Speaker 1: Pushkin. Welcome back to Risky Business, our show about making
Speaker 1: better decisions. I'm Maria Kanikova.
Speaker 2: And I'm Nate Silver.
Speaker 1: So today, Yeah, Nate, I.
Speaker 2: Think I think so much better at the intros, in
Speaker 2: the positions, and now we're reverting me. It's been a
Speaker 2: couple of weeks since we've had like a normal episode.
Speaker 1: That's true, it's true. It's good to see you. You
Speaker 1: are in Jackson Hole.
Speaker 2: Yeah, Jackson Hole, Wyoming, a very you know, God's country
Speaker 2: as they might call it, and that is very pretty.
Speaker 1: Yes, and so it's actually quite appropriate. I'm back in
Speaker 1: New York City, So we're in two different parts of
Speaker 1: the country to discuss something that hopefully will help unite
Speaker 1: those different parts of the country, the presidential debate from
Speaker 1: last night. So we are recording this the morning of Wednesday,
Speaker 1: September eleventh. So last night you and I both were
Speaker 1: listening to the debate from our respective different parts of
Speaker 1: the country, and Kamala Harris tried to make her appeal
Speaker 1: to both of us, right to all Americans all over
Speaker 1: the country. So what'd you think, Nate.
Speaker 2: You know, I'm here in Teaton County. Well, actually it's
Speaker 2: the one blue County in all of Wyoming.
Speaker 1: Yeah, I love your voices. I love your voice.
Speaker 2: I thought Kamala Harris had an excellent debate, or maybe
Speaker 2: maybe I think subtly more that former President Trump had
Speaker 2: a really bad debate, playing into basically every critique that
Speaker 2: you might have of Donald Trump, the fact that repeatedly
Speaker 2: she was able to tease them about his rally crowd
Speaker 2: sizes and things like that, and how foreign leaders don't
Speaker 2: really respect him, and every single time he took the
Speaker 2: bait and got distracted and had these long two minute
Speaker 2: segments with no mics off, no interruption, and would spend
Speaker 2: the first minute complaining about whatever Kamala said, and then
Speaker 2: the next thirty seconds with a coherent point, and then
Speaker 2: veering off in some other random direction for another thirty seconds.
Speaker 2: A lot of talk about things like a reference to
Speaker 2: if you're not really into politics, this will sound bizarre
Speaker 2: because it is, but Haitian immigrants, oh.
Speaker 1: My god, yes, in.
Speaker 2: Ohio killing dogs and cats, you know, talking about Sean
Speaker 2: Hanny and Laura Ingram and like just kind of not
Speaker 2: really able to escape the fact that he's trying to
Speaker 2: persuade over this tiny fraction five percent of the country
Speaker 2: that is still undecided.
Speaker 1: Yeah, can we just pause for a second. Not just
Speaker 1: killing dogs and cats, but eating them, eating them. And
Speaker 1: this is a conspiracy theory that came from like the
Speaker 1: deep bowels of conspiracy theoryedom and here we have the
Speaker 1: former president just like losing it and completely, you know,
Speaker 1: just going off on this. He was actually fact chucked
Speaker 1: on this by the moderators during the debate, which they
Speaker 1: did a few times, which was new, right, they haven't
Speaker 1: done that before, where they said, you know, actually there's
Speaker 1: zero evidence of this. But he just didn't know where
Speaker 1: to go. I think, you know, I was worried, you know,
Speaker 1: going into this debate. I thought it could go a
Speaker 1: lot of different ways, and I was just hoping that
Speaker 1: she wouldn't let him get to her right because as
Speaker 1: a female also, the risk is so much bigger because
Speaker 1: if she starts feeling defensive or indignant or anything, you know,
Speaker 1: because she's female, it's going to come off a lot
Speaker 1: worse and it's going to just completely blow up. She
Speaker 1: did not, and it was actually the other way around
Speaker 1: where she was able to kind of just needle him,
Speaker 1: and he every single time squandered most of his airtime
Speaker 1: in responding to the needles as opposed to saying anything substantive,
Speaker 1: which I think was the entire point.
Speaker 2: Yeah, she is very different about gender issues tactically than
Speaker 2: Hillary Clinton was, and to my male eye, more effect
Speaker 2: I think in part by like sometimes jabbing. In poker terms,
Speaker 2: we might call it. This is probably too esoteric. A
Speaker 2: donk bet donk bet is when you unexpectedly lead with
Speaker 2: a bet into the person that you're expecting to bet right, donk,
Speaker 2: di O, and k. A donkey in poker is a
Speaker 2: name for a bad player. A fish donk is a
Speaker 2: shortening of donkey. So this was thought to be a
Speaker 2: play that a bad player makes it doesn't know to
Speaker 2: check to the person who made the last bet. It
Speaker 2: turns out that and the fancy computer simulations you're supposd
Speaker 2: to this sometimes but can also be a way to
Speaker 2: exploit somebody, to get under their skin. And it can
Speaker 2: I'm not gonna talk about the game theory here, but
Speaker 2: it can throw them off rhythm. Sometimes it is correct
Speaker 2: actually under game theory, but it's a way to take
Speaker 2: charge of the hand. And she did that a couple
Speaker 2: of times, like kind of premptively saying, Hey, Trump's going
Speaker 2: to lie a lot, you know, even on issues that
Speaker 2: would seem like relative weaknesses for her, like, for example,
Speaker 2: the unpopularity of President Biden in the fact that she's
Speaker 2: been the vice president for three and a half years.
