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Speaker 1: Welcome everybody. Wednesday edition of the Clay Travis and Buck

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Speaker 1: Sexton Show kicks off right now. It is post debate

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Speaker 1: day and look we're going to get into it the

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Speaker 1: details best exchanges policy and also take a look at

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Speaker 1: the numbers the needle did it move? The aftermath of

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Speaker 1: the debate last night, Clan, I will share our top

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Speaker 1: line thoughts on this with all of you. Also want

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Speaker 1: to get a lot of your reaction to eight hundred

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Speaker 1: eight two eight A two. Definitely give us a call

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Speaker 1: and we'll want to hear from you and you can

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Speaker 1: tell us how how you think that it went. I

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Speaker 1: think based on Twitter or ex Clay and I on

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Speaker 1: the on the big stuff see this one pretty much

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Speaker 1: the same way. And we can get into this right away. Yes,

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Speaker 1: I know that if any of you don't hear right away,

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Speaker 1: you're gonna yell at me. So I don't want you

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Speaker 1: to yell at me. The moderators were awful, even in

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Speaker 1: comparison to me thinking that it would be a rig job,

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Speaker 1: that it would be an ambush. It was an ABC

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Speaker 1: News ambush of Donald Trump on behalf of Kamala Harris.

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Speaker 1: We will go into why that is and the most

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Speaker 1: obvious point is the constant fact checking of Trump, sometimes

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Speaker 1: incorrectly and other times just fact checking on an opinion

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Speaker 1: not a fact, which would also be incorrect. But I

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Speaker 1: mean sometimes they even had the facts wrong. Never once

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Speaker 1: did Theay fact check Commel. The most egregious instance of

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Speaker 1: this was when she once again tried it out to

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Speaker 1: Charlottesville good people on both sides lie. That is completely

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Speaker 1: taken out of context. Donald Trump did not say that

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Speaker 1: there were good neo Nazis. This is a lie. Even

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Speaker 1: Snopes has admitted this is a lie. This is wrong.

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Speaker 1: You know, this would be like taking a set from

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Speaker 1: the beginning of a sentence and cutting out the end

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Speaker 1: of it and pretending like that is the intent of

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Speaker 1: what a person said. And and so that was egregious.

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Speaker 1: It was gross, Clay. I'll just I'll say it. I mean,

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Speaker 1: I thought that Trump, given that he had to fight

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Speaker 1: through a three on one, did reasonably well for Trump.

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Speaker 1: It was not a strong night for Trump. I did

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Speaker 1: not I look, everyone's una tell their opinion on this one.

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Speaker 1: I thought he would bring it a little more. I

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Speaker 1: know it's unfair, but this is the deal that they

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Speaker 1: signed up for. I would also put this out there, Republicans,

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Speaker 1: stop doing this to yourselves. Stop stepping on a rake.

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Speaker 1: Stop making this mistake of oh I'm gonna go to

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Speaker 1: the the ABC or CBS or NBC, they'll do a

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Speaker 1: fair debate. Let's stop it, okay, especially when it matters

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Speaker 1: they turn this on and away that it blows up

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Speaker 1: in our faces. And unfortunately Kamala, as much as her

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Speaker 1: record is awful and she's a phony and a fake,

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Speaker 1: she showed up very prepared and I think her remarks

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Speaker 1: were all canned. I think they were rehearsed speeches effectively.

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Speaker 1: But Clay, to me, it's kind of I would say

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Speaker 1: a draw, which I know everyone says that's what you

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Speaker 1: say when your person loses. But it was unfair. It

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Speaker 1: was rigged. So maybe you give Trump the edge based

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Speaker 1: on that. But it wasn't the night that we needed

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Speaker 1: to get a knockout of the Kamala campaign, that's for sure.

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Speaker 2: Trump had multiple opportunities to absolutely obliterate Kamala Harris, to

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Speaker 2: knock her out, and he consistently swung and missed and

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Speaker 2: played into her traps. I thought it was a poor

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Speaker 2: performance by him. And look, some people are gonna say, oh,

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Speaker 2: well you I don't sugarcoat things, right.

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Speaker 3: I come from the world of sports.

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Speaker 2: When your team performs at its less than optimal level,

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Speaker 2: you don't come on and say, hey, they were great.

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Speaker 2: I thought, look, the rig job was in effect. I

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Speaker 2: thought it was disgraceful how Mure and Lindsay Davis behaved

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Speaker 2: the fact checking in quotation marks. To me, the debate

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Speaker 2: really pivoted when Lindsey Davis stepped in on the abortion

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Speaker 2: issue and decided to weigh in. It was like she

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Speaker 2: was giving a wife raft to Kamala, who I thought

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Speaker 2: was really struggling at that point.

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Speaker 3: But let me go to the very start of the debate.

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Speaker 3: To me, this is.

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Speaker 2: When Trump could have completely taken command and dominated her.

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Speaker 2: The very first question was about to Kamala Harris, essentially,

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Speaker 2: are people better off now than they were before you

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Speaker 2: came into office. The answer is incontrovertibly no. Every single

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Speaker 2: person out there, white, Black, Asian, Hispanic is worse off

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Speaker 2: because Biden and Kamala have failed. And she started off

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Speaker 2: because I wrote it down. I've got my notepad here,

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Speaker 2: buck of all the things that I jotted down as

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Speaker 2: I watched this from my home. After she got asked

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Speaker 2: if there are people better off than they were four

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Speaker 2: years ago? Kamala Harris started with a canned answer. Her

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Speaker 2: first answer was I was raised as a middle class kid.

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Speaker 2: She completely avoided the answer of the question that then

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Speaker 2: went to Trump. She didn't even make an argument that

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Speaker 2: people were better off four years ago now than they

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Speaker 2: were four years ago.

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Speaker 3: Trump.

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Speaker 2: She whiffed on an epic level. She looked nervous, she

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Speaker 2: was jumping around. She whiffed, and all Trump had to

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Speaker 2: say was point out in his response she didn't answer

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Speaker 2: the question because she can't. Every person, white, Black, Asian, Hispanic, gay,

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Speaker 2: straight male female is worse off today because Biden and

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Speaker 2: Kamala have failed. I want all of you to note

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Speaker 2: that she didn't answer the question. He had a chance

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Speaker 2: to knock her down on the very first question, and

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Speaker 2: he whiffed. And then the other thing I'll point two

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Speaker 2: buck is he played into her attacks. They had a

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Speaker 2: question on immigration. She brought up how many people go

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Speaker 2: to his rallies and said they were boring, And instead

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Speaker 2: of hitting her on now saying she wants to build

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Speaker 2: a wall and letting tens of millions of illegals into

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Speaker 2: this country, Trump argued with her. He went down the

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Speaker 2: rabbit hole about how many people go to his rallies

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Speaker 2: and about how they have a good time, and she

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Speaker 2: can't even get as many people as her rallies. She

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Speaker 2: baited them, and Trump took the bait all night long

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Speaker 2: on those. She left her chin exposed in a boxing analogy,

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Speaker 2: and he never delivered multiple knockout punches. If you want

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Speaker 2: to take it away from boxing, buck, I understand the

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Speaker 2: refereeing was rigged. It was, but the people who talk

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Speaker 2: about refereeing being rigged do it because they lost. If

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Speaker 2: you have crappy refs and you still win, you might say, hey,

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Speaker 2: the refs were crappy, but you still won. I hope

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Speaker 2: that it doesn't have a major lasting impact. Trump had

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Speaker 2: a chance to end the race tonight. She was not good.

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Speaker 2: He didn't take it advantage of it. To me, it

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Speaker 2: was an incredibly frustrating debate to watch.

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Speaker 1: You know, we talk about beat the cheat in the

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Speaker 1: context of getting enough votes to win even with whatever

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Speaker 1: shenaniganst Democrats are planning. If you're going into an ABC

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Speaker 1: News debate as a Republican this close to election day,

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Speaker 1: in particular, you've got to be prepared to beat the cheat.

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Speaker 1: When it comes to the refs or the moderators in

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Speaker 1: this case. You know, I've gone in before, I've gone

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Speaker 1: done CNN, and I've been on le Bill Marshaw and

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Speaker 1: I've I've done shows with leftists. You know, the game

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Speaker 1: is the game, right, I mean, you can't show up

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Speaker 1: and be like, oh, but it's so unfair. I mean,

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Speaker 1: if you're agreeing to be there, you've got to do

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Speaker 1: the best with what you've got. I would say, yeah,

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Speaker 1: I mean it wasn't. It wasn't strong from Trump in

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Speaker 1: a bunch of places where it needed to be. And

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Speaker 1: that was frustrating as somebody watching and who is very

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Speaker 1: invested in Trump winning obviously for the for the benefit

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Speaker 1: of the call of the whole country. But Clay, if

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Speaker 1: you remember, and I think it was the twenty twelve

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Speaker 1: primary or twenty eleven primary. In the twenty twelve election,

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Speaker 1: I remember Nute Gingrich had one moment it was it was

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Speaker 1: a primary, it wasn't even a general election. Yes, where

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Speaker 1: he went after I wonder who the I wonder which

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Speaker 1: anchor it was. Was it Chris Wallace? He went after

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Speaker 1: one of the questioners in a way that got him

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Speaker 1: his moment, right, that was the one nude, gingrich moment

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Speaker 1: of that cycle. I bring it up because I don't

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Speaker 1: understand why Trump didn't say attack the moderator, go right

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Speaker 1: at the moderators, And I tweeted this during the debate.

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Speaker 1: Others were tweeting this TOOCU. I think it was so obvious.

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Speaker 1: At some point, you've got to say, this is just

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Speaker 1: you guys are being unfair. This is outrageous. And then

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Speaker 1: that that resets for a lot of the audience, Oh

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Speaker 1: oh no, he knows, Okay, we understand what's going on here,

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Speaker 1: And it reframes a lot of the conversation that comes afterwards,

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Speaker 1: because then everyone's more aware of it and everyone sees

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Speaker 1: that Trump isn't taking it lying down. You know, there

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Speaker 1: were a few things. I mean the fact that it

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Speaker 1: never was really there was no looking into the camera

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Speaker 1: and saying she has been the vice president for four years.

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Speaker 1: Biden's administration is a disaster. You can afford half the house.

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Speaker 1: You could when she and Biden came into office, she

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Speaker 1: lied about Biden being of sound mind for years up

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Speaker 1: until the very very end. She was a part of

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Speaker 1: that lie. She is changing all of her policy positions

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Speaker 1: that are disadvantageous for her now, as though it all

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Speaker 1: meant nothing, just from a few years ago. She's a phony,

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Speaker 1: she's a fraud, and she would be a terrible president.

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Speaker 1: I mean, yeah, people can point to me to say, well,

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Speaker 1: he said Trump said this, or Trump said that. You know.

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Speaker 1: I mean, you know, man, nobody cares about the crowd size.

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Speaker 1: I don't know what else this. Nobody else cares. I mean,

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Speaker 1: that's what he cares about. That the period everybody was

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Speaker 1: seeing at home saying he's doing she's doing that to

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Speaker 1: paid him. We all saw it. It was so obvious

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Speaker 1: and sure enough. So it's frustrating. Look on the good news.

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Speaker 1: By the way, we're not gonna lie. It's not like

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Speaker 1: whining today Trump. I don't think this moves the polls

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Speaker 1: at all. I still think Trump is going to win.

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Speaker 1: I have not moved off of that. But I think

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Speaker 1: he could have given himself a little more momentum and

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Speaker 1: a little bit of an insurance policy last night. And

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Speaker 1: I don't think he did it.

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Speaker 3: He could have ended it.

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Speaker 2: She is a uniquely awful candidate, and he led her

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Speaker 2: off the hook time after time.

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Speaker 3: It reminds me of my fishing.

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Speaker 2: I went fly fishing recently, and I got a bunch

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Speaker 2: of bites, and every time I tried to get the

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Speaker 2: big fish in, they got off.

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Speaker 3: Right.

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Speaker 2: He had so many opportunities to reel her in and exposure.

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Speaker 2: Now did the moderators help. I thought he had a

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Speaker 2: good moment in the abortion thing when he went directly

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Speaker 2: to Kamala and said, do you think there should be

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Speaker 2: abortions in the seventh, eighth, and ninth month? And then

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Speaker 2: they cut it off. There was an element of officiating

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Speaker 2: where when Trump is felt like had her a bit

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Speaker 2: cornered and would hit her with a punch, that suddenly

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Speaker 2: the moderator swept in and tried to protect her. Which

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Speaker 2: is why I think you're right, Buck. I think at

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Speaker 2: some point Trump should have turned to Mrror and to

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Speaker 2: Lindsey Davis, and I think he should have absolutely ripped

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Speaker 2: them to shreds now. I bet that this is where

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Speaker 2: you get trained. I bet they've said to him to

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Speaker 2: a large extent, don't get controlled by the moderators. But

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Speaker 2: I think this was such a blatant rig job, and

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Speaker 2: when they did it correct the very fine people, the

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Speaker 2: blood bath, the Charlottesville hoax. I don't think the moderator

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Speaker 2: should be in the business of trying to do fact checks, because,

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Speaker 2: as you mentioned, a lot of times, the fact checks

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Speaker 2: are wrong. That is, they get the actual facts wrong,

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Speaker 2: and they just disrupt the flow of the actual debate.

