintaining possession of the ball, tend not to be very productive. And that is true, even if the player takes a large number of shots. In sum, scorers who are not outstanding with respect to shooting efficiency (and/or the possession factors) really don’t help their respective teams win many games
So that is the story. And here are the numbers from last year.
One should note that these numbers are slightly different from the numbers Andres Alvarez posts. The numbers from Andres are referred to as “automated Wins Produced”. This is partially because the position adjustment Andres employs is derived from an algorithm that considers such factors as the position designations listed on-line, a player’s height and weight, and the height, weight, and position designations of his teammates. In general, this algorithm is good enough to tell us if a player was a center, power forward, small forward, shooting guard, or point guard. But sometimes it might place a player at a position “incorrectly.”
The approach I have taken could be called “hands-crafted” Wins Produced. Essentially, I go through each roster, and assign positions by considering height, weight, position designations (i.e. same factors as Andres) and also my understanding of what position the player is probably playing. This process is fairly tedious (hence the inability to provide updated numbers throughout a season). In general, Andres and I reach the same conclusion for most players (so the automated approach – since it is easier – is preferred). Sometimes, though, there are differences.
It is also possible that a person looking at the lists Andres and I offer would disagree. If that is the case, I have presented the ADJ P48 numbers (you can look here for what the means) and the position averages. This will allow one to calculate their own WP48 numbers for each player.
One last note…Andres Alvarez will soon be posting automated Wins Produced numbers for the 2009-10 (for an early glimpse — and remember, it is very early — Arturo Galletti offered WP estimates yesterday).