Speaker 2: She would say, by the way, I'm not Joe Biden,
Speaker 2: and like actually lean into that. And I think she
Speaker 2: was well prepared for this event. And I don't know
Speaker 2: to what extent that credit goes to her versus her campaign.
Speaker 2: The Democrats to have a lot of data. I mean,
Speaker 2: Donald Trump has had one, two, three, four or five.
Speaker 2: This is his seventh general election debate, and he doesn't
Speaker 2: really change form that much, except in the Biden debate,
Speaker 2: where Biden was so bad that some instinctual part of
Speaker 2: Trump knew that you have to maybe not go for
Speaker 2: the jugular that much. Although Trump was actually kind of
Speaker 2: bad in that debate too, it's just that when Biden.
Speaker 1: In comparison, he was he was fine.
Speaker 2: Yeah, but you know, Biden couldn't like nail him on
Speaker 2: the things he were saying that were very very false
Speaker 2: and or crazy. So I mean, first of all, if
Speaker 2: nothing else, if Harris loses and we'll talk about this
Speaker 2: in a minute, probably still in the vicinity of fifty
Speaker 2: to fifty. If nothing else, you have this a b
Speaker 2: test where replacing Joe Biden with Kamal Harris was a
Speaker 2: really good idea.
Speaker 1: Yeah, and I actually think your dunk bet analogy is
Speaker 1: really really a good one. First of all, just talking
Speaker 1: from personal experience. The first, you know, I've actually let
Speaker 1: people get under my skin doing that, you know, because
Speaker 1: it's so it's unexpected, and the attitude is, you know,
Speaker 1: you check to the pre flop aggressor, right, so the
Speaker 1: person who has them, has the aggressive lead, is supposed
Speaker 1: to be allowed to continue that aggression. And there have
Speaker 1: been a few times I even remember when I've made
Speaker 1: big mistakes and hands because someone has donked it to me,
Speaker 1: and I'm like, no, you fucker, you don't get to
Speaker 1: do that, and I raise, which is exactly what I
Speaker 1: shouldn't be doing in some specific scenarios where they actually,
Speaker 1: like clearly are donk betting because they have something. And
Speaker 1: I remember those hands vividly because it's very unlike me
Speaker 1: to to start tilting in that particular way. I've gotten
Speaker 1: over it now, but it's actually, you know, it can
Speaker 1: be a very effective strategy. And she did that. There
Speaker 1: was actually one time where at first I was like, wait,
Speaker 1: what the hell did she just do? And then I
Speaker 1: realized what she was doing right when she was answering
Speaker 1: a question and all of a sudden she says, by
Speaker 1: the way, you know, I invite you to go to
Speaker 1: Donald Trump's rallies. And I'm like, wait, you know what
Speaker 1: a non sequort or what did she Why is she
Speaker 1: doing that? And then it became very clear was a
Speaker 1: very good strategic move because she was kind of deflecting
Speaker 1: away from her record on something that she didn't really
Speaker 1: want to talk about, and instead then Trump kept, you know,
Speaker 1: for the next two minutes talking about how he has
Speaker 1: the biggest rallies in history.
Speaker 2: Yeah, and she is taking some I mean, she is
Speaker 2: veering off topic, and she often did it on questions
Speaker 2: like immigration that are not great topics for her. Yeah,
Speaker 2: And if Trump had responded coherently and not taken the bait,
Speaker 2: then you'd have his media buzz about how she went
Speaker 2: really off topic and was evasive, right, And instead he's
Speaker 2: more often absolutely absolutely.
Speaker 1: But yes, I actually thought, you know, it was it
Speaker 1: was quite funny because I was like, oh, you know,
Speaker 1: she's learned to play the game of not answering the question,
Speaker 1: because Donald Trump never answers the question. And as the
Speaker 1: debate went on, she was doing the exact same thing,
Speaker 1: and I'm like, huh, okay, well you know what that's
Speaker 1: I guess how these debates go. But she she definitely
Speaker 1: learned to play that game, and I actually thought she
Speaker 1: became much stronger as a night war on. I was
Speaker 1: very nervous when she started giving her first response, because
Speaker 1: you could tell she was nervous, you know, as someone
Speaker 1: who has done public speaking, who's kind of watched a
Speaker 1: lot of debaters, you know, you and I were both
Speaker 1: debaters all through school. You could tell, like the first
Speaker 1: few minutes, you know, she was nervous and she was
Speaker 1: a little stiff. But then she kind of got over it,
Speaker 1: and I think she kind of became much more fluid
Speaker 1: and really kind of picked up in style. And I
Speaker 1: was very happy to see that. And he had kind
Speaker 1: of some of the opposite trajectory where kind of he
Speaker 1: started off thinking that, you know, I'm gonna just completely
Speaker 1: demolish her, and then he started getting very defensive.
Speaker 2: Yeah, public speaking for me, at least, I don't know
Speaker 2: if you're different, Maria, but like it's not It isn't
Speaker 2: actually like just having a conversation with a friend at
Speaker 2: a bar that your body recognizes that this is a
Speaker 2: high stakes momentolutely and you're operating under a elevated person
Speaker 2: but also a stress response. Now, in my experience, what
Speaker 2: you have to do is just kind of be a
Speaker 2: little bit self conscious about it. Right, You're like, I
Speaker 2: am on terrain that I either rehearsed or that I've
Speaker 2: spoken about many times, and I'm just gonna say words
Speaker 2: and lo and behold, they come across coherent most of
Speaker 2: the time. If you're tired or fatigued, or or you're
Speaker 2: in a room where the setting is weird, the lighting is,
Speaker 2: you can be thrown off and that can be hard
Speaker 2: to recover from. But you have to like you can't
Speaker 2: overthink it too much, and you have to trust your
Speaker 2: experience base that like, yeah, this is actually gonna go fine,
Speaker 2: and some people are even better in that setting than
Speaker 2: they would be a meeting or something.