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Speaker 3: Let people argue it out. I thought CNN did that well.

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Speaker 2: I thought that ABC was in on the rig job

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Speaker 2: with Kamala because she's from losing and they know that

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Speaker 2: desperately they need to elevate her.

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Speaker 1: You also can tell how it's going based on are

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Speaker 1: the most rapidly partisan leftists online all praising what a

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Speaker 1: great job the moderators are doing right away? And that happened, right,

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Speaker 1: I mean you had, like, yes, like Chris Hayes from MSNBC.

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Speaker 1: I mean, you know, think of somebody who is an

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Speaker 1: outright comi and has absolutely no interest whatsoever in a

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Speaker 1: fair debate, and who was criticizing the CNN debate. I'm

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Speaker 1: sure all the monitors were, but I mean that was

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Speaker 1: really Biden has to mention. Everyone saw it. It was absurd,

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Speaker 1: But the moderators were in the tank. These are newsreaders too,

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Speaker 1: I would just point out, I mean, these are people

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Speaker 1: whose job is really to look a certain way and

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Speaker 1: read words off a prompter. They are not politically astute,

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Speaker 1: they are not particularly educated. Neither one of them is

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Speaker 1: somebody who would be impressive if you were to have

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Speaker 1: a conversation. I can assure you having worked at CBS

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Speaker 1: even News with Dan Rather as an intern when I

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Speaker 1: was eighteen and hearing this guy talk and be like, oh,

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Speaker 1: so he's kind of an idiot. What a shock making

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Speaker 1: seven million dollars a year at the time to read

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Speaker 1: off a prompters. So the fact that they would or

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Speaker 1: the idea that they would fact check Clay in real time,

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Speaker 1: you know, they're not in a position.

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Speaker 2: And here's the other thing I think I haven't heard

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Speaker 2: anybody else point this out. My wife was fired up

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Speaker 2: about it. They were ready for the fact checks, so

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Speaker 2: they were prepared to go after Trump because they were

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Speaker 2: instantaneous in the fact checks.

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Speaker 1: They the questions wanting to do this. Yes, I mean

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Speaker 1: the framing of the questions was very favorable for Kamala

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Speaker 1: and very you know, it's not hard to do. You'd

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Speaker 1: be like, all right, tell us your economic plan, tell

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Speaker 1: us your economic plan. There are where it is in

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Speaker 1: fact possible to give questions that are neutral and topic based.

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Speaker 1: The fact I mean, the fact that they asked Trump

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Speaker 1: about Kamala's black identity or however there was that was

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Speaker 1: that is just a shot in the ribs at Trump

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Speaker 1: on the stage. They're correct, the fact they didn't ask

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Speaker 1: about the assess nation attempt on Donald Trump. You go

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Speaker 1: through these things, you say, it couldn't be any.

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Speaker 3: That's about January, not that.

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Speaker 1: Yes, the framing about Ukraine, Ukraine cannot defeat Russia. Do

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Speaker 1: all the little babies out there need to hear this.

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Speaker 1: Ukraine cannot beat Russia in a drawn out war. So

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Speaker 1: Trump want to negotiate an end to the conflict so

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Speaker 1: people stop dying.

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Speaker 4: And if.

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Speaker 2: You say that you're rooting for one side or the

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Speaker 2: other to win, it actually makes it far more difficult

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Speaker 2: to get a negotiated settlement, which is I mean, it

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Speaker 2: was a childlike level of debate preparation that was designed

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Speaker 2: to try to make Kamala Harris look good.

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Speaker 3: My problem is Trump had a lot of layups.

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Speaker 2: He had a lot of easy shots, and he missed

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Speaker 2: a lot of them.

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Speaker 1: Yeah, I mean, I don't I don't disagree. I mean

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Speaker 1: I was very frustrated at home, but hey, good news. Everybody,

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Speaker 1: don't go anywhere gonna win. It's gonna be fine. Don't

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Speaker 1: worry about it. Call us to eight hundred two two

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Speaker 1: eight A two. I want to hear your thoughts about

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Speaker 1: the debate. As you know, today is a day for remembrance.

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Speaker 1: We remember those who lost their lives on airplanes and

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Speaker 1: in buildings at the hands of Al Kaeda terrorists. We

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Speaker 1: remember those who bravely charged into buildings and saved lives

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Speaker 1: while sacrificing their own. One of them was firefighter Steven Siller,

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Speaker 1: aged thirty four. His brother Frank started the Tunnel to

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Speaker 1: Towers Foundation so that we never forget. Tunnel to Towers

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Speaker 1: Foundation has been doing everything they can to honor the

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Speaker 1: lives of those we lost on September eleventh and in

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Speaker 1: the following days. They provided surviving families with mortgage free

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Speaker 1: homes wherever possible, so that those families may experience less

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Speaker 1: stress by never having to worry about losing their home.

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Speaker 1: And they're teaching children in schools of the unfortunate events

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Speaker 1: of nine to eleven, so that every generation learns of

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Speaker 1: the heroism and patriotism of so many first responders. Is

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Speaker 1: there a better day you could possibly decide to donate

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Speaker 1: eleven dollars a month to taunt to towers. I don't

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Speaker 1: think so play and I donat eleven dollars every month.

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Speaker 1: Please join us. That's all it takes, all of us.

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Speaker 1: Donate eleven dollars a month. Think of all the good

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Speaker 1: that can be done. Go to T two t dot org.

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Speaker 1: That's t the number two t dot org.

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Speaker 5: Clay Travison, Buck Sexton, Mike drops that never sounded so good.

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Speaker 5: Find them on the free iHeartRadio app or wherever you

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Speaker 5: get your podcasts.

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Speaker 4: Detailed and dangerous plan called Project twenty twenty five that

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Speaker 4: the former president intends on implementing. Couples who pray and

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Speaker 4: dream of having a family are being denied IVF treatments.

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Speaker 4: If Donald Trump were to be reelected, he will sign

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Speaker 4: a national abortion band. Wants to be a dictator. On

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Speaker 4: day one, according to himself, and what did the president

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Speaker 4: then at the time say, there will fine people on

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Speaker 4: each side. On that day, one hundred and forty law

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Speaker 4: enforcement officers were injured and some died. Donald Trump, the candidate,

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Speaker 4: has said in this election, there will be a bloodbath

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Speaker 4: if this and the outcome of this election is not

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Speaker 4: to his liking.

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Speaker 1: So many lies and no fact checks from the moderators

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Speaker 1: last night. The bloodbath line, for example, that she quotes

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Speaker 1: is in reference to how I think the car industry

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Speaker 1: would do under the you.

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Speaker 2: Know this, we talked about it back then, Buck, The

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Speaker 2: bloodbath is used all the time in the context of

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Speaker 2: business like, it's not even an abnormal phrase.

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Speaker 1: And the people on the fine people on both sides,

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Speaker 1: So that's Biden really has been carrying that lie further

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Speaker 1: than absolutely anyone else. That's always been Biden's thing, you know.

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Speaker 1: And then that's why he had to He had to

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Speaker 1: run because of the fine people on both sides line.

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Speaker 1: And it's a figment of his imagination that Trump actually

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Speaker 1: intended to say, they're a good people any you know,

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Speaker 1: you go down all this. It was a lot of

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Speaker 1: a lot of nonsense, a lot of garbage, really, no

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Speaker 1: new attacks, Clay. Which was one of my frustrations was

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Speaker 1: that Trump has heard all this stuff before and.

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Speaker 3: Should have been ready.

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Speaker 1: People have said to me, and I get that they've

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Speaker 1: been saying, you know, oh, but you know, maybe she

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Speaker 1: got the questions in advance. I'm sitting here, I'm like, guys,

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Speaker 1: we all know what the topics are going to be,

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Speaker 1: you know, that there was no surprise.

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Speaker 2: You're not gonna suddenly come out with a crazy question

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Speaker 2: like she was better prepared.

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Speaker 1: She was better prepared. And it's also, you know, it's

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Speaker 1: not like they came at Trump with, uh, you know,

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Speaker 1: who is the current you know, president of of of Georgia,

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Speaker 1: Twana or Thailand or something, you know what I mean,

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Speaker 1: Like it's you know, there weren't there weren't. It wasn't

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Speaker 1: a trivia contest. What about the economy? What about the border?

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Speaker 1: What this is the stuff you're talking now. The framing

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Speaker 1: of it was all to give openings for Kamala to

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Speaker 1: go into a cant speech. And I think that she

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Speaker 1: was giving prepared speeches. But yes, it's debate prep. That's

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Speaker 1: not you know, it's not like that's illegal. You're allowed

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Speaker 1: to do that. And and I think that with with Trump, Look,

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Speaker 1: I'm I I speak Trump is I think at some

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Speaker 1: level I think I I understand the guy pretty well.

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Speaker 1: And the rambling got to a point where I had

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Speaker 1: a hard time kind of following where he was going

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Speaker 1: and stuff, and so I'm and I was watching very intently.

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Speaker 1: So look, it wasn't a good night for him, But

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Speaker 1: it's okay. I think if we see the polls, you'll

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Speaker 1: see very little to no movement, which is why maybe

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Speaker 1: you know, I think Clay said that he thought that

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Speaker 1: Kamala got You'd say Kama got the best of him

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Speaker 1: last night as a debate, right. I think that's probably true,

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Speaker 1: But I think it's a polling draw, or rather a

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Speaker 1: numbers draw. So you know, maybe you give you give

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Speaker 1: Trump a little bit of an out with a three

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Speaker 1: on one you taught you told me Clay that the

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Speaker 1: biggest TV markets for last night. I thought this, which

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Speaker 1: was interesting. You know, we were in radio, we got

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Speaker 1: to think about market size on a regular basis. What

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Speaker 1: were the biggest TV markets?

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Speaker 2: Yeah, so my friend Mike Mulvahill, who is a Fox

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Speaker 2: Sports data and analytics guru, ratings like shares all this stuff.

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Speaker 3: I'm always fascinated by the data.

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Speaker 2: These are the top ten markets that we're watching on

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Speaker 2: television last night. And by the way, it seems like

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Speaker 2: the audience is going to be bigger than the audience

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Speaker 2: was for the debate with Joe Biden, but not necessarily

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Speaker 2: orders of magnitude larger, so somewhat similar ish in the audience.

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Speaker 2: But this was what stood out to me top ten markets.

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Speaker 2: The top two Pittsburgh and Pennsylvania. Buck Pittsburgh and Pennsylvania. Sorry,

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Speaker 2: Pittsburgh and Philadelphia in Pennsylvania, the two biggest cities in

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Speaker 2: the state of Pennsylvania. Whoever wins Pennsylvania is winning this race.

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Speaker 2: In my opinion, if you have to go to one

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Speaker 2: state and say give me one state outcome, you tell

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Speaker 2: me who's winning Pennsylvania, I'll tell you who the next

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Speaker 2: president is going to be. Pittsburgh and Philadelphia, followed by

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Speaker 2: West Palm, which is always massively high in the ratings.

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Speaker 3: Shout out West Palm. I don't know why.

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Speaker 2: Maybe a lot of retirees, people are very plugged in.

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Speaker 2: It always rates highly on political relate. Florida was the

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Speaker 2: top of the rad high five West Palm. Minneapolis. By

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Speaker 2: the way, thanks to our listeners in Minneapolis saw the

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Speaker 2: ratings data the other day. We've been skyrocketing there. Milwaukee. Fuck,

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Speaker 2: we have a sixteen share right now in Milwaukee. We

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Speaker 2: just got the ratings data the other day for people

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Speaker 2: out there, like Milwaukee loves this show like they love cheese.

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Speaker 2: In the state of Wisconsin. And by the way, I'm

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Speaker 2: going to be in Madison this weekend. I look forward

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Speaker 2: to seeing a lot of you, Badger and tied faithful.

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Speaker 2: I'm going to be at the Wisconsin Alabama game up

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Speaker 2: in up in Madison, Milwaukee, Detroit. Also, we're doing really

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Speaker 2: well in Detroit. Appreciate our new affiliate there. New York

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Speaker 2: City up forty percent in the last year. Just FYI

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Speaker 2: shout out New York City for this show. Kansas City,

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Speaker 2: Saint Louis, and Providence. Okay, that was the top ten

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Speaker 2: to me. What stands out to me is Pittsburgh, Philadelphia, Milwaukee, Detroit.

