DAVID GREENE, HOST:
On Election Night last year, one pundit said the real winner of the presidential race was Nate Silver. The creator of the FiveThirtyEight blog used exhaustive statistical analysis of polling data to closely predict President Obama's substantial victory in the Electoral College, as many political analysts were saying the race was too close to call. Silver's blog became a huge generator of traffic for the New York Times website throughout the campaign. But Silver's first love is sports, not politics. He'll get to do a little bit of both now that he's leaving the Times to join ESPN and ABC News. Silver believes the data mining style he brought to politics can play a bigger role in many times of journalism. Nate Silvers joined us on the line from New York.
So, Nate, I'm curious - ESPN. Are you turning full-time to sports, or is this just a way to pass time until the next election comes?
NATE SILVER: The idea is to cover a whole range of topics where data-driven journalism can be helpful. And sports is certainly among those. I was in sports before I covered politics. We're still going to be covering politics, but also issues like economics, culture and entertainment, science and technology. Weather is one we thought about a little bit.
GREENE: Uh-huh. Are you now finally going to be able to predict blizzards and hurricanes perfectly, so we can all get ready?
SILVER: The irony is the reason weather forecasters are good is because they know their limitations. When you see a forecast and it says there's a 30 percent chance of rain in Brooklyn tomorrow...
GREENE: Yeah. Leave them some wiggle room.
SILVER: Yeah. But that's how the world works. It's not about clairvoyance. This is not mysticism. It's about using science to know kind of where's the order between what we know and what we don't know.
GREENE: Do you feel like, in all of these types of fields, whether politics, sports, that the numbers have not played a large enough role?
SILVER: It's a case-by-case basis. I mean, I think certainly that sports coverage, for example, has come a long way since Michael Lewis wrote "Moneyball" about 10 years ago now. In baseball in particular, almost every team has a statistical analyst on their payroll. Sometimes, the so-called stat head is running the team.
So baseball and other sports are the one place where you've seen, I think, already reaching equilibrium. But it's way behind, I think, still, in coverage of elections, for example. Part of the problem is people are looking for narratives. It's always a better narrative when, oh, the candidate who's behind is coming back. Oh, it's a really close race, down to the wire. But sometimes that isn't true. Sometimes you have a close, but clear lead, the kind of rooting-for-the-story component, wanting to sell copy - to put it a bit more cynically - kind of goes against what the statistical evidence, what the history would say, I think. And we try and provide clarity on that for people.
GREENE: Some of the people who have covered politics for a long time, Nate, you know, came down on you, and they felt that what you were doing was sending a message that the old way didn't work so well. How did you deal with that criticism? Did it get uncomfortable?
Yeah. At some point, I began to push back and to kind of launch a counter-critique of some of the conventions of horse race journalism and punditry. You know, I think I have less of a critique of kind of traditional shoe-leather reporting. I think that's very valuable. But, yeah, I felt that somewhat became important to kind of put what I was saying in context. And I'm not a guy who says, oh, we can just press a button and predict everything. I'm saying that we have to be more careful about how we weigh information. We have to be more accountable about how we characterize future events and not just kind of flippantly say, oh, it's a tossup when one candidate's ahead in most, but not all of the polls. And that led, I think, to some ideological clash.
OK. So, you're going to ESPN. It's not going to be sports, but it does kind of take you back to your original passion, which was sports, and then baseball in particular.
SILVER: Yeah. So, I worked for a baseball prospectus for four or five years in 2004 to 2008. You know, one great thing about baseball is that it's probably the world's best data set. I mean, some people put it to me that it was almost devised to gives statisticians a fun problem to work with, where everything that happens on the field has been recorded for 150 years. So it's a unique environment there to kind of train yourself to use data and statistics in a better way.
GREENE: You know, I'm a big consumer of sports, and I'm just - in listening to you, I remember a recent story about my Pittsburgh Pirates. They dropped a player, Brandon Inge, a veteran. His batting average was awful. He wasn't performing at all. But a lot of the players on the team talked about the value he brought to the clubhouse as a clubhouse leader. I mean, that's the kind of thing that you can't really quantify.
SILVER: Yeah, and we have to be careful here. I think sometimes staties(ph) can make a mistake of assuming that because something is hard to quantify that it doesn't matter. That's not quite true. In science, you'd want to set up some kind of a testable hypothesis, right? So take all the guys who are seen as good clubhouse leaders and see what happens when they leave. Does a team play inexplicably worse? And my guess is what you'd find is that if you take all these clubhouse leader guys and look at what happens when they're released or traded or injured doesn't make a ton of difference. But I don't know. I think both sides should be willing to contemplate actually setting up an experiment for that.
GREENE: Nate, best of luck with the move, and thanks for talking to us.
SILVER: Of course. Thank you. Transcript provided by NPR, Copyright NPR.