Speaker 1: Yeah, I think that's absolutely true. And I actually have
Speaker 1: a stress response every single time I give a talk
Speaker 1: right before I go on stage every single time, and
Speaker 1: I give lots of talks. So this is something that
Speaker 1: that definitely happens. But then you know, you could you
Speaker 1: could tell that she does have the experience, she was prepared,
Speaker 1: and she was able to kind of establish the momentum.
Speaker 1: The other thing that I thought was very interesting was,
Speaker 1: you know, Trump won the coin toss and decided that
Speaker 1: he was going to give the closing, you know, the
Speaker 1: final closing, and I actually think that that worked against him,
Speaker 1: because he spent most of his closing remarks yelling at
Speaker 1: what she said, as opposed to kind of giving any
Speaker 1: summary of anything that he had said. So so I think
Speaker 1: that she came across much better at the end of
Speaker 1: the debate. And the way that you know, impressions and
Speaker 1: memory formation works, I think that that really works in
Speaker 1: her favor.
Speaker 2: And the beginning too. I mean, in the beginning, I
Speaker 2: agreed at the very first question on the economy is
Speaker 2: strong territory for Trump. But then you have extended remarks
Speaker 2: on abortion for a moment, I thought that might be
Speaker 2: the story of the night. And then you have which is,
Speaker 2: by the way, if you're not a very good issue
Speaker 2: for Democrats.
Speaker 1: Since she did very well, she did very well Onlke Biden,
Speaker 1: who kind of you know, pivoted to immigration instead of
Speaker 1: talking about abortion. She really nailed the abortion.
Speaker 2: And then you have the bait taking phase. I mean, look,
Speaker 2: we may look back if Harris wins and say that
Speaker 2: the Trump can made a series of really predictable mistakes.
Speaker 2: The lack of preparation tonight were even in the closing statement.
Speaker 2: He can't really stay on focus and talk about Harris's record,
Speaker 2: for example, I mean other things too. I mean, naming
Speaker 2: Jadie Vance is one. Not preparing for the transition from
Speaker 2: Biden to Harris when they had been telegraphed at least
Speaker 2: for a few weeks as a possibility, a strong possibility.
Speaker 2: His convention speech where he rambled off topic after a
Speaker 2: more subdued thirty minutes on the assassination attempt, you know,
Speaker 2: frankly accepting that first debate with Biden. I mean, I
Speaker 2: guess you may not have played out all the tactics,
Speaker 2: but if he hadn't done that, then Biden's on stage
Speaker 2: tonight having that debate from June tonight, and Democrats are
Speaker 2: appropriately panicking because they're probably totally fucked at that point.
Speaker 2: So thanks to the White House for moving that forward.
Speaker 2: If you're a Democrat, I guess yeah, for sure. By
Speaker 2: the way, did you notice that he did not call
Speaker 2: her by her name a single time during the night.
Speaker 2: He kept saying she and pointing at her, and he
Speaker 2: never said vice President Harris. He never said Kamala Harris.
Speaker 2: He used her name exactly zero times. I've actually haven't
Speaker 2: seen anyone mention that, But that's something that really struck
Speaker 2: me and kind of shows how, you know, it shows
Speaker 2: you so much about his attitude about kind of his
Speaker 2: conception of women, his conception of her. You know, she's
Speaker 2: not even worthy of calling by the name. Because I
Speaker 2: was I was actually paying attention to it because I
Speaker 2: was wondering if he was going to mispronounce her name
Speaker 2: on purpose the way he's always done, and what her
Speaker 2: reaction was going to be.
Speaker 1: But he didn't. He didn't even say her name. So
Speaker 1: I thought that that was something that was an interesting point,
Speaker 1: and I thought that she tried to do a really
Speaker 1: she tried to do a nice job since she was
Speaker 1: in Pennsylvania of talking about the fact that she wasn't
Speaker 1: going to stop fracking and that she, you know, was
Speaker 1: upping well production in all of these things. And it's
Speaker 1: a very fine line for her to walk right to
Speaker 1: try to say, you know, I want a green future.
Speaker 1: I'm worried about climate change, but believe me, I'm not
Speaker 1: going to hurt your jobs. So I think that she
Speaker 1: tried her best to appeal to Pennsylvania, which is obviously crucial, and.
Speaker 2: She is flip flopping on a lot of this stuff.
Speaker 2: So there's a lot of fertile ground that Trump could
Speaker 2: what's the metaphere they could have trod or I'm not
Speaker 2: sure what their metaphor is exactly. Yep. And again the
Speaker 2: lack of discipline from Trump, you know, just to say
Speaker 2: she's a radical left winger, as she showed in San
Speaker 2: Francisco and in twenty nineteen when she wanted to do
Speaker 2: X and Y and Z, and now she's flip flopping
Speaker 2: because she's desperate to, you know, make up for Joe
Speaker 2: Biden's mistakes. You can do a fair amount of that.
Speaker 2: I do think that's an issue for Harris with some voters.
Speaker 2: But look, they got another data point. So the convention,
Speaker 2: we can talk about the trajectory of the horse race.
