COWEN: I have a big compound question. It’s about a few things. Feel free to touch on it what you want. But one of them is sports, one is fantasy sports, and one is gambling. They’re all interrelated.

What’s your take on — what do these actually do for us? How socially productive are they? You’re of a mixed mind on drug legalization. I could ask a comparable question about gambling, either legalization or liberalization. But what’s the net social externality on this mix of sports, fantasy sports, gambling?

What’s your view? I know it’s maybe fun for you.

SILVER: I’m biased, I make my living as a — you know.

One of the things about the regular fantasy football league that you’re in with your friends is that you get a lot out of it. You get to hang out with people you might not see very often, especially as you get older, into your 30s or 40s or whatnot. You get to watch a lot of games with more of a rooting interest.

The thing about daily fantasy sports is that a lot of that is really taken away. It’s very much a brute force approach to watching sports.

I did this for a few weeks and then got bored with it. But basically I had a program that would randomly generate high-scoring lineups. Then you scrape that data, and you load it up, 200 lineups at a time, and it kind of took all the joy out of it.

But that’s not quite what you’re asking, really. Right?

COWEN: Right. [laughter]

What if people just watched sports? Like, I watch sports. If it’s a good game, I enjoy it. I don’t feel I need to gamble on it. I don’t want rotisserie, I don’t want — I want to read analytics and I want to read you or your people at FiveThirtyEight on the game, which is great, and then watch the game and I’m done. If they’re good players, I’m happy.

What am I missing, if anything?

SILVER: For one thing, gambling and fantasy sports are a good way to teach people applied analytics. I’m not being jokey, like, I think this has probably a measurable benefit to society.

But look, it’s the case where, unlike drug legalization — where there are not a lot of countries where drugs apart from marijuana are even there fairly rarely — worldwide, people are much more relaxed about gambling, and it’s normalized.

You can go to the betting shop, any Ladbrokes anywhere in the United Kingdom and place a bet and it doesn’t seem to ruin society. Maybe you have in low-paying leagues or in tennis, the occasional betting scandal which is not great. But I think it’s a way for a substantial number of people to enjoy sports and develop critical thinking skills.

You can go to the betting shop, any Ladbrokes anywhere in the United Kingdom and place a bet and it doesn’t seem to ruin society. Maybe you have in low-paying leagues or in tennis, the occasional betting scandal which is not great. But I think it’s a way for a substantial number of people to enjoy sports and develop critical thinking skills. Again, I say if it’s close, let people do it, and I feel that way about gambling.

Again, I say if it’s close, let people do it, and I feel that way about gambling. But in that case, you do have examples of many, many Westernized countries where spending on sports is legal, and there seems not to be, at least, grave societal harm.

COWEN: You Run the website, FiveThirtyEight. It’s your vision, you founded it, you developed it. You took it to ESPN. Over those years, what would you say is the most important thing you’ve learned about managing?

SILVER: Basically there are three strategies, three fundamental strategies of management when you have a disagreement with something that your, one of your employees is doing.

One of which is you can give up. Right? You can say, “Well, I’m not going to pick this battle to fight, because there’s a consequence to lowering this person’s morale, or I’m tired, I have other issues.” So you can capitulate.

Caren Louise Photographs

Number two, you can fiat. You can say, “Well, sorry, but I’m ultimately the one who signs your checks,” or my boss signs their checks, but, “This is the line of authority, and we are not going to publish that article. I’ll explain my mind later on.”

Number three is you can try and persuade instead. Which sounds perfect except persuasion is really, really time consuming.

Figuring out which ones of those three tactics to use and in what ratio is important. I actually found though, overall, that there’s like a little bit more value in micromanagement than I thought. Not about everything, but strategically saying, “I’m going to spend a lot of time going into detail on this one.” Or, I guess it’s just mentoring, I guess, is a way to put it.

COWEN: Which sports coach or manager are you most like? Vince Lombardi, Gregg Popovich? Who do you draw inspiration from? Do you think about it in these terms?

SILVER: I’m not arrogant enough to compare myself to Popovich. But I’m like, I’m laissez-faire, but when I weigh in on something, I’ll weigh in pretty directly. I think you do have to pick your battles a little bit. You have to hire really well.

