Many Words on Why I No Longer Write about the Productivity of NBA Players Like Jimmy Butler!

Box Score Geeks is Back and It Has All Your NBA Player Evaluation Answers!

The Miami Heat may be moving on from Jimmy Butler. At least, they will for seven games. What will this mean for the Heat?

Sports pundits can offer endless answers to this question. But ultimately this is an empirical question. Specifically, Butler’s impact on the Heat depends on how many wins Butler produces. And in basketball, the number of wins a player produces can be objectively measured.

The story of how this was determined begins about thirty years ago. At that time, I started thinking about doing research in sports and economics. The first paper I wrote on the subject (while just a graduate student) was a literature review that looked at how economists had measured the economic value of a baseball player.

Having been born in Detroit, I was much more interested in basketball in the mid-1990s (remember, this is right after the “Bad Boys” era had ended). I soon decided as a graduate student I wanted to write a paper examining the economic value of a basketball player. Such a project required that I first measure a basketball player’s on-court productivity.

It was then I learned that people who had studied the economic value of a baseball player had it relatively easy. Economists could easily find several accurate measures of player performance for baseball hitters. Accurate measures for basketball players in the mid-1990s simply didn’t exist. Yes, there was a box score for NBA players. But no one had translated those numbers into something that would capture a player’s impact on wins. The measures that did exist were obviously contrived by people who thought the best way to measure performance was to create a metric that matched people’s perceptions. To do this, the value of the individual statistics was subjectively adjusted until a measure was created that “made sense” to the inventor of the measure. This is most definitely not how one should do research in academia. Hence, all of the subjective measures – like TENDEX, Points Created, PER, etc… -- were useless to me.

This point needs to be emphasized. Ultimately, we want to know how rebounds, steals, turnovers, made shots, etc… impact wins. A researcher can’t simply say that the weights they use “make sense” to them. You must have some objective and empirical evidence that what you are saying is valid. Hence the aforementioned models – as well as Win Shares, Wins Above Replacement, etc… -- shouldn’t be used in academic research.

Consequently, while I was officially working on research on international trade (that was my dissertation topic), I began researching how to measure the productivity of a basketball player. Like so many other people, my initial thought was this must be very complicated. And my first published research on the subject didn’t offer the best answers.

At least, they weren’t as good as what came later. As I continued to work on the question, I eventually developed the model we described with just words in The Wage of Wins. And then I explained the math in this paper published in 2008:

Berri, David J. (2008) “A Simple Measure of Worker Productivity in the National Basketball Association.” In The Business of Sport; eds. Brad Humphreys and Dennis Howard, 3 volumes, Westport, Conn.: Praeger: 1-40.

The title of the paper is not an accident. The Wins Produced model is relatively simple. Eventually this measure was used (and also described) in a collection of academic papers. One can even find an extensive description of Wins Produced (and numbers for the NBA, ABA, WNBA, college women’s basketball, and college men’s basketball) at Rod Fort Sport’s Business Page.

Yes, Wins Produced has been applied across professional and college basketball. Even though the underlying data used to generate the weights is different, the results – as I detailed in my textbook on sports economics – are remarkably consistent. In fact, in 2021 – in a paper I wrote on the impact of Oscar Robertson on labor negotiations in the NBA (you can read that paper online)– I detailed how we can use data from the ABA and NBA in the 1960s and 1970s and create a model to explain wins in the NBA in the 21^st century.

Again, basketball is a very simple and consistent game. This point was made again in the most recent paper I have published utilizing Wins Produced.

Berri, David. (2024) “No One Got Paid What They Were Worth! Exploring Player Value in the Early History of Professional Basketball” International Journal of Empirical Economics https://doi.org/10.1142/S2810943024500070

This paper – which you can also read online – looked at the productivity and economic value of players in the ABA and NBA in the late-1960s and the early 1970s. In this paper I repeated the following quick summary of what truly matters in the evaluation of a basketball player’s productivity (this quote has appeared in a number of places!):

Basketball is a fairly simple game. Teams win because they (a) acquire possession of the ball without the other team scoring (i.e., grab defensive rebounds, create turnovers); (b) keep possession of the ball (i.e., avoid turnovers, grab offensive rebounds); and (c) turn possessions into points (i.e., shoot efficiently from the field and the line).

