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Speaker 1: Morning Europe.

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Speaker 2: About to enter the arena and.

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Speaker 1: Join the battle to save.

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Speaker 3: America with your host Sean Carnell. Good evening, America. This

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Speaker 3: show that you're watching tonight is called Battleground Live. This

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Speaker 3: is the show where we kick ass, and we take

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Speaker 3: names and we lock horns with the radical left. We

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Speaker 3: never quit, we never surrender. From sea to shining Sea

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Speaker 3: and everybody in between. Welcome patriots on this glorious Thursday.

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Speaker 3: What are we like, five days before election Day, five

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Speaker 3: days before we save this extraordinary country, folks. A couple

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Speaker 3: things right off the top, Happy Halloween. You know, got

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Speaker 3: to take some just a couple of minutes to acknowledge

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Speaker 3: what's on the calendar. And I know that my wife,

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Speaker 3: Commander Melanie, she and I were talking about how, you know,

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Speaker 3: we've got five kids. People that are ogs and have

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Speaker 3: been listening to the show for a long time know that.

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Speaker 3: But our kids are getting older, and we both lamented

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Speaker 3: the fact that they don't really get dressed up.

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Speaker 1: They don't get really dressed up like they used to

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Speaker 1: do for.

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Speaker 3: Halloween and even in the moment when they were kids

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Speaker 3: at the time, like they get back from school, it's

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Speaker 3: fast and furious you've got to get them all dressed up.

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Speaker 1: It was chaotic, it was hectic, and there were a few.

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Speaker 3: Times back then who I found myself, you know, complaining

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Speaker 3: about that or thought it was stressful or whatever. But

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Speaker 3: now that we don't have it anymore, we miss it.

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Speaker 3: So that is what we are dealing with here in

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Speaker 3: Fort Parnell today. But happy Halloween nonetheless. Also, folks, President

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Speaker 3: Trump is the most electrifying political figure of my lifetime. Again,

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Speaker 3: Ogs of the Battle Group. Folks who've been listening to

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Speaker 3: this show for the last year, you know, I'm a

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Speaker 3: rider died Trump guy. I always have been. But there

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Speaker 3: will never be another politician like this guy. He took

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Speaker 3: biden insane garbage comment that the media tried to cover

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Speaker 3: up and gaslight us into believing it didn't actually happen,

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Speaker 3: and turned it into a news cycle that dominated just

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Speaker 3: about the entire day yesterday, it even part of today.

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Speaker 3: So we're gonna talk a little bit about that. But

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Speaker 3: I've also got the great Seth Keshel in the arena tonight.

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Speaker 3: He's on deck here very soon. I really like Seth.

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Speaker 3: He's a former Army captain, he's a military intelligence officer,

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Speaker 3: he's an Afghanistan veteran like myself. But what I admire

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Speaker 3: the most about Seth, and we'll get to him here

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Speaker 3: in just a second after I get a couple of

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Speaker 3: ad reads in, is that in the wake of the

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Speaker 3: twenty twenty election, and you all know I had my

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Speaker 3: name on the ballot, was running in western Pennsylvania in

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Speaker 3: the biggest swing district in the state, and for many

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Speaker 3: of you all who followed my race, which I know

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Speaker 3: many of you did, there were so many statistical anomalies

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Speaker 3: in twenty twenty, including the fact that I overperformed President

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Speaker 3: Trump in my district and my opponent underperformed Biden. So

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Speaker 3: even that statistic alone, mathematically, how does how does how

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Speaker 3: does Biden and my opponent win? But nevertheless that this

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Speaker 3: isn't this isn't a post mortive of my election in

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Speaker 3: twenty twenty. But I've told you all many times that

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Speaker 3: I felt like I was alone in twenty twenty and

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Speaker 3: presenting all of this what were a mountain of evidence

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Speaker 3: of fraud to the media and to people who would

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Speaker 3: investigate such things, and most of it fell on deaf ears.

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Speaker 3: People like Seth Keshel were few and far between, stood

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Speaker 3: up and were unafraid of the media pressure and the

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Speaker 3: intense pressure to cave, calling the people conspiracy theorists or

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Speaker 3: election deniers or what have you. Seth didn't bend, buckle

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Speaker 3: or break And you know, I love that. I love

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Speaker 3: when people have the backbone to stand up for what

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Speaker 3: they believe in. I mean, I had lawyers who represented

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Speaker 3: me on what were very strong foundational constitutional cases on

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Speaker 3: election integrity bail because they were getting threats from people.

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Speaker 3: Why had Antifa showing up at my house and spray

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Speaker 3: peating my home and everything else. I never backed down.

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Speaker 3: So my point is I learned a lot through those

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Speaker 3: very tumultuous times in my life of who the good

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Speaker 3: people were. And Seth is one of them. So stick

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Speaker 3: with us. He's on deck. Going to get to him

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Speaker 3: just a second. Don't forget about Official Sean Parnell dot com,

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Speaker 3: your one stop shop for all things America first news

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Speaker 3: specifically cultivated for you the Battle Crew. Also locals that

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Speaker 3: We've got a subscription page there. If you can subscribe, great,

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Speaker 3: If not, also fine. We just want you in the

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Speaker 3: conversation beyond this show. Also, make sure you smash that

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Speaker 3: like button, that little green thumb beneath the video. Okay,

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Speaker 3: everyone thinks they're keeping their families safe, but are you really?

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Speaker 3: With elections coming up, anything might happen, and if you

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Speaker 3: dare defend yourself or crazy twisted legal system will probably

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Speaker 3: put you behind bars while the criminal walks free. How

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Speaker 3: many times have we seen that play out in the

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Speaker 3: news right before our eyes.

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Speaker 1: You see, they've got us.

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Speaker 3: To a point here in America where we're fighting to

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Speaker 3: keep our Second Amendment rights, yet risk losing everything if

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Speaker 3: we actually use them. That's why over eight hundred thousand

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Speaker 3: Americans are members of the us CCA, because not only

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Speaker 3: will you get access to the Protector Academy to learn

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Speaker 3: vital skills like precision shooting and how to fortify your

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Speaker 3: home against criminals, but you'll also get access to the

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Speaker 3: twenty four to seven Critical Response Team and the included

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Speaker 3: benefit of self defense Liability insurance to make sure you

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Speaker 3: and your family are prepared for anything. And for a

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Speaker 3: limited time, text Sean sea in to eight seven to two,

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Speaker 3: two to two to get the USCCA. He's free life

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Speaker 3: saving Concealed Carry and Family Defense Guide and a chance

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Speaker 3: to win seventeen hundred dollars to buy any self defense

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Speaker 3: gear you need.

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Speaker 1: Before it's too late.

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Speaker 3: So tex Sean s e A N to eight seven

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Speaker 3: to two, two to two right now, So without further ado,

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Speaker 3: let me introduce you all to Seth Keshel. Welcome, my friend,

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Speaker 3: Army Captain Afghanistan veteran, twenty twenty election denier.

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Speaker 1: Welcome to the show, my friend. It's great to have you.

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Speaker 2: Well, it's going to be on with you, Sean, and

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Speaker 2: let me fix your verbage a little bit. I'm not

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Speaker 2: an election denier. I'm a fraud affirmer.

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Speaker 3: There see, I see, Seth, this is I like the

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Speaker 3: cut of your jib, even though you're not a navy guy. See,

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Speaker 3: I went to your substack and I was reading up

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Speaker 3: on you for so. First of all, Seth has a substack.

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Speaker 3: You should go subscribe to it. He's got twenty six

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Speaker 3: thousand subscribers over there. But he has this like little

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Speaker 3: paragraph about himself on and I was reading about him.

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Speaker 3: And I've known Seth for a couple of years now,

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Speaker 3: But it says intense exposure on several Mainline Right broadcasts

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Speaker 3: like appearances with Sean Spicer and Jesse Jesse Kelly, plus

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Speaker 3: an interview on doctor Steve Turley's one point two million

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Speaker 3: followers and counting on YouTube channel has brought many new

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Speaker 3: followers here to this journal, and the event that you're

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Speaker 3: not one of those new followers, one reason you may

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Speaker 3: not have heard of me till now is because I

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Speaker 3: don't come with much of a filter. And when it

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Speaker 3: comes to discussing the state of today's elections in this country,

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Speaker 3: I'm the guy that gets invited to headline a Lincoln

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Speaker 3: Reagan dinner only for legacy GOP bigwigs to opt out

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Speaker 3: with a date night with the misses. And I thought,

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Speaker 3: you know what, You're a pretty good fit for this show, Seth,

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Speaker 3: because we like to kind of tell.

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Speaker 1: It like it is here.

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Speaker 2: Well, you know, the humor is always something that keeps

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Speaker 2: us going as a military man. I think you understand

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Speaker 2: that that some people get so serious about every little thing,

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Speaker 2: Like right now we're melting down and freaking out about

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Speaker 2: a gender gap and early voting which had like the

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Speaker 2: damn gender gap of every early voting episode. But you know,

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Speaker 2: we can get into that as we get in the weeds.

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Speaker 2: But I will say about the Navy, so I was

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Speaker 2: a captain in the Army three Junior Company, great officer.

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Speaker 2: Most military guys that get out as an officer that

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Speaker 2: get out, you know, without retiring or captains. And I

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Speaker 2: was in Washington State in twenty twenty two, across the

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Speaker 2: Columbia River in Clark County, and I did an elections

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Speaker 2: event there. You may not know this, but Washington State

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Speaker 2: makes Pennsylvania's elections look amazingly clean. And Washington State Washington State.

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Speaker 2: My calculation was that Washington State probably had forty nine

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Speaker 2: thousand fraudulent ballots per elect tour in the twenty twenty election.

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Speaker 2: That and right now they're finding sixteen ballots per apartment

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Speaker 2: in some of these places in Seattle. But I went

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Speaker 2: down there to diss on the elections in Washington State,

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Speaker 2: and Seattle Time sent somebody down I five to cover

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Speaker 2: the event. And first off, they described me as lanky,

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Speaker 2: which I kind of took offense to that because I'm

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Speaker 2: not lanky. I'm two hundred and forty five pounds, but

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Speaker 2: you know, they wrote that up. But they called me.

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Speaker 2: They called me a former military captain, which is correct

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Speaker 2: but not precise. And then the next paragraph said I

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Speaker 2: was an ex Navy officer. So I actually got promoted

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Speaker 2: three pay grades to naval captain.

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Speaker 1: Yeah.

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Speaker 3: So we've got like we've got all all branches here

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Speaker 3: on the battle crew that watched this show.

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Speaker 1: But yeah, man, so you were very well appreciated here.

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Speaker 3: And we talk about the twenty twenty election often on

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Speaker 3: the show, and not because we are incapable of addressing

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Speaker 3: what's coming. I mean, the the elites and the establishment

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Speaker 3: GOP and certainly the Democrats and their allies and the media.

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Speaker 3: They like to pretend that we can't walk and chew

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Speaker 3: gum at the same time I talked, they don't want

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Speaker 3: us talking about the twenty twenty election because they want

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Speaker 3: us to keep making the same mistakes moving forward. They

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Speaker 3: don't want us to change and secure our elections, and

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Speaker 3: if we talked about it, it's more likely that we

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Speaker 3: do that. So we talk about the twenty election a

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Speaker 3: lot on the show because it's important to expose what

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Speaker 3: they did then to shore up elections moving forward, because

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Speaker 3: if we don't have secure elections, we don't really have

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Speaker 3: a country that's representative of the people, which is what

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Speaker 3: our founders always intended. And when my election happened in

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Speaker 3: twenty twenty, you and I that's how you and I connected,

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Speaker 3: And I mean Pennsylvania was a disaster. But the math,

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Speaker 3: and I don't want to spend too much time on

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Speaker 3: twenty twenty because I want to get into the battleground

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Speaker 3: state numbers with you, and you they're just a data guy,

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Speaker 3: and you're awesome with all that stuff. But the math

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Speaker 3: simply did not add up in my district because the

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Speaker 3: number of mail in ballots, as you know, is not

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Speaker 3: speculative any way that you cut it, even with the

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Speaker 3: ballots remaining after election day, I was going to have

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Speaker 3: about a thirteen thousand vote margin of victory any way

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Speaker 3: you cut it, even with the mail in ballots out

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Speaker 3: there as they were. And then four days after election day,

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Speaker 3: a ballots up of four thousand votes, then one of

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Speaker 3: nine thousand votes curiously adds up to thirteen thousand, and

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Speaker 3: the rest is history. And so what did you see?

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Speaker 3: Let me ask you this, seth, What did you see

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Speaker 3: in twenty twenty that made you say to yourself, Okay,

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Speaker 3: you know, I'm a military guy, but I got to

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Speaker 3: step up and get involved in this fight.

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Speaker 2: Well, it's interesting because my initial story, the one that

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Speaker 2: people were learning three years ago when I became a

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Speaker 2: name with elections. It's it's something you read in a movie,

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Speaker 2: and I was not somebody that wanted a big social

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Speaker 2: media following, and I really don't know that I want one.

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Speaker 2: I have one, you know, and I'm gonna make the

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Speaker 2: best use of it until I no longer do. But

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Speaker 2: the twenty twenty election, to me, it was a hobby

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Speaker 2: until the firing range went hot. And in twenty sixteen,

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Speaker 2: I wound up creating as a hobby, winning electoral matt

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Speaker 2: for Trump that matched fifty out of fifty states. And

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Speaker 2: the reason I deciphered it was because so at the

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Speaker 2: end of an election cycle, the media does something called

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Speaker 2: hurting hgrbing. Now, I know you're friends with Rich Barris,

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Speaker 2: and you know, Rich and I communicate sometimes and I

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Speaker 2: like a lot of his terminology. But you know, I'm

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Speaker 2: sure Rich and you understand hurting. Where hey, we need

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Speaker 2: to preserve some credibility. Let's get to these results.

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Speaker 1: Yeah, we talked about this just last night. Yeah yeah.