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Speaker 2: Those four cities are wheelhouse gonna decide the election cities,

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Speaker 2: and people were really tuned in there. I would think

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Speaker 2: Buck partly this is advertising. You can't escape the fact

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Speaker 2: that there is an election if you live in a

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Speaker 2: swing state city. Right now, I've been down to Atlanta

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Speaker 2: quite a bit. Every time I turn on the television

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Speaker 2: in Atlanta, it is undeniable that there is a major

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Speaker 2: election going on. Harris Trump ads. Some people out there say,

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Speaker 2: you're not seeing a lot of ads. I think if

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Speaker 2: you live in one of these seven battleground states, guess what.

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Speaker 2: You cannot escape the money that they are pouring into

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Speaker 2: your location. But anyway, So I thought that was super interesting.

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Speaker 2: People are paying attention in the battlegrounds.

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Speaker 1: I certainly hope that the Trump campaign is doing effective

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Speaker 1: messaging in those states about who Kamala is and really

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Speaker 1: who Kamala isn't. Yeah, because there's a lot of rewriting

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Speaker 1: of her history in terms of the policies and the

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Speaker 1: things that she has support in the past. You know,

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Speaker 1: they gave her opportunities to try to clean that up.

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Speaker 1: The moderators did last night and exactly the thing that

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Speaker 1: we've been talking about, which is they were completely in

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Speaker 1: the tank for it was very, very obvious. ABC News

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00:23:14,520 --> 00:23:16,960
Speaker 1: should just be blacklisted by any Republican going.

433
00:23:16,720 --> 00:23:17,520
Speaker 3: Forward for debate.

434
00:23:17,560 --> 00:23:21,120
Speaker 1: Iory they have to say, no, look, we are fair

435
00:23:21,200 --> 00:23:25,439
Speaker 1: about this. I certainly believe we are. CNN did a

436
00:23:25,480 --> 00:23:27,320
Speaker 1: good job, and we said they did a good job.

437
00:23:27,480 --> 00:23:30,600
Speaker 1: And I know that Biden. Now people say, well, that's

438
00:23:30,640 --> 00:23:33,159
Speaker 1: because they wanted Biden to be out. Yeah, but I mean,

439
00:23:33,160 --> 00:23:35,840
Speaker 1: they can't make Biden have dementia. Like all they did

440
00:23:35,880 --> 00:23:37,960
Speaker 1: was run a fair debate and that was enough for

441
00:23:38,040 --> 00:23:41,880
Speaker 1: Biden itself, you know, to reveal it right to try

442
00:23:41,920 --> 00:23:44,320
Speaker 1: to cover for a guy with dementia in that situation, Like,

443
00:23:44,400 --> 00:23:46,480
Speaker 1: I don't know what CNN really could have done there,

444
00:23:46,520 --> 00:23:51,600
Speaker 1: But the point is the questions were fair. They didn't

445
00:23:51,640 --> 00:23:54,720
Speaker 1: interrupt one side and not the other, they didn't fact

446
00:23:54,800 --> 00:23:57,280
Speaker 1: check one side and not the other. They let the

447
00:23:57,320 --> 00:24:01,080
Speaker 1: two people on the stage speak, and the question weren't, Hey,

448
00:24:01,160 --> 00:24:04,199
Speaker 1: Donald Trump, you're like a flandering scumbag, Like what's it

449
00:24:04,280 --> 00:24:07,080
Speaker 1: like to be that way? I mean, you know, last

450
00:24:07,160 --> 00:24:09,720
Speaker 1: night was the worst of everything from from the moderator

451
00:24:09,800 --> 00:24:11,520
Speaker 1: side of things. So I do think that going forward

452
00:24:11,520 --> 00:24:13,840
Speaker 1: they should just say, you know, if CNN is willing

453
00:24:13,840 --> 00:24:15,920
Speaker 1: to run a fair debate, maybe you do see Ann again,

454
00:24:16,520 --> 00:24:19,000
Speaker 1: you know, under the same kind of auspices in the past.

455
00:24:19,040 --> 00:24:22,679
Speaker 1: But ABC News was a total catastrophe. I really, people,

456
00:24:23,040 --> 00:24:25,639
Speaker 1: I might have missed this again. Trump was a little,

457
00:24:26,080 --> 00:24:28,080
Speaker 1: a little meandery. He also didn't seem like he was

458
00:24:28,080 --> 00:24:31,000
Speaker 1: having fun. One of the things about Trump that is

459
00:24:31,080 --> 00:24:36,840
Speaker 1: so infectious, that is just so powerful politically, Clay is

460
00:24:37,160 --> 00:24:40,480
Speaker 1: he's having a good time with it. He loves the country,

461
00:24:40,560 --> 00:24:43,320
Speaker 1: he loves the people, and he's out there and he's

462
00:24:43,320 --> 00:24:47,480
Speaker 1: doing his thing, and he's he's indefatigable and he's unflappable.

463
00:24:48,000 --> 00:24:51,439
Speaker 1: And he's having fun, and last night he looked a

464
00:24:51,480 --> 00:24:54,960
Speaker 1: little bit like, you know, somebody didn't have enough milk

465
00:24:54,960 --> 00:24:57,800
Speaker 1: for his cheerios or something like. It wasn't the Trump

466
00:24:57,840 --> 00:24:59,960
Speaker 1: that we're used to now. I think part of the

467
00:25:00,119 --> 00:25:03,480
Speaker 1: that was Kamala was you know, irking him, purposely going

468
00:25:03,560 --> 00:25:07,159
Speaker 1: at him on some things. But you know, he didn't

469
00:25:07,200 --> 00:25:09,200
Speaker 1: smile that much. I mean, it just wasn't the true

470
00:25:09,240 --> 00:25:12,520
Speaker 1: It wasn't the best of Trump. Even it's not like

471
00:25:12,920 --> 00:25:14,520
Speaker 1: not like I'm saying, why isn't he all of a

472
00:25:14,520 --> 00:25:17,399
Speaker 1: sudden the second coming of Cicero. I mean, it wasn't

473
00:25:17,400 --> 00:25:19,199
Speaker 1: the best of Trump, and that I think is part

474
00:25:19,240 --> 00:25:21,679
Speaker 1: of the frustration. But again, I don't know. I mean,

475
00:25:21,720 --> 00:25:23,720
Speaker 1: I think a debate that's not a disaster, it doesn't

476
00:25:23,760 --> 00:25:26,600
Speaker 1: really matter to people very much. Barack Obama twenty and

477
00:25:26,840 --> 00:25:31,560
Speaker 1: twelve first debate was horrible, horrible even his own side

478
00:25:31,800 --> 00:25:35,120
Speaker 1: there there was almost like anti Obama coup to push

479
00:25:35,200 --> 00:25:37,040
Speaker 1: him out. I mean, didn't quite get that bad, but

480
00:25:37,080 --> 00:25:39,560
Speaker 1: they were freaking out about how badly he did, and

481
00:25:39,640 --> 00:25:43,480
Speaker 1: he crushed Mitt Romney. I think to your point on

482
00:25:43,560 --> 00:25:47,320
Speaker 1: the moderator, I said this yesterday, I've been saying it

483
00:25:47,320 --> 00:25:50,280
Speaker 1: for a long time. If you leave a debate talking

484
00:25:50,280 --> 00:25:54,680
Speaker 1: about the moderators, they failed. Now for their purposes, they

485
00:25:54,800 --> 00:25:58,639
Speaker 1: wanted to rig things for Kamala, but Jake Tapper and

486
00:25:58,760 --> 00:26:00,399
Speaker 1: Dana bash I had to go back and look up

487
00:26:00,400 --> 00:26:02,640
Speaker 1: who exactly were the moderators for CNN.

488
00:26:03,320 --> 00:26:06,640
Speaker 2: They provided a forum for the candidates to express their

489
00:26:06,680 --> 00:26:10,600
Speaker 2: differences and debate each other. You should be in the

490
00:26:10,640 --> 00:26:13,879
Speaker 2: business of getting out of the way. I think for

491
00:26:14,000 --> 00:26:17,600
Speaker 2: many people out there, the reaction today is Trump walked

492
00:26:17,640 --> 00:26:22,359
Speaker 2: into a ambush, and he should have been prepared for

493
00:26:22,400 --> 00:26:24,800
Speaker 2: the ambush, and he didn't acquit himself as well as

494
00:26:24,800 --> 00:26:29,960
Speaker 2: he could have given those scenarios. To me, the biggest

495
00:26:30,000 --> 00:26:33,159
Speaker 2: takeaway is going to be how long.

496
00:26:32,960 --> 00:26:34,360
Speaker 3: Does this story linger.

497
00:26:35,800 --> 00:26:39,320
Speaker 2: The thing about Biden's performance on June twenty seventh wasn't

498
00:26:39,400 --> 00:26:42,560
Speaker 2: just that he was a disaster on June twenty seventh.

499
00:26:42,960 --> 00:26:45,360
Speaker 2: It's that the media put him in the spin cycle,

500
00:26:45,560 --> 00:26:48,080
Speaker 2: and they didn't allow him to get out until he

501
00:26:48,160 --> 00:26:49,800
Speaker 2: had to drop out on July twenty.

502
00:26:49,800 --> 00:26:50,119
Speaker 1: First.

503
00:26:50,680 --> 00:26:53,080
Speaker 2: They trained all of their attention on it. They didn't

504
00:26:53,119 --> 00:26:57,399
Speaker 2: allow it to alter. My suspicion, and it's just a suspicion,

505
00:26:57,840 --> 00:27:00,760
Speaker 2: is they're going to try to do it with this debate.

506
00:27:01,080 --> 00:27:04,200
Speaker 2: They're going to try to make it a multi day,

507
00:27:04,840 --> 00:27:08,600
Speaker 2: multi week story to try to drive it in the

508
00:27:08,640 --> 00:27:12,760
Speaker 2: same way Buck that they basically eliminated the assassination attempt

509
00:27:12,800 --> 00:27:15,479
Speaker 2: of Donald Trump. I mean, it really is a great

510
00:27:15,520 --> 00:27:17,639
Speaker 2: study for some of you out there, of your kids.

511
00:27:18,720 --> 00:27:23,000
Speaker 2: Jan six. They have spent four years talking about. They

512
00:27:23,040 --> 00:27:25,919
Speaker 2: won't allow it to escape the news cycles, such that

513
00:27:26,000 --> 00:27:30,960
Speaker 2: we got a direct Jan six question in yesterday. They

514
00:27:31,040 --> 00:27:34,159
Speaker 2: didn't ask about the assassination attempt on Trump, which happened

515
00:27:34,200 --> 00:27:37,400
Speaker 2: on July thirteenth, because they are trying to memory hold

516
00:27:37,480 --> 00:27:41,119
Speaker 2: it and pretend it never existed. I wish Trump when

517
00:27:41,160 --> 00:27:43,639
Speaker 2: he got his rallies made fun of again, who the

518
00:27:43,720 --> 00:27:47,119
Speaker 2: fuck that gotta be careful? Who cares how many people

519
00:27:47,200 --> 00:27:48,040
Speaker 2: go to the rallies?

520
00:27:48,640 --> 00:27:50,480
Speaker 3: Trump does? This goes back to my issue.

521
00:27:50,880 --> 00:27:53,160
Speaker 1: Unfortunately Trump does. That's the problem, right.

522
00:27:53,119 --> 00:27:54,240
Speaker 3: This goes back to my thing.

523
00:27:54,600 --> 00:27:57,679
Speaker 2: If I ever got inaugurated president of the United States

524
00:27:57,720 --> 00:28:01,240
Speaker 2: and four people showed up and the crowd wasn't very big,

525
00:28:01,480 --> 00:28:04,120
Speaker 2: I'd be like that kind of stings. I guess it's

526
00:28:04,119 --> 00:28:07,200
Speaker 2: cold in DC, but I'm the frigging president. It doesn't

527
00:28:07,200 --> 00:28:09,359
Speaker 2: matter how many people show up to wait, make me

528
00:28:09,600 --> 00:28:12,359
Speaker 2: raise my right hand. I wish Trump had seen that

529
00:28:12,440 --> 00:28:15,679
Speaker 2: attack coming and instead, which he could and should have,

530
00:28:16,040 --> 00:28:18,280
Speaker 2: and instead of going down the rabbit hole of my

531
00:28:18,520 --> 00:28:21,000
Speaker 2: rallies are great people, if he had said, I'm glad

532
00:28:21,040 --> 00:28:23,920
Speaker 2: you brought up the rallies, Kamala. We lost a brave

533
00:28:24,000 --> 00:28:27,119
Speaker 2: American patriot who came to Butler, Pennsylvania to watch me.

