This is a post about communication.
One of the through-lines of my academic and professional career is conflict between entrenched subject matter experts (SME) and hot-shot quantitative analysts. As a young undergraduate, I followed Baseball Prospectus Fangraphs through the SABRmetric revolution. I watched Nate Silver bring data-driven prognostication to the world of political journalism which had previously (and arguably still is) dominated by punditry. In my current job, I work with experienced analysts who have often been working on the same systems for years.
I wanted to talk a little bit more about how different metrics account for variation in player performance, and some various flavors of NBA plus/minus statistics provide nice examples. This is building a bit off of some concepts I discussed in Choosing the right metric for sports.
Plus/Minus Metrics One approach for estimating individual player contribution to overall outcome is to look at the net points scored while an individual player was on the court.
I think its great that sports statistics are a big thing in popular media. It makes fans and media better informed about their team and players, and it provides an entry point for people to get interestd in statistics.
That said, there seems to be a perpetual innumeracy in the way folks talk about a lot of these metrics. One thing I see come up repeatedly is the distinction between metrics that look at a player’s past performance and say, “How important was that player to the team’s success?