But it’s a culture of creatives and a culture of journalists, and journalists are strange and wonderful people, and data journalists are still journalists too, but you have to kind of trust people to make their own decision.

A big thing, too, is kind of figuring out which one of my deputies, the other managers and editors on the staff, what’s my agreement ratio with them. It’s incredibly valuable to have someone who, without your intervention, agrees with you 80 percent of the time. Then the 20 percent of the time that they don’t agree with you, that they’re right as often as not.

If it goes to 95 percent, then they’re a sycophant, and it’s probably bad. If it goes to 60 percent, well, then, you might as well do the work yourself. Figure out the people who will listen to you, but also challenge you at the right times.

It’s incredibly valuable to have someone who, without your intervention, agrees with you 80 percent of the time. Then the 20 percent of the time that they don’t agree with you, that they’re right as often as not. If it goes to 95 percent, then they’re a sycophant, and it’s probably bad. If it goes to 60 percent, well, then, you might as well do the work yourself. Figure out the people who will listen to you, but also challenge you at the right times.

COWEN: You mentioned food before. Let’s take a data intensive approach to food. You’re trying to find a good place to eat. What is the underrated statistic about a restaurant that you will consult or advocate others consult in this endeavor?

SILVER: This is a fairly basic one. But I’d rather look, if you’re looking at Yelp or TripAdvisor, the number of reviews is a better signal than the average star rating. Especially the number of reviews relative to how long a place has been open.

We’ve done some work on this, too, where when you’re drawing from a more diverse segment of people — there’s something I want to vent about how, like, every book on Amazon, in the long run, gravitates toward having four stars. A lot of 9/11 conspiracy books are rated pretty well on Amazon, because only the conspiracists bother to read them.

Whereas, Othello or Macbeth or something, everyone reads, a lot of kids have to read it for homework when they don’t want to, necessarily, so they’ll leave a bad review there, potentially. But I think that problem is more acute than people might realize when it comes to restaurants, where a place is notorious for drawing people who might not like that cuisine as much.

People also, when I go — and I used to do more Yelping and stuff like that — if I go to a mom-and-pop place in a small town somewhere and it’s not very good, there’s almost no way that I’m going to leave a negative review for that place.

I don’t want to hurt anyone’s feelings, I don’t want to — there’s actually studies showing that Yelp reviews can, like, a one-star Yelp review can cost like thousands of dollars in business for a restaurant that has under 50 reviews or something like that.

COWEN: In New York City, is there better food on the avenues or the streets?

SILVER: I read you on this. I think the — but New York is weird, because there are really, there are kind of three New Yorks from a culinary perspective. Right? There’s rich Michelin-starred New York, there’s kind of hip Soho and Williamsburg New York, and there’s ethnic New York, for lack of a better term.

Making sure that you have a mental list of places from all three types of those. There’s some rules that work well in one of those lanes that don’t work well in the others, necessarily.

In the very high-end restaurants of New York, it’s like so competitive that I think your rule about, order the weirdest thing on the menu, I think there are parts of New York where that probably isn’t true, because it’s so hyper competitive that the menu couldn’t afford to lead people astray.

Sometimes the thing that the menu is very clearly pointing you toward in New York is the kind of thing that you would want to order instead. That might not be true if you go out to Queens or something like that, where, frankly, pound for pound, probably the food is better than Manhattan or Brooklyn.

But yeah, you could write a whole book and maybe I will, especially if we have Trump win the election or something, maybe I’ll write a whole book about heuristics for eating food in New York.

COWEN: I said before and I’ll tell the whole crowd, one of my dreams is that someday you write the quantitative history of New York City. This would be one of my favorite books.

Question about the weather reporting. There’s some evidence that there’s what is called wet bias, so storms are over-forecast. Why is that? Is this even true?

SILVER: It’s true the further downstream you go, so the local meteorologist here in Virginia or in Washington on TV, they want to get higher ratings.

COWEN: They’re trying to scare us.

SILVER: They’re trying to scare you, yeah.

COWEN: It’s like they want the Iraq War, so to speak, so that people turn on CNN.