534
00:28:28,040 --> 00:28:30,800
Speaker 2: I think about him every single day, and that's what

535
00:28:30,840 --> 00:28:33,359
Speaker 2: I'm fighting for. That's why right after they tried to

536
00:28:33,440 --> 00:28:35,719
Speaker 2: kill me and they hit me with a bullet, I

537
00:28:35,800 --> 00:28:38,400
Speaker 2: got up and said, fight, fight, fight, because I'm in

538
00:28:38,440 --> 00:28:40,760
Speaker 2: this to win this, to fight on behalf of innocent

539
00:28:40,840 --> 00:28:43,760
Speaker 2: people that are getting taken advantage of in this country

540
00:28:43,800 --> 00:28:47,320
Speaker 2: every single day the pit. And that's me just reacting

541
00:28:47,400 --> 00:28:50,080
Speaker 2: like we said this yesterday, Buck, and I'll say it again.

542
00:28:50,600 --> 00:28:53,720
Speaker 2: I would pay millions of dollars to have had a

543
00:28:53,760 --> 00:28:57,680
Speaker 2: freaky Friday opportunity where you or I could be inside

544
00:28:57,720 --> 00:29:00,640
Speaker 2: of Donald Trump's body to answer every question and to

545
00:29:00,640 --> 00:29:03,360
Speaker 2: get to debate against Kamala, because I think we would

546
00:29:03,360 --> 00:29:05,760
Speaker 2: have knocked her out. I think if you or I

547
00:29:05,840 --> 00:29:07,600
Speaker 2: had been on that stage, we would have knocked her out,

548
00:29:07,600 --> 00:29:10,640
Speaker 2: not because we're excellent debaters, but because Kamala is such

549
00:29:10,640 --> 00:29:14,800
Speaker 2: a uniquely far left wing, lying, awful candidate that her

550
00:29:14,960 --> 00:29:18,240
Speaker 2: chin was exposed the whole night, and Trump got very

551
00:29:18,360 --> 00:29:21,960
Speaker 2: limited contact on what should have been one knockout punch

552
00:29:22,000 --> 00:29:24,520
Speaker 2: after another, And it started with that first question. He

553
00:29:24,520 --> 00:29:26,920
Speaker 2: could have put her in the corner standing eight count style.

554
00:29:26,960 --> 00:29:29,959
Speaker 2: When she couldn't answer the question about whether things are

555
00:29:30,000 --> 00:29:32,360
Speaker 2: better now than four years ago, he led her off

556
00:29:32,400 --> 00:29:33,959
Speaker 2: the hook one time after another.

557
00:29:34,040 --> 00:29:35,840
Speaker 3: I think that's what made it so frustrating to me

558
00:29:35,920 --> 00:29:36,600
Speaker 3: to watch.

559
00:29:36,800 --> 00:29:39,480
Speaker 1: Take some of your calls on this one. Agreed, disagree,

560
00:29:39,520 --> 00:29:42,480
Speaker 1: We want to hear it. Light us up. One out

561
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Speaker 5: Have fun with the guys on Sundays This Sunday Hang podcast,

577
00:30:36,200 --> 00:30:40,040
Speaker 5: It's Silly, It's Goofy, It's good times. Fight it in

578
00:30:40,120 --> 00:30:43,240
Speaker 5: the Clay and Buck podcast feed on the iHeartRadio app

579
00:30:43,360 --> 00:30:45,320
Speaker 5: or wherever you get your podcasts.

580
00:30:45,360 --> 00:30:49,560
Speaker 1: Our friend, Ryan Gridusky joins us. He is the author

581
00:30:49,600 --> 00:30:53,560
Speaker 1: of the National's populist newsletter on Substack, also founder of

582
00:30:53,600 --> 00:30:57,239
Speaker 1: the seventeen seventy six Project Pack. Ryan, good to have

583
00:30:57,320 --> 00:30:58,400
Speaker 1: you as always.

584
00:30:59,080 --> 00:30:59,920
Speaker 6: Thanks for having me.

585
00:31:00,880 --> 00:31:04,840
Speaker 1: Let's take a look first at the numbers as you

586
00:31:05,040 --> 00:31:08,680
Speaker 1: see them today, the day after the debate. What are

587
00:31:08,720 --> 00:31:11,360
Speaker 1: the debate numbers and what are the poll numbers looking like?

588
00:31:11,520 --> 00:31:13,800
Speaker 1: As much as we can dive into that data.

589
00:31:14,720 --> 00:31:16,959
Speaker 6: So in the debate numbers, we'll start with that, the

590
00:31:17,000 --> 00:31:21,560
Speaker 6: CNN insta pole results had Kamala winning the debate with

591
00:31:21,640 --> 00:31:25,040
Speaker 6: sixty three percent and Trump having thirty seven percent. Thirty

592
00:31:25,040 --> 00:31:27,680
Speaker 6: seven percent of viewers said Trump won sixty three percent.

593
00:31:27,760 --> 00:31:30,960
Speaker 6: Can I say Kamala one? This is fairly in line

594
00:31:31,000 --> 00:31:35,080
Speaker 6: with almost every single debate Trump has ever had CNN

595
00:31:35,400 --> 00:31:37,959
Speaker 6: instapoles that chem I mean, which are not you know

596
00:31:38,080 --> 00:31:42,120
Speaker 6: signs because it's right afterwards only among viewers, Trump will

597
00:31:42,120 --> 00:31:45,720
Speaker 6: got twenty seven percent versus Hillary's sixty two percent in

598
00:31:45,800 --> 00:31:50,000
Speaker 6: twenty sixteen, and in twenty twenty the first debate with Biden,

599
00:31:50,040 --> 00:31:53,959
Speaker 6: he got twenty eight percent to Biden's sixty percent. Trump

600
00:31:54,040 --> 00:31:57,440
Speaker 6: is not a very good debater, never really has been.

601
00:31:57,720 --> 00:32:00,760
Speaker 6: With the sole exception of the Life Last debate with

602
00:32:00,840 --> 00:32:04,840
Speaker 6: Joe Biden, Trump has never won a single debate in

603
00:32:04,880 --> 00:32:09,240
Speaker 6: a CNN instapole. Going into how he's performing election wise,

604
00:32:09,480 --> 00:32:14,760
Speaker 6: according to all the major poll aggregate websites. In the

605
00:32:14,920 --> 00:32:19,160
Speaker 6: national polls, Trump is either behind from one point to

606
00:32:19,280 --> 00:32:23,080
Speaker 6: three points, and that's according to pol agragil gets including

607
00:32:23,160 --> 00:32:26,160
Speaker 6: Nate Silver, including five thirty eight, the Economist Race to

608
00:32:26,200 --> 00:32:29,960
Speaker 6: the White House Voter Hub jaje k forecast. They all

609
00:32:30,000 --> 00:32:33,960
Speaker 6: have Kamala with a lead, but it's a slight lead.

610
00:32:34,000 --> 00:32:37,120
Speaker 6: It's a lead between one and three points. As I said,

611
00:32:37,200 --> 00:32:40,440
Speaker 6: if there is a p in Comma's favor, the same

612
00:32:40,440 --> 00:32:44,320
Speaker 6: way there was a polling error in Joe Biden's favor

613
00:32:44,400 --> 00:32:47,880
Speaker 6: in twenty twenty and in Hillary's favor in twenty sixteen,

614
00:32:47,920 --> 00:32:51,160
Speaker 6: although Hillaries was in the margin of error that would

615
00:32:51,160 --> 00:32:56,240
Speaker 6: put Kamala at about a point ahead of Trump nationally,

616
00:32:56,280 --> 00:32:59,200
Speaker 6: which is what you're looking at the last three major

617
00:32:59,280 --> 00:33:02,880
Speaker 6: polls that came out all within the span of last

618
00:33:03,280 --> 00:33:06,040
Speaker 6: seventy two hours or last week. Rather the New York

619
00:33:06,040 --> 00:33:08,320
Speaker 6: Times Sienna Pole which had Trump up one point, the

620
00:33:08,360 --> 00:33:11,880
Speaker 6: Marquete Pole, which had Horsed up by one point. I

621
00:33:11,920 --> 00:33:13,760
Speaker 6: was sorry that was the Maris pole that had a

622
00:33:13,840 --> 00:33:17,440
Speaker 6: Comma up one point. The uh and then the Pew

623
00:33:17,480 --> 00:33:19,520
Speaker 6: Research poll which had at a dead tie are all

624
00:33:19,520 --> 00:33:23,520
Speaker 6: telling about the same story, which is a close national race.

625
00:33:24,840 --> 00:33:27,560
Speaker 2: Ryan, Isn't this race just gonna come down to who

626
00:33:27,560 --> 00:33:30,880
Speaker 2: wins Pennsylvania? If you had to say, I want to

627
00:33:30,920 --> 00:33:34,640
Speaker 2: know one state and I told you the exact results

628
00:33:34,640 --> 00:33:38,880
Speaker 2: for Pennsylvania, couldn't you tell almost entirely based on how

629
00:33:38,880 --> 00:33:41,480
Speaker 2: Pennsylvania votes. What's going to happen in the national race.

630
00:33:42,600 --> 00:33:45,080
Speaker 6: So I wrote this in the National Populis Substack, my

631
00:33:45,160 --> 00:33:48,120
Speaker 6: Nationalpis newsletter on substack. There are three states that will

632
00:33:48,120 --> 00:33:51,959
Speaker 6: decide this election. Georgia, North Carolina, and Pennsylvania. Those are

633
00:33:52,000 --> 00:33:57,640
Speaker 6: the three. If it guarantee, whatever happens in those three states,

634
00:33:57,880 --> 00:34:00,560
Speaker 6: there is no way for the winner of those three

635
00:34:00,600 --> 00:34:04,040
Speaker 6: states to lose nationally. So yeah, Pennsylvania is one of

636
00:34:04,080 --> 00:34:06,880
Speaker 6: the three, and it is the largest electoral getter of

637
00:34:06,920 --> 00:34:10,360
Speaker 6: the three at most most amount of Electoral College votes

638
00:34:10,400 --> 00:34:12,840
Speaker 6: of the three. But those are the three that decide.

639
00:34:12,840 --> 00:34:14,480
Speaker 6: They're all on these coasts.

640
00:34:14,040 --> 00:34:16,080
Speaker 2: And you would sorry, sorry to cut you off, but

641
00:34:16,080 --> 00:34:18,200
Speaker 2: Trump would be in the lead in Georgia and North

642
00:34:18,239 --> 00:34:23,200
Speaker 2: Carolina based on general consensus, gambling markets, all those things,

643
00:34:23,480 --> 00:34:26,440
Speaker 2: and Pennsylvania basically is a straight toss up.

644
00:34:27,920 --> 00:34:30,600
Speaker 6: In most of the ones that factor in things like

645
00:34:30,680 --> 00:34:33,880
Speaker 6: polling errors. North Carolina and Georgia are within Trump or

646
00:34:34,160 --> 00:34:38,640
Speaker 6: Trump a very small lead, and have Harris has a

647
00:34:38,800 --> 00:34:42,359
Speaker 6: very small lead in Pennsylvania. They average out that North

648
00:34:42,400 --> 00:34:46,919
Speaker 6: Carolina and Georgia have about a lead of about half

649
00:34:46,920 --> 00:34:50,160
Speaker 6: a point for Trump and lead for Harris by one

650
00:34:50,160 --> 00:34:53,040
Speaker 6: point in Pennsylvania. But I will I will sit there

651
00:34:53,080 --> 00:34:59,680
Speaker 6: and say North Carolina and Pennsylvania polsters usually oversample Democrats

652
00:35:00,160 --> 00:35:04,640
Speaker 6: these polls Georgia, they usually oversample Republicans. Georgia, like many

653
00:35:04,719 --> 00:35:09,640
Speaker 6: other states, including Texas, Virginia, Wisconsin, do not register voters

654
00:35:09,680 --> 00:35:12,640
Speaker 6: by party. They just register to vote, and they vote

655
00:35:12,640 --> 00:35:14,360
Speaker 6: in the primaries in which they want to vote. In

656
00:35:14,800 --> 00:35:18,359
Speaker 6: Pennsylvania and North Carolina registered voters by party, it's a

657
00:35:18,400 --> 00:35:22,279
Speaker 6: lot easier than they aren't identified voters based upon you know,

658
00:35:22,280 --> 00:35:24,759
Speaker 6: if they're actually a Democrat or actually a Republican in

659
00:35:24,800 --> 00:35:30,280
Speaker 6: those states. But Georgia typically the polls usually overly favor Republicans,

660
00:35:30,320 --> 00:35:34,239
Speaker 6: and in North Carolina and Pennsylvania they overly favor Democrats.

661
00:35:35,360 --> 00:35:39,080
Speaker 1: So Ryan, as far as you can tell and as

662
00:35:39,080 --> 00:35:42,080
Speaker 1: far as the numbers are are speaking to this are

663
00:35:42,080 --> 00:35:47,880
Speaker 1: we essentially guaranteed a very tight election in terms of

664
00:35:48,000 --> 00:35:51,239
Speaker 1: just the vote totals in the states that matter. When

665
00:35:51,280 --> 00:35:53,600
Speaker 1: all said and don I mean, is there any way

666
00:35:53,680 --> 00:35:55,480
Speaker 1: that you could see this turning into some kind of

667
00:35:55,480 --> 00:35:57,720
Speaker 1: a route I mean.

