Oliver talks about the role his statistical analysis plays in the NBA.
SLAM: How is it working with the scouting department?
DO: It’s evolved. Originally, there were a series of questions about what I was suggesting [in my analysis]. Since I’ve been in Denver, it’s been pretty good. Of course there are things that come out of my analyses that are different than the analyses that scouts do. But I think the culture we’ve been able to develop is that those differences are healthy. And you question why. I try to question why before I throw a name out there. That hopefully leads to productive discussions about who to choose, or at least who to better understand.
SLAM: It seems like Michael Lewis’ New York Times article on Shane Battier has been the link to making casual NBA observers and those traditionally opposed to quantitative analysis become a little more comfortable with it.
DO: It’s funny how much that one does get brought up. I’m always a little bit surprised. But Michael Lewis is a very good writer, and I enjoy his stuff. I had lunch with him I think it was either Fall of 2004 or spring of 2005, so about three years after his book Moneyball came out. Which was very helpful to us in basketball. I wrote my book, and it came out a few months after Moneyball so I got lucky there. His book got read by a number of people in NBA front offices and they were interested. I was able to, through a series of lucky circumstances, be able to walk around and hand my book to certain people and say ‘You read Moneyball, I can help you do that.’ When I had lunch with Michael Lewis, I said thank you. [Laughs]
SLAM: Basketball is ideal for quantitative analysis. The pace is there, there’s enough action going on.
DO: I certainly love it. It’s interesting. There are a lot of sports out there not getting near the attention of the numbers, but there’s a number of sports that haven’t gotten the attention of the media for how much the numbers have helped. My wife is from Brazil and the Brazilian women’s volleyball team uses numbers extensively. They are very, very good. I think there has been a little bit of media attention on soccer. There are some efforts in soccer from using analytics to make a difference. I do think about these other sports and try and put basketball in perspective.
With regard to those, what basketball has is a lot of elements from the other sports. Or looking at it the other way, there are elements in basketball that can be taken to help in some of those other sports, as well. There is a lot that happens in a game. You have a pretty long record of those things. That does help. Some of these other sports will pick up in the data collection process.
SLAM: I’m interested to know a couple overvalued and undervalued statistical measures you see.
DO: Oh boy, this question is always difficult because the market for these things is not clear to me. How much people are using unadjusted plus/minus…I think that’s actually a very interesting number, and I don’t hear people talk about it too much. It has certainly some flaws to it. It’s been around a long time. On the surface of it, I would say that’s under-appreciated right now. The NBA is putting it in its box scores now. I think last year was the first full year I saw it.
SLAM: With plus/minus, it’s difficult for people to accept that sometimes. Wasn’t Kevin Durant considered before last season someone who cost his team too much value in that category?
DO: There was simple analysis done on Durant that came out that way. I remember that. I remember thinking that I went to grad school, and I used statistics. There are certain pieces of data that come out that they look correct, but the answer is just wrong. There’s this temptation now to do it every time a result is weird. If you do the analysis right, there will be a handful of cases where it’s just wrong. And I think anybody who has seen Kevin Durant, anybody who has done other types of analysis on Durant, would have said that doesn’t make sense. Getting back to the media, you guys are a mouthpiece for a lot. I’ve been asked about [that Durant analysis] a few times, and i think about how it’s not anybody’s fault that it got out there and got all that news. Because it’s so weird, you have to say ‘wait a minute.’ Somebody did the analysis, and it gets blown up because it’s so weird.
SLAM: Well, it’s like in baseball where a lot of sabermetricians say RBIs don’t matter. It’s hard for people to accept that because it’s been such a fundamental statistic.
DO: Yeah, well I think the conversation about what works and what doesn’t work gets a little bit noisy. If you get people to actually discuss without taking a right or wrong position…historically a lot of people have said, ‘Well, yeah he got an RBI because that guy set it up for him, he moved the runner over.’ So you’ve heard that for a very long time. Perhaps the voices now are more definitive and more broad. Now, the voices are saying a lot of things. A lot of RBIs aren’t that valuable, or overvalued. People have been saying a lot of these things, just not as broadly or strongly.
SLAM: Are there any overvalued/undervalued measure you can point out.
DO: Overvalued, I’m not sure.
SLAM: I mean, assists, right? Assists aren’t representative of a player’s passing ability.
DO: Well, yeah, that’s a better way to phrase it, actually. Whether it’s overvalued or not, it’s not necessarily a reflection of a player’s passing ability. It’s certainly a reflection of how much they have the ball. There’s a subtle difference in the language, of course, in whether it’s overvalued. It can be easily misinterpreted.
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