SILVER: The irony though is the data the government produces is very well calibrated and doesn’t really have a wet bias. There are a few individual like models for winter weather that do. But I don’t know, it’s been kind of interesting, in my shoes, going from someone who was a total outsider, to someone who has more reputational risk.

To a first approximation, I think it might make someone a worse forecaster, potentially.

By the way, another thing about the Trump thing I’ve been thinking about is — so my early view, that Trump had a very low chance — not zero, but very low — of winning the nomination was not based on any formal model, per se. I wonder what if I had even like a fairly bad model instead?

The good thing about building a statistical model is that it commits you to rules, right? Instead of just kind of saying, “Well, early polls aren’t very predictive and your prior is it currently probably won’t win, therefore, probably not.”

It pins you down and says, “Well, OK, early polls aren’t predictive, but at what point do they become more predictive?” When Trump went from being at 25 percent in the polls to 35 percent after Paris and San Bernardino, how significant is that?

To have an answer that is set up by an algorithm you designed ahead of time is actually maybe more helpful than people would think.

The long way of saying this is that I’m not sure that I’m any better than the average pundit unless I have a model. The disciplining effect of a model, doing your thinking in advance, and setting up rules of evidence is probably quite important.

The long way of saying this is that I’m not sure that I’m any better than the average pundit unless I have a model. The disciplining effect of a model, doing your thinking in advance, and setting up rules of evidence is probably quite important.

On why so few professional athletes have come out as gay

COWEN: I have a question about the economics and sociology of sports. This has puzzled me for a while. You may have thought about this. But I’m struck by the relatively small number of professional athletes who have come out as being gay.

In Hollywood it’s a lot of people, even in Washington, which is a very conservative town, I wouldn’t say it’s a lot of people, but it happens in a quiet kind of way.

In sports, why is there so little? If we applied some kind of economic or statistical model, in which sports would you expect to see the new breakthroughs coming when they come?

SILVER: I’m sure there are a lot of athletes in the closet. I don’t assume that it’s four or five percent or whatever the population average is. I assume it’s a fair amount lower than that, but I don’t know, I think people forget about how much the economics change when you’re talking about people who are in the 0.001 percent of something.

Where the fact that, until fairly recently, until maybe a few years ago, and in many parts of the country, obviously, still now. Until fairly recently, growing up gay is something that was, if not traumatic, at least required a lot of bandwidth, it requires a lot of energy.

Caren Louise Photographs

Because the fact that, for example, there’s data from Freakonomics about how hockey players who are born in January, just because they start a little bit earlier than their peer group, that’s a very powerful effect versus being born in November or December instead.

If something that minor can have that profound an effect, where I don’t know if it’s twice as many NHL players from January as December, then something as important to your identity as being gay in a society that until recently didn’t accept it, that’s a comparative disadvantage.

Maybe there are also correlations on what kinds of skills and traits people have, I don’t know, but we’ll see.

The prediction, if that theory is true, is that as it’s become more normalized, and now people who are growing up in middle school and high school where being gay is not as much of a disadvantage. Then you’d expect from that generation there to be substantially more gay athletes.

COWEN: In which sport will that happen first? What’s the implied prediction? We see a bit of it in women’s tennis, right?

SILVER: Women’s tennis.

COWEN: Individual sports, maybe, over team sports? Yes? No?

SILVER: Yeah, you would think that in tennis and golf you might see it first. The NBA, where talent is so manifest and one player can make so much difference. LeBron James could come out as gay tomorrow and I think it would not hurt his ability to get a max, max plus contract at all.

COWEN: But it could hurt endorsements.

SILVER: It could hurt endorsements. He is kind of a high default, but I don’t know. I think it’s no longer about kind of the marketing side of it so much as the fact that it just kind of — sports is still a very conformist culture. Some of the reason I might say the NBA is I think it’s a little bit more individualistic as a culture. Guys are free to express themselves more.

Listen to baseball players talk. They’re boring as hell. Right? Kevin Durant or something, these guys are smart and they’re interesting to listen to.

COWEN: Kareem Abdul-Jabbar, right?

SILVER: Kareem Abdul-Jabbar.

COWEN: Yeah.

SILVER: So I would think basketball might be a sport where you’d see it relatively soon.