668
00:35:58,160 --> 00:35:58,600
Speaker 6: Could there?

669
00:35:58,719 --> 00:35:58,879
Speaker 3: Yeah?

670
00:35:59,040 --> 00:36:01,720
Speaker 6: Nate silver as this as a rapit they have Trump

671
00:36:01,760 --> 00:36:05,080
Speaker 6: winning every single swing state. Most other predictors say it

672
00:36:05,080 --> 00:36:07,000
Speaker 6: will split. The Sun Belt will go for Trump, the

673
00:36:07,080 --> 00:36:10,120
Speaker 6: Roughs Belt will go for Kamala. I do not believe that, though.

674
00:36:10,200 --> 00:36:12,920
Speaker 6: I think that there is a massive polling era, as

675
00:36:12,920 --> 00:36:14,920
Speaker 6: I've written about this over and over again, where they

676
00:36:14,960 --> 00:36:19,800
Speaker 6: are overpolling old liberal voters who have a heavy response bias.

677
00:36:20,040 --> 00:36:22,560
Speaker 6: Their answering polls are too high of a number. In

678
00:36:22,640 --> 00:36:25,840
Speaker 6: the Survey USA and Quinnepiac poll, I think Survey USA

679
00:36:25,920 --> 00:36:29,799
Speaker 6: had Trump up by five among North Carolina seniors and

680
00:36:29,920 --> 00:36:33,359
Speaker 6: Quinnepiac had I think Comma up eight or nine among

681
00:36:33,440 --> 00:36:37,040
Speaker 6: North Carolina seniors. That's a demographic that is heavily Republican.

682
00:36:37,080 --> 00:36:39,680
Speaker 6: Trump won it by twenty points last time, and I

683
00:36:39,680 --> 00:36:43,160
Speaker 6: think by about nineteen points the time before. It's a heavy, heavy,

684
00:36:43,200 --> 00:36:47,920
Speaker 6: heavy Republican demographic. There's no way on this planet that

685
00:36:48,040 --> 00:36:51,040
Speaker 6: it's going to even resemble close to that. Poles and

686
00:36:51,080 --> 00:36:54,480
Speaker 6: why I say seniors over like African Americans or Hispanics,

687
00:36:54,480 --> 00:36:57,200
Speaker 6: which are a very small sample size in the sub sect,

688
00:36:57,560 --> 00:37:00,880
Speaker 6: Seniors are about third thirty percent of time twenty five percent,

689
00:37:01,160 --> 00:37:03,600
Speaker 6: so it's a very large sample size. It is a

690
00:37:03,680 --> 00:37:06,080
Speaker 6: very small margin of error. So when you're talking about

691
00:37:06,120 --> 00:37:10,720
Speaker 6: a twenty five thirty point twenty point difference between elections

692
00:37:10,760 --> 00:37:15,359
Speaker 6: and polls. With subsets of cross tabs, you're looking at

693
00:37:15,400 --> 00:37:17,840
Speaker 6: a real response bias, and this was true of the

694
00:37:17,920 --> 00:37:20,880
Speaker 6: response bias in twenty twenty and in twenty sixteen. The

695
00:37:21,040 --> 00:37:24,719
Speaker 6: illusion of the silent Trump voter often comes from the

696
00:37:24,719 --> 00:37:29,680
Speaker 6: fact that seniors, old liberal seniors are oversampled in these polls.

697
00:37:29,760 --> 00:37:33,759
Speaker 6: They want polsters to know their opinion. Old liberals love

698
00:37:33,880 --> 00:37:36,360
Speaker 6: to tell you their opinions. At this point, they're calling

699
00:37:36,400 --> 00:37:37,960
Speaker 6: polsters and like, hey, do you want to hear.

700
00:37:37,800 --> 00:37:38,960
Speaker 1: My opinion on this election?

701
00:37:39,560 --> 00:37:42,719
Speaker 6: That is what we're seeing over and over and over again.

702
00:37:42,920 --> 00:37:44,520
Speaker 6: I think that's where you're going to sit there and

703
00:37:44,520 --> 00:37:48,360
Speaker 6: see Trump gain a point nationally is in the senior vote.

704
00:37:48,400 --> 00:37:51,319
Speaker 6: And that's where states like Pennsylvania, North Carolina could very

705
00:37:51,320 --> 00:37:54,400
Speaker 6: well easily decided. And none of these holes have the debate.

706
00:37:54,680 --> 00:37:58,600
Speaker 6: You know in if factored in, Kamala very well likely

707
00:37:58,680 --> 00:38:02,239
Speaker 6: may see a bump because Trump's very poor performance in

708
00:38:02,280 --> 00:38:06,680
Speaker 6: the debate last night, But that will who knows how

709
00:38:06,719 --> 00:38:09,040
Speaker 6: long that will last. For it they typically do not

710
00:38:09,239 --> 00:38:12,960
Speaker 6: last all the way to election day, So a lot

711
00:38:13,000 --> 00:38:15,759
Speaker 6: of people have lost their first debates went on to

712
00:38:15,800 --> 00:38:19,680
Speaker 6: win their election. Barack Obama, Donald Trump, George W. Bush

713
00:38:19,760 --> 00:38:22,719
Speaker 6: lost his first debate pretty badly, and they all won

714
00:38:22,800 --> 00:38:25,880
Speaker 6: their election. So it doesn't mean, you know, it's definite

715
00:38:26,239 --> 00:38:28,240
Speaker 6: for that it will definitely decide the election.

716
00:38:29,000 --> 00:38:31,799
Speaker 2: The answer may be yes, but our buck and eye

717
00:38:31,880 --> 00:38:37,360
Speaker 2: crazy for looking in the Midwest and saying just on

718
00:38:37,640 --> 00:38:40,319
Speaker 2: our belief I think he and I are aligned on this.

719
00:38:41,080 --> 00:38:46,520
Speaker 2: Old white people in Pennsylvania, Wisconsin, and Michigan in particular

720
00:38:47,239 --> 00:38:51,200
Speaker 2: are not going to support Kamala as much as they

721
00:38:51,239 --> 00:38:55,399
Speaker 2: supported Biden. The Scranton Joe appeal. While we may think

722
00:38:55,440 --> 00:38:58,400
Speaker 2: it was bs based on the way he governed, did

723
00:38:58,600 --> 00:39:03,600
Speaker 2: persuade some old white moderate voters in those big ten states.

724
00:39:04,000 --> 00:39:08,120
Speaker 2: That's how he won in twenty twenty, there's no again,

725
00:39:08,280 --> 00:39:10,600
Speaker 2: I think there's no way that Kamala gets that same

726
00:39:10,719 --> 00:39:13,719
Speaker 2: level of support. So this part of this is is

727
00:39:13,760 --> 00:39:16,600
Speaker 2: there a black or Hispanic vote that she's gaining or

728
00:39:16,880 --> 00:39:19,400
Speaker 2: could that be dispositive for you in the Midwest.

729
00:39:20,360 --> 00:39:23,160
Speaker 6: So there's two groups that will change it for Kamala.

730
00:39:23,239 --> 00:39:25,719
Speaker 6: One is gen Z because there are millions of new

731
00:39:25,800 --> 00:39:29,640
Speaker 6: voters that were not registered to vote four years ago

732
00:39:29,920 --> 00:39:32,960
Speaker 6: that will be tilting heavily towards Kamala. That was a

733
00:39:33,040 --> 00:39:35,600
Speaker 6: huge fact in the twenty twenty two election, and abortion

734
00:39:35,760 --> 00:39:38,960
Speaker 6: is a major issue for them. The second is that

735
00:39:39,000 --> 00:39:44,440
Speaker 6: there have been three point three million new naturalized citizens

736
00:39:44,680 --> 00:39:47,839
Speaker 6: legal immigrants who vote two and a half or three

737
00:39:47,880 --> 00:39:53,480
Speaker 6: to one Democrat since the twenty twenty election. President Biden

738
00:39:53,680 --> 00:39:56,719
Speaker 6: ramped up the speed in which people became citizens for

739
00:39:56,840 --> 00:40:01,399
Speaker 6: a reason they vote heavily Democrat during the last year

740
00:40:01,440 --> 00:40:04,719
Speaker 6: of the last few years of Obama's presidency, where he

741
00:40:04,880 --> 00:40:08,360
Speaker 6: was pushing for refugee resettlements, like the same way that

742
00:40:08,400 --> 00:40:11,759
Speaker 6: Biden where he's pushing a refugee resettlement is oftentimes in

743
00:40:11,840 --> 00:40:14,640
Speaker 6: swing states. So that's why you see huge clusters of

744
00:40:15,560 --> 00:40:18,879
Speaker 6: migrant voters going to swing state places where you're like,

745
00:40:18,960 --> 00:40:21,240
Speaker 6: this isn't weird. It's not like there's a huge Haitian

746
00:40:21,320 --> 00:40:25,680
Speaker 6: population in Springfield, Ohio. Now they're being purposely put into

747
00:40:25,800 --> 00:40:29,080
Speaker 6: swing states, and three point three million new people who

748
00:40:29,160 --> 00:40:31,920
Speaker 6: could vote, who will overwhelmingly be voting Democrat, as well

749
00:40:31,960 --> 00:40:35,120
Speaker 6: as the millions of new Gen Z voters will definitely

750
00:40:35,239 --> 00:40:37,960
Speaker 6: play a huge factor in it. The thing that they

751
00:40:38,000 --> 00:40:41,000
Speaker 6: need to sit there and to change that is they

752
00:40:41,040 --> 00:40:45,240
Speaker 6: need to increase voter turnout among non college educated whites.

753
00:40:45,480 --> 00:40:47,759
Speaker 6: Non college educated whites have the and I've said this

754
00:40:47,800 --> 00:40:51,600
Speaker 6: on your show before, have the worst voter participation among

755
00:40:51,680 --> 00:40:55,680
Speaker 6: any demographic except for recent immigrants. They do not vote

756
00:40:55,680 --> 00:40:59,920
Speaker 6: in high numbers. If they voted as often as whites

757
00:41:00,080 --> 00:41:03,439
Speaker 6: with a college degree, did it, I mean Oregon would

758
00:41:03,480 --> 00:41:05,760
Speaker 6: be a red state. It wouldn't even be a close election.

759
00:41:05,880 --> 00:41:08,279
Speaker 6: Virginia would be a red state. It's just a matter

760
00:41:08,320 --> 00:41:11,839
Speaker 6: of turnout. Trump is going to improve performance among Hispanics

761
00:41:11,880 --> 00:41:15,440
Speaker 6: and among Asians and among blacks. But this election is

762
00:41:15,520 --> 00:41:17,960
Speaker 6: boiled down to the white vote. Do whites without a

763
00:41:17,960 --> 00:41:20,560
Speaker 6: college degree turn up? Do they show up for Trump?

764
00:41:21,280 --> 00:41:23,399
Speaker 6: And do they feel like Kamala does not have their

765
00:41:23,400 --> 00:41:24,480
Speaker 6: best interests?

766
00:41:25,120 --> 00:41:27,440
Speaker 1: What do you think is the most important focus the

767
00:41:27,480 --> 00:41:30,080
Speaker 1: Trump campaign can have between now an election day so

768
00:41:30,120 --> 00:41:33,400
Speaker 1: that we don't have a super sad day coming up

769
00:41:33,440 --> 00:41:35,440
Speaker 1: in November where we have to have Ryan on have

770
00:41:35,480 --> 00:41:36,520
Speaker 1: a big cry session.

771
00:41:38,520 --> 00:41:41,520
Speaker 6: You know, I think that Kamala Harris, at the age

772
00:41:41,520 --> 00:41:44,360
Speaker 6: of sixty, had a major life event where she changed

773
00:41:44,400 --> 00:41:48,600
Speaker 6: all of her beliefs overnight. Trump could have cornered her

774
00:41:48,640 --> 00:41:51,880
Speaker 6: on all those things. And I'm not talking about just fracking,

775
00:41:51,880 --> 00:41:53,640
Speaker 6: which was the issue they brought up over and over again.