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Speaker 2: So of course, here in the close of this election,

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Speaker 2: everybody's gonna give North Carolina to Trump. You know, everybody's

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Speaker 2: gonna write Florida and Texas off, which they've been written

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Speaker 2: off for a long time. And now you see people

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Speaker 2: hurting Pennsylvania to the right, which is a huge tell

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Speaker 2: where this selection should be going. But you know, other

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Speaker 2: people may not do polling, but like Frank Luntz, he hurts.

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Speaker 2: You know, he's been hedging the whole last couple of weeks.

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Speaker 2: Will Trump might win? Yeah, yeah, no, no kidding, Frank.

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Speaker 1: I think that's exactly right.

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Speaker 3: Like just yesterday he was like and he does like

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Speaker 3: Frank is like I he's like the perpetual doomer. You know,

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Speaker 3: he's like, oh, you know, Biden said the garbage comment

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Speaker 3: and oh my gosh, there's three percent left undecided. Like

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Speaker 3: he was like, gone, CNN, does that Trump could win now,

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Speaker 3: like because of the garbage comment, not as if Trump

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Speaker 3: has been strong all along.

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Speaker 1: Just because you know, just because of the garbage comment.

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Speaker 2: Well, so the media heard at Ohio in twenty sixteen,

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Speaker 2: in September, two months out right, so you don't usually

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Speaker 2: heard that early, but they pretty much gave it to Trump.

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Speaker 2: So somebody got the duty to dump a poll that

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Speaker 2: Trump's gonna win Ohio by five or more. And of

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Speaker 2: course that's media speak for it's going to be eight

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Speaker 2: or more. And I pegged Ohio right about eight points,

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Speaker 2: and then I learned about voter registration by party, and

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Speaker 2: I wound up crafting my own map, deconstructing the known map,

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Speaker 2: calling Pennsylvania Michigan for Trump, and understanding where the rest

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Speaker 2: of the states were going to fall. And presidential elections

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Speaker 2: are extremely predictable based on past trends and tendencies. And

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Speaker 2: Rich likes to call the twenty twenty election a quasi election,

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Speaker 2: and I'd say that's a really good description of it,

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Speaker 2: because I've researched that thing for four years. I've had time.

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Speaker 1: To I know you have.

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Speaker 2: I've had time to dump my brain out and question myself,

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Speaker 2: question of my insanity, go back and rehash numbers. And

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Speaker 2: what I've been able to find is enough clearing inconsistencies

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Speaker 2: where I can tell something that has a normal looking

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Speaker 2: output and a normal looking where it seems like something

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Speaker 2: did not happen here, Like Miami Dade County's a great example.

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Speaker 2: I believe Trump carried three states in twenty twenty with

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Speaker 2: the certified results that he wasn't supposed to. I think

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Speaker 2: that he was supposed to have North Carolina, Florida, and

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Speaker 2: Texas ripped out from under him. Yes, Texas, Joe Biden

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Speaker 2: had six hundred thousand more votes in Texas in a

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Speaker 2: losing effort than Donald Trump won with in twenty sixteen.

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Speaker 1: So Trump say that again, is for real? That for real?

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Speaker 2: Joe Biden's vote total in Texas in twenty twenty was

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Speaker 2: six hundred thousand higher than Trump's winning total from twenty sixteen.

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Speaker 1: How is that even possible that Trump's saying?

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Speaker 2: So part of the eighty one million votes is a

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Speaker 2: lot of votes in losing columns all over the country.

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Speaker 2: So you know, I've been screaming that Biden looks like

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Speaker 2: he's got a million fraudulent votes in Texas in twenty twenty,

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Speaker 2: and everybody says, well, you're crazy. Trump won the state. Yeah,

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Speaker 2: he won the state. And his gain was the largest

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Speaker 2: Republican gain in the history of the Republican Party in

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Speaker 2: any won election, and the only one by five and

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Speaker 2: a half points. And little by little, people have been

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Speaker 2: unpacking that in Tarrant County and in Harris County, and

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Speaker 2: there's two hundred and fifty four counties in Texas. Now

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Speaker 2: we're looking like we're going to have a more normalized turnout.

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Speaker 2: So I'm wondering if these twenty twenty four stats are

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Speaker 2: a confirmation that Trump is surging or a double confirmation

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Speaker 2: that I was right about twenty twenty.

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Speaker 3: You're saying that these that these you know, million additional

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Speaker 3: votes in Texas for example, aren't They're not showing up,

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Speaker 3: They're not there, seth.

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Speaker 1: So let me ask you a question.

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Speaker 3: Is that just because Republicans have gotten better at identifying it?

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Speaker 3: Or is the deep state just like screw it Kamala

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Speaker 3: is worse. I mean, what's your take on why those

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Speaker 3: those votes aren't there at this time around, or at

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Speaker 3: least it seems that way as of right now, right Texas.

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Speaker 2: Has dumped more than a million registered voters from the

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Speaker 2: role since twenty twenty, very quietly and over a long

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Speaker 2: period of time. Texas doesn't register by party, but it

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Speaker 2: does seem to voter role purges only hurt one party

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Speaker 2: in particular. And that's very evident in your state, in

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Speaker 2: Philadelphia County. But what I was gonna say about Miami

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Speaker 2: Dade County is that Miami Dade County is the only

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Speaker 2: county in America with more than one hundred or with

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Speaker 2: more than a million votes certified in twenty twenty where

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Speaker 2: Biden lost votes from Hillary. Every other county of that size.

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Speaker 2: He gained massive amounts of votes, so something did not

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Speaker 2: happen in Miami. So I can spot this stuff in

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Speaker 2: the states where this seems to be low. It seems

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Speaker 2: to be let off the gas here. And I think

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Speaker 2: the best explanation is that there were organized ballot harvesting

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Speaker 2: efforts in conjunction with massive expanded early in mail end

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Speaker 2: voting to max out the Democrat vote share everywhere possible.

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Speaker 2: And of course it has to thrive on existing voter registrations,

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Speaker 2: which absolutely out Michigan. Michigan is the worst of the

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Speaker 2: blue collar Big three, Pennsylvania, Michigan, Wisconsin. Pennsylvania is in

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Speaker 2: the middle. In Wisconsin is the most winnable for Trump

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Speaker 2: because it has the cleanest voter roles.

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Speaker 3: Wow, I did not know that, tell me. Yeah, just

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Speaker 3: so people are tracking Seth. I've told people this before

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Speaker 3: that in Pennsylvania, for example, with you, if there's an

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Speaker 3: electronic voter regie stration database, third party groups you know

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Speaker 3: that are that have political allegiances can gain access to

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Speaker 3: those databases. And if the voter rolls aren't clean, people die,

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Speaker 3: People move away the Democrats all they need, especially at

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Speaker 3: the height of COVID when it was simple, and there's

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Speaker 3: no deadline, no postmark requirement, no signature signature verification. Hell,

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Speaker 3: every first time voter in the state of Pennsylvania that

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Speaker 3: was voting via absentee or via mail in they didn't

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Speaker 3: submit a photocopy of their ID, which is required by law.

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Speaker 3: I mean, there were so many things in Pennsylvania that

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Speaker 3: happened that just that just were indicative of fraudulent votes.

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Speaker 3: But like, tell people how that works.

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Speaker 1: They can.

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Speaker 3: All you need is, you know, two people, a printer,

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Speaker 3: a ballot, and a secrecy envelope, and you can vote

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Speaker 3: for people, which is why so many people showed up

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Speaker 3: on election day and being told they were told that

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Speaker 3: they already voted.

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Speaker 1: You know.

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Speaker 2: Well, so Number one, ballot harvesting in Pennsylvania, I believe

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Speaker 2: that falls more in a gray area than a straight

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Speaker 2: up illegality. But in a number of states ballot harvesting

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Speaker 2: is one hundred percent illegal. Georgia a great example. It's

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Speaker 2: not legal. But and now two thousand mules. I don't

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Speaker 2: swear by two thousand mules. There are some issues with

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Speaker 2: two thousand mules, but it is fact that they've got

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Speaker 2: video footage of people showing up at drop boxes with

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Speaker 2: massive stacks of ballots and handing it into the drought

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Speaker 2: box and turning around like a quarterback about to make

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Speaker 2: a handoff and dropping gloves off in a garbage camp

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Speaker 2: like they've been there multiple times. So some of these

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Speaker 2: canvassers we've gotten in states like so Tony Schupin aughtit

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Speaker 2: the vote, Pa. She's fantastic, right, you got people all

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Speaker 2: over Wisconsin. Some of the Wisconsin election integrity groups they

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Speaker 2: did canvassing and they went to Madison, Wisconsin, Dane County,

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Speaker 2: which is one of their heartbeats. If the Democrats have

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Speaker 2: a hope in Wisconsin and they're finding apartment buildings with

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Speaker 2: twenty one, twenty three, twenty six voter registrations per unit,

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Speaker 2: I mean we're talking about massive if. I mean, I

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Speaker 2: don't think anybody's got family units that are that big

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Speaker 2: in Wisconsin. But we've got twenty thirty people registered in

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Speaker 2: each unit. Because what happens is they live there and

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Speaker 2: they never clean out. They never they ever removed themselves

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Speaker 2: from a voter role. The only way we're gonna get

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Speaker 2: around the voter role corruption problem is to go North Dakota.

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Speaker 2: North Dakota is the only state without voter registration, and

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Speaker 2: by my measurements of the twenty twenty election easily had

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Speaker 2: the cleanest election of all fifty states, with fewer new

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Speaker 2: votes cast in twenty twenty than in twenty sixteen.

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Speaker 1: Wow.

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Speaker 2: Meanwhile, the rest of the country had this massive turnout

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Speaker 2: boom which was artificial because of the corruption of voter registration.

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Speaker 1: God.

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Speaker 3: So, okay, so in twenty twenty, that's what you think

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Speaker 3: that the Democrats? Did you think that it was all

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Speaker 3: voter registrartion? I mean, I agree with you, but is

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Speaker 3: that what you think?

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Speaker 2: That is a multi prompt problem. You've heard a lot

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Speaker 2: of the people with the theories about the voting systems,

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Speaker 2: electronic voting systems and software. So I don't miss the

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Speaker 2: news has just.

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Speaker 3: Came out with Jocelyn Benson and Mission of Jess yesterday

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Speaker 3: we talked about the show with Dominion. That issue happened

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Speaker 3: in twenty twenty as well, but it's just coming out

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Speaker 3: today as if it's a new thing.

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Speaker 2: Then they're setting the stage for when Trump wins the

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Speaker 2: election to delegitimize this victory. In my opinion, but how

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Speaker 2: is the fraud happening? Number One, The foundation of it's

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Speaker 2: in the roles, there's manual blocking and tackling for cheating,

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Speaker 2: which is the mail in scheme and the ballot harvesting.

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Speaker 2: So I think that relies on known corrupt counties where

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Speaker 2: you know for a fact that these folks are Soros funded.

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Speaker 2: These are absolutely corrupt human beings, like the Milwaukee elections

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Speaker 2: officials that have femail traffic about their election stuff. I

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Speaker 2: think that they're outsourcing shopping the list of available voter

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Speaker 2: registrations that aren't going to be shown up and claimed

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Speaker 2: by a real human being, where you've got ten thousand

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Speaker 2: of these names that are not real people, but we

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Speaker 2: can generate or request a ballot for these ten thousand people.

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Speaker 2: So what happens is you request Seth Keshel's ballot. I'm

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Speaker 2: going to show up as a four to four voter

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Speaker 2: wanting to vote, and you're going to have me already voted,

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Speaker 2: and I'm going to raise holy hell about that. So

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Speaker 2: you don't want to get caught. But when you have

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Speaker 2: ten thousand people out of a million registrations that can't vote,

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Speaker 2: but they're still in the roles and they're coded and

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Speaker 2: you can find them, then someone can shop those registrations

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Speaker 2: out and what's happening. And this is why I know

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Speaker 2: this is because I read between the lines. I don't

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Speaker 2: trust much that the agencies do. But the FBI has

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Speaker 2: busted a few voter fraud rings. They will not touch

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Speaker 2: a presidential, a gubernatorial, a congressional, or a Senate race, okay,

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Speaker 2: but they go after some of these small fries like

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Speaker 2: somebody say, why, uh, I think to show that there's

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Speaker 2: a modicum of diligence, and hey, we we checked it out.

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Speaker 2: We found fraud here. But no, there was no fraud

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Speaker 2: in the presidential race. What they've been busting is Democrats

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Speaker 2: cheating against other Democrats and Democrat primaries. And there's two

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Speaker 2: states that.

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Speaker 1: Are I have seen this too, Yes, its Connecticut.

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Speaker 2: And New Jersey. So in Paterson, New Jersey. The FBI

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Speaker 2: investigated some of this stuff and I sourced it one

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Speaker 2: of my substack articles because the investigation was interesting. Maybe

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Speaker 2: they found a field agent who actually cared. And what

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Speaker 2: they found was there's there's one dude. So basically he's

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Speaker 2: a political consultant. And you obvious, if you were to

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Speaker 2: run for office again, you would have ten people in

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Speaker 2: your inbox wanting to get you to get your campaign

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Speaker 2: to buy their slight and you know them by name.

435
00:22:09,119 --> 00:22:10,920
Speaker 2: You're going to have the regulars and then maybe a

436
00:22:10,920 --> 00:22:14,280
Speaker 2: few upstarts that want your business. So what happens is

437
00:22:14,400 --> 00:22:17,720
Speaker 2: one of these guys who's a you know, somebody that

438
00:22:17,720 --> 00:22:21,360
Speaker 2: can do all things for the campaign. He can go

439
00:22:22,119 --> 00:22:24,560
Speaker 2: get the names that are on these lists and then

440
00:22:24,680 --> 00:22:28,080
Speaker 2: go collect a ballot for them and swear on a

441
00:22:28,080 --> 00:22:30,800
Speaker 2: written form that he's getting the ballot for them and

442
00:22:30,840 --> 00:22:33,800
Speaker 2: taking it to them, And then he buys the ballot

443
00:22:33,880 --> 00:22:36,680
Speaker 2: from that person, and then he gets a hundred of

444
00:22:36,720 --> 00:22:38,840
Speaker 2: those and casts it as he wants. And in some

445
00:22:38,880 --> 00:22:40,960
Speaker 2: of these races where there's not big turnout, you can

446
00:22:41,000 --> 00:22:42,840
Speaker 2: swing a race on one hundred and fifty or two

447
00:22:42,920 --> 00:22:45,919
Speaker 2: hundred fake ballots. Now imagine you've got twenty people that

448
00:22:45,960 --> 00:22:48,080
Speaker 2: are doing that. Then you can get two thousand fake

449
00:22:48,119 --> 00:22:50,439
Speaker 2: ballots in a county and a lot of my numbers

450
00:22:50,480 --> 00:22:55,000
Speaker 2: in Pennsylvania, So like Alleghany County likely has the most

451
00:22:55,040 --> 00:22:56,879
Speaker 2: fake ballots of any county in Pennsylvania.