On forecasting

COWEN: Let me ask you a general question about forecasting, and I worry about this in the context of finance. I see a lot of money managers, so there’s Ray Dalio at Bridgewater. He saw one basic point about real interest rates, made billions off of that over a great run. Now it’s not obvious he and his team knew any better than anyone else.

Peter Lynch, he had fantastic insights into consumer products. Use stuff, see how you like it, buy that stock. He believed that in an age when consumer product stocks were taking off.

Warren Buffett, a certain kind of value investing. Worked great for a while, no big success, a lot of big failures in recent times.

Is it possible the so-called true model is always shifting, and there’s a kind of selection bias where different forecasters are elevated and they have their run for three, five, however many years? Then the true model shifts and what they’re good at isn’t valued. We turn them over and replace them with other forecasters.

As, like, our best forecaster, do you worry about this?

SILVER: Sure. Even if you are skeptical about the efficiency of markets, if you have a great gig and you’re picking up hundred dollar bills off the ground, then boy if you can extend that by three or five years without adapting and evolving, that’s on the extreme high end I think. Three or five years is a very long and fortunate run.

That’s part of why even though now we’re very immersed in the election cycle, it’s part of why I wanted to make sure that FiveThirtyEight was not just an election site. We’re going to blow an election sooner or later. We might blow this one. To be doing a whole diverse array of things both intellectually and commercially is important.

The follow-up to that is, “Are there people who have the skills to find the next underweighted opportunity?” Maybe, that’s trickier. I think a lot of people have one or two really good insights, and if you’re very lucky that can take you a long way.

COWEN: Here’s a related worry. It’s clear in the data, stock market volatility is correlated with itself over time. If you have some volatile days, you’re likely to get more. That’s pretty clear. That’s another way to say those returns, for a while, are hard to forecast and stay hard.

This year politically, it’s already a big surprise to me, to a lot of people. Could it be the case we’re entering a new era where political volatility is higher and basically all forecasters will just do much worse than they have been doing?

SILVER: It’s possible. Again, I go back in saying what people take to be the equilibrium baseline condition may actually have been an outlier, instead. You have this relatively stable, long boom politics and economics from the ’50s to the ’90s or the early 2000s, thereabouts, and that could potentially reverse itself.

Again, looking at examples outside of the United States I think is instructive. Maybe I’m more of a believer in American exceptionalism than I thought. You see constituencies that are Trumpian in different parts of Europe and have been extant for a long time, so maybe America just got really lucky for 50 years.

Maybe I’m more of a believer in American exceptionalism than I thought. You see constituencies that are Trumpian in different parts of Europe and have been extant for a long time, so maybe America just got really lucky for 50 years.

COWEN: Nassim Taleb has a hypothesis that, in some ways, the world is getting weirder. There’s the example of plane crashes. Planes used to crash a lot for pretty normal reasons. The engine would fall apart. Obviously, we invested more resources in making planes safer.

I just read in the Wall Street Journal last year, there were actually zero deaths from jetliner crashes other than terror attacks. We have strange events like the Germanwings pilot flying into the Alps. Malaysian Air disappears, no one knows why. The events people talk about, we’re left with only the weird ones.

Do you think we’re headed toward a future where we’re only going to be talking about weird, very hard to forecast events, precisely because we get good at avoiding a lot of problems and mistakes?

SILVER: For sure. There’s some stupid metaphor I use in the book, where one of the problems with comparing how shortstops play for example, is that you always evaluate players who are on the edge of their range. Can they make the spectacular diving catch?

To the first approximation, everyone is equally good at the edge of their range. The question is how much territory do they cover in between the nonspectacular plays, that we can miss potentially? It’s probably more true — one reason why I like when we forecast sports, is you have a chance to build up your sample size.

A perfectly routine Wizards versus Cavaliers game, where we have the Cavs favorite at home and they win, that counts. You get hundreds and hundreds of those on the course of the season, whereas in politics you’re more drawn to the spectacular and the weird events.

A lot of models are good heuristics, when conditions are fairly normal. They don’t deal all that well with the edge cases, because they’re fully designed, or because you have nonlinearity, or because they have small sample sizes, or whatever else. How well do models deal with the weird cases versus other types of heuristics, I’m not sure. Maybe the advantage is more in the baseline cases instead.