776
00:41:53,840 --> 00:41:58,399
Speaker 6: She was radical on things like reparations, which is an

777
00:41:58,560 --> 00:42:03,720
Speaker 6: enormously unpopular idea. Kamala Harris supported a multi trillion dollar

778
00:42:03,840 --> 00:42:08,200
Speaker 6: reparation plan for the descendants of slaves. This is something

779
00:42:08,239 --> 00:42:11,279
Speaker 6: that's overwhelming and not only opposed by white voters, but

780
00:42:11,320 --> 00:42:14,279
Speaker 6: it's opposed by Asians and Hispanic voters who feel like

781
00:42:14,320 --> 00:42:16,400
Speaker 6: they were never part of the Civil War or anything

782
00:42:16,440 --> 00:42:19,479
Speaker 6: that followed it. I would bring up that. I would

783
00:42:19,520 --> 00:42:22,200
Speaker 6: bring up the fact that she was very radical left

784
00:42:22,239 --> 00:42:25,160
Speaker 6: on a number of issues, from taxes to the Green

785
00:42:25,239 --> 00:42:30,440
Speaker 6: New Deal to gun confiscation. She had a major life

786
00:42:30,480 --> 00:42:33,319
Speaker 6: change in one thousand days where she changed all of

787
00:42:33,320 --> 00:42:37,000
Speaker 6: her fundamental beliefs. She went from being a Bernie Sanders

788
00:42:37,040 --> 00:42:41,880
Speaker 6: Democrat to being, you know, a pro choice George W.

789
00:42:42,000 --> 00:42:45,680
Speaker 6: Bush Republican in one thousand days, when she is close

790
00:42:45,719 --> 00:42:49,320
Speaker 6: to being a senior citizen. Life transformations don't usually happen

791
00:42:49,440 --> 00:42:52,920
Speaker 6: that free, at at that age, that quickly, but for

792
00:42:52,960 --> 00:42:56,040
Speaker 6: some reason, she did. And I think cornering her on

793
00:42:56,120 --> 00:42:59,200
Speaker 6: who she actually is, who is the real Kamala Harris,

794
00:42:59,560 --> 00:43:02,440
Speaker 6: is the thing because the beliefs that she had in

795
00:43:02,480 --> 00:43:05,439
Speaker 6: twenty nineteen were so unpopular not even Democrats would vote

796
00:43:05,440 --> 00:43:07,399
Speaker 6: for her. And that's what you need to because that's

797
00:43:07,440 --> 00:43:09,839
Speaker 6: and that's why she's running basically as a pro choice

798
00:43:09,880 --> 00:43:14,719
Speaker 6: Republican nowadays. I mean, she's about military, about cutting spending,

799
00:43:14,800 --> 00:43:18,480
Speaker 6: about you know, increasing child child tax credit.

800
00:43:18,480 --> 00:43:22,759
Speaker 1: It's about building a wall. She wants to build a wall, right, she.

801
00:43:22,680 --> 00:43:24,560
Speaker 6: Wants to build the wall. I mean, this is the

802
00:43:24,640 --> 00:43:29,680
Speaker 6: new Kamala Harris, a one thousand day life transformation. It's

803
00:43:29,719 --> 00:43:32,640
Speaker 6: never been seen before. And I think exposing that is

804
00:43:32,719 --> 00:43:33,400
Speaker 6: what she needed.

805
00:43:33,200 --> 00:43:37,000
Speaker 2: To sit there and say, you mentioned young voters. Taylor

806
00:43:37,120 --> 00:43:44,560
Speaker 2: Swift endorses right after the debate. It's clearly staged. But

807
00:43:45,320 --> 00:43:47,759
Speaker 2: what is the impact of someone like Taylor Swift? Do

808
00:43:47,760 --> 00:43:50,920
Speaker 2: you buy into celebrity endorsements moving anything?

809
00:43:52,280 --> 00:43:55,160
Speaker 6: I mean, back when celebrity was a real thing, like

810
00:43:55,200 --> 00:43:58,080
Speaker 6: when Oprah endorsed Obama, it was a real thing, but

811
00:43:58,160 --> 00:44:02,040
Speaker 6: there was a media was a much much more organized

812
00:44:02,080 --> 00:44:05,400
Speaker 6: around very few people, what real celebrities were. Taylor Should

813
00:44:05,480 --> 00:44:09,680
Speaker 6: is a real celebrity. I don't know how, I don't

814
00:44:09,920 --> 00:44:14,480
Speaker 6: I don't know what appeal Taylor has with especially young people.

815
00:44:14,760 --> 00:44:17,400
Speaker 6: The way that people, maybe people are older think to this,

816
00:44:17,680 --> 00:44:21,320
Speaker 6: Taylor's was almost middle aged. I mean, she's not twenty

817
00:44:21,400 --> 00:44:26,200
Speaker 6: one anymore. She's not Charlie XCX or uh or people

818
00:44:26,239 --> 00:44:28,719
Speaker 6: that younger people are always listening.

819
00:44:28,560 --> 00:44:32,840
Speaker 3: To TikTok knowledge No, but she's.

820
00:44:32,680 --> 00:44:34,760
Speaker 6: Been there for two she's been around for two decades.

821
00:44:34,760 --> 00:44:38,239
Speaker 6: She's not a young person. She's young, relatively young, but

822
00:44:38,280 --> 00:44:41,000
Speaker 6: she's not young young. She's not a twenty one year

823
00:44:41,000 --> 00:44:44,320
Speaker 6: old who excites people. And media is not where everyone

824
00:44:44,640 --> 00:44:47,480
Speaker 6: watched the same nine to ten things and that was

825
00:44:47,520 --> 00:44:50,600
Speaker 6: how we consume media. I don't know how much how

826
00:44:50,680 --> 00:44:52,640
Speaker 6: much appeal it has. I looked at people that I

827
00:44:52,719 --> 00:44:55,080
Speaker 6: knew on Instagram who maybe I didn't know their opinions,

828
00:44:55,080 --> 00:44:57,160
Speaker 6: and when they liked who liked it? Everyone I know

829
00:44:57,280 --> 00:44:59,319
Speaker 6: who I saw who liked it I knew was a

830
00:44:59,360 --> 00:45:02,120
Speaker 6: liberal who was voting for her. So I don't know

831
00:45:02,120 --> 00:45:04,640
Speaker 6: if that, really, you know, will change anyone's vote. Maybe

832
00:45:04,640 --> 00:45:06,440
Speaker 6: it will motivate some people to go out and get

833
00:45:06,440 --> 00:45:09,000
Speaker 6: out of a vote. She's clearly not campaigning for her

834
00:45:09,120 --> 00:45:12,120
Speaker 6: as of anything I've ever seen yet. And it didn't

835
00:45:12,120 --> 00:45:15,239
Speaker 6: help celebrities in twenty sixteen when they were all saying

836
00:45:15,280 --> 00:45:19,160
Speaker 6: they are campaigning heavily for Hillary Clinton. And you know

837
00:45:19,200 --> 00:45:22,279
Speaker 6: it's not like celebrities were you, like supported George W.

838
00:45:22,480 --> 00:45:22,760
Speaker 1: Bush.

839
00:45:22,920 --> 00:45:27,320
Speaker 6: We've never really seen celebrities in the modern age support Republican.

840
00:45:27,440 --> 00:45:32,480
Speaker 1: So remember that celebrity. Remember the celebrity montage they did

841
00:45:32,480 --> 00:45:35,359
Speaker 1: for Hillary with the fight song, and they had like

842
00:45:37,880 --> 00:45:39,320
Speaker 1: the level of cringe.

843
00:45:39,760 --> 00:45:43,080
Speaker 6: So they watched that like once a month. Yeah it's great.

844
00:45:43,160 --> 00:45:45,839
Speaker 1: Yeah, it's still very good. Brian or Dusky everybody. If

845
00:45:45,840 --> 00:45:47,920
Speaker 1: you want to know what's going on, follow him. Go

846
00:45:47,960 --> 00:45:51,359
Speaker 1: to the National Populace newsletter on substack. Ryan. Always great

847
00:45:51,360 --> 00:45:51,960
Speaker 1: to have you, buddy.

848
00:45:52,800 --> 00:45:53,160
Speaker 3: Thank you.

849
00:45:54,480 --> 00:45:57,640
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864
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865
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867
00:46:59,719 --> 00:47:03,239
Speaker 1: Radio s A b R E radio dot com or

868
00:47:03,760 --> 00:47:07,359
Speaker 1: call eight four four eight two four safe. That's eight

869
00:47:07,440 --> 00:47:10,080
Speaker 1: four four eight two four safe.

870
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Speaker 5: You know them as conservative radio hosts, now, just get

871
00:47:14,320 --> 00:47:18,200
Speaker 5: to know them as guys on this Sunday Hang podcast

872
00:47:18,280 --> 00:47:21,239
Speaker 5: with Clay and Fuck. Find it in their podcast feed

873
00:47:21,280 --> 00:47:25,720
Speaker 5: on the iHeartRadio app or wherever you get your podcasts happens.

874
00:47:25,400 --> 00:47:29,520
Speaker 1: Now, where is it all heading? My friends? We are

875
00:47:30,680 --> 00:47:35,080
Speaker 1: in almost mid September here, we got an election coming

876
00:47:35,160 --> 00:47:37,920
Speaker 1: up less than two months away. I can't believe how

877
00:47:37,960 --> 00:47:42,480
Speaker 1: this is all coming together. It feels like with each

878
00:47:42,520 --> 00:47:44,799
Speaker 1: passing day, the days are getting shorter on this. Well,

879
00:47:44,800 --> 00:47:46,560
Speaker 1: I guess technically they are getting shorter, right because of

880
00:47:46,560 --> 00:47:48,840
Speaker 1: the light you know, daylight savings. But you know what

881
00:47:48,880 --> 00:47:52,040
Speaker 1: I mean, Yes, not even a metaphor not even a metaphor,

882
00:47:52,080 --> 00:47:54,120
Speaker 1: just a real thing. The days are getting shorter in

883
00:47:54,160 --> 00:47:54,720
Speaker 1: every sense.

884
00:47:55,520 --> 00:47:55,640
Speaker 7: Uh.

885
00:47:56,080 --> 00:47:57,880
Speaker 1: And I think that we're getting closer and closer to

886
00:47:58,520 --> 00:48:02,919
Speaker 1: what'll certainly be a a tense election day. I still

887
00:48:02,920 --> 00:48:05,480
Speaker 1: feel good about things. I'm not too concerned. Trump here,

888
00:48:05,520 --> 00:48:08,680
Speaker 1: this has cut twenty three. He says that they we

889
00:48:08,719 --> 00:48:10,120
Speaker 1: didn't really get into this play. We'll get in a

890
00:48:10,120 --> 00:48:13,719
Speaker 1: little more. That they want a second debate because they

891
00:48:13,880 --> 00:48:16,399
Speaker 1: lost play twenty three. You commit to.

892
00:48:16,400 --> 00:48:18,840
Speaker 4: A second debate with Kamala Harris say.

893
00:48:18,680 --> 00:48:21,880
Speaker 7: From the recond debate because she lost tonight for Eventley,

894
00:48:21,960 --> 00:48:25,120
Speaker 7: so they won. They immediately called for second debate because

895
00:48:25,160 --> 00:48:28,239
Speaker 7: they lost. So we'll you don't think about that, but

896
00:48:29,120 --> 00:48:31,799
Speaker 7: she immediately called for a second. Look, we're looking at

897
00:48:31,840 --> 00:48:35,839
Speaker 7: at polls, we're looking at both The worst call that

898
00:48:35,880 --> 00:48:39,520
Speaker 7: we've had was seventy one. That I see seventy to

899
00:48:39,640 --> 00:48:41,640
Speaker 7: like twenty four or twenty five.

900
00:48:43,040 --> 00:48:46,520
Speaker 1: So I see this to two ways. Right now, it

901
00:48:46,640 --> 00:48:50,719
Speaker 1: hasn't been set yet, right, They haven't officially. Officially, it

902
00:48:50,880 --> 00:48:53,959
Speaker 1: sounds like the campaigns are leaning toward a second debate.

903
00:48:54,000 --> 00:48:56,880
Speaker 1: We also, I should just note, as an aside here,

904
00:48:57,480 --> 00:49:04,080
Speaker 1: we have the vice presidential debate coming up on October one,

905
00:49:04,160 --> 00:49:09,200
Speaker 1: between JD Vance and Tim Walls. I think that he's

906
00:49:09,239 --> 00:49:11,480
Speaker 1: going to be very good. JD. Van's gonna be very

907
00:49:11,480 --> 00:49:13,919
Speaker 1: good in the debate. I don't think anybody cares about

908
00:49:13,920 --> 00:49:16,120
Speaker 1: that vice president debate. I really, I just don't think

909
00:49:16,120 --> 00:49:20,080
Speaker 1: that it's just a it's a side show. And I

910
00:49:20,080 --> 00:49:22,080
Speaker 1: don't even know why they're having it. I mean, for

911
00:49:22,200 --> 00:49:23,879
Speaker 1: JD it's good. I guess that people get a look

912
00:49:23,880 --> 00:49:27,560
Speaker 1: at him for the future. But you know it's not

913
00:49:27,560 --> 00:49:29,960
Speaker 1: gonna matter. I mean, I'll watch it because this is

914
00:49:30,000 --> 00:49:33,040
Speaker 1: our job, but you know, I wouldn't recommend any of

915
00:49:33,040 --> 00:49:35,480
Speaker 1: you watch it, like we'll tell you what happens. I

916
00:49:35,480 --> 00:49:38,479
Speaker 1: promise it'll waste your time. But the second presidential debate

917
00:49:38,560 --> 00:49:42,440
Speaker 1: would be a bigger deal. And you know Trump's analysis here,

918
00:49:42,719 --> 00:49:46,279
Speaker 1: He's Trump, so he sees things a certain way that

919
00:49:46,360 --> 00:49:50,160
Speaker 1: tends to be favorable to all things Trump. There's two

920
00:49:50,160 --> 00:49:51,920
Speaker 1: ways that I could see this play. On the one hand,

921
00:49:52,800 --> 00:49:57,880
Speaker 1: wanting another debate is an admission that the Kamala campaign

922
00:49:58,200 --> 00:50:04,040
Speaker 1: is still behind. But there's also the other hand. Kamala's

923
00:50:04,040 --> 00:50:06,000
Speaker 1: campaign may see this as a way to try to

924
00:50:06,040 --> 00:50:08,080
Speaker 1: make up some more of those points because they think

925
00:50:08,120 --> 00:50:10,520
Speaker 1: they did some of that last night.