452
00:22:56,880 --> 00:23:00,600
Speaker 3: So, guests, Seth, you and I haven't discussed this prior

453
00:23:00,640 --> 00:23:03,440
Speaker 3: to the show, but it's I'm interesting that you say

454
00:23:03,480 --> 00:23:05,920
Speaker 3: that because when I talked to people, people talk about

455
00:23:05,920 --> 00:23:08,200
Speaker 3: Philly and yeah, Philly, Philly's bad. You talk to people

456
00:23:08,240 --> 00:23:10,320
Speaker 3: in Philly, I'm like, you ask someone straight up on

457
00:23:10,359 --> 00:23:12,600
Speaker 3: the street, is their voter fraud in Philly, They're like, man, it's.

458
00:23:12,520 --> 00:23:14,199
Speaker 1: Philadelphia, Like, of course there is.

459
00:23:14,480 --> 00:23:19,120
Speaker 3: But Pittsburgh, Alleghany County was worse than twenty twenty big time.

460
00:23:19,520 --> 00:23:22,520
Speaker 2: My estimate for Alleghany County was likely forty eight thousand

461
00:23:22,600 --> 00:23:26,119
Speaker 2: minimum fraudulent ballots in Allegheny County. And most of that

462
00:23:26,200 --> 00:23:28,919
Speaker 2: was not in the core of deep urban Pittsburgh. Who

463
00:23:29,000 --> 00:23:31,400
Speaker 2: was out in the in the more conservative.

464
00:23:30,800 --> 00:23:32,600
Speaker 1: Work, Yeah, that was in my district.

465
00:23:33,080 --> 00:23:35,840
Speaker 3: Like, I had eighty five percent of Alleghany County outside

466
00:23:35,840 --> 00:23:36,280
Speaker 3: the city.

467
00:23:36,520 --> 00:23:39,200
Speaker 2: So you were a desired target. Donald Trump was the

468
00:23:39,320 --> 00:23:40,440
Speaker 2: number one target in the state.

469
00:23:40,640 --> 00:23:44,280
Speaker 3: Were well, yeah, yes, at PA seventeen. And but this

470
00:23:44,400 --> 00:23:47,480
Speaker 3: was before they they jerrymandered the district into the new

471
00:23:47,560 --> 00:23:51,120
Speaker 3: PA seventeen. But PA seventeen back then, Seth had eighty

472
00:23:51,160 --> 00:23:54,560
Speaker 3: five percent of Alleghany County outside of the city of Pittsburgh,

473
00:23:54,600 --> 00:23:57,520
Speaker 3: all of Beaver County, in a small portion of Butler County,

474
00:23:57,760 --> 00:24:00,680
Speaker 3: and that was the I was ground zero for all

475
00:24:00,720 --> 00:24:03,600
Speaker 3: of that. This was the county that uh where the

476
00:24:03,640 --> 00:24:06,960
Speaker 3: Democrats sent out thirty thousand ballots a month before election

477
00:24:07,040 --> 00:24:09,840
Speaker 3: day and President Trump was calling it out to wrong addresses.

478
00:24:09,880 --> 00:24:13,040
Speaker 3: The Democrats are saying, count every ballot, even the ballots

479
00:24:13,040 --> 00:24:15,600
Speaker 3: that were cast outside the district. I mean, it was

480
00:24:15,640 --> 00:24:19,160
Speaker 3: absolutely insane. And I witnessed this stuff with my own

481
00:24:19,200 --> 00:24:21,640
Speaker 3: two eyes. And that's why I say to people said

482
00:24:21,680 --> 00:24:24,000
Speaker 3: that I'll never be gas lit into believing anything else.

483
00:24:24,040 --> 00:24:26,080
Speaker 3: That they one hundred percent stole the twenty twenty election,

484
00:24:26,400 --> 00:24:28,800
Speaker 3: and no one will convince me otherwise because I saw it.

485
00:24:28,840 --> 00:24:32,080
Speaker 2: I was there, right, So Butler County. I'm sure most

486
00:24:32,119 --> 00:24:33,960
Speaker 2: of your listeners probably know Butler County as well.

487
00:24:33,960 --> 00:24:35,400
Speaker 1: Oh yeah, yes, yes.

488
00:24:35,680 --> 00:24:38,919
Speaker 2: When Trump survived the assassination attempt, So Butler.

489
00:24:38,960 --> 00:24:41,160
Speaker 1: I was there as well. Seth. That was with President

490
00:24:41,200 --> 00:24:42,160
Speaker 1: Trump twenty minutes before.

491
00:24:42,440 --> 00:24:44,760
Speaker 2: Yet I saw that he's that ridiculous. You played that,

492
00:24:44,800 --> 00:24:46,680
Speaker 2: you played the role of a hero. I remember that.

493
00:24:46,680 --> 00:24:49,760
Speaker 2: That's all that wasn't supposed to be doing well, thank you, jeez.

494
00:24:50,280 --> 00:24:53,440
Speaker 2: Butler County is just due north of Alleghany and Pittsburgh,

495
00:24:53,640 --> 00:24:57,479
Speaker 2: and so I mapped every preseat in Pennsylvania of all

496
00:24:57,520 --> 00:25:00,680
Speaker 2: sixty seven counties for an estimate of like the fraudulent

497
00:25:00,720 --> 00:25:02,800
Speaker 2: activity in the twenty twenty race, because I think it

498
00:25:02,880 --> 00:25:06,240
Speaker 2: matters still. But this was my map of Butler County,

499
00:25:07,440 --> 00:25:11,320
Speaker 2: all right, So just so you know, Pittsburgh is right

500
00:25:11,359 --> 00:25:14,199
Speaker 2: below where this is, and it looks to me like

501
00:25:14,359 --> 00:25:17,840
Speaker 2: harvesters made their way into Butler County and got this corner,

502
00:25:18,640 --> 00:25:21,320
Speaker 2: the southwest corner, which is like the Cranberry area.

503
00:25:21,160 --> 00:25:23,120
Speaker 1: That's right in that I lived just north of there.

504
00:25:23,280 --> 00:25:25,640
Speaker 2: And the further you go up into the hinter lands,

505
00:25:26,200 --> 00:25:28,679
Speaker 2: then the cleaner the trends get, meaning the vote totals

506
00:25:28,720 --> 00:25:31,920
Speaker 2: aligned with past trends and voter registration trends. But people

507
00:25:31,920 --> 00:25:33,640
Speaker 2: did not get out there as far.

508
00:25:33,800 --> 00:25:38,400
Speaker 3: Seth that it's so crazy. But that red portion back then,

509
00:25:39,160 --> 00:25:41,680
Speaker 3: this is insane. You and I did not coordinate any

510
00:25:41,720 --> 00:25:44,359
Speaker 3: of this at all. But that red portion on the

511
00:25:44,400 --> 00:25:46,760
Speaker 3: map that you just showed was the small bit of

512
00:25:46,800 --> 00:25:51,480
Speaker 3: Butler from PA seventeen. That was just the Butler County

513
00:25:51,800 --> 00:25:52,800
Speaker 3: that was in my district.

514
00:25:52,840 --> 00:25:55,200
Speaker 2: This is probably your portion of Beaver County right closest

515
00:25:55,200 --> 00:25:55,920
Speaker 2: to Pittsburgh.

516
00:25:56,080 --> 00:25:59,320
Speaker 3: Yes, that's all of it, Yes, I have all of

517
00:25:59,440 --> 00:26:01,200
Speaker 3: I've got all of Beaver County.

518
00:26:01,680 --> 00:26:04,480
Speaker 2: Right so Beaver County. That's where that's where Tony actually lives.

519
00:26:04,720 --> 00:26:06,040
Speaker 1: But this was back then.

520
00:26:06,119 --> 00:26:08,240
Speaker 3: By the way, this was like when this is when

521
00:26:08,359 --> 00:26:11,280
Speaker 3: like because they they jerrymandered the district and made it

522
00:26:11,280 --> 00:26:13,719
Speaker 3: more favorable for Democrats. This was back in twenty twenty.

523
00:26:13,800 --> 00:26:16,320
Speaker 3: But yes, it was insane what was going on back then.

524
00:26:16,600 --> 00:26:19,000
Speaker 2: So I'm one, I am telling you, I am, I am.

525
00:26:19,080 --> 00:26:20,800
Speaker 2: This is why the media calls me one of the

526
00:26:20,840 --> 00:26:23,280
Speaker 2: four horsemen of the election denial of Popably.

527
00:26:23,920 --> 00:26:27,360
Speaker 1: That's a pretty you should incorporate that into your branding.

528
00:26:27,680 --> 00:26:32,000
Speaker 2: A founding father of the election denial movement every pre

529
00:26:32,080 --> 00:26:36,119
Speaker 2: scene in Pennsylvania. And of course this is a zoomable

530
00:26:36,160 --> 00:26:36,960
Speaker 2: PDF file.

531
00:26:38,240 --> 00:26:39,560
Speaker 1: That's pretty amazing. Man.

532
00:26:39,880 --> 00:26:43,520
Speaker 3: See, folks, this is why we have military intelligence data

533
00:26:43,560 --> 00:26:46,119
Speaker 3: guys on this show that can bring the receipts. And

534
00:26:46,440 --> 00:26:48,640
Speaker 3: what's crazy is that you just heard Seth go through

535
00:26:48,640 --> 00:26:51,159
Speaker 3: the facts and I was there on the ground and

536
00:26:51,200 --> 00:26:53,640
Speaker 3: I lived them, and that's exactly what happened.

537
00:26:53,760 --> 00:26:55,199
Speaker 1: That's one hundred percent what happened.

538
00:26:55,320 --> 00:26:58,280
Speaker 2: So my theory is that the corrupt counties are direct

539
00:26:58,359 --> 00:27:02,840
Speaker 2: participants in this where I think they're probably shopping voter lists.

540
00:27:03,000 --> 00:27:05,840
Speaker 2: I think that they're extending hours as need be. I

541
00:27:05,880 --> 00:27:09,080
Speaker 2: think they're ignoring rules and laws basically like the rick

542
00:27:09,119 --> 00:27:11,800
Speaker 2: flares of the election game. All right, and then you've

543
00:27:11,840 --> 00:27:15,600
Speaker 2: got the other counties, your Bradford's and your Armstrongs, that

544
00:27:15,640 --> 00:27:18,560
Speaker 2: are not corrupt counties. But because of the way the

545
00:27:18,640 --> 00:27:21,960
Speaker 2: law is structured and the exploitation of it, you know,

546
00:27:22,040 --> 00:27:24,240
Speaker 2: like good example, I can drive down the street I

547
00:27:24,280 --> 00:27:27,320
Speaker 2: live on and probably get away with ripping up campaign

548
00:27:27,320 --> 00:27:30,399
Speaker 2: signs I don't like. Now that's against the law, but

549
00:27:30,440 --> 00:27:32,120
Speaker 2: if I can't be caught, then it's going to get

550
00:27:32,160 --> 00:27:35,520
Speaker 2: ripped up. So it's very hard for sheriffs to patrol

551
00:27:35,880 --> 00:27:38,040
Speaker 2: a county with you know how Pennsylvania set up.

552
00:27:38,040 --> 00:27:40,880
Speaker 1: It's old, right, and that's exactly right.

553
00:27:41,040 --> 00:27:43,520
Speaker 2: Yeah, You've got roads set up in every different direction

554
00:27:43,640 --> 00:27:45,480
Speaker 2: coming off and it takes twenty minutes to get a

555
00:27:45,480 --> 00:27:47,960
Speaker 2: few miles through the woods, depending what the weather's doing.

556
00:27:48,280 --> 00:27:50,359
Speaker 2: So it's very hard to police all this stuff up.

557
00:27:50,440 --> 00:27:52,640
Speaker 2: And those kind of counties that are not corrupt counties

558
00:27:52,960 --> 00:27:56,880
Speaker 2: are still open four hundreds or thousands of MAX ballots. Now,

559
00:27:56,880 --> 00:27:59,880
Speaker 2: what the twenty twenty election does allow me to anticipate

560
00:28:00,359 --> 00:28:02,760
Speaker 2: is I do not believe in most of these Trump

561
00:28:02,800 --> 00:28:05,880
Speaker 2: counties in Pennsylvania, the smaller ones. I don't believe that

562
00:28:06,119 --> 00:28:11,640
Speaker 2: Harris can possibly exceed Joe Biden's vote count in those counties.

563
00:28:11,920 --> 00:28:14,919
Speaker 2: I think that whatever Biden's count was is the absolute

564
00:28:15,040 --> 00:28:19,040
Speaker 2: lid for Democrat votes in this election and certainly below.

565
00:28:19,320 --> 00:28:21,199
Speaker 2: So it helps me to forecast because I don't think

566
00:28:21,240 --> 00:28:23,280
Speaker 2: they have the ability, based on the current mail trends

567
00:28:23,280 --> 00:28:25,919
Speaker 2: and the turnout rates and the registration data, to exceed

568
00:28:26,040 --> 00:28:27,719
Speaker 2: Biden's vote counts in those counties.