COWEN: Other than skilled with data, what are the personal qualities of good predictors?

SILVER: You have to have a certain mistrust of conventional wisdom, and that’s a tricky thing. On the one hand we know that I’m not that smart, that this room is way way way way smarter than me, and a market is way way way way smarter than me. At the same time people are social beings, and they behave in herds sometimes.

This is easier in politics than almost any other field, because the political press corps literally is kind of a herd. It’s the perfect example of it. You have a few hundred journalists who travel around together, who are all reading one another on Twitter, who are all talking to one another.

It’s not 500 really smart people. It’s one or two really smart people, and 489 followers instead. I don’t know. We get ourselves in a little bit of trouble I think at FiveThirtyEight at times, because we are fairly combative. For a long time I thought, “Well this is kind of part of my personality, and the kind of more happy warrior data side is more part of it too.”

They’re actually kind of sides of the same coin. When you read the New York Times or the Post, not basic factual statements where they say, “Today, Donald Trump was in Arizona,” but when there’s a piece of analysis that isn’t necessarily obvious, to say, “Boy, there might be a 40 percent chance that that’s basically wrong.”

That leaves you in a weird place kind of. But to believe that is, I think, the source of a lot of the healthy skepticism that we have and also some of our failings sometimes.

COWEN: Now let me get to the question that maybe the crowd most wants to hear. Who will be the next president of the United Arab Emirates?

[laughter]

Now this is a trick question because it’s a hereditary monarchy, but here’s my background question. Intelligence agencies and scholars did very poorly forecasting the Arab Spring and did very poorly forecasting ISIS.

So you’re put on the case, someone from Washington, McLean, wherever. They call you in. They say, “What variables should we be looking at to understand the Middle East that we’re underweighting right now?”

I know it’s a tough question, but who will be the next president of the United Arab Emirates? Will there be a next president? How do you think about what’s happening there? Black swans or a regularized process?

SILVER: We have all certain compromises. I don’t know that much about international politics, even enough to have fun sitting like this to speculate all that much. I flew via Emirates Airlines. It’s the extent of my knowledge about the UAE pretty much. [laughs]

COWEN: Not this election cycle but four more years out, this nation, what’s your best pick for who will be elected president?

SILVER: Who will be president in 2020?

COWEN: Correct.

SILVER: I mean the boring pick is probably Hillary Clinton still.

COWEN: Number two, next best pick?

SILVER: I think it’s close between Donald Trump and Marco Rubio. [laughs] Although I think Trump might be a one-termer.

COWEN: If that.

[laughter]

COWEN: Who is the most likely next vice president?

SILVER: John Kasich maybe seems tailor-made for the vice presidential role.

COWEN: Even if you think Hillary is more likely to win, he may be the single individual most likely to be the next vice president. Is that the right way to frame it?

SILVER: I think that might be. Hillary has a very long list to pick from and a lot of tactical objectives that she would want to fulfill. I think it’s probably a shorter list for the GOP.

On Supreme Court picks and vacation tips

COWEN: Can we apply data analysis to figure out the next Supreme Court pick — again not to know who it will be but to get that 52 percent edge up on what other people are thinking?

SILVER: Potentially. There are some fledgling attempts at Supreme Court analytics although this is also a case where we’re in a sample size of zero, where you have a nominee who’s very unlikely to be confirmed but there’s still high political stakes. My uninformed guess would be maybe Srinivasan who was confirmed 97 to nothing.

Caren Louise Photographs

I would tend to think that — my hunch and this is just a hunch, the theory is that either Obama nominates someone with unimpeachable credentials and makes Republicans look very unreasonable or he makes a pick that trolls Republicans and plays to Democratic base.

I’m more of a believer in the former as Obama’s mode of doing things. I think he’d push things in their way and have someone who might just be at the risk of pissing off the liberal base, but the Republicans have to look ridiculous opposing, as opposed to the other way around.

COWEN: Now my last question before we get to the crowd. As you said before, we have a lot of same interests, food, travel, sports, not sure if politics counts as one of mine but in a broad sense politics. You’ve taken a lot of trips, some for work, some vacation.