Speaker 2: Maybe in a moment. I thought she gave a very
Speaker 2: good convention speech. Also that was also kind of agro
Speaker 2: and aimed at male voters. And she 's some of
Speaker 2: these same themes tonight, talking about competitiveness with China, talking
Speaker 2: about how aggressive and lethal our military is. For instance,
Speaker 2: sometimes when you hear something for the second time, it
Speaker 2: closes a deal, right, you know, So obviously there's some
Speaker 2: chance that there's a bounce in the polls Harris, by
Speaker 2: the way, so we're not just totally giving you our
Speaker 2: subjective opinion. In the CNN post debate poll, she won
Speaker 2: sixty three thirty seven or something, and Market.
Speaker 1: As well also had her her odds going up, So
Speaker 1: I think that that is also I think by three points, right,
Speaker 1: she moved up by thy point.
Speaker 2: Before the debate, it had been like Trump fifty four,
Speaker 2: Harris forty six. These are not vote shares, these are
Speaker 2: win probabilities, and after it's fifty to fifty technically forty
Speaker 2: nine forty nine, they price in some chance that I
Speaker 2: don't know, somebody has to drop out due to a
Speaker 2: health issue, I guess, But basically drew the race back
Speaker 2: to even. In the Silver Bulletin forecast, she had been
Speaker 2: at thirty eight thirty nine percent heading in. If she
Speaker 2: were to get that polymarket bounce, then she'd be in
Speaker 2: the you know, forty five percent range. So fairly close
Speaker 2: to fifty to fifty. The way the model works, the
Speaker 2: model was very disappointed. Shall we say, not that it
Speaker 2: has emotions. It's not some large language model that the
Speaker 2: model is disappointed with Harris's post convention polling, where typically
Speaker 2: after a convention is one of the best periods for
Speaker 2: a candidate throughout the life of the election cycle. And
Speaker 2: Harris was not only not getting a sustained bounce, she
Speaker 2: may have gotten one for a couple of days and
Speaker 2: then RFK drops out the new cycle changes, but actually
Speaker 2: been declining. She had lost a point or two in
Speaker 2: polls of Michigan, Wisconsin, you know, Pennsylvania, most of those
Speaker 2: rust belt blue wall swing states. So it's like this
Speaker 2: should be a really good period and it's a really
Speaker 2: bad period. Therefore, it had gotten really grumpy about her polling,
Speaker 2: and therefore a lot of Democrats, some of whom are
Speaker 2: completely insane and should go, I don't know, moved to
Speaker 2: Fiji or some nice country where they don't have to
Speaker 2: blow up my Twitter mentions. We're upset with me as
Speaker 2: a result, But we have to talk about that.
Speaker 1: Yes we do, Nate, Yes we do. Because you had
Speaker 1: such a great takedown all right, I'm going to read
Speaker 1: a tweet from yesterday night. Hey bet, understand you may
Speaker 1: still be frustrated. Silence of the Lambs came out the
Speaker 1: same year as for the Boys, so you were pretty
Speaker 1: much always going to lose best Actress to Jodie Foster
Speaker 1: in poker. We'd call that a bad beat. But that's
Speaker 1: no reason to tweet out conspiracy theories.
Speaker 2: Please discuss no, so Bette Midler among other Democrats, you know,
Speaker 2: Stuart Stevens, this guy at the Lincoln Project. Yeah, you
Speaker 2: have certain people who are convinced that.
Speaker 1: You've been bought.
Speaker 2: If I've been I must have been bought. This is
Speaker 2: like literally what Stuart Stevens and Bette Midler are implying.
Speaker 2: And sometimes it comes up in the context of so
Speaker 2: I consult. I'm an advisor to Pollymarket, and Polly Market
Speaker 2: has been invested in by Founder's Fund, which is you know,
Speaker 2: one of the principles is Peter Teal at Founder's Fund,
Speaker 2: So it therefore gets twisted into Peter Teal is secretly
Speaker 2: funding Nate, which is bizarre. I mean, Founder's Fund has
Speaker 2: invested in in Lift and Airbnb and Facebook and and
Speaker 2: you know all these all these startups eventually get invested
Speaker 2: in by most of the big VC firms at some
Speaker 2: stage of fundraising. I mean, if you work for open Ai.
Speaker 2: Elon Musk co founded open Ai, are you on Elon
Speaker 2: Musk's payroll? You know substack Mark Andreeson and recent Horror,
Speaker 2: which is a big investor in substack. I think he
Speaker 2: isn't as triggering for people as Elon or Peter Teal,
Speaker 2: but like, but yeah, you know, you have to understand
Speaker 2: how business works and how vet your capital works. But
Speaker 2: people people cannot fathom because their brains are so poisoned
Speaker 2: by politicscept Like, you know, it's not like I want Trump.
Speaker 2: I mean, you know, I'm disclosed here. I'm trying to
Speaker 2: be nonpartisan to our audience. You know, I'm gonna vote
Speaker 2: for Harris if if I'm being super duper honest, I mean,
Speaker 2: most of the audience for kind of high brow news
Speaker 2: content are Democratic leaning voters. The audience at the newsletter
Speaker 2: is very is very colle educated. You know, when when
Speaker 2: Harris is doing well in the polls, then we probably
Speaker 2: convert a little better from we get traffic either way,
Speaker 2: we convert a little better to paid subscriptions when there's
Speaker 2: good news for Harris.
Speaker 1: Of course, of course, I mean confirmation bias, right, and
Speaker 1: people people really when they when you're saying things that
Speaker 1: they agree with and they like you, and then otherwise
Speaker 1: you're you know, you're a paid shill, and I can't
Speaker 1: I can't believe that I'm associated.