569
00:28:27,760 --> 00:28:31,760
Speaker 3: Which so let's stay stay right there, let me take

570
00:28:31,760 --> 00:28:33,960
Speaker 3: a quick break, let me get two more sponsorship breeds,

571
00:28:33,960 --> 00:28:36,440
Speaker 3: and then I want to I want to shift to

572
00:28:36,600 --> 00:28:39,320
Speaker 3: this cycle and the battlegrounds, and we can start with Pennsylvania,

573
00:28:39,360 --> 00:28:41,760
Speaker 3: if that's cool, since we're already there, got it all right?

574
00:28:41,760 --> 00:28:44,200
Speaker 3: Stay right there, Seth. I'll be right back back with

575
00:28:44,480 --> 00:28:48,840
Speaker 3: Seth Keshell. Former Army captain same rank as me, veteran

576
00:28:48,880 --> 00:28:51,800
Speaker 3: of the Afghan War and one of the four Horsemen

577
00:28:52,000 --> 00:28:54,240
Speaker 3: of what was the title, Seth four Horsemen.

578
00:28:53,960 --> 00:28:56,840
Speaker 2: One of the four horsemen of the Election denial Apocalypse

579
00:28:56,960 --> 00:29:00,120
Speaker 2: or original gangster founding father of the election denial.

580
00:29:02,600 --> 00:29:05,080
Speaker 3: That if you that should be front and center on

581
00:29:05,280 --> 00:29:07,960
Speaker 3: all of your branding because it's just so freaking great.

582
00:29:09,120 --> 00:29:11,880
Speaker 3: All right, So let's let's shift gears to twenty twenty four.

583
00:29:11,920 --> 00:29:14,040
Speaker 3: We talked a little bit about the polling yesterday of

584
00:29:14,080 --> 00:29:16,560
Speaker 3: these battleground states, and.

585
00:29:16,480 --> 00:29:18,920
Speaker 1: So we're on Pennsylvania. Let's talk about Pennsylvania.

586
00:29:19,040 --> 00:29:22,880
Speaker 3: You you said it's gonna be hard for Kamala to

587
00:29:23,000 --> 00:29:27,480
Speaker 3: exceed Biden's cap and what's a better way to say it,

588
00:29:27,760 --> 00:29:30,160
Speaker 3: to exceed Biden's vote.

589
00:29:30,280 --> 00:29:33,520
Speaker 1: Count in a lot of these Pennsylvania counties. Why do

590
00:29:33,600 --> 00:29:34,280
Speaker 1: you think that is?

591
00:29:34,880 --> 00:29:36,880
Speaker 2: All right? So if you look at the data in

592
00:29:36,920 --> 00:29:39,080
Speaker 2: two thousand and eight, oh, it's an important year for

593
00:29:39,160 --> 00:29:46,080
Speaker 2: understanding the political situation in Pennsylvania. Pennsylvania was a reliable

594
00:29:46,480 --> 00:29:52,240
Speaker 2: Democrat state, but without fantastic margins and James Carville's right,

595
00:29:52,680 --> 00:29:56,200
Speaker 2: James Carville's described the state as as Philadelphia and Pittsburgh

596
00:29:56,240 --> 00:30:00,280
Speaker 2: with Alabama in between. Right, So Pennsylvania is is not

597
00:30:00,360 --> 00:30:03,560
Speaker 2: a liberal state. People don't understand this. People that don't

598
00:30:03,560 --> 00:30:06,280
Speaker 2: travel and don't understand the political equation or the working

599
00:30:06,280 --> 00:30:10,280
Speaker 2: class dynamics of America have too often associated Blue Coast

600
00:30:10,400 --> 00:30:14,360
Speaker 2: with Pennsylvania, Minnesota, and now they may have bubbles. You know,

601
00:30:14,400 --> 00:30:18,200
Speaker 2: you might have Westchester, Pennsylvania, but Pittsburgh is not a

602
00:30:18,240 --> 00:30:21,440
Speaker 2: liberal place, neither are the surrounding areas. It may have

603
00:30:21,480 --> 00:30:25,520
Speaker 2: its bubbles and its core, but it's not a liberal state.

604
00:30:25,600 --> 00:30:28,479
Speaker 2: So as the wokeness has taken over the Democrats, and

605
00:30:28,680 --> 00:30:30,880
Speaker 2: not just the wokeness but the party. In two thousand

606
00:30:30,920 --> 00:30:34,880
Speaker 2: and eight to ten timeframe, Obama high pointed Pennsylvania with

607
00:30:34,920 --> 00:30:37,320
Speaker 2: a ten point four percent margin of victory and that

608
00:30:37,400 --> 00:30:40,320
Speaker 2: was the biggest margin for either party since nineteen sixty

609
00:30:40,320 --> 00:30:43,880
Speaker 2: four Linda Johnson National Landslide. And ever since then, the

610
00:30:43,960 --> 00:30:46,640
Speaker 2: state has been losing Democrats strength, and that started in

611
00:30:46,680 --> 00:30:49,880
Speaker 2: the twenty ten midterms. Around that time, the Democrats began

612
00:30:50,040 --> 00:30:54,840
Speaker 2: openly being portrayed as anti industry, anti fossil fuels, anti

613
00:30:54,920 --> 00:30:58,520
Speaker 2: working class, and they lost white men. That showed up

614
00:30:58,520 --> 00:31:01,000
Speaker 2: in the vote totals in twenty twelve. Obama lost more

615
00:31:01,000 --> 00:31:03,240
Speaker 2: than three hundred thousand of his votes back in the

616
00:31:03,240 --> 00:31:06,600
Speaker 2: twenty twelve election. Romney's problem was he couldn't pick them

617
00:31:06,640 --> 00:31:10,040
Speaker 2: up off the ground like Donald Trump did. Romney only

618
00:31:10,080 --> 00:31:13,000
Speaker 2: shifted the Philly suburbs and got some of the interior

619
00:31:13,040 --> 00:31:15,360
Speaker 2: somewhat more red but his margin still was in half.

620
00:31:15,400 --> 00:31:17,520
Speaker 2: It was a five point four margin for Obama in

621
00:31:17,560 --> 00:31:20,560
Speaker 2: twenty twelve, so the trent was already on. And then

622
00:31:20,560 --> 00:31:24,080
Speaker 2: when Trump came on board, Republican membership actually serged and

623
00:31:24,160 --> 00:31:27,800
Speaker 2: Democrats continued to drop registrations, and that was signifying that

624
00:31:27,840 --> 00:31:30,200
Speaker 2: this is going to close inside of five points, and

625
00:31:30,280 --> 00:31:32,720
Speaker 2: Trump wound up flipping the state. Trump gained three hundred

626
00:31:32,720 --> 00:31:36,280
Speaker 2: thousand votes. Clinton continued to drop, and in twenty twenty

627
00:31:37,360 --> 00:31:40,040
Speaker 2: it was twenty one to one Republican Party registration edge.

628
00:31:40,080 --> 00:31:42,040
Speaker 2: For new registrations, it was two hundred and forty two

629
00:31:42,080 --> 00:31:45,800
Speaker 2: thousand new Republican registrations and the Dems only gained eleven thousand.

630
00:31:46,200 --> 00:31:49,080
Speaker 2: So all that signified that Trump should have expanded his

631
00:31:49,160 --> 00:31:53,320
Speaker 2: margins in Pennsylvania. I've come up with numbers over six points. Now,

632
00:31:53,400 --> 00:31:55,880
Speaker 2: it's hard to calculate exactly where that should have ballparked,

633
00:31:55,920 --> 00:31:58,040
Speaker 2: given the expanse and turnout, but Trump should have easily

634
00:31:58,080 --> 00:32:01,440
Speaker 2: held Pennsylvania in twenty twenty. And when I look at

635
00:32:01,440 --> 00:32:04,200
Speaker 2: these flyover counties in Pennsylvania, which is most of them,

636
00:32:04,280 --> 00:32:07,280
Speaker 2: Trump trended sixty four of sixty seven counties more Republican

637
00:32:07,320 --> 00:32:08,200
Speaker 2: in the last four years.

638
00:32:08,240 --> 00:32:09,120
Speaker 1: That's exactly right.

639
00:32:09,520 --> 00:32:12,520
Speaker 2: Oat Su County went to the right. So when you

640
00:32:12,560 --> 00:32:15,280
Speaker 2: look at it, let's just take Juniata County, or maybe

641
00:32:15,280 --> 00:32:18,880
Speaker 2: we could take Jefferson County. Those counties have a Biden

642
00:32:18,960 --> 00:32:21,600
Speaker 2: vote total that is higher than Hillary in twenty sixteen,

643
00:32:21,840 --> 00:32:23,840
Speaker 2: and in a lot of cases higher than Obama in

644
00:32:23,880 --> 00:32:26,800
Speaker 2: twenty twelve, but not at the two thousand and eight number.

645
00:32:27,280 --> 00:32:29,360
Speaker 2: So they weren't able to get back to the eight number.

646
00:32:29,360 --> 00:32:31,480
Speaker 2: But they did elevate from twelve and sixteen. That is

647
00:32:31,520 --> 00:32:34,760
Speaker 2: because many weeks and months of ballot harvesting and planning

648
00:32:34,840 --> 00:32:37,560
Speaker 2: and mail in ballots scams were put in place to

649
00:32:37,720 --> 00:32:43,200
Speaker 2: maximize Biden's vote totals in the extremely trumpy, almost Wyoming

650
00:32:43,400 --> 00:32:47,120
Speaker 2: like portions of Pennsylvania. I do not believe that based

651
00:32:47,120 --> 00:32:50,400
Speaker 2: on organic lack of appeal and based on electioneering, I

652
00:32:50,400 --> 00:32:52,920
Speaker 2: don't think Harris can reach those vote totals. In twenty

653
00:32:52,960 --> 00:32:55,600
Speaker 2: twenty four, Trump is going to consume more of the vote.

654
00:32:55,600 --> 00:32:56,960
Speaker 2: I don't think they'll be able to turn out as

655
00:32:57,040 --> 00:32:58,640
Speaker 2: many ballots ballots not so.

656
00:32:59,000 --> 00:33:00,520
Speaker 3: I mean, you see that play out in the data

657
00:33:00,600 --> 00:33:03,320
Speaker 3: right now. I've been running this vote banking operation for

658
00:33:03,400 --> 00:33:07,200
Speaker 3: mail in ballots who built this infrastructure here and kind

659
00:33:07,240 --> 00:33:09,600
Speaker 3: of fighting the way the Democrats do, except for without

660
00:33:09,600 --> 00:33:12,520
Speaker 3: the cheating. But they only have a three hundred and

661
00:33:12,520 --> 00:33:16,400
Speaker 3: seventy nine thousand person mail in ballot firewall, which back

662
00:33:16,400 --> 00:33:18,920
Speaker 3: in twenty twenty, it's like it was like one point

663
00:33:18,920 --> 00:33:19,640
Speaker 3: one million.

664
00:33:20,320 --> 00:33:23,840
Speaker 2: I am really only worried as far as margins slide goes.

665
00:33:23,880 --> 00:33:28,560
Speaker 2: I'm only worried about Montgomery and Delaware Counties, Philadelphia County.

666
00:33:28,600 --> 00:33:30,760
Speaker 2: Trump actually lost Philly County by less than he lost

667
00:33:30,760 --> 00:33:33,600
Speaker 2: it by in twenty sixteen. Now are they packing votes, yes,

668
00:33:33,640 --> 00:33:35,560
Speaker 2: because what we don't know one of our intel gaps

669
00:33:35,600 --> 00:33:37,840
Speaker 2: is how many of these votes are fraudulent and have

670
00:33:37,960 --> 00:33:40,240
Speaker 2: always been fraudulent for the last thirty years. I don't

671
00:33:40,280 --> 00:33:42,680
Speaker 2: know the answer. And so maybe they have a well

672
00:33:42,720 --> 00:33:44,840
Speaker 2: where they go to get half a million ballots right

673
00:33:44,880 --> 00:33:47,400
Speaker 2: off the bat, But they've they're down big time in

674
00:33:47,400 --> 00:33:49,720
Speaker 2: Philly County. I think they're missing ninety three mail in

675
00:33:49,800 --> 00:33:52,719
Speaker 2: requests based on this time last year, ninety three thousand,

676
00:33:52,720 --> 00:33:56,080
Speaker 2: I should say, So they're missing big in the urban centers.

677
00:33:56,080 --> 00:33:59,120
Speaker 2: They're also missing big time in Cora, Allegheny County. So

678
00:33:59,360 --> 00:34:00,720
Speaker 2: I think they're gonna be missing a lot of the

679
00:34:00,840 --> 00:34:02,560
Speaker 2: urban vote, a lot of the minority vote's going to

680
00:34:02,640 --> 00:34:05,640
Speaker 2: move towards Trump. Richard says that Trump's got eleven percent

681
00:34:05,680 --> 00:34:07,880
Speaker 2: of black women and more than a quarter of black men.

682
00:34:08,360 --> 00:34:11,680
Speaker 2: Then you have a not insignificant amount of the Hispanic

683
00:34:11,719 --> 00:34:14,359
Speaker 2: working class out East Berks County's a good example of that.

684
00:34:14,760 --> 00:34:16,640
Speaker 2: And I'd be shocked if he doesn't get a better

685
00:34:16,640 --> 00:34:18,399
Speaker 2: share of the white working class vote than he got

686
00:34:18,440 --> 00:34:21,360
Speaker 2: even in twenty sixteen, because I doubt Kamala Harris has

687
00:34:21,400 --> 00:34:23,200
Speaker 2: ever held a wrench or a hammer or warn a

688
00:34:23,239 --> 00:34:25,440
Speaker 2: hard hat, and she wants to be in fracking.

689
00:34:26,040 --> 00:34:28,839
Speaker 1: That's exactly right. I mean, wow, So so.

690
00:34:28,840 --> 00:34:31,000
Speaker 2: Pa smells like a poor man's Ohio to.

691
00:34:31,000 --> 00:34:34,279
Speaker 3: Me, you just took the words out of my mouth.