If you apply data analysis to those trips, what do you learn about what makes for a good trip and what can you do or what can we all do to have better trips?

SILVER: I just love travel so much. I had an unintended experiment where I went to Hawaii for, I guess, two Christmases ago. For some reason I sat on my phone and my phone didn’t work. We were flying through Portland for some reason or flying New York to Kansas City to Portland to Honolulu, don’t ask why. But the day I was in Portland, I was panicked.

We drove, we got to this strip mall on the edge of town and they’re like, “You have to wait in line two hours for us to replace your phone.” So I didn’t have a phone in Hawaii, and it was the most amazing thing pretty much.

[laughter]

COWEN: You’ve repeated that experience each subsequent trip.

SILVER: No.

[laughter]

SILVER: But no. I was in Thailand, by contrast, this Christmas, and I had to build the goddamn primaries election model, and so yeah, your enjoyment goes down a lot. A little bit of work, working 20 percent of the time, I think reduces your enjoyment by 70 percent.

Q&A

AUDIENCE MEMBER: Hi, my name is Caleb. We talked a little bit earlier about superforecasters, and I was wondering if you’ve ever considered incorporating the work of superforecasters into FiveThirtyEight?

SILVER: You mean literally the guys who wrote the book, or?

AUDIENCE MEMBER: Or getting a market of superforecasters to help you make your models better.

SILVER: I guess I find crowdsourcing sort of boring. As a journalist, I find it boring. Even though if you’re in a business setting, that’s exactly what you should do.

We actually are doing that a little bit with the Oscars this year. We found eight different people who created different models, and we’re seeing how well they do. Of course six awards is not anywhere near a sufficient sample size to deal with something like that.

I don’t know. I’m very process-driven as a person. For me, a lot of the joy is in thinking through the process of it, so reading a book like this is really useful, because I talk about a process I think is pretty great. But to actually publish the projections, in some sense, is almost beside the point, in the sense that you’re still probably dealing with sample sizes that are too small to really tell you all that much.

When you start to do that, then I think it takes folks away from thinking about process and heuristics for forecasting. That’s kind of an unsatisfying answer, I guess.

COWEN: We’ve printed out a lot of Nate’s columns. Many of them are here, so there’s plenty you can ask about. Next question.

AUDIENCE MEMBER: Hi. I’m Michael Willie, thanks for coming. If it winds up being Clinton versus Trump, is that the first time where we’ve had two candidates with the highest unfavorables going against each other?

SILVER: Yeah, I would think so. There have been a few candidates — I think Romney was basically breakeven when he was nominated, as Obama was, but Clinton is negative 10, and Trump is negative 25, or something. There probably will be some reversion to the mean in both cases.

Remember, one reason why — and I’d say Trump’s a fairly heavy underdog if he wins the nomination. But it’s a conditional probability. Conditional on having won the GOP nomination, Trump will have had to display some staying power, some acumen, because sooner or later he will have to get beyond 35 percent to win 50 percent or so, and probably will have done something to improve his image with people who are not in his core constituency.

But yeah, it would be pretty unprecedented, certainly. I wonder if you have to adjust — in baseball, you have to adjust stats for the era, where if you’re in the home run or steroid era, then 50 home runs doesn’t matter as much. Maybe now, Obama with a 48 percent approval rating, is at a 56 park-adjusted approval rating. I’m not sure, maybe.

[laughter]

COWEN: Next question.

AUDIENCE MEMBER: Hi. My name’s Tom. Earlier, Tyler brought up the question, “How much data do people want?” A two-part question. Does the amount of data that people want, is that influenced by the way data is presented? The second part would be, what advice would you give as far as presenting data, or visualizing it?

SILVER: Visualizing it might be some of the advice. People seem to learn a lot better from visualization. One thing I think a lot about as a journalist is preferring simple models to more complicated models. There are other virtues of simple models. People can also take it too far.

But as a journalist, for example, to have something I can say this is a benchmark, and I understand what it’s doing, and I can explain what it’s doing, and I can also understand what the limitations of it might be, and so I know which direction to lean relative to that baseline. It’s more useful than a place where you just say, “Well, we fed some data into a random number generator, or a magic machine, and here’s what it spit out.”