Once again, people tend to think basketball is complicated. But if you take the time to connect the box score statistics tracked for players to team wins, you learn the game is quite simple. Players who shoot efficiently, rebound, and avoid turnovers tend to be productive. Players who can’t do this – even if they score lots of points – aren’t very valuable.

It was this story that Malcolm Gladwell focused on when he discussed The Wages of Wins in the New Yorker in 2006. Around the time that story appeared, I started a blog (i.e. what we used to call a substack!) called The Wages of Wins Journal. During the NBA season, I would often calculate the Wins Produced of NBA players on specific teams and write a story detailing what those numbers meant. Unfortunately, I lacked the computer skills to do this for all teams all the time. So, if your favorite team was the Chicago Bulls and I wrote about them in December, you may not see another comment on the Bulls until the end of the season (after I had talked about most other teams!).

For fans of specific teams, this turned out to be a bit frustrating. There simply was no way for me — given my limited computer programming skills — to give you updated numbers on your favorite players while the season was in progress.

According to Andres Alvarez, sometime around the time Stumbling on Wins appeared in 2010 he and Patrick Minton decided to end this frustration. Alvarez and Minton replicated the Wins Produced model and then created a website that presented the Wins Produced of every NBA player. This calculation was continuously updated throughout the season.

This was great news for NBA fans. Unfortunately for me, once Box Score Geeks appeared (the name of the current website, not the original name!), there was really no need for me to write the stories I once wrote at The Wages of Wins Journal.

To illustrate, imagine I was going to write a column centered on the question I asked at the onset of this story. What is the value of Jimmy Butler to the Miami Heat?

Well, once you know of the existence of Box Score Geeks, you don’t need me to answer this question. You can just look at the answer at the Miami Heat page. As one can see, Jimmy Butler is really good. After 22 games, Butler 4.5 wins. More impressively, Butler has produced 0.319 wins per 48 minutes played. An average player will produce 0.100 wins per 48 minutes (that is because a team of 5 average players will win 0.500 games per 48 minutes!). Butler in 2024-25 has been three times better than average. Only three players have played at least 500 minutes this year and produced more wins per 48 minutes.

Why is Butler so good? Box Score Geeks can also answer that question. As the website notes, relative to an average NBA wing player, is above average with respect to shooting efficiency, rebounds, and turnovers (he doesn’t commit many turnovers!). In other words, when it comes to what primarily determines wins in basketball, Butler is good at all of this!

Once again, you don’t need me to tell you that story. Because Box Score Geeks exists, you can easily see how much Butler matters to the Heat. You can also answer any other question you have about player productivity in the NBA. In fact, you can answer any question you have about player value in the NBA back to 1977-78!

Of course, you should be warned that if you think the best players are the players who score the most, you will not always like the answer you see. Players who don’t’ shoot efficiently, don’t rebound well for their position (yes, Wins Produced measure value relative to a player’s position!), or commit too many turnovers are not going to produce many wins. That is going to be true regardless of how many shots they take and how many points they score.

Wins Produced was created so that a player’s economic value could be determined. This required an objective and empirical measure of player productivity. Along the way, it became clear that scoring was overvalued in basketball and other aspects of player productivity were discounted. As we noted in Stumbling on Wins, the best coaches understand this point. Unfortunately, many fans and members of the media do not.

All of that is a story that has been told before (and will probably be told again). For now, losing Jimmy Butler is going to hurt Miami. Of course, one could see that clearly on Saturday night. Without Butler in the line-up, the Heat lost at home to a very bad Utah Jazz team by 36 points! Yes, Butler really is very valuable to the Heat.

Perhaps when the Heat trade him they can acquire some players who can restore his lost productivity. To see if that happens, though, you don’t have to wait for me to tell you the answer. When it comes to who is productive (or not!) in the NBA, you can just look at Box Score Geeks!