692
00:34:34,320 --> 00:34:38,840
Speaker 3: I'm telling you seth Pennsylvania's elections. I'm talking the margin

693
00:34:38,880 --> 00:34:41,799
Speaker 3: of victory would be almost identical to Ohio if our

694
00:34:41,840 --> 00:34:43,760
Speaker 3: elections were as secure as Ohio.

695
00:34:43,840 --> 00:34:45,359
Speaker 2: I think you've got a little bit of a left

696
00:34:45,360 --> 00:34:47,359
Speaker 2: skew because I think your urban areas are a little

697
00:34:47,360 --> 00:34:50,960
Speaker 2: bit more troublesome than Ohio's. But I do see like Pennsylvania.

698
00:34:51,000 --> 00:34:54,000
Speaker 2: When I run the numbers, I ran a pessimistic forecast

699
00:34:54,080 --> 00:34:56,480
Speaker 2: where the Dems gained on a lot of their margins

700
00:34:56,480 --> 00:34:58,800
Speaker 2: in twenty twenty and Trump still won by a point

701
00:34:58,920 --> 00:35:03,200
Speaker 2: seventy five thousand votes. But in my registration based forecast,

702
00:35:03,239 --> 00:35:04,800
Speaker 2: I get numbers like you're seeing come out of the

703
00:35:04,800 --> 00:35:07,080
Speaker 2: big posters today. I've got about four and a half points.

704
00:35:07,160 --> 00:35:13,200
Speaker 3: Yeah, Echelon Echelon Insights had Pennsylvania Trump plus six. I

705
00:35:13,200 --> 00:35:15,719
Speaker 3: mean an atlas who who people like to say on

706
00:35:15,760 --> 00:35:18,040
Speaker 3: social media is the most accurate poster at twenty twenty

707
00:35:18,200 --> 00:35:20,760
Speaker 3: has Pennsylvania just today in their final poll of Trump

708
00:35:20,800 --> 00:35:21,439
Speaker 3: plus one.

709
00:35:22,480 --> 00:35:24,120
Speaker 2: Yeah, well it was actually one and a half before

710
00:35:24,120 --> 00:35:27,120
Speaker 2: the rounding. But I think that some people are kind

711
00:35:27,120 --> 00:35:29,680
Speaker 2: of hedging and maybe even accounting for the cheap machine.

712
00:35:30,120 --> 00:35:32,800
Speaker 2: I don't I personally don't think Josh Shapiro wants Harris

713
00:35:32,840 --> 00:35:33,640
Speaker 2: to win Pennsylvania.

714
00:35:33,640 --> 00:35:36,200
Speaker 3: I say this all the time. I completely agree. I mean,

715
00:35:36,200 --> 00:35:38,120
Speaker 3: the guy doesn't want to have to wait eight years

716
00:35:38,200 --> 00:35:38,920
Speaker 3: to be president.

717
00:35:39,160 --> 00:35:40,880
Speaker 2: So most people are going to say, well, how can you,

718
00:35:41,000 --> 00:35:43,640
Speaker 2: how can the governor do anything about that? It is easy? Well,

719
00:35:43,680 --> 00:35:46,960
Speaker 2: he has his own personal ballot collection.

720
00:35:46,800 --> 00:35:49,040
Speaker 1: Network, absolutely absolutely of.

721
00:35:49,080 --> 00:35:52,160
Speaker 2: People that he knows that that work closely with him,

722
00:35:52,400 --> 00:35:54,279
Speaker 2: and then he could just order Philly and Pittsburgh to

723
00:35:54,360 --> 00:35:56,560
Speaker 2: run a tight ship and guess what, It's an automatic

724
00:35:56,640 --> 00:35:58,960
Speaker 2: Trump win. Same thing with Michigan.

725
00:35:59,400 --> 00:36:01,759
Speaker 3: Happy, Okay, So okay, So take us to Michigan. Tell

726
00:36:01,840 --> 00:36:03,440
Speaker 3: us about the early vote numbers there.

727
00:36:03,320 --> 00:36:05,239
Speaker 2: All right, First and foremost, we don't have a lot

728
00:36:05,239 --> 00:36:07,600
Speaker 2: of early voting data off of Michigan. They just expanded

729
00:36:07,600 --> 00:36:09,439
Speaker 2: early votes to the whole state this week, I believe,

730
00:36:09,480 --> 00:36:12,040
Speaker 2: is the first time they've done it. From what I've

731
00:36:12,080 --> 00:36:15,719
Speaker 2: read anecdotally, very similar vibes as most of the other

732
00:36:15,719 --> 00:36:19,920
Speaker 2: places where it's just massive Trump counties are dwarfing urban

733
00:36:20,000 --> 00:36:24,719
Speaker 2: county turnout, like Oakland County, McComb County, Wayne County, Michigan.

734
00:36:25,800 --> 00:36:28,799
Speaker 2: Of all that I consider, there'll be eight battlegrounds this year,

735
00:36:29,719 --> 00:36:32,000
Speaker 2: and seven of them are in my decisive states, and

736
00:36:32,040 --> 00:36:33,840
Speaker 2: one of them is North Carolina. I don't call it

737
00:36:33,880 --> 00:36:35,800
Speaker 2: a decisive because I've got it baked in for Trump.

738
00:36:35,880 --> 00:36:37,800
Speaker 2: It's decisive if she were to get it, for sure.

739
00:36:38,080 --> 00:36:41,000
Speaker 2: But Michigan is the most corrupt battleground state we have.

740
00:36:41,360 --> 00:36:44,040
Speaker 2: And here's why. It's because eighty three and a half

741
00:36:44,080 --> 00:36:48,520
Speaker 2: percent of the total population, including miners, not miners like

742
00:36:48,560 --> 00:36:50,400
Speaker 2: you have in Pennsylvania, but miners under the age of

743
00:36:50,440 --> 00:36:53,840
Speaker 2: eighteen and eighty three and a half percent of the

744
00:36:53,880 --> 00:36:58,280
Speaker 2: population is registered to vote. Right, So seventy seven percent

745
00:36:58,320 --> 00:37:00,920
Speaker 2: of any state's population is over the age of eighteen

746
00:37:01,000 --> 00:37:03,799
Speaker 2: and therefore old enough to vote. So there's your math,

747
00:37:03,880 --> 00:37:05,600
Speaker 2: right there is it's got six and a half percent

748
00:37:05,640 --> 00:37:08,520
Speaker 2: more of the population register than is even eighteen years old.

749
00:37:08,760 --> 00:37:11,120
Speaker 2: And that's before we deduct people who are not eligible

750
00:37:11,120 --> 00:37:13,440
Speaker 2: to vote who are of age. That means you've got

751
00:37:13,840 --> 00:37:18,240
Speaker 2: that possible automatic voter registration, lack of voter role maintenance,

752
00:37:18,440 --> 00:37:22,160
Speaker 2: and the facilitation of this by an extremely corrupt trio

753
00:37:22,280 --> 00:37:25,480
Speaker 2: of women that run that state. And so Michigan is

754
00:37:25,520 --> 00:37:28,080
Speaker 2: the worst of all these battleground states. Now, I do

755
00:37:28,200 --> 00:37:30,920
Speaker 2: believe if Trump runs with the election, if he grabs

756
00:37:31,000 --> 00:37:33,600
Speaker 2: up the quickest three states to the election for Trump

757
00:37:33,680 --> 00:37:35,640
Speaker 2: or North Carolina, Georgia, Pennsylvania, Bambaia.

758
00:37:35,719 --> 00:37:38,799
Speaker 3: And by the way, I don't think Whitmer wants Comma either.

759
00:37:38,880 --> 00:37:40,880
Speaker 3: She wants to be run for president as well.

760
00:37:41,080 --> 00:37:43,880
Speaker 2: I don't either. So Michigan sits on average, and Trump's

761
00:37:43,920 --> 00:37:46,960
Speaker 2: two elections, Michigan is averaged fifty three thousand votes left

762
00:37:46,960 --> 00:37:49,719
Speaker 2: of Pennsylvania. So if Trump does grab paight.

763
00:37:49,600 --> 00:37:52,440
Speaker 1: How do you know this stuff? Man? Where do you get.

764
00:37:52,360 --> 00:37:54,560
Speaker 2: I'm one of the founding fathers of the Elections Denile

765
00:37:54,640 --> 00:37:58,799
Speaker 2: movement kind of stuff that I do. But I've got

766
00:37:58,800 --> 00:38:01,279
Speaker 2: all this stuff in graphics. I've just memorized it same

767
00:38:01,280 --> 00:38:03,160
Speaker 2: way I used to pick up baseball cards and read

768
00:38:03,200 --> 00:38:04,680
Speaker 2: the back of the stats, and that's how I got

769
00:38:04,680 --> 00:38:07,759
Speaker 2: good at baseball status. So Michigan, and you were an.

770
00:38:07,760 --> 00:38:10,600
Speaker 3: Army intel guy, were you like a Savage S two

771
00:38:10,680 --> 00:38:13,239
Speaker 3: for some battalion, like educating knuckleback?

772
00:38:13,719 --> 00:38:16,880
Speaker 2: I was the S two and assistant S two of

773
00:38:16,920 --> 00:38:19,400
Speaker 2: an aviation task force and then eventually in a striker

774
00:38:19,440 --> 00:38:25,360
Speaker 2: brigade in Alaska. So I sorry, I had a steep

775
00:38:25,440 --> 00:38:27,120
Speaker 2: learning curve. I've really had to learn how to get

776
00:38:27,120 --> 00:38:29,080
Speaker 2: more direct with That's why I told you before we

777
00:38:29,120 --> 00:38:31,120
Speaker 2: did this, you need to lead the questions because I

778
00:38:31,120 --> 00:38:34,439
Speaker 2: can roam with this. But Michigan, Michigan sits fifty three

779
00:38:34,480 --> 00:38:37,400
Speaker 2: thousand left of Pennsylvania on average and two Trump races,

780
00:38:37,719 --> 00:38:40,239
Speaker 2: So Trump at two hundred thousand plus and Pa isn't

781
00:38:40,280 --> 00:38:42,880
Speaker 2: gonna jive with Michigan going the other way. So I

782
00:38:43,120 --> 00:38:45,319
Speaker 2: don't know that the effort to steal Michigan will be

783
00:38:45,400 --> 00:38:49,480
Speaker 2: very intense if Trump runs off with the East coast,

784
00:38:49,840 --> 00:38:53,800
Speaker 2: North Carolina, Georgia and Pennsylvania. But Michigan is absolutely filthy.

785
00:38:54,000 --> 00:38:57,120
Speaker 2: Pennsylvania has about sixty eight percent of its population register

786
00:38:57,760 --> 00:38:59,640
Speaker 2: and Wisconsin only fifty eight.

787
00:39:01,360 --> 00:39:05,680
Speaker 3: Geez okay, So you think, so, what's the So what

788
00:39:05,719 --> 00:39:07,480
Speaker 3: does Michigan look like for Trump?

789
00:39:07,520 --> 00:39:08,080
Speaker 1: What do you think?

790
00:39:08,480 --> 00:39:12,799
Speaker 2: Well, if I've got Pennsylvania ballparking four, then Michigan looks

791
00:39:12,840 --> 00:39:14,440
Speaker 2: like two and a half to three and a half.

792
00:39:14,239 --> 00:39:17,600
Speaker 1: Points, Holy smoke. So you really.

793
00:39:17,760 --> 00:39:20,320
Speaker 2: Yeah, Michigan has been left of Pennsylvania in every election

794
00:39:20,360 --> 00:39:23,480
Speaker 2: since ninety two. Now they do have a bigger they

795
00:39:23,480 --> 00:39:26,520
Speaker 2: have more white working class voters. There's also some very

796
00:39:26,560 --> 00:39:30,200
Speaker 2: notable coalition shifting, as Rich would call it, going on.

797
00:39:30,280 --> 00:39:32,400
Speaker 2: You got the Arab voters.

798
00:39:32,000 --> 00:39:34,359
Speaker 1: Down there in the south, right right, right right, Well.

799
00:39:34,239 --> 00:39:36,319
Speaker 2: They're only two to three percent of the vote, but

800
00:39:36,840 --> 00:39:40,040
Speaker 2: the minority drift is very real. Latino votes not much

801
00:39:40,040 --> 00:39:41,640
Speaker 2: of a thing there in Michigan, but they've got a

802
00:39:41,640 --> 00:39:43,600
Speaker 2: big black vote in the southeast. And if it doesn't

803
00:39:43,640 --> 00:39:47,320
Speaker 2: come out and then the other minorities change sides at

804
00:39:47,360 --> 00:39:49,439
Speaker 2: a bigger rate, and then the white working class moves

805
00:39:49,440 --> 00:39:51,319
Speaker 2: back to the right. There's not really a way that

806
00:39:51,360 --> 00:39:53,640
Speaker 2: she can carry the state. And once again, I think

807
00:39:53,680 --> 00:39:55,799
Speaker 2: that she's capped. I don't think that she'll be able

808
00:39:55,800 --> 00:39:57,680
Speaker 2: to match Biden's vote totals and a lot of the

809
00:39:57,680 --> 00:39:59,080
Speaker 2: flyover portions of the state.

810
00:40:00,600 --> 00:40:03,799
Speaker 3: Seth, do you think that some of this and Rich

811
00:40:03,840 --> 00:40:07,319
Speaker 3: and I have talked about this before, but the Democrats

812
00:40:07,360 --> 00:40:10,480
Speaker 3: just I don't know that. Look, they have unlimited money,

813
00:40:10,600 --> 00:40:13,960
Speaker 3: they can buy volunteers if need be, but like they

814
00:40:14,000 --> 00:40:16,440
Speaker 3: haven't developed over the last couple of cycles the muscle

815
00:40:16,480 --> 00:40:19,440
Speaker 3: memory to physically turn people out, and the way that

816
00:40:19,520 --> 00:40:21,880
Speaker 3: some of the trends are going in early vote, it

817
00:40:21,960 --> 00:40:24,800
Speaker 3: means because they're not getting as many early votes or

818
00:40:24,840 --> 00:40:26,960
Speaker 3: banked mail in votes that they did in twenty twenty,

819
00:40:27,480 --> 00:40:30,319
Speaker 3: they're gonna have to physically turn out those people. Now

820
00:40:30,360 --> 00:40:33,680
Speaker 3: that is possible, but I feel like it's a heavier

821
00:40:33,719 --> 00:40:35,839
Speaker 3: lift for Democrats than it is for Republicans.

