In an interview on Economics is Fun

Let’s talk about your next book, Michael Lewis’s Moneyball.

Everybody knows this now because Brad Pitt is in the movie.

Is the movie as good as the book?

It has to be presented in a different way, but it is a good reflection of the book, yes. It hits all the high points as well as being wonderfully entertaining. For example, in both the book and the movie, you really do get a feel for this guy, Billy Beane, who everybody said looked like a great baseball player. He wasn’t, for a remarkable variety of reasons, none of which you can put your finger on. He got the idea that if you started thinking about this (ie, how you recruit new players to your team) in a formal way, you can do better than people who just do it based on their gut. I’ve assigned this book to a “first week of the year” group a couple of times. The guys think it’s wonderful, though sadly the women did not find it very interesting. I also have kids read it in my econometrics class. There’s a huge amount of econometric research on baseball. What the book is really about is a guy who is using some econometrics to predict which players will do better in advancing wins, which is a remarkable use of economic thinking. These guys really thought out of the box.

So one of the guys is from Harvard and he has knowledge of economics but not of baseball. Using his computer, he is able to help Billy Beane choose the right players for the team?

Yes, he’d done some modelling. But without Billy Beane’s feel for the game, and willingness to use it, it wouldn’t have happened either. Like most good things, it’s rarely just one person – it’s a juxtaposition of a couple of people’s views that makes a nice innovation. There was a paper written by Raymond Sauer of Clemson University, published four years ago. The key point of the paper, and the point of the movie, is that the big guys, like the New York Yankees (whom I hate with a passion and have since I was five years old) have all this money. Of course they do well, because they can buy the best. Nonetheless, for a few years, because of what Billy Beane and his statistical people did, the Oakland As did phenomenally well on a truly miserable payroll. What was neat, that this paper showed, is that within three years, the As were back on the regression line. In other words, the innovation that they created spread very rapidly, so everybody started doing the same thing, and their competitive advantage disappeared. It’s another great illustration of how competition can erode an innovating entrepreneur’s advantages.

And the innovation was that people who look like they’re good at baseball aren’t necessarily, and people who look rubbish can be good?

If you look at their ability to increase the chance of a win, people used to look at batting average, which is hits over at bats. But an at bat doesn’t occur if you get a walk, or if you do a sacrifice fly. But a walk is as good as a single. So what he started looking at is bases or on-base average, and using these to predict how well a player would do. If you do very well at getting on base, if you walk every single time, you’re golden, but your batting average would be zero. So he started thinking about different statistics and people started putting these inputs into a production function for runs and wins. That’s the technical innovation.

So some people are good at walking are they?

Some people get walks a lot. For example, during the World Series, Albert Pujols walked about three times in a row because people didn’t want to pitch to him. They were afraid he’d get a hit. That didn’t help his average, but it made him worth a lot, and people pay off on that. He’s paid a bundle. Some people, for whatever reason – they have a stance, or because of their size, or the fear they instill – get walks. That’s just one example. But the book is neat because it brings together both this technical innovation and the very human story of this guy who was going to be a superstar, and didn’t quite make it. The movie doesn’t quite give you the same feel of sympathy for the Brad Pitt character as the book does. I found him more sympathetic in the book. In the movie there wasn’t sufficient time to develop him as a character.

And he probably wasn’t quite as good looking in real life?

He’s quite a good-looking guy, actually.

Generally, the philosophy you’re advocating in this interview and for your students is that they can get excited about economics and then apply the skills they learn to the real world in innovative ways?

They can apply it to almost anything they do. That’s what’s so neat. This stuff is just everywhere, like dealing with your roommates. Your roommates’ relation with you is a game theoretic problem. Who does the dishes? Who does the cleaning? For anything involving interpersonal relationships, the stuff we do in economics will be useful. On the first day of class, I tell my students: “You think economics is about money. It’s not. It’s about scarce resources.” Even if you have all the money in the world. It so happens that one of the richest people in America lives in this town, Michael Dell. He’s tremendously constrained because he has only 24 hours, just like you and me. So much money to spend! So little time! So these are the ideas I try to get across. I’m one of the few remaining people who are regular professors, who teach large classes. Mostly it’s farmed out to temporary staff, sadly enough. I think this is a loss, because if we just tell our kids this is a bunch of formulas, or a bunch of graphs, and don’t give the appreciation that, firstly, it’s about the real world, secondly, that it’s a more useful way of looking at the real world than any other and thirdly, that it’s fun, we’re losing a whole lot of people who will never find out what economics has to offer.

In an interview on My Life and Luck

Moneyball is the story of the Oakland Athletics baseball team and how they successfully used rigorous and innovative statistical analysis to improve their chances against wealthier clubs. Why did you choose it?

I discovered it when I was in the US and was a visiting writer at Harvard in 2003. I think I was one of the only English writers to talk about this book when I came back to Britain at the end of that year. I wrote a review of it and I tried to use it practically when I was captain of Middlesex – we used some Moneyball-like statistical methods to inform our selection of our Twenty20 teams. So my interest in it started off as intellectual, but then became practical.

Of course, the idea of using statistics to gain an edge is anti-luck if you like – it’s about using numbers to gain an advantage. But it’s more complicated than that I think. Moneyball is a superb book and credit should go to Michael Lewis for turning a book about baseball statistics into a bestseller and for attracting readers who do not like or have any interest in baseball. He makes the strongest possible case for using thinking to help win more games and using statistics to work out how a baseball match is won. And it’s not won in the way that we all think it’s won – by just scoring runs in the obvious sense. He breaks down how those runs are scored, who it is who is scoring, in much the same way as a financial analyst would do it. Since then, every baseball team, including the very richest, have tried to adopt this method. For some it has worked, for others it hasn’t.

What I take from the book now is that we would be crazy not to use the latest mathematical tools to help understand how games are won and lost, but I think the book takes to an extreme the idea that human judgements are absolutely obsolete in the face of scientific data. That idea has been shown to be a little dated. It’s almost as if Moneyball was the high watermark of enlightenment self-confidence – the idea that the numbers will tell the truth and human beings, with their gut instincts and judgements, will inevitably make mistakes. A lot of baseball teams haven’t benefited from the Moneyball methods. The Oakland Athletics team did, but that was assisted by their business model. I think success in sport will always be a mixture of statistical based analysis and human judgement. One without the other will never be enough.

I’m glad you said that, as I found the whole Moneyball thesis, that human judgement and instinct in sport could be replaced with statistical modelling, slightly depressing.

I think what Michael Lewis did brilliantly was expose the clubbability of professional sport. There is a tendency to be very suspicious of new thinking and I experienced this too. So he’s saying: “Hang on a minute, these guys are just recycling conventional wisdom and are closing themselves off to new and better ways of doing this.” I completely agree with him on that. But what I wouldn’t agree with him about is the idea that a computer can make all the right decisions about selecting players. That does not fit with my experience nor indeed of the evidence of today’s sport. So I don’t think that statistical modelling, whether in sport or financial risk, will ever supplant a shrewd combination of modelling and human judgement.