For example, I highly prefer — this is going off on a tangent — but I prefer regression-based modeling to machine learning, where you can’t really explain anything. To me, the whole value is in the explanation. But I do think likewise, people, when you explain it and say, “Hey, we probably have the same interests here in mind,” to say this is actually pretty simple once you start peeling away the BS.

To me, that approach works a lot better in the long run than the approach of saying, arguments from authority, “Well, this is rigorous, and empirical, and objective, so therefore believe the numbers.” I think explaining to people why it’s actually not all that complicated, and why you’re making very defensible assumptions how that leads you to an answer that might surprise them.

COWEN: Next question.

AUDIENCE MEMBER: Frank Manheim, School of Policy. Could you put some numbers on the criteria that the median voter would use in the United States to elect major politicians, like president? For example, emotions, personal acquaintance, rational concepts, information, and so on?

SILVER: The classic political science answer is that people are deeply concerned about the economy, and that the economy makes up 50 percent or so of what people vote about. There’s room to dispute that. There’s esoteric critiques that maybe these models are overfit. But leaving that aside for now.

One of the reasons why I was initially skeptical about Trump is that America has a history of not nominating candidates, and electing candidates, rightly, who are blatantly unfit for office.

[laughter]

COWEN: I have a softball follow-up question to that.

[laughter]

COWEN: We’re in the state of Virginia. To the best of my knowledge, you’re the only person to have calculated correctly, what is the chance if you are a voter in the state of Virginia, that your vote will sway a presidential election?

SILVER: It was pretty high. I think it was — oh, as an individual voter?

COWEN: Individual voter. What’s the chance that your vote in the state of Virginia will matter? If you don’t remember, I do, but it’s from your paper.

SILVER: It’s like 10 percent divided by 4 million or something?

COWEN: It’s 1 out of 10 million, the highest of any state. So if you’re going to vote anywhere, vote here.

[laughter]

COWEN: Next question.

AUDIENCE MEMBER: Hi, Tyler O’Neil, a reporter with PJ Media. My question is, you mentioned how difficult it is, the weakness of empirical models when predicting presidential elections. Is it possible to look at congressional elections, House of Representatives races, and draw more information in modeling from those?

SILVER: Yeah, I think we would say that even though it’s less sexy to predict Senate races or congressional races that having larger quasi-independent samples, that would be the better test, ultimately. Although even there, the errors — so we saw in the Senate races last year how the polls were off, on average, by three or four points, which is pretty bad. It’s happened before.

The problem is that all those errors were in the same direction, so Republicans won when a lot of races around the country that they were underdogs in — not huge underdogs, except Virginia was almost a major upset. But yeah, it’s a much purer form of the exercise to do data mining on congressional elections and weighing polls versus fundamentals and whatever else.

COWEN: Next question.

AUDIENCE MEMBER: Hi. My name’s Harold Walbert. You mentioned some things like limited data, limited observations, nonlinearity, and things of that nature that make traditional tools like statistics and econometrics difficult.

What are your thoughts on more computationally intensive methods like agent-based modeling for dealing with these things, like you mentioned herd behavior, that make some of these analyses more difficult?

SILVER: Agent-based modeling is interesting, and there is some, if you can simulate the underlying mechanisms. This is how weather forecasting works, by the way, is that weather forecasting is not particularly statistically-driven as we would think of it. They actually are creating a physical model of the atmosphere which they are resolving mathematically.

If you have reason to know exactly how certain people would behave and how they behave as a system, then agent-based modeling could give you insights you couldn’t get from regression analysis.

On the other hand, if you’re somewhat wrong about those assumptions, then the things could go very haywire in a hurry. When I’m building models myself now, I spend a lot more time thinking about the edge cases, say, let’s put some really weird inputs in here that are on the edge of plausible, and see how the model responds to those.

Maybe you have a function that’s approximately linear, but can’t be at the edge case. It would say that, for example, if you have a model saying that Hillary Clinton will get 106 percent of the vote in Washington, DC, or something, against Trump, I used to think, “Well, who really cares? She’s going to win DC anyway.”