822
00:40:36,480 --> 00:40:39,880
Speaker 2: People are worried about the election day cannibalization of the

823
00:40:39,960 --> 00:40:44,560
Speaker 2: Republican vote. I'm not I think that we've created these

824
00:40:44,560 --> 00:40:47,440
Speaker 2: boxes for ourselves because we suffered under so many terrible

825
00:40:47,480 --> 00:40:50,879
Speaker 2: Republican figure hits, and really like Trump had a very

826
00:40:50,880 --> 00:40:53,759
Speaker 2: standard Republican vote total in twenty sixteen. He got the

827
00:40:53,840 --> 00:40:56,200
Speaker 2: votes in the right states to win the electoral College.

828
00:40:56,239 --> 00:40:59,880
Speaker 2: He actually ran weaker in Texas, Georgia and Arizona, ran

829
00:41:00,080 --> 00:41:02,839
Speaker 2: stronger in the rest Belt, and then we have twenty twenty.

830
00:41:02,920 --> 00:41:04,960
Speaker 2: Trump has an enormous vote game. So here's another one

831
00:41:05,000 --> 00:41:08,200
Speaker 2: for you, twenty twenty buffs. In twenty twenty, Donald Trump

832
00:41:08,200 --> 00:41:11,080
Speaker 2: gained eleven million votes from his previous election, which made

833
00:41:11,120 --> 00:41:13,719
Speaker 2: him the first incombent president to gain votes and not

834
00:41:13,800 --> 00:41:16,760
Speaker 2: be re elected since eighteen eighty eight, when Grover Cleveland

835
00:41:16,840 --> 00:41:19,440
Speaker 2: gained votes from eighteen eighty four. So, of course that

836
00:41:19,520 --> 00:41:21,439
Speaker 2: was the safest and most secure election of all time.

837
00:41:22,880 --> 00:41:25,359
Speaker 2: But Trump still got us eleven million new votes, which

838
00:41:25,400 --> 00:41:27,719
Speaker 2: just doesn't work with what Biden came in at. But

839
00:41:27,880 --> 00:41:31,440
Speaker 2: Trump is blowing up records at at an amazing pace.

840
00:41:31,560 --> 00:41:34,000
Speaker 2: The Democrats are consuming more of their three out of

841
00:41:34,000 --> 00:41:35,799
Speaker 2: four and four out of four voters than we are

842
00:41:35,840 --> 00:41:39,759
Speaker 2: almost everywhere. The Republicans continue to expand margins of early

843
00:41:39,840 --> 00:41:42,880
Speaker 2: voting in Arizona and Nevada. Florida is almost r plus

844
00:41:42,920 --> 00:41:45,320
Speaker 2: twelve right now. In early vote it was d plus

845
00:41:45,320 --> 00:41:48,200
Speaker 2: one last time before election day, all right, So Florida

846
00:41:48,239 --> 00:41:51,000
Speaker 2: is blowing up like crazy, which trends almost always with

847
00:41:51,040 --> 00:41:55,200
Speaker 2: Pennsylvania and Michigan. So I think that when you analyze

848
00:41:55,239 --> 00:41:57,319
Speaker 2: the question of how does all this pour ten the

849
00:41:57,320 --> 00:42:01,360
Speaker 2: early voting pertend for the Democrats, they're creatored in the

850
00:42:01,480 --> 00:42:04,920
Speaker 2: urban areas, in the inner cities. And it doesn't make

851
00:42:04,960 --> 00:42:08,279
Speaker 2: sense to my logical mind that Joe Biden's gonna have

852
00:42:08,320 --> 00:42:12,239
Speaker 2: eighty one million ballots in twenty twenty and it was

853
00:42:12,320 --> 00:42:15,319
Speaker 2: done primarily by not voting on election Day. It was

854
00:42:15,400 --> 00:42:20,160
Speaker 2: voting by mail, voting, early ballot harvesting to whatever, and

855
00:42:20,200 --> 00:42:22,320
Speaker 2: they didn't vote on election day. Somebody told me that

856
00:42:22,400 --> 00:42:25,680
Speaker 2: Trump won election day voting in Hawaii seventy thirty Hawaii.

857
00:42:26,560 --> 00:42:29,759
Speaker 2: So election day is massively Republican. And I just saw

858
00:42:29,760 --> 00:42:31,799
Speaker 2: a poll today that says Trump should win Election Day

859
00:42:31,800 --> 00:42:35,120
Speaker 2: in Pennsylvania by nineteen points. And when we look at

860
00:42:35,120 --> 00:42:38,240
Speaker 2: that and we stretch it out, why would they wait

861
00:42:38,520 --> 00:42:42,080
Speaker 2: in the very next election after getting eighty one million ballots?

862
00:42:42,440 --> 00:42:44,480
Speaker 2: Why would they start suddenly become the in person on

863
00:42:44,560 --> 00:42:45,440
Speaker 2: election day party?

864
00:42:45,640 --> 00:42:48,879
Speaker 3: I completely agree with you I mean seth, I tell

865
00:42:48,880 --> 00:42:51,880
Speaker 3: people on the show, I am I'm not a doomer.

866
00:42:52,080 --> 00:42:54,600
Speaker 3: I love being in the data. I don't see any

867
00:42:54,640 --> 00:42:56,960
Speaker 3: warning signs in the data. In fact, we've been we're

868
00:42:57,000 --> 00:42:59,000
Speaker 3: in a stronger position now than we've ever had, we

869
00:42:59,040 --> 00:43:03,120
Speaker 3: ever have been, but having had an election stolen completely

870
00:43:03,160 --> 00:43:05,480
Speaker 3: from me, I still worry that the Democrats are going

871
00:43:05,520 --> 00:43:07,680
Speaker 3: to pull the rug out in front, out from underneath

872
00:43:07,719 --> 00:43:11,280
Speaker 3: a somehow. But it's just I don't see any flashing

873
00:43:11,360 --> 00:43:12,400
Speaker 3: red lights, do you.

874
00:43:13,000 --> 00:43:16,160
Speaker 2: Well, That's why I'm I'm somewhat reserved in my writing,

875
00:43:16,239 --> 00:43:19,279
Speaker 2: so when people really want my official statement, it's on

876
00:43:19,320 --> 00:43:22,400
Speaker 2: my substack. In today's article, I talk about astros. Roger

877
00:43:22,440 --> 00:43:24,759
Speaker 2: Maris had an ASTSK when he hit sixty one home runs,

878
00:43:24,800 --> 00:43:28,040
Speaker 2: Barry Bonds has one, and all of my predictions are

879
00:43:29,440 --> 00:43:32,480
Speaker 2: they are astros. When it's like, hey, this is my

880
00:43:32,520 --> 00:43:35,800
Speaker 2: prediction if and only if we have a modestly fair election,

881
00:43:36,280 --> 00:43:38,520
Speaker 2: because there's some results that are so far off of

882
00:43:38,560 --> 00:43:41,320
Speaker 2: reality in twenty twenty it's not even funny. Now here's

883
00:43:41,360 --> 00:43:45,000
Speaker 2: what I will say. Trump had the votes in twenty twenty,

884
00:43:45,040 --> 00:43:47,360
Speaker 2: he did not have command of the narrative, which is

885
00:43:47,400 --> 00:43:50,040
Speaker 2: why that result wound up standing up even though we

886
00:43:50,080 --> 00:43:53,520
Speaker 2: had valid complaints about election fraud. One of the problems

887
00:43:53,520 --> 00:43:56,120
Speaker 2: with the election challenges and courts is in most states

888
00:43:56,120 --> 00:43:58,879
Speaker 2: they make you find specifically, you know, if Carrie Late

889
00:43:58,920 --> 00:44:02,520
Speaker 2: lost by ten thousand or seventeen one hundred and seventeen votes,

890
00:44:02,840 --> 00:44:05,879
Speaker 2: then we need seventeen one hundred and eighteen votes given

891
00:44:05,920 --> 00:44:07,759
Speaker 2: to us, which you know are fraudulent, or we won't

892
00:44:07,800 --> 00:44:10,319
Speaker 2: rule on it. So you know, they threw all these

893
00:44:10,360 --> 00:44:12,960
Speaker 2: marvels all across the kitchen floor, you know, and mom

894
00:44:12,960 --> 00:44:14,759
Speaker 2: went chasing them up under the fridge and under the

895
00:44:14,760 --> 00:44:17,120
Speaker 2: tables and everything else, and the kids ran off right,

896
00:44:17,360 --> 00:44:20,040
Speaker 2: And that's what happened with the votes. But we are

897
00:44:20,480 --> 00:44:22,600
Speaker 2: we are at this point where if they don't have

898
00:44:22,760 --> 00:44:26,080
Speaker 2: the narrative this time Trump has it, they don't have

899
00:44:26,200 --> 00:44:29,320
Speaker 2: the quantity of mail in votes in Georgia, North Carolina,

900
00:44:29,480 --> 00:44:34,080
Speaker 2: Pennsylvania out to replicate exactly what happened in twenty twenty,

901
00:44:34,080 --> 00:44:36,440
Speaker 2: which is, all right, we see what Trump has pause,

902
00:44:36,800 --> 00:44:38,320
Speaker 2: all right, and we're gonna count all these mail in

903
00:44:38,400 --> 00:44:40,600
Speaker 2: votes that we had on the front end. So if

904
00:44:40,600 --> 00:44:43,080
Speaker 2: the election were to take a turn like it did

905
00:44:43,080 --> 00:44:45,279
Speaker 2: in twenty twenty, it will not be the half back

906
00:44:45,360 --> 00:44:47,080
Speaker 2: dive up the middle until we get it into the

907
00:44:47,160 --> 00:44:49,319
Speaker 2: end zone. It's gonna have to be something off the

908
00:44:49,360 --> 00:44:52,400
Speaker 2: back end or something that we've never seen before that

909
00:44:52,440 --> 00:44:54,080
Speaker 2: has to do with software. Which I don't want to

910
00:44:54,080 --> 00:44:56,759
Speaker 2: go too far to this and demoralize people, but it

911
00:44:56,840 --> 00:45:00,000
Speaker 2: smells like narratives are being planted to blame another country

912
00:45:00,239 --> 00:45:02,719
Speaker 2: for intruding in our election, or to blame Trump or

913
00:45:02,719 --> 00:45:05,920
Speaker 2: plant evidence against Trump that he cheated the election. Therefore,

914
00:45:05,960 --> 00:45:08,960
Speaker 2: if he goes in, then he must have done so illegitimately,

915
00:45:09,040 --> 00:45:11,359
Speaker 2: and he lacks the mandate that he might get in

916
00:45:11,520 --> 00:45:12,040
Speaker 2: at the polls.

917
00:45:12,160 --> 00:45:13,200
Speaker 1: I mean, listen, listen.

918
00:45:13,480 --> 00:45:16,720
Speaker 3: Jamie Raskin has already said this in an interview publicly

919
00:45:16,760 --> 00:45:19,640
Speaker 3: that even if Trump wins, they're going to do everything

920
00:45:19,640 --> 00:45:22,600
Speaker 3: they can to prevent him from being inaugurated. He said

921
00:45:22,719 --> 00:45:25,399
Speaker 3: this in live interviews, and I've said on the show

922
00:45:25,440 --> 00:45:28,000
Speaker 3: many times, I think the most dangerous time in American history,

923
00:45:28,160 --> 00:45:31,640
Speaker 3: certainly during my life, is if Trump wins from November

924
00:45:31,640 --> 00:45:35,640
Speaker 3: sixth to January twenty first, what happens during that time period,

925
00:45:35,760 --> 00:45:38,120
Speaker 3: Because it's not a stretch of the imagination to say

926
00:45:38,160 --> 00:45:40,799
Speaker 3: said that the Democrats They've already accused Trump of being

927
00:45:40,840 --> 00:45:44,960
Speaker 3: an illegitimate president. They've already impeached him on bogus charges

928
00:45:45,440 --> 00:45:47,279
Speaker 3: or voted to impeach him on bogus charges in the

929
00:45:47,320 --> 00:45:50,160
Speaker 3: House twice. They're trying to throw the guy in prison

930
00:45:50,239 --> 00:45:52,560
Speaker 3: for the rest of his life based on bogus charges.

931
00:45:52,640 --> 00:45:54,920
Speaker 3: Is it really a stretch to say, oh, there's foreign

932
00:45:54,920 --> 00:45:59,000
Speaker 3: election interference, Trump cheated. Of course, that's the next logical step.

933
00:45:59,280 --> 00:46:02,720
Speaker 2: I mean, well, that was really the crux of Russia

934
00:46:02,760 --> 00:46:06,279
Speaker 2: Gate years ago, and where well, there's foreign interference, and

935
00:46:07,200 --> 00:46:08,759
Speaker 2: that's what they did, you know. And what they've done

936
00:46:08,800 --> 00:46:10,839
Speaker 2: is they spent all these years blasting veterans and not

937
00:46:10,880 --> 00:46:12,520
Speaker 2: just veterans, but I mean most of the people I've

938
00:46:12,560 --> 00:46:14,359
Speaker 2: worked with elections or people that want to be left

939
00:46:14,400 --> 00:46:17,000
Speaker 2: alone and raise their families. That's what they are. Tony

940
00:46:17,080 --> 00:46:20,600
Speaker 2: is one of these people. And they defame you, blast

941
00:46:20,680 --> 00:46:23,759
Speaker 2: you for simply speaking out. Like the country itself was

942
00:46:23,800 --> 00:46:26,880
Speaker 2: founded on the precept that we cannot trust the government.

