I posted the following last June. Unfortunately I made the mistake of giving it the title: What Wins Produced Says and What it Doesn’t Say. Apparently, you can’t use the word “Doesn’t” in the title. Now when I link to this story the link won’t work. So I am re-posting so that in the future when I discuss Wins Produced I can refer readers to this post.
The NBA tracks a variety of statistics to measure a player’s performance on the court. NBA fans are familiar with points scored, rebounds, steals, assists, turnovers, blocked shots, etc… The difficulty with these statistics is that some players excel at some aspects of the game, but not at others. And what we want to know when confronted with players with different skills is how each player impacts the final outcome we observe on the court.
The approach we took in The Wages of Wins is simply to utilize regression analysis – a common technique in economics – to determine the relative impact of each statistics on team wins. We had three objectives in constructing our model. Ultimately we wanted a measure that was simple, complete, and accurate. In the end, we think each of these objectives was met. The Wins Produced model is not hard to understand, it incorporates each of the statistics tracked for individual players, and it connects accurately to team wins.
With the Wins Produced model one can begin with a player’s statistics – his points, shot attempts, rebounds, steals, turnovers, etc.. – and translate these into how many wins those statistics creates. And with this measure we can tell three basic stories about talent evaluation in the NBA.
- Players who do many things well – like Michael Jordan, LeBron James, Shaquille O’Neal, Tim Duncan, and Kevin Garnett – are very productive players, just like most people believe.
- Players who only score, though, or have deficiencies in their game (i.e. low shooting efficiency, high turnover rates) – like Allen Iverson, Antoine Walker, and Carmelo Anthony – are not as productive as people believe.
- Players who are prolific rebounders – like Dennis Rodman, Ben Wallace, and Marcus Camby – are more productive than people tend to believe.
Now it is important to understand what Wins Produced says, and what it doesn’t say. Specifically, Wins Produced tells us how productive a player has been. It does not, though, tell us why that player is productive. This is a point we made in the following excerpt from The Wages of Wins.
p. 125 in The Wages of Wins
One cannot end the analysis when one has measured the value of player performance. Knowing the value of each player is only the starting point of analysis. The next step is determining why the player is productive or unproductive. In our view, this is where coaching should begin. We think we can offer a reasonable measure of a player’s productivity. Although we have offered some insights into why players are productive, ultimately this question can only be answered by additional scrutiny into the construction of a team and the roles a player plays on the floor.
The Wins Produced measure does not replace the insights of coaching and NBA analysts. What it does is correct flaws in the evaluation of talent in The Association. Players who do not shoot efficiently, or turn the ball over frequently, do not help a team win many games. Players who can accumulate large numbers of rebounds can indeed have a large impact on final outcomes. Of course, why a player shoots inefficiently, commits turnovers, or rebounds well, is not a question Wins Produced will answer.
In The Wages of Wins we do explore some factors that cause players to perform better or worse. For example, we spend some time discussing how a player with more productive teammates will tend to be less productive. Or low levels of roster turnover – specifically, keeping a team together – will cause a player’s performance to improve.
And we did consider other issues with respect to player performance – and if you wish to see these please read the book. Or just wait. At the rate we’re going, we might eventually get the entire book on-line, one excerpt at a time.
– DJ
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A question about your methodology. You use a large number of factors to determine a player’s worth. Why not follow the hockey method for determining worth and look at plus-minus? I don’t think basketball even keeps that statistic. All you have to do is determine whether a given player is contributing more or less than the team average to the team’s plus-minus. For example, if a player is a Plus 4, and the Team is a Plus 6, that means the player is contributing less than the rest of his team, on average. All this talk of rebounds, scoring, steals, and blocks is really meaningless, isn’t it? Isn’t the important stat the simplest one: i.e. whether a player is contributing to a team scoring more than the opponents? And who cares what he is doing to accomplish that. Maybe he is the best pick-setter in the league. Anyway, I do not follow basketball, but I find this obsession with individualstatistics curious but in the end rather limiting. — Michael
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