COWEN: She may. [laughs]

SILVER: She may, right? You can vote twice in some parts of DC.

[laughter]

SILVER: But now, that bothers me more, so I’m trying to think more about the correct functional form of a model that would apply when the going gets weird, because when the going gets weird is when things are interesting, anyway.

COWEN: We have four minutes left. Next question.

AUDIENCE MEMBER: I’m Holly Richard. I’m an intern at the House of Representatives. Do you believe Facebook and Twitter, where people create their own newsfeed, has led to possibly confirmation bias, and has led to people choosing more extreme views of political ideologies such as socialism, nationalism, Marxism?

SILVER: Perhaps. Though I would also say that the traditional two-dimensional political spectrum is a strange and contrived thing, too. It’s the result of a very messy process of coalition building between parties.

I mentioned reasons to be pessimistic earlier. A reason to be optimistic as a fan of democracy is that you are seeing voice given to quirkier ideologies that are no less intellectually coherent in the kind of Democratic versus Republican axis that we have in the United States.

I believe in the notion of a filter bubble, where people surround themselves where they’re getting like information and not confronting themselves with unpleasant facts, necessarily. You saw that a lot during the 2012 election, where the polling was a lot more straightforward than it is this time around, and people still were cherry-picking data to tell themselves that Romney might win.

You saw Democrats doing the reverse, by the way, in the 2014 midterms, more or less. But yeah, as someone who’s a critic of media, I think the way people consume media is important, and has probably fairly large effects on our politics.

COWEN: Last question.

AUDIENCE MEMBER: Hi, Mike Bliley. I’m a law student here, and I get my coverage of the election exclusively from FiveThirtyEight.

[laughter]

AUDIENCE MEMBER: I do that largely because of the unbiased nature, except for Harry’s unabashed love for Chris Christie.

[laughter]

AUDIENCE MEMBER: I noticed that specifically in your debate coverage, one of the things that you all always mention is that the mainstream media’s portrayal of the debate matters more than anything else. When they say that someone wins, that coverage carries, and then at the end of those pieces, you and your staff put together grades for how the candidates did.

You may see where I’m going with this. You strike me as someone who would rather predict rather than influence, but do you see yourself playing into this zeitgeist where you could carry some weight in this election?

SILVER: That’s why the primaries, although they’re fun, are a little tricky. The general election people are fairly sensible and retreat to their corners, but the primaries are so momentum-driven, that it’s a little bit weird. I’m sure people do read what we say and so forth. It’s not the type of influence that I want.

At the same time, the fact is that all news coverage is influential, and I would say at the very least, we promise some self-awareness, that we’re aware that the way the events are covered by the press can affect voters’ views. Sometimes the press can be surprised that it doesn’t go the way they expect, but you can have these big feedback loops.

I’m surprised how difficult it is. I think one big edge we have — I’m glad that you read us — but I think one big edge we have over, say, the New York Times or something is that we can talk about the media as a political actor.

We are the media, too, and so I’m aware of the circularity of that. Frankly, I think one reason why during the primaries sometimes the conservative sites are more interesting to me than liberal sites, is that they also start off being more suspicious of the media, sometimes in ways that I think are wrong, like about the polls in 2012.

But I think having that skepticism and seeing the media as a political actor instead of a benevolent umpire is to a first approximation the right way to do things, and that’s reflected in our coverage, I guess sometimes at the risk of being a little bit hypocritical, potentially.

We do try and be very transparent about what we think is a fact, what’s an opinion, what’s an analysis, what is a provocation. One reason why I like your blog is that you have a lot of provocations. Sometimes you put the Tyrone label on it, but it’s clear what they are. It’s clear that they’re provocations meant to incite discussion and debate, and so we’ll have a few of those, too, at times.

Speaking in the first person, I think, is important, and breaking from the voice of God where “A storm cloud gathered on New Hampshire today, and the voters decided that — .” Speaking as a subjective individual trying to understand what the objective world is like is a lot of what we’re all about.

It’s not for everyone, but I think that should be reflected at least in the tone and approach of our coverage, even where we wind up getting things wrong in the end.

COWEN: Here’s Nate’s book. Read Nate’s site. Nate, thank you for a great chat.

SILVER: Thank you.