Speaker 2: With you, but like people, I think people are. I
Speaker 2: call it the uh. It's called the called the Bonyar
Speaker 2: threshold after a particularly hackish online Democrat named Tom Bonyer,
Speaker 2: who just cannot seem to understand that anybody could ever
Speaker 2: try to want to be true seeking about anything. But
Speaker 2: once you pass the Bonyar threshold, you're no longer capable
Speaker 2: of assuming anyone else acts in good faith. This is
Speaker 2: a mistake poker players make. Actually they assume that everybody
Speaker 2: else plays the same way that they do, right that
Speaker 2: if they'd be bluffing in a particular spot, and maybe
Speaker 2: they have the wrong bluffing frequency, we call it that.
Speaker 2: Therefore the other player must be also and they're mapping
Speaker 2: themselves to the rest of the world.
Speaker 3: So yeah, we'll be back in a minute with yet
Speaker 3: more on the election, the debate, the polls, and the models.
Speaker 2: Here's the guide to how to interpret the polls and
Speaker 2: the models in the coming week or two. And this
Speaker 2: is going to preview a post. It's actually the post
Speaker 2: and silver builting will probably be up by the time
Speaker 2: you listen to this, so go check that post out
Speaker 2: too if you want, like a more precise version. The
Speaker 2: first thing that will come out are poles that are
Speaker 2: kind of crappy, the reason being that like poles that
Speaker 2: you conduct in just today, are gonna have a harder
Speaker 2: time capturing a representative sample electorate. And also the news
Speaker 2: story itself. Part of the benefit of the debate is
Speaker 2: people watching debate night, but also then these clips circulate
Speaker 2: of Trump talking about immigrants eating dogs and cats, and
Speaker 2: the abortion stuff circulates, and you get buzz and favorable
Speaker 2: headlines for Harris. By the way, Taylor Swift, yeah, I.
Speaker 1: Was gonna I was gonna bring that up for sure,
Speaker 1: because that's also a little bounce. While we can talk
Speaker 1: about whether it's a bounce or not.
Speaker 2: It's interesting that she did that, whether they chose to.
Speaker 2: I'm sure I'm sure Tat is coordinating this with her
Speaker 2: friends and the Biden excuse me, not by her, the
Speaker 2: Harris Walls campaign. So they really wanted to drive like
Speaker 2: a big boom news cycle instead of like if it
Speaker 2: were me, I would not have done that tonight. I
Speaker 2: have said I think my debate was strong enough. We'll
Speaker 2: tell Taylor, Hey, Taylor, just hold off. Let's save us
Speaker 2: for a couple of weeks from now, when if there
Speaker 2: is a debate bounce that it might fade in the
Speaker 2: new cycle changes. But anyway, so first you get these
Speaker 2: kind of either online polls that have these large panels,
Speaker 2: that have very large samples, which can be fine poles,
Speaker 2: but tend not to show a lot of movement for
Speaker 2: reasons that aren't getting worth into or really crappy one
Speaker 2: day IVR automated polls, So I wouldn't pay too mu
Speaker 2: attention to anything until maybe this weekend. This weekend, the
Speaker 2: first traditional polls that survey people Wednesday, Thursday, Wednesday, Thursday,
Speaker 2: Friday will come out probably Saturday or Sunday. Those might
Speaker 2: show more movement. If there is movement, those are a
Speaker 2: bigger deal. And then in the following week you'll start
Speaker 2: to see probably more state polling data. So by the
Speaker 2: end of next week we'll have a pretty good idea
Speaker 2: of where the race stands. Now, if I had to
Speaker 2: guess you look at that number in the CNN poll
Speaker 2: typically that does actually correlate with movement in the head
Speaker 2: to have polls. You know, one of the biggest numbers
Speaker 2: ever because gaps ever in the c and M pole
Speaker 2: was in the first debate in twenty twelve when ntt Romney,
Speaker 2: you know, kind of clean Barack Obama's clock and Rodney
Speaker 2: gained about temporarily it faded, but gained about three points
Speaker 2: in polls as a result. After the first debate with
Speaker 2: Trump and and Biden, Trump only gained three points or so.
Speaker 2: Right as disastrous that the bit was for Biden. Now,
Speaker 2: maybe that Trump is like near his theoretical ceiling anyway, Right,
Speaker 2: it's hard for Trump to get much more than fifty
Speaker 2: percent of the electorate. He's a pretty unpopular guy. But
Speaker 2: you know, so Beasonville, the guest might be that Harris
Speaker 2: gets half that a point or a point and a half.
Speaker 2: The question is kind of what the baseline is exactly.
Speaker 2: If you look at the Silver bulletin pulling average, she
Speaker 2: had been ahead by two point two points, I think
Speaker 2: or something. So that gets her to three and a
Speaker 2: half or so. On top of that, our model assumes
Speaker 2: that we're no longer in this convention period, so it's
Speaker 2: no longer penalizing Harris's polling. If she were to get
Speaker 2: up to three and a half point lead, depending on
Speaker 2: what happens in the swing stage, she would emerge out
Speaker 2: of that as frankly a slight favorite in the model. Now.
Speaker 2: I don't want to guarantee that, though, because there's a
Speaker 2: little bit of ambiguity about where the race stood beforehand.
Speaker 2: In some of the very recent national polling, The New
Speaker 2: York Times has this very good poll to do with
Speaker 2: Santa College, very large sample size, very rigorous methodology. Trump
Speaker 2: had been ahead by a point in the popular vote,
Speaker 2: and Trump's a head by a point nationally. He wins
Speaker 2: electoral college like for sure. So there have been some
Speaker 2: bad data for Harris recently. If you can get back
Speaker 2: though to the three and a half point range three
Speaker 2: four that you know, that would count as a as
Speaker 2: a big tournament events.