926
00:50:10,560 --> 00:50:12,040
Speaker 3: What do you think.

927
00:50:13,520 --> 00:50:18,240
Speaker 2: I think who moderates this is maybe the determinive factor

928
00:50:18,360 --> 00:50:20,760
Speaker 2: of whether I would do another debate if I were Trump,

929
00:50:21,400 --> 00:50:25,479
Speaker 2: I don't think he benefits. He's already done CNN, He's

930
00:50:25,520 --> 00:50:30,640
Speaker 2: now done ABC, two different networks that clearly hate him.

931
00:50:30,960 --> 00:50:34,799
Speaker 2: The vice presidential debate is on NBC. I don't think

932
00:50:34,880 --> 00:50:38,719
Speaker 2: he benefits from going into the lions Den again. If

933
00:50:38,760 --> 00:50:41,800
Speaker 2: I were Trump and I were advising him, I would

934
00:50:41,800 --> 00:50:46,120
Speaker 2: say I did CNN, I did ABC. Those are left

935
00:50:46,200 --> 00:50:50,520
Speaker 2: leaning media outlets. I will do Fox News, as he

936
00:50:50,560 --> 00:50:54,520
Speaker 2: has proposed before. I will do Fox News on October eleventh.

937
00:50:55,040 --> 00:50:57,160
Speaker 2: If you show and I would take the I would

938
00:50:57,160 --> 00:50:59,960
Speaker 2: take it now, meaning I would put that out there

939
00:51:00,120 --> 00:51:04,640
Speaker 2: are in the public today, because then it's like, hey.

940
00:51:04,480 --> 00:51:08,120
Speaker 3: Here, I agreed to your prescriptions. I've agreed to this.

941
00:51:08,239 --> 00:51:11,120
Speaker 2: I'll do Fox News on October tenth or whatever date

942
00:51:11,160 --> 00:51:14,960
Speaker 2: it is, and I'm gonna show up and do a

943
00:51:15,000 --> 00:51:15,560
Speaker 2: town hall.

944
00:51:15,600 --> 00:51:16,680
Speaker 3: If you don't show up.

945
00:51:16,760 --> 00:51:20,080
Speaker 2: I'm showing up either way, and then it puts the

946
00:51:20,080 --> 00:51:23,480
Speaker 2: onus on Kamalo. Will she go on Fox News? I

947
00:51:23,480 --> 00:51:26,160
Speaker 2: think the answer is no, and then you get into

948
00:51:26,200 --> 00:51:29,000
Speaker 2: wrangling over debate terms and you can see how the

949
00:51:29,040 --> 00:51:32,560
Speaker 2: poll wing looks and make a decision then on whether

950
00:51:32,640 --> 00:51:33,360
Speaker 2: or not you want to do it.

951
00:51:33,400 --> 00:51:34,400
Speaker 3: That's how I would play it.

952
00:51:35,040 --> 00:51:36,920
Speaker 1: This is gonna sound a little whiny, but I'm just

953
00:51:36,920 --> 00:51:38,760
Speaker 1: gonna say it because I think it needs to be said.

954
00:51:39,360 --> 00:51:42,680
Speaker 1: You know what's unfair about all this too? If Kamala

955
00:51:42,800 --> 00:51:46,440
Speaker 1: went on Fox News, yes, it would be a fair debate.

956
00:51:46,600 --> 00:51:49,319
Speaker 3: You're our team just won't do that.

957
00:51:49,480 --> 00:51:51,759
Speaker 1: They will. There will not be a five everyone. There

958
00:51:51,760 --> 00:51:54,759
Speaker 1: will not be a Fox News ambush. The anchors, if

959
00:51:54,760 --> 00:51:57,520
Speaker 1: they would choose, would run it fair. They'd run it straight.

960
00:51:57,760 --> 00:51:59,560
Speaker 1: And we all know this and this is just one

961
00:51:59,600 --> 00:52:03,440
Speaker 1: of these they're willing to, you know, hit you in

962
00:52:03,480 --> 00:52:05,759
Speaker 1: the ribs when the ref isn't looking and our team isn't.

963
00:52:05,800 --> 00:52:07,399
Speaker 1: I don't know what else to say, but that's true,

964
00:52:07,440 --> 00:52:07,880
Speaker 1: the truth.

965
00:52:08,560 --> 00:52:09,080
Speaker 3: Yeah.

966
00:52:09,400 --> 00:52:14,040
Speaker 2: Martha McCollum and Brett Baer are who Trump suggested. I

967
00:52:14,080 --> 00:52:17,160
Speaker 2: can guarantee you that they would be straight down the middle,

968
00:52:17,239 --> 00:52:18,640
Speaker 2: and they would be completely fair.

969
00:52:18,960 --> 00:52:22,239
Speaker 1: In fact, the only the complaints about them because of

970
00:52:22,280 --> 00:52:25,160
Speaker 1: the lopside in an insane way that the Democrats view

971
00:52:25,160 --> 00:52:28,200
Speaker 1: this stuff. The complaints about them would be why didn't

972
00:52:28,239 --> 00:52:32,239
Speaker 1: they fact check tru fact checked Trump complaints that Jake

973
00:52:32,280 --> 00:52:34,839
Speaker 1: Tapper got from the left right. I mean, you know

974
00:52:34,920 --> 00:52:38,600
Speaker 1: so so running. Just to be to be clear, running

975
00:52:38,719 --> 00:52:43,959
Speaker 1: a straight and fair debate is always unacceptable to Democrats,

976
00:52:44,160 --> 00:52:46,719
Speaker 1: especially when it comes to Trump. If you just ask

977
00:52:46,920 --> 00:52:51,160
Speaker 1: questions and let the people talk who are the candidates?

978
00:52:51,520 --> 00:52:54,520
Speaker 1: That is unacceptable to Democrats. They will complain about that.

979
00:52:55,120 --> 00:52:57,600
Speaker 2: I think that's important because it also ties in with

980
00:52:57,880 --> 00:53:03,560
Speaker 2: larger societal free speed each codes. They're angry that Elon

981
00:53:03,760 --> 00:53:08,200
Speaker 2: Musk on Twitter slash x is just allowing people to

982
00:53:08,280 --> 00:53:11,640
Speaker 2: say what they think. They don't want a free and

983
00:53:11,800 --> 00:53:15,640
Speaker 2: open forum where candidates can make arguments and the American

984
00:53:15,640 --> 00:53:19,359
Speaker 2: public can decide which arguments they find more compelling. They

985
00:53:19,400 --> 00:53:22,480
Speaker 2: demand a referee that is going to put his or

986
00:53:22,520 --> 00:53:26,040
Speaker 2: her hands on the scales in their favor. We're not

987
00:53:26,080 --> 00:53:28,799
Speaker 2: even arguing for that, We're just saying, hey, let's have

988
00:53:28,840 --> 00:53:31,839
Speaker 2: an open forum. You and I came on and said

989
00:53:31,880 --> 00:53:35,320
Speaker 2: after the CNN debate. Hey, Jake Tapper and Dana Bash

990
00:53:35,400 --> 00:53:38,439
Speaker 2: pretty much stayed out of the forray. They let Joe

991
00:53:38,440 --> 00:53:42,120
Speaker 2: Biden and Donald Trump go after each other, and the

992
00:53:42,200 --> 00:53:45,280
Speaker 2: goal is to give people more information. If the same

993
00:53:45,360 --> 00:53:50,000
Speaker 2: thing is true of this debate, then we would have

994
00:53:50,040 --> 00:53:51,480
Speaker 2: come on and we would have said, hey, you know,

995
00:53:51,640 --> 00:53:54,440
Speaker 2: it was a fair fight. They stayed out of the way. Instead,

996
00:53:54,520 --> 00:53:58,480
Speaker 2: Lindsay Davis and David Muir decided to make themselves really

997
00:53:58,520 --> 00:54:00,759
Speaker 2: strong parts of the debate. Is the thing that's really

998
00:54:00,800 --> 00:54:03,800
Speaker 2: a kick in the teeth to me, Buck. In so doing,

999
00:54:04,520 --> 00:54:09,359
Speaker 2: they made themselves millions of dollars out to say their

1000
00:54:09,440 --> 00:54:14,560
Speaker 2: contract extension ever never get fired. Their contract extensions were

1001
00:54:14,680 --> 00:54:18,920
Speaker 2: a done deal after last night's debate. MRR is probably

1002
00:54:18,920 --> 00:54:22,279
Speaker 2: making twenty million a year, twenty five million a year

1003
00:54:22,320 --> 00:54:22,960
Speaker 2: or something like that.

1004
00:54:23,040 --> 00:54:24,400
Speaker 1: I don't know what the I don't even know the

1005
00:54:24,400 --> 00:54:25,800
Speaker 1: other lady's name, but I well.

1006
00:54:25,680 --> 00:54:27,919
Speaker 2: Lindsay Davis, I have no idea what she makes. They're

1007
00:54:27,920 --> 00:54:30,759
Speaker 2: never getting fired. They have lifetime tenure at ABC News.

1008
00:54:30,800 --> 00:54:34,839
Speaker 1: Now. Yeah, so this is always remember this for Democrats.

1009
00:54:35,760 --> 00:54:37,680
Speaker 1: They take care of their team, they take care of

1010
00:54:37,719 --> 00:54:39,920
Speaker 1: their side, and that is why they get the outcomes

1011
00:54:39,960 --> 00:54:43,120
Speaker 1: that they do so and on our side, sometimes people

1012
00:54:43,480 --> 00:54:47,120
Speaker 1: do the good deed, they show bravery and courage and character,

1013
00:54:47,600 --> 00:54:49,399
Speaker 1: and everyone's like, well, I don't know, I guess their

1014
00:54:49,400 --> 00:54:51,440
Speaker 1: career is ruined. Like maybe they'll open up, you know,

1015
00:54:51,480 --> 00:54:54,040
Speaker 1: a pawn shop somewhere so they'll figure it out. You know,

1016
00:54:54,400 --> 00:54:56,239
Speaker 1: we don't take care of our team the same way.

1017
00:54:56,239 --> 00:54:57,840
Speaker 1: It's one of our I know, it sounds like a

1018
00:54:57,840 --> 00:54:59,759
Speaker 1: little thing. It's actually one of the biggest failings we

1019
00:54:59,800 --> 00:55:03,960
Speaker 1: have because in this environment where Democrats run the politics

1020
00:55:03,960 --> 00:55:06,920
Speaker 1: of personal destruction using the Internet and everything else in

1021
00:55:06,920 --> 00:55:09,279
Speaker 1: a way that is way beyond what they could do

1022
00:55:09,320 --> 00:55:11,640
Speaker 1: in the past, being able to ruin someone's career in

1023
00:55:11,680 --> 00:55:15,200
Speaker 1: their livelihood because they're a political threat to you, very powerful.

1024
00:55:15,800 --> 00:55:17,160
Speaker 3: Oh look at what they did to Trump.

1025
00:55:17,360 --> 00:55:20,799
Speaker 2: I mean, when Democrat presidents move out of office, they

1026
00:55:20,880 --> 00:55:24,880
Speaker 2: get lifetime sinecures. Heck, even Joe Biden was making millions

1027
00:55:24,920 --> 00:55:28,680
Speaker 2: of dollars and he was only a VP. Trump is president,

1028
00:55:28,960 --> 00:55:32,520
Speaker 2: leaves office, they won't even play pro golf tournaments at

1029
00:55:32,560 --> 00:55:37,080
Speaker 2: his courses. The PGA Tour pulls out on the PGA Championship,

1030
00:55:37,400 --> 00:55:37,800
Speaker 2: and they.

1031
00:55:37,640 --> 00:55:38,600
Speaker 3: Try to put him in prison.