943
00:46:27,320 --> 00:46:29,120
Speaker 2: We don't trust government, and the founders were like, hey,

944
00:46:29,120 --> 00:46:31,480
Speaker 2: we got to have a government because men are not angels,

945
00:46:31,480 --> 00:46:34,960
Speaker 2: but don't trust the government. So somehow we wound up

946
00:46:34,960 --> 00:46:37,839
Speaker 2: with an election system in which the government runs the

947
00:46:37,920 --> 00:46:41,160
Speaker 2: test on which they are retained or not retained, which

948
00:46:41,320 --> 00:46:43,640
Speaker 2: I can't. I think that if we were to fashion

949
00:46:43,760 --> 00:46:47,160
Speaker 2: humanity as if the Starship Troopers novel were to be real,

950
00:46:47,600 --> 00:46:50,239
Speaker 2: that somebody would probably call out how stupid it was

951
00:46:50,280 --> 00:46:53,440
Speaker 2: that previous civilizations allowed the government to run the elections.

952
00:46:54,640 --> 00:46:58,680
Speaker 1: Yes, that's a great point. Actually, it really.

953
00:46:58,480 --> 00:47:01,000
Speaker 2: Is what are we doing? Like you want the fox

954
00:47:01,040 --> 00:47:03,080
Speaker 2: to guard the hen house? You literally set it up

955
00:47:03,080 --> 00:47:04,800
Speaker 2: to where we're gonna go tell the fox not to

956
00:47:04,880 --> 00:47:07,040
Speaker 2: go mess with the hens. When we're gone, government, here's

957
00:47:07,040 --> 00:47:09,480
Speaker 2: your votes, we want you gone. Okay, well let's process them.

958
00:47:09,480 --> 00:47:11,799
Speaker 2: We got early voting. Uh, we don't have to report

959
00:47:11,840 --> 00:47:14,480
Speaker 2: our results for thirteen days, and we'll let you know

960
00:47:14,520 --> 00:47:16,720
Speaker 2: if you fired us and put us out of work.

961
00:47:18,160 --> 00:47:21,560
Speaker 1: That's fascinating to me. I think that's a fascinating point.

962
00:47:23,080 --> 00:47:25,160
Speaker 2: It doesn't make sense to me that anybody would not

963
00:47:25,200 --> 00:47:26,200
Speaker 2: be an election denier.

964
00:47:27,320 --> 00:47:31,160
Speaker 3: Yeah, yeah, I completely agree. The Democrats are every single

965
00:47:31,280 --> 00:47:34,959
Speaker 3: cycle set every single time that they lose, they deny

966
00:47:35,040 --> 00:47:39,440
Speaker 3: that they lost every single time. Seth, What do you

967
00:47:39,480 --> 00:47:43,719
Speaker 3: think about what do you think about Nevada right now?

968
00:47:43,760 --> 00:47:48,120
Speaker 3: Nevada's kind of been elusive for Republicans. We've lost lost

969
00:47:48,160 --> 00:47:50,520
Speaker 3: it for the past couple of cycles, but it looks

970
00:47:50,520 --> 00:47:53,839
Speaker 3: like the early vote numbers are extraordinary for us.

971
00:47:53,960 --> 00:47:56,280
Speaker 2: Well, I think the ship, I think that Harris's ship

972
00:47:56,320 --> 00:47:59,239
Speaker 2: in Nevada has sailed. I don't. I don't really, I

973
00:47:59,280 --> 00:48:00,799
Speaker 2: don't think the jew this is going to be worth

974
00:48:00,800 --> 00:48:03,880
Speaker 2: the squeeze for her to even pursue it anymore. In

975
00:48:03,960 --> 00:48:06,360
Speaker 2: most of my scenarios, Nevada is not the state that

976
00:48:06,400 --> 00:48:09,839
Speaker 2: wins Trump the presidency. Now where could it potentially win

977
00:48:09,880 --> 00:48:16,840
Speaker 2: Trump the presidency. It's if Trump wins wins Pennsylvania, loses Georgia,

978
00:48:17,840 --> 00:48:20,920
Speaker 2: and then wins Arizona and Nevada, that would win Trump

979
00:48:20,960 --> 00:48:25,319
Speaker 2: the presidency. But other than that, you know, to make

980
00:48:25,400 --> 00:48:27,120
Speaker 2: Nevada part of the winning hand, you're gonna have to

981
00:48:27,120 --> 00:48:29,800
Speaker 2: get to the situation where Trump gets Georgia, can't carry

982
00:48:29,800 --> 00:48:33,240
Speaker 2: Pennsylvania or Michigan, and has to win one of Arizona

983
00:48:33,320 --> 00:48:35,880
Speaker 2: or in Wisconsin, and then pair up Nevada with New Hampshire,

984
00:48:35,920 --> 00:48:38,920
Speaker 2: which is a real reach. But so Nevada, seven out

985
00:48:38,920 --> 00:48:41,920
Speaker 2: of eight votes come from two counties they override the

986
00:48:42,040 --> 00:48:46,080
Speaker 2: other fifteen county equivalents that are overwhelmingly Trump counties. The

987
00:48:46,160 --> 00:48:49,120
Speaker 2: problem with those fifteen those fifteen counties is they're pretty

988
00:48:49,160 --> 00:48:51,920
Speaker 2: much maxed out where we can't really ring that cloth

989
00:48:51,920 --> 00:48:53,640
Speaker 2: a lot more. I think there are maybe ten thousand

990
00:48:53,719 --> 00:48:56,239
Speaker 2: more margin stuck in those counties for Trump, So you

991
00:48:56,320 --> 00:48:58,240
Speaker 2: have to do the heavy lifting in Clark and Washoe,

992
00:48:58,280 --> 00:49:00,799
Speaker 2: and that's exactly what he's done. The Dems lost a

993
00:49:00,840 --> 00:49:03,960
Speaker 2: ton of their voter registration advantages down below fifteen thousand

994
00:49:03,960 --> 00:49:06,560
Speaker 2: now heading into the election, and Trump has run about

995
00:49:06,600 --> 00:49:09,000
Speaker 2: forty or fifty thousand to the right of the registration

996
00:49:09,080 --> 00:49:12,000
Speaker 2: advantage in every one of his races so far. In Nevada,

997
00:49:12,719 --> 00:49:14,919
Speaker 2: the independent vote leans right, a lot of the working

998
00:49:14,960 --> 00:49:17,240
Speaker 2: class de vote leans to the right, kind of like Pa,

999
00:49:17,560 --> 00:49:19,840
Speaker 2: and he's going to pull Latino vote way bigger than

1000
00:49:19,880 --> 00:49:22,160
Speaker 2: he did last time. I really don't think the numbers

1001
00:49:22,160 --> 00:49:24,560
Speaker 2: are there. The GOP's got to lead over forty thousand,

1002
00:49:25,120 --> 00:49:27,640
Speaker 2: just for perspective, four years ago, the DEM lead was

1003
00:49:27,680 --> 00:49:30,320
Speaker 2: forty plus thousand, So that's a swing of eighty some

1004
00:49:30,440 --> 00:49:32,680
Speaker 2: one thousand votes in the state decided by thirty three

1005
00:49:32,719 --> 00:49:35,920
Speaker 2: thousand ballots. So I don't think that it's going to

1006
00:49:36,000 --> 00:49:39,160
Speaker 2: be worth the effort, given her her obvious vulnerabilities in

1007
00:49:39,200 --> 00:49:42,279
Speaker 2: Georgia and Pennsylvania, North Carolina and Arizona. So I think

1008
00:49:42,280 --> 00:49:43,719
Speaker 2: that it's kind of going to rot on the vine

1009
00:49:43,719 --> 00:49:45,800
Speaker 2: for them, and Trump is going to carry Nevada by default.

1010
00:49:46,160 --> 00:49:48,360
Speaker 1: Wow, So what about what about Arizona.

1011
00:49:48,560 --> 00:49:50,520
Speaker 2: Well, here's here's a factoid for you. This is why

1012
00:49:50,560 --> 00:49:55,040
Speaker 2: I'm your Swiss Army knife of election mccaunics. So do

1013
00:49:55,120 --> 00:49:57,719
Speaker 2: you do any of that sports betting? Of course, yeah,

1014
00:49:57,719 --> 00:50:01,200
Speaker 2: because Richard likes Barnes a lot.

1015
00:50:00,239 --> 00:50:02,480
Speaker 1: I used to.

1016
00:50:02,520 --> 00:50:05,560
Speaker 2: Do DraftKings and FanDuel a little bit because I love baseball.

1017
00:50:05,640 --> 00:50:07,879
Speaker 2: But for some reason, oddly enough, my luck never worked

1018
00:50:07,880 --> 00:50:10,840
Speaker 2: out for me to stay with it long enough. But

1019
00:50:10,960 --> 00:50:12,759
Speaker 2: there's a term in that kind of industry called the

1020
00:50:12,920 --> 00:50:16,279
Speaker 2: chalk chalk, the chalk pick. Now, what the chalk pick

1021
00:50:16,400 --> 00:50:19,239
Speaker 2: is I may not feel like playing Mike Trout in

1022
00:50:19,280 --> 00:50:22,080
Speaker 2: my lineup today because I've got a vibe that he's

1023
00:50:22,320 --> 00:50:24,640
Speaker 2: you know, he's been hurt or something like that. But

1024
00:50:24,680 --> 00:50:27,760
Speaker 2: the stats say that this guy kills left handed pitchers,

1025
00:50:28,280 --> 00:50:31,000
Speaker 2: so you should play him because if you pick him

1026
00:50:31,080 --> 00:50:33,319
Speaker 2: enough times against lefties, he is going to deliver x

1027
00:50:33,360 --> 00:50:35,920
Speaker 2: amount of points. It's kind of like stock picks. So

1028
00:50:36,600 --> 00:50:39,600
Speaker 2: the chalk pick on the history of Nevada in Arizona

1029
00:50:39,800 --> 00:50:43,319
Speaker 2: is that if Nevada is going Republican, then Arizona's going

1030
00:50:43,320 --> 00:50:46,080
Speaker 2: Republican because we've never had an election where Nevada voted

1031
00:50:46,120 --> 00:50:48,880
Speaker 2: for the Republican for president and Arizona voted for the Democrat.

1032
00:50:48,920 --> 00:50:52,240
Speaker 2: It's never happened. And Arizona's been a state since nineteen twelve.

1033
00:50:52,560 --> 00:50:54,880
Speaker 2: So my gut is, with one hundred and twelve years

1034
00:50:54,880 --> 00:50:58,719
Speaker 2: of information informing my decision that if Nevada goes Republican,

1035
00:50:58,880 --> 00:51:00,000
Speaker 2: then Arizona will too.

1036
00:51:00,400 --> 00:51:04,320
Speaker 1: Good lord man, you are one of the four horsemen.

1037
00:51:05,120 --> 00:51:07,880
Speaker 2: You really are, basically the guy at the end of

1038
00:51:07,920 --> 00:51:10,080
Speaker 2: the level where the election affirmers come back and on

1039
00:51:10,200 --> 00:51:11,680
Speaker 2: the end of level boss there.

1040
00:51:13,680 --> 00:51:15,480
Speaker 1: All right, So what about Georgia?

1041
00:51:15,560 --> 00:51:17,120
Speaker 2: All right? So where are we at? We've got We've

1042
00:51:17,120 --> 00:51:18,520
Speaker 2: got Nevada and Arizona.

1043
00:51:19,360 --> 00:51:23,359
Speaker 3: Yeah, we went to Nevada Arizona. Now we're Georgia, all right.

1044
00:51:23,440 --> 00:51:27,840
Speaker 2: So Georgia pairs up with Duval County in Florida. Duval

1045
00:51:27,920 --> 00:51:32,640
Speaker 2: County is Jacksonville Metro. Now Georgia doesn't register voters by party.

1046
00:51:33,200 --> 00:51:35,320
Speaker 2: When I started running my analysis on Georgia, I was

1047
00:51:35,360 --> 00:51:38,279
Speaker 2: thinking I was gonna compe it with nearby North Carolina,

1048
00:51:38,360 --> 00:51:40,680
Speaker 2: and I started running the numbers, and the states are

1049
00:51:40,760 --> 00:51:43,359
Speaker 2: kind of in two different directions where I think they're

1050
00:51:43,400 --> 00:51:45,640
Speaker 2: both gonna run right this year. But for the first

1051
00:51:45,719 --> 00:51:48,080
Speaker 2: time since eighty eight, North Carolina voted to the right

1052
00:51:48,080 --> 00:51:51,040
Speaker 2: of Georgia in the last election, and that was probably legitimate,

1053
00:51:51,040 --> 00:51:53,840
Speaker 2: even when we deduct all the fraudulent ballots. So Georgia

1054
00:51:53,960 --> 00:51:55,680
Speaker 2: is a little bit tough. It's filling up with a

1055
00:51:55,719 --> 00:51:58,600
Speaker 2: lot of the educated white class, so the white Republican

1056
00:51:58,680 --> 00:52:01,239
Speaker 2: vote isn't as strong as it was, and the black

1057
00:52:01,320 --> 00:52:04,960
Speaker 2: vote is the dominant opposing political force. And there's another

1058
00:52:05,680 --> 00:52:08,400
Speaker 2: fifteen percent or so others, including a Latino vote. But

1059
00:52:09,200 --> 00:52:11,920
Speaker 2: Georgia is a state where you're gonna have to do

1060
00:52:11,960 --> 00:52:13,919
Speaker 2: better with a black mail vote, and that's Trump's bread

1061
00:52:13,920 --> 00:52:17,000
Speaker 2: and butter. And Duval County, Florida does register by party

1062
00:52:17,000 --> 00:52:18,839
Speaker 2: with the rest of the state of Florida, and it's

1063
00:52:18,880 --> 00:52:22,120
Speaker 2: four points more Republican than it was in twenty twenty

1064
00:52:22,120 --> 00:52:25,440
Speaker 2: when Trump supposedly lost Duval. Duval and Georgia have moved

1065
00:52:25,440 --> 00:52:28,239
Speaker 2: together and almost by the same exact amounts since two

1066
00:52:28,239 --> 00:52:28,879
Speaker 2: thousand and four.

1067
00:52:29,080 --> 00:52:30,480
Speaker 1: There said this yesterday.