Speaker 1: Yeah, but it's still it's still incredibly close, right and
Speaker 1: we're still how many weeks out from the election, right?
Speaker 1: Six weeks? We still have we still have quite some
Speaker 1: time to go where things can change, which is why
Speaker 1: I actually I totally agree with you. I thought it
Speaker 1: was so strange that the Taylor Swift endorsement came right now,
Speaker 1: because it kind of got buried right because it was
Speaker 1: late at night, and obviously her her followers are gonna
Speaker 1: are going to be looking at it. But I think
Speaker 1: that you do need to have some of these things
Speaker 1: that you can sprinkle in along the way because it's
Speaker 1: a long road ahead, and as we've talked about before,
Speaker 1: like for Harris, any little slip up is going to
Speaker 1: really really matter. And she doesn't even have to mess up,
Speaker 1: she just has to, you know, do something that's perceived
Speaker 1: the wrong way. She's the one who has to prove,
Speaker 1: I think, and to be kind of on she has
Speaker 1: to be perfect, right, she has to be one hundred percent.
Speaker 2: Although although I think that, you know, let's do another
Speaker 2: poker term, I think they've been a little bit nitty,
Speaker 2: meaning risk averse and neurotic about, for example, not doing
Speaker 2: more media at sure.
Speaker 1: Yeah, yeah that that actually I really do not understand.
Speaker 2: She right now is at forty nine percent of the
Speaker 2: vote in polls. To win, she has to get to
Speaker 2: fifty one percent fifty one because she has a disadvantage
Speaker 2: and all likely hid in the electoral college, so she
Speaker 2: needs to find two percent of the electorate somewhere, which
Speaker 2: seems easy, But there's only about six percent that's undecided
Speaker 2: or voting third party at the moment. Probably one percent
Speaker 2: of that will stay with Jill Stein or whatever else. Right,
Speaker 2: but like, you know, maybe you have five percent of
Speaker 2: the actual electorate in play or four percent or something
Speaker 2: like that, right, you need to get probably half that.
Speaker 2: It's non trivial problem, actually, And like so really reaching
Speaker 2: into like the marginal constituencies, maybe not doing the mainstream
Speaker 2: media hits, but doing some of the weird podcasts and find,
Speaker 2: you know, profiling who are the undecided voters. Maybe it's
Speaker 2: maybe it's men who just are a little uncomfortable with
Speaker 2: voting for a woman. Don't like Trump, but maybe a
Speaker 2: little uncomfortable voting for a woman or things like that.
Speaker 2: I don't know, you know, I think they tend to
Speaker 2: over index on like the Nikki Hayley, Liz Cheney voters.
Speaker 2: They do fine with those. But maybe the more marginalized
Speaker 2: it might be all you know, it might be younger
Speaker 2: black voters and Hispanic voters who you know, do not
Speaker 2: grow up with memories of the Civil rights era and
Speaker 2: require a little bit more persuasion.
Speaker 1: Well, we can invite her to come talk on our podcast,
Speaker 1: right U, Kamala Harris, come on on and help convince
Speaker 1: Donald Trump.
Speaker 2: Donald Trump, yept, what if we moderate a debate? That
Speaker 2: would be funny, that would be amazing.
Speaker 1: Okay, we will, we will host a debate on risky business.
Speaker 1: Let's let's go, and.
Speaker 2: Actually we were you know, some of us is even
Speaker 2: like the area I describe as the river in the book,
Speaker 2: it's like some of the Silicon Valley stuff. And she's
Speaker 2: tried to moderate. I mean she's like, you know, reduced,
Speaker 2: I have not paid all that much touch in this
Speaker 2: policy stuff. She like has a less aggressive plan for
Speaker 2: taxing capital gains then Biden has. You know, Silicon Valley
Speaker 2: seems a little bit less opposed to Harris than they
Speaker 2: were to Biden. I mean, it's a tiny constituency, but
Speaker 2: like the crypto people are a group that, like Trump,
Speaker 2: has gone out after bitcoin declined after debate last night
Speaker 2: because they saw Trump as losing. For instance, areas like that,
Speaker 2: perhaps she.
Speaker 1: Does have some low hanging fruit where if she actually
Speaker 1: comes out, you know, and says something that shows that
Speaker 1: she's going to be supportive of crypto, which right now,
Speaker 1: her actions are not showing right, given given who she
Speaker 1: showsen for her administration, if she does a few key
Speaker 1: things like that, I think she might be able to
Speaker 1: pick up like one percent, right which, as we know,
Speaker 1: like one percent matters, every single percent matters.
Speaker 2: Or point or point one percent, which also matters. Kamala coin, Yes,
Speaker 2: Kamala coin, Yep.
Speaker 1: Absolutely, she can do a cat she can do a
Speaker 1: cat coin for cat ladies, right. I think that that
Speaker 1: would work. I mean, Taylor Swift's endorsement had a cat
Speaker 1: in the picture. So lean into that, you know, show
Speaker 1: that you understand the culture. Nate, I do have a question,
Speaker 1: and you don't have to answer if you don't want to.
Speaker 1: But I'm curious, how strongly do you believe kind of
Speaker 1: in the current output of your model, Like, do you
Speaker 1: do you think that Harris right now is kind of
Speaker 1: poised to lose?