1032
00:55:38,600 --> 00:55:40,640
Speaker 2: For the rest of his life. I mean, it's not

1033
00:55:40,680 --> 00:55:43,360
Speaker 2: even just you don't get a golden parachute. It's that

1034
00:55:43,440 --> 00:55:46,680
Speaker 2: they try to put you in a jail cell. It

1035
00:55:46,800 --> 00:55:49,879
Speaker 2: is true. And these guys, I mean, that's why it's

1036
00:55:49,920 --> 00:55:53,439
Speaker 2: so disgusting to me. David Muir and Lindsay Davis, they

1037
00:55:53,520 --> 00:55:55,359
Speaker 2: now are taken care of it. And we didn't even

1038
00:55:55,400 --> 00:55:59,080
Speaker 2: hardly talked about this. But the president of ABC News

1039
00:55:59,760 --> 00:56:04,520
Speaker 2: is a thirty year friend of Kamala Harris. Yep, thirty years.

1040
00:56:04,640 --> 00:56:08,360
Speaker 1: They have been best to introduced Kamala to the first

1041
00:56:08,480 --> 00:56:10,880
Speaker 1: husband guy or whatever. The second was a girl. I

1042
00:56:10,880 --> 00:56:12,759
Speaker 1: think her name is Dana Walden. You guys in the

1043
00:56:12,760 --> 00:56:18,840
Speaker 1: studio yet, sorry, didn't she introduced to the Kamala Yeah, yeah.

1044
00:56:18,840 --> 00:56:19,480
Speaker 3: I think that's right.

1045
00:56:19,640 --> 00:56:24,160
Speaker 2: And their they're bosom buddies from LA who hang out

1046
00:56:24,200 --> 00:56:27,280
Speaker 2: together all the time, have been friends for thirty years,

1047
00:56:28,400 --> 00:56:30,960
Speaker 2: and she runs the network that gets the debate. And

1048
00:56:31,040 --> 00:56:35,080
Speaker 2: you don't think that David Muir and Lindsey Davis know

1049
00:56:35,239 --> 00:56:37,239
Speaker 2: that their boss is best friends with one of the

1050
00:56:37,239 --> 00:56:40,800
Speaker 2: two people that they're doing the debate of. I mean, again,

1051
00:56:41,280 --> 00:56:44,799
Speaker 2: the rig job was in effect and I get the

1052
00:56:45,280 --> 00:56:46,480
Speaker 2: if you've listened to the show. You go back and

1053
00:56:46,520 --> 00:56:48,440
Speaker 2: listen to podcast. I encourage you go listen to it.

1054
00:56:48,920 --> 00:56:51,880
Speaker 2: Trump was not his best version, and that, to me

1055
00:56:52,000 --> 00:56:54,600
Speaker 2: is the frustrating part, because I think there were It's

1056
00:56:54,640 --> 00:56:56,440
Speaker 2: like when you watch go back and watch film of

1057
00:56:56,480 --> 00:56:58,600
Speaker 2: a game and you're like, it's one thing. If he

1058
00:56:58,640 --> 00:57:00,719
Speaker 2: had been going up against the greatest debater of all time,

1059
00:57:00,760 --> 00:57:03,000
Speaker 2: you'd be like, man, that person's really good. There were

1060
00:57:03,040 --> 00:57:05,640
Speaker 2: lots of layups to be made, there were lots of

1061
00:57:05,680 --> 00:57:08,680
Speaker 2: easy points to be scored, and I think Trump missed

1062
00:57:08,680 --> 00:57:11,480
Speaker 2: on it. But the rig job that he walked into

1063
00:57:12,280 --> 00:57:15,799
Speaker 2: is unprecedented in its nature. I truly never think we've

1064
00:57:15,800 --> 00:57:18,320
Speaker 2: seen anything like this. I think in all things, self

1065
00:57:18,320 --> 00:57:22,080
Speaker 2: honesty is very important. And when you're assessing whether it's

1066
00:57:22,080 --> 00:57:24,880
Speaker 2: a debate performance or a politician in general, or a

1067
00:57:24,920 --> 00:57:28,919
Speaker 2: whole political platform, if you have never once at this point,

1068
00:57:29,000 --> 00:57:31,760
Speaker 2: I mean, Trump has been on the scene now for

1069
00:57:31,920 --> 00:57:35,200
Speaker 2: eight years, right as the rest one on nine, since

1070
00:57:35,240 --> 00:57:37,480
Speaker 2: he came down the staircase to run in twenty sixteen.

1071
00:57:38,080 --> 00:57:41,080
Speaker 2: If you've never once found yourself saying I disagree with

1072
00:57:41,440 --> 00:57:44,600
Speaker 2: or I have a problem with what Trump said.

1073
00:57:45,160 --> 00:57:47,680
Speaker 1: You need to get out a little more you need

1074
00:57:47,720 --> 00:57:50,080
Speaker 1: to think. You know, it's you can't always agree. I

1075
00:57:50,080 --> 00:57:52,160
Speaker 1: don't always agree with my family members, you know what

1076
00:57:52,200 --> 00:57:55,120
Speaker 1: I mean. I don't always agree with don't tell anyone, Clay,

1077
00:57:55,120 --> 00:57:57,880
Speaker 1: I don't always agree with my wife. You know, you

1078
00:57:57,920 --> 00:58:01,240
Speaker 1: don't always agree with anyone, and you don't always think

1079
00:58:01,280 --> 00:58:04,080
Speaker 1: what they do is perfect all the time. And if

1080
00:58:04,120 --> 00:58:08,560
Speaker 1: you find yourself in that situation, you're losing objectivity such

1081
00:58:08,560 --> 00:58:12,240
Speaker 1: that it does you and that person a disservice. So

1082
00:58:12,480 --> 00:58:14,360
Speaker 1: people can say that they thought Trump agreed, that's not

1083
00:58:14,440 --> 00:58:17,120
Speaker 1: That's fine, But I'm just saying, if you've only ever

1084
00:58:17,160 --> 00:58:20,439
Speaker 1: thought to yourself, I hate when Trump is criticized. I've

1085
00:58:20,440 --> 00:58:23,160
Speaker 1: never criticized him, or I've never agreed with the criticism

1086
00:58:23,240 --> 00:58:27,040
Speaker 1: of him, that's not where That's not where we want

1087
00:58:27,040 --> 00:58:29,320
Speaker 1: to be in terms of the honesty meter, I would

1088
00:58:29,360 --> 00:58:32,200
Speaker 1: agree you should never one hundred percent agree with anybody,

1089
00:58:32,280 --> 00:58:34,640
Speaker 1: not even yourself. You should be willing to challenge your

1090
00:58:34,640 --> 00:58:38,560
Speaker 1: own thoughts. I also think this is important. If you

1091
00:58:38,720 --> 00:58:44,760
Speaker 1: find yourself listening to media people who only say that

1092
00:58:44,840 --> 00:58:49,520
Speaker 1: somebody is amazing or awesome or the best version of themselves,

1093
00:58:50,240 --> 00:58:53,240
Speaker 1: you are I think falling victim to the same lies

1094
00:58:53,280 --> 00:58:56,320
Speaker 1: that Karine Jean Pierre was saying at the podium, and

1095
00:58:56,360 --> 00:58:58,920
Speaker 1: frankly that Kabala argued for years about Biden. It was

1096
00:58:58,960 --> 00:59:01,400
Speaker 1: self evident for anybody who the brain that Biden wasn't

1097
00:59:01,480 --> 00:59:03,800
Speaker 1: able to do the job. Now, you often bring the

1098
00:59:04,360 --> 00:59:08,320
Speaker 1: sort of the sports commentary flavor into things. I don't

1099
00:59:08,360 --> 00:59:10,680
Speaker 1: think anybody would trust a coach who had been serving

1100
00:59:10,760 --> 00:59:14,160
Speaker 1: for a decade of a professional team who after every

1101
00:59:14,200 --> 00:59:17,200
Speaker 1: single game, win or lose, was like, we were awesome.

1102
00:59:17,240 --> 00:59:20,479
Speaker 1: I wouldn't change a thing. That's not why and why

1103
00:59:20,560 --> 00:59:22,960
Speaker 1: is that bad? It's bad because it's not honest. It's

1104
00:59:23,000 --> 00:59:25,080
Speaker 1: not honest, it's not helpful. It's not helpful, it's not

1105
00:59:25,080 --> 00:59:28,280
Speaker 1: going to help you win. So again, I still think

1106
00:59:28,320 --> 00:59:30,240
Speaker 1: Trump is ahead. I still think Trump is going to win.

1107
00:59:30,560 --> 00:59:35,120
Speaker 1: But as part of the process of having that conversation again,

1108
00:59:35,160 --> 00:59:36,600
Speaker 1: it's not just like you and me are sitting on

1109
00:59:36,640 --> 00:59:38,400
Speaker 1: a stoop somewhere saying it. You, me and a few

1110
00:59:38,440 --> 00:59:42,200
Speaker 1: million friends, including people who work for Trump. I think

1111
00:59:42,240 --> 00:59:47,040
Speaker 1: that that having some degree of reflection on what could

1112
00:59:47,080 --> 00:59:50,040
Speaker 1: have gone a little better last night is actually a

1113
00:59:50,160 --> 00:59:53,680
Speaker 1: service to the Trump campaign. That's how I view it now.

1114
00:59:53,680 --> 00:59:55,400
Speaker 1: People can disagree with that, that's fine.

1115
00:59:55,800 --> 01:00:00,760
Speaker 2: I also think this is important too. You can't surround

1116
01:00:00,880 --> 01:00:04,600
Speaker 2: yourself in any facet of life with people who only

1117
01:00:04,680 --> 01:00:07,880
Speaker 2: say you're awesome. And you know this, Buck, this happens

1118
01:00:07,880 --> 01:00:09,000
Speaker 2: in media all the time.

1119
01:00:09,280 --> 01:00:09,760
Speaker 3: All the time.

1120
01:00:09,800 --> 01:00:13,920
Speaker 2: People cloister themselves, They surround themselves by people who say,

1121
01:00:14,440 --> 01:00:18,640
Speaker 2: you're amazing, you did everything perfectly. It happens probably in

1122
01:00:18,680 --> 01:00:21,160
Speaker 2: many of your businesses where the boss has a lot

1123
01:00:21,200 --> 01:00:24,240
Speaker 2: of yes men or women who just walk around and

1124
01:00:24,280 --> 01:00:26,920
Speaker 2: it doesn't matter what the data says, it doesn't matter

1125
01:00:26,960 --> 01:00:30,280
Speaker 2: what the performance was, and that works, and that works,

1126
01:00:30,320 --> 01:00:33,480
Speaker 2: and then it's the Emperor with no clothes syndrome. At

1127
01:00:33,520 --> 01:00:37,680
Speaker 2: some point it blows up. And I think this is

1128
01:00:37,760 --> 01:00:42,960
Speaker 2: where Trump needs to have people with him who say, Hey,

1129
01:00:43,720 --> 01:00:45,560
Speaker 2: you could have been better than you were last night,

1130
01:00:46,200 --> 01:00:48,560
Speaker 2: and in order to win the election you're gonna have

1131
01:00:48,600 --> 01:00:51,960
Speaker 2: to be better than this going forward. Now, everybody is

1132
01:00:51,960 --> 01:00:53,400
Speaker 2: not their best. Look, Buck, you and I talked for

1133
01:00:53,480 --> 01:00:56,680
Speaker 2: three hours every day. Sometimes we finished the show and

1134
01:00:56,920 --> 01:00:58,920
Speaker 2: it wasn't the best show we ever did. I wish

1135
01:00:58,960 --> 01:01:01,840
Speaker 2: every day was perfect. We screw things up. The audio

1136
01:01:01,880 --> 01:01:05,080
Speaker 2: doesn't get played, We read the wrong read the wrong ad.

1137
01:01:05,320 --> 01:01:08,520
Speaker 2: We get a fact wrong, or we missstate. Certainly I

1138
01:01:08,560 --> 01:01:10,920
Speaker 2: get grammar wrong all the time. I sound like Tim

1139
01:01:10,960 --> 01:01:15,000
Speaker 2: Walls here. We're imperfect. But the goal is to get

1140
01:01:15,040 --> 01:01:18,240
Speaker 2: better and better, and I don't think that Trump improved

1141
01:01:18,240 --> 01:01:19,680
Speaker 2: from June.

1142
01:01:20,000 --> 01:01:22,439
Speaker 1: You know, we all need energy to thrive during the day.

1143
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Speaker 1: It's one thing to get a good night's rest and

1144
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1151
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1152
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Speaker 1: debate last night, make sure your testosterone level is high enough.

1153
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1160
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Speaker 1: The number is fifty chalk three thousand. Say Clay and

1161
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1162
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Speaker 5: Clay, Travis and Buck Sexton telling it like it is.

1163
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Speaker 5: Find them on the free iHeartRadio app or wherever you

1164
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Speaker 5: get your podcasts.