Speaker 2: Not right now because now you have an absence of
Speaker 2: post debate data that could move the numbers quite a bit,
Speaker 2: but you know, as of like as of uh, Tuesday
Speaker 2: morning or Tuesday night before the debate, when she's at
Speaker 2: thirty eight percent, thirty eight and a half percent, yeah,
Speaker 2: more or less. I mean, look, I'm aware that there
Speaker 2: are other models out there, some of which are good,
Speaker 2: some of which you are less good. I'm aware that
Speaker 2: prediction markets are generally pretty smart, and those also Harris,
Speaker 2: you know, Polly market her whatever, forty five is, forty
Speaker 2: four is percent range instead of thirty eight. That's like
Speaker 2: not a huge gap. But look, one reason to believe
Speaker 2: the model is that like is that, you know, if
Speaker 2: I were doing this subjectively, then I'd be rooting for Harris,
Speaker 2: probably right. I am not a Trump fan, not a
Speaker 2: huge fan of Harris's politics, frankly either, but I consider
Speaker 2: after January sixth, there are lots of reasons why I
Speaker 2: would never vote for Trump, and she's the alternative, you know,
Speaker 2: for various reasons. I think. Probably also, if you were
Speaker 2: somebody who was really agitating, as I was, for somebody,
Speaker 2: not necessarily Harris, frankly, but somebody to replace Biden, then
Speaker 2: you're gonna look really smart if you're one of the
Speaker 2: people who said you gotta get rid of Biden, and
Speaker 2: then that person wins and Harris is probably good for
Speaker 2: site traffic and newsletter subscriptions. Frankly. So the fact that
Speaker 2: I have all these incentives to root for Harris is
Speaker 2: the reason to trust the process I set up ahead
Speaker 2: of time, before I knew how this would affect anything,
Speaker 2: and the same process yielded reliable model results since two
Speaker 2: thousand and eight over many elections, And so I'm not
Speaker 2: involving my emotions. So yeah, if I were, you know, look,
Speaker 2: as a Bayesian, you'd kind of combine your forecast with
Speaker 2: other information, other data. So probably realisticly would be like
Speaker 2: forty two percent, taking the mid point of like polymarkets
Speaker 2: forty six and our models thirty eight, and you get to,
Speaker 2: like Harris forty two or forty three is probably my
Speaker 2: subjective belief that seems not to go out on too
Speaker 2: far of a limb.
Speaker 1: That makes sense.
Speaker 2: It would now be higher now she's gained, you know,
Speaker 2: but now I think, you know, if I did predict
Speaker 2: what our model will say in two weeks, it might
Speaker 2: be fifty percent Harris fifty three or something like that.
Speaker 1: Well, here's hoping after the break travel with us to Barcelona,
Speaker 1: where I was just playing in EPT Barcelona, the European
Speaker 1: Poker Tour, and we'll have a little poker for you.
Speaker 2: So Maria, well, I've been bouncing back and forth between
Speaker 2: the West coast and the East Coast and the UK
Speaker 2: for a couple of days. You have been in fabulously
Speaker 2: beautiful Barcelona, Spain playing poker. I see from the hand
Speaker 2: and mom database that you cashed three times, including one
Speaker 2: rather large cash. Do you want to tell us about that? Yeah?
Speaker 1: Absolutely, I had a nice trip. This was the Poker
Speaker 1: Star's twentieth anniversary of the European Poker Tour, so it
Speaker 1: was a huge event with some record setting fields and
Speaker 1: there was one event. So there's a new format that
Speaker 1: was introduced a few years ago in poker. That's the
Speaker 1: mystery bounty, which appeals to djens such as Nate. Because
Speaker 1: I'm not a djen. Nate as a jen, right, I
Speaker 1: mean it does.
Speaker 2: I don't like mystery bounties that much. I mean, I
Speaker 2: don't know KOs are more from. These are different, We're
Speaker 2: not maybe a little above people's heads. But yeah, so
Speaker 2: Wester go ahead. So the mystery bounty is that if
Speaker 2: you knock out a player, usually after some threshold, if
Speaker 2: you get to day two of a tournament, then you
Speaker 2: knock out a player, you get like a little card
Speaker 2: that says you get to draw from this like big
Speaker 2: vat literally of envelopes, and some of the envelopes contain
Speaker 2: very large amounts of money, such as what was top
Speaker 2: prize here, like something one hundred thousand, one hundred thousand
Speaker 2: euro Yes, one hundred thousand euros. It's one hundred and
Speaker 2: ten whatever thousand American dollars. So yeah, it's a way
Speaker 2: for a cheap entry to have. Like usually you can
Speaker 2: only make these six figure sums if you like win
Speaker 2: the tournament or finish in the top like two or three.
Speaker 2: This is a way to have another opportunity without having
Speaker 2: to win, without having to beat everybody, just knocking one
Speaker 2: player out and you win one hundred thousand euros or
Speaker 2: a million dollars and some of the worldsairs of poker ones.
Speaker 2: So did you win a big bounty then.
Speaker 1: Maria, Yeah, so well, first of all, you know, so
Speaker 1: in this mystery bounty tournament, it was a three three
Speaker 1: thousand euro buy in. I ended up coming in fifth,
Speaker 1: which is huge. I beat out over eleven hundred players
Speaker 1: in order to make the final table, so really nice,
Speaker 1: deep run. I was very happy with the result. And
Speaker 1: so I had ten bounties to pull, which is a lot, right,
Speaker 1: ten bounties is a good amount and I have never
Speaker 1: yet wow, and I have never pulled anything other than
Speaker 1: a min bounty. So a min bounty is a minimum bounty.
Speaker 1: In this particular tournament, that was one thousand euros, and
Speaker 1: this was by far the most common bounty. So we
Speaker 1: are going to now pivot to a very non risky
Speaker 1: business way of thinking. So here I am with ten
Speaker 1: bounties to draw. I draw the first one. It's a men.
Speaker 1: I wait a while to draw another one. It's another men.
Speaker 1: So at some point I've drawn five men bounties and
Speaker 1: I have five left. Now the one hundred k's are gone.
Speaker 1: And there is a player who everyone in the poker
Speaker 1: world knows and anyone who was following the main event
Speaker 1: this year knows as well. Nicholas Sausted, otherwise known as
Speaker 1: Lena by his online screen name. He had a very
Speaker 1: deep run in the main event, and a lot of
Speaker 1: poker players, including me, were rooting for him to win
Speaker 1: because he's a phenomenal player and a really really nice guy.
Speaker 1: Lena is also someone who's quite lucky and runs incredibly well.
Speaker 1: He plays well. But see this is why I said,
Speaker 1: We're about to pivot into a non risky business way
Speaker 1: of thinking. By this point, he had been knocked out
Speaker 1: of the bounty event, and he had drawn two bounties.
Speaker 1: He had drawn a twenty five K and a ten K.
Speaker 1: So what I decided to do was send a text
Speaker 1: message to Nicholas and ask him if he would draw
Speaker 1: my remaining bounties. This is an incredibly non scientific, irrational
Speaker 1: way of thinking. I was like, I am going to
Speaker 1: get this very lucky player who's very good at drawing bounties.
Speaker 1: By the way, we know, right, you cannot be good
Speaker 1: or bad at drawing bounties. This is random. But I'm
Speaker 1: going to get him to draw my remaining bounties. So
Speaker 1: he said, sure, he would do it.
Speaker 2: He charge a fee.
Speaker 1: Now he did not charge a fee because he's a
Speaker 1: nice guy. So here I am playing, did not even know,
Speaker 1: you know, if he was actually going to show up.
Speaker 1: So we're down to two tables. You know, Nicholas is
Speaker 1: still not there. You know, I'm getting worried that I'm
Speaker 1: gonna have to draw my other bounties. Tap on my shoulder,
Speaker 1: there he is. He said, are you ready to draw?
Speaker 1: He said, oh my god, yes, So I give him
Speaker 1: the five bounties. We go up and he says what
Speaker 1: are the top bounties left? And I said, well, there's
Speaker 1: a twenty five K left and a ten K left.
Speaker 1: And he said, okay, we got this. So he draws
Speaker 1: and he draws, and you know, he draws my five
Speaker 1: bounties and he said, do you want to open them?
Speaker 1: Do I open them? I said, let's take turns. So
Speaker 1: I opened the first one. It's a twenty five K.
Speaker 1: He opens the second one it's a ten K, and
Speaker 1: he's like, okay, I did it for you. He's like,
Speaker 1: the only other ones left are the one case right,
Speaker 1: And I was like, yep, so then the other three
Speaker 1: were one case.
Speaker 2: So my little bounties were there remaining at this point
Speaker 2: about forty so there are two good ones out of forty.
Speaker 1: Yep in the restaurant and he picks those ten picked five,
Speaker 1: He picked five.
Speaker 2: He picked five, yep, so five out of forty and
Speaker 2: they have to I mean, do some combinatorics readers. I'm
Speaker 2: sure we have readers who can do the math here,
Speaker 2: but like, are you sure that? Because there are these
Speaker 2: envelope politic conspiracies if you're an NBA fan. Supposedly, the
Speaker 2: NBA lottery was rigged for New York Knicks to get
Speaker 2: in Patrick Ewing out of Georgetown, for example, And like
Speaker 2: one of the envelopes was like the others had like
Speaker 2: a bet edge.
Speaker 1: There were any no marked envelopes, and I saw him drawing.
Speaker 1: He just he has the magic touch, which is the single.
Speaker 2: Special contacts or glasses.
Speaker 1: Maybe this is the single most irrational thing I will
Speaker 1: ever say on this podcast. Thank you so much, Nicholas
Speaker 1: for adding thirty five thousand euros to my life.
Speaker 2: Let's be here. What if he had said I wanted
Speaker 2: two percent feet? Uh huh? Would you have accepted that feet?
Speaker 2: He gets two percent of whatever bounty you in above
Speaker 2: the minimum.
Speaker 1: I don't know.
Speaker 2: We didn't.
Speaker 1: We didn't have to go there. Okay, I did not
Speaker 1: think he would ask. I think I would pay him
Speaker 1: one percent too, but as a basi, and at the
Speaker 1: end I said that I would buy him a nice
Speaker 1: dinner wherever he wanted to go. But he did not
Speaker 1: take it up on me. Take me up on it,
Speaker 1: and I will reiterate the invitation, Nicholas, if you're listening
Speaker 1: any stop anywhere, it's on me. Thank you so much.
Speaker 1: And if we're ever playing a mystery bounty together, I
Speaker 1: hope that you will draw my envelopes for me again,
Speaker 1: because I'm a very rational person who does not aspire
Speaker 1: to be superstitious ever.
Speaker 2: Risky Business is hosted by me Nate Silver and me
Speaker 2: Maria Kanakova. The show was a co production of Pushkin
Speaker 2: Industries and iHeartMedia. This episode was produced by Isabel Carter.
Speaker 2: Our associate produce is Gabriel Hunter Chang. Our engineer is
Speaker 2: Sarah Bruger. Our executive producer is Jacob Goldstein.
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