1068
00:52:30,719 --> 00:52:32,800
Speaker 2: Yeah, they were big from they were big for Bush

1069
00:52:32,800 --> 00:52:35,760
Speaker 2: and O four, then they were for McCain but tighter

1070
00:52:35,800 --> 00:52:38,560
Speaker 2: in eight. Then they were bigger for Romney and twelve,

1071
00:52:38,600 --> 00:52:40,880
Speaker 2: they were for Trump but tighter in sixteen, and then

1072
00:52:40,880 --> 00:52:44,280
Speaker 2: they flipped against Trump and twenty twenty. So Duval's movement

1073
00:52:44,320 --> 00:52:47,240
Speaker 2: and Douval turnout right now, Florida turnout is off the charts.

1074
00:52:47,560 --> 00:52:49,759
Speaker 2: Douval turnout right now is R plus three and a

1075
00:52:49,800 --> 00:52:52,600
Speaker 2: half even though it's a D plus two county, so

1076
00:52:52,680 --> 00:52:55,360
Speaker 2: it's in overdrive for the Republican Party. Even with the

1077
00:52:55,400 --> 00:52:57,680
Speaker 2: shift already in play, Trump looks like he's going to

1078
00:52:57,760 --> 00:53:01,479
Speaker 2: carry Duval comfortably, and that pairs up. If I've got Trump,

1079
00:53:01,560 --> 00:53:03,440
Speaker 2: would duvall at two and a half points, which is

1080
00:53:03,600 --> 00:53:06,720
Speaker 2: conservative estimate, then Georgia's at Trump plus five point six,

1081
00:53:07,239 --> 00:53:10,840
Speaker 2: So I do expect Trump to get Georgia fairly comfortably,

1082
00:53:10,880 --> 00:53:14,880
Speaker 2: probably not by Suburbia Republican margins. But the early vote

1083
00:53:14,880 --> 00:53:18,000
Speaker 2: totals also look promising, where most of the high high

1084
00:53:18,040 --> 00:53:20,840
Speaker 2: high turnout counties right now are not just Trump counties,

1085
00:53:20,840 --> 00:53:23,880
Speaker 2: but they're like the Crimson eighty percent or Trump counties

1086
00:53:24,000 --> 00:53:26,400
Speaker 2: and most of the urban areas with a lot of

1087
00:53:26,440 --> 00:53:28,840
Speaker 2: the black vote are lagging the total state share of

1088
00:53:28,880 --> 00:53:30,000
Speaker 2: the twenty twenty vote.

1089
00:53:31,320 --> 00:53:35,840
Speaker 1: Holy smokes, Okay, North Carolina.

1090
00:53:35,040 --> 00:53:39,760
Speaker 2: North Carolina. I think that unofficially Harris has probably abandoned

1091
00:53:39,840 --> 00:53:44,160
Speaker 2: North Carolina. The polls I do understand. I don't know

1092
00:53:44,239 --> 00:53:45,640
Speaker 2: why this is. I can tell you why it is

1093
00:53:45,640 --> 00:53:48,560
Speaker 2: in Wisconsin, but I think polling in North Carolina's difficult,

1094
00:53:48,600 --> 00:53:50,840
Speaker 2: probably because a lot of the more conservative regions have

1095
00:53:50,920 --> 00:53:55,239
Speaker 2: less responsive voters. But North Carolina is only It's only

1096
00:53:55,320 --> 00:53:58,160
Speaker 2: D plus one point four. It was D plus nine

1097
00:53:58,160 --> 00:53:59,759
Speaker 2: and a half when Trump won it the first time.

1098
00:54:00,040 --> 00:54:02,200
Speaker 2: It was D plus five point three when Trump won

1099
00:54:02,280 --> 00:54:04,239
Speaker 2: it again, but with a very tight margin thanks to

1100
00:54:04,280 --> 00:54:07,480
Speaker 2: the mail election, And this time we've got ninety seven

1101
00:54:07,520 --> 00:54:09,640
Speaker 2: out of one hundred counties are more Republican than they

1102
00:54:09,640 --> 00:54:13,440
Speaker 2: were in twenty twenty. It looks to me like Core Charlotte,

1103
00:54:13,520 --> 00:54:15,919
Speaker 2: Core Raley are not getting the turnout that they need

1104
00:54:15,960 --> 00:54:18,080
Speaker 2: to get that massive black vote at the urban core.

1105
00:54:18,440 --> 00:54:21,399
Speaker 2: And if they don't max out Charlotte and Raleigh, they

1106
00:54:21,440 --> 00:54:25,320
Speaker 2: cannot win North Carolina. My studies on North Carolina suggest

1107
00:54:25,360 --> 00:54:28,120
Speaker 2: that Harris's ceiling in the absolute best case would be

1108
00:54:28,160 --> 00:54:32,480
Speaker 2: about twenty nine thousand votes above. I don't think they're

1109
00:54:32,480 --> 00:54:34,920
Speaker 2: going to hit the thresholds to do that. So North Carolina,

1110
00:54:34,960 --> 00:54:37,439
Speaker 2: I ran the registration analysis. It looks like Trump plus six.

1111
00:54:38,480 --> 00:54:41,439
Speaker 1: God, I mean, you think this plays out on election day?

1112
00:54:41,880 --> 00:54:43,839
Speaker 2: Well, if it's Trump plus six, and even does half

1113
00:54:43,880 --> 00:54:46,759
Speaker 2: of that's Trump plus three, it definitely should be. It

1114
00:54:46,800 --> 00:54:49,239
Speaker 2: should be Trump plus four or more.

1115
00:54:49,280 --> 00:54:52,839
Speaker 3: I would say, all right, So what about I want

1116
00:54:52,840 --> 00:54:55,279
Speaker 3: to ask about Wisconsin. Because we talked about Pennsylvania, we

1117
00:54:55,280 --> 00:54:57,719
Speaker 3: talked about Michigan. We kind of skipped over Wisconsin. But

1118
00:54:57,719 --> 00:55:00,400
Speaker 3: you said Wisconsin as the cleanest voter rolls. What do

1119
00:55:00,400 --> 00:55:01,400
Speaker 3: you think about Wisconsin.

1120
00:55:02,080 --> 00:55:04,200
Speaker 2: I feel really good about Wisconsin. And the reason I

1121
00:55:04,239 --> 00:55:07,319
Speaker 2: do is because I studied Iowa. Iowa has moved from

1122
00:55:07,400 --> 00:55:09,560
Speaker 2: R plus one to R plus ten in the last

1123
00:55:09,560 --> 00:55:12,359
Speaker 2: four years, and some of that is just a rearrangement

1124
00:55:12,360 --> 00:55:14,840
Speaker 2: of the deck chairs, you know, like Pennsylvania is another example,

1125
00:55:14,880 --> 00:55:17,759
Speaker 2: whereas it's only D plus three point one. But as

1126
00:55:17,840 --> 00:55:21,319
Speaker 2: that change in party registration accelerates the impact of it

1127
00:55:21,400 --> 00:55:24,319
Speaker 2: flattens out a little bit because people formally will change

1128
00:55:24,360 --> 00:55:27,360
Speaker 2: their party registration. So Iowa may not give you a

1129
00:55:27,440 --> 00:55:30,279
Speaker 2: nine point swing because of the party registration, but it's

1130
00:55:30,280 --> 00:55:33,040
Speaker 2: definitely showing you all ninety nine counties in Iowa are

1131
00:55:33,080 --> 00:55:36,160
Speaker 2: on a Republican trend, including the urban ones and including

1132
00:55:36,160 --> 00:55:39,200
Speaker 2: the ones along the banks of the Mississippi that parallel Wisconsin,

1133
00:55:39,320 --> 00:55:42,040
Speaker 2: in those southwestern working class counties that Trump flipped in

1134
00:55:42,160 --> 00:55:44,239
Speaker 2: order to flip the state and should have held the

1135
00:55:44,239 --> 00:55:47,200
Speaker 2: state in twenty twenty. Most important thing to know about

1136
00:55:47,239 --> 00:55:50,399
Speaker 2: Wisconsin is there's really only two counties to really watch

1137
00:55:50,440 --> 00:55:53,319
Speaker 2: out for in the state, and that's Dane County, home

1138
00:55:53,360 --> 00:55:56,160
Speaker 2: of Madison and the University of Wisconsin. Extremely liberal white

1139
00:55:56,160 --> 00:55:59,000
Speaker 2: people there. And then you have Milwaukee, which is your

1140
00:55:59,040 --> 00:56:02,360
Speaker 2: standard urban wreck that Trump can probably pick up major

1141
00:56:02,400 --> 00:56:07,120
Speaker 2: margin in with the Latino and black populations. Milwaukee County's

1142
00:56:07,160 --> 00:56:11,120
Speaker 2: voter role is substantially reduced from its size in twenty twenty.

1143
00:56:11,200 --> 00:56:13,719
Speaker 2: Last time I checked, it's nine percent smaller than it

1144
00:56:13,760 --> 00:56:16,200
Speaker 2: was in twenty twenty, So that's a lot fewer ballots

1145
00:56:16,200 --> 00:56:18,720
Speaker 2: that can be harvested, and the turnout in the inner

1146
00:56:18,760 --> 00:56:21,920
Speaker 2: wards of Milwaukee is garbage right now. So it looks

1147
00:56:21,960 --> 00:56:24,080
Speaker 2: to me like if Iowa is on a right trend.

1148
00:56:24,239 --> 00:56:27,520
Speaker 2: Wisconsin will mirror that like it almost always does. And

1149
00:56:27,560 --> 00:56:29,399
Speaker 2: the two have never been more than nine point eight

1150
00:56:29,400 --> 00:56:32,759
Speaker 2: percent apart since nineteen sixty in any direction. So Trump

1151
00:56:32,800 --> 00:56:35,040
Speaker 2: plus ten in Iowa is going to bring you a

1152
00:56:35,080 --> 00:56:36,319
Speaker 2: Wisconsin result too.

1153
00:56:37,280 --> 00:56:41,279
Speaker 3: Okay, that's uh, that's staggering to me. Okay, Uh, I

1154
00:56:41,320 --> 00:56:43,880
Speaker 3: got a couple like just one last. Well, I've got

1155
00:56:43,880 --> 00:56:46,040
Speaker 3: a couple last questions for you. What about some of

1156
00:56:46,120 --> 00:56:48,879
Speaker 3: these states that are blue but look like they could

1157
00:56:48,920 --> 00:56:49,560
Speaker 3: be Trump?

1158
00:56:50,080 --> 00:56:52,080
Speaker 1: What about say New Jersey.

1159
00:56:53,200 --> 00:56:55,360
Speaker 2: Now there's four states that are in July that I

1160
00:56:55,440 --> 00:56:59,840
Speaker 2: pegged as leaners, And my definition of leaner is anything

1161
00:57:00,040 --> 00:57:02,160
Speaker 2: it's going to be likely won by either candidate but

1162
00:57:02,280 --> 00:57:04,640
Speaker 2: less than ten points. So I would call two Trump

1163
00:57:04,680 --> 00:57:07,560
Speaker 2: leaners North Carolina and Texas. Now Texas looks like it's

1164
00:57:07,560 --> 00:57:10,000
Speaker 2: probably a clear ten at this rate, but I had

1165
00:57:10,000 --> 00:57:12,120
Speaker 2: both of those as Trump leaners where I'm confident Trump

1166
00:57:12,160 --> 00:57:14,239
Speaker 2: will win but less than ten points. And then I

1167
00:57:14,280 --> 00:57:17,080
Speaker 2: put four states full state, so I split the one

1168
00:57:17,160 --> 00:57:20,080
Speaker 2: vote from Nebraska, and then I split statewide main for Harris.

1169
00:57:20,120 --> 00:57:24,640
Speaker 2: But four Harris leaners were New Mexico, New Hampshire, or sorry,

1170
00:57:24,720 --> 00:57:29,160
Speaker 2: New Mexico, Virginia, and Minnesota, and I wound up with

1171
00:57:29,400 --> 00:57:31,920
Speaker 2: New Hampshire over in the battle in the decisive states

1172
00:57:31,920 --> 00:57:34,960
Speaker 2: because of its propensity to put Trump in there on

1173
00:57:35,280 --> 00:57:39,120
Speaker 2: a Hail Mary. But just recently the Trump campaign announced

1174
00:57:39,200 --> 00:57:42,000
Speaker 2: rallies in most of those an interest in all of them.

1175
00:57:42,040 --> 00:57:44,320
Speaker 2: So it looks to me like I was correct. So

1176
00:57:44,520 --> 00:57:49,720
Speaker 2: I have Virginia and Minnesota tentatively ballparked at three to

1177
00:57:49,840 --> 00:57:53,720
Speaker 2: five points. Dim that's just my ballpark setting. Now at

1178
00:57:53,720 --> 00:57:55,760
Speaker 2: three points, were at a point where if election day

1179
00:57:55,760 --> 00:57:58,360
Speaker 2: turnout is a monster for Republicans and things are worse

1180
00:57:58,360 --> 00:57:59,840
Speaker 2: than we thought in the cities, then you could get

1181
00:57:59,880 --> 00:58:02,360
Speaker 2: an upset. So we're in potential striking range on that.

1182
00:58:04,240 --> 00:58:06,640
Speaker 2: New Hampshire is going to be probably one of the

1183
00:58:06,680 --> 00:58:09,320
Speaker 2: tightest states in this race, and the voter.

1184
00:58:09,400 --> 00:58:11,840
Speaker 3: Has just moved a toss up calum today by I

1185
00:58:11,880 --> 00:58:12,800
Speaker 3: think people.

1186
00:58:12,520 --> 00:58:14,520
Speaker 2: Thought it was crazy six weeks ago when I put

1187
00:58:14,560 --> 00:58:16,120
Speaker 2: that up to people though I was nuts. But the

1188
00:58:16,200 --> 00:58:19,400
Speaker 2: voter registration stats that state has moved from D plus

1189
00:58:19,440 --> 00:58:22,040
Speaker 2: one to R plus four and a half in the

1190
00:58:22,120 --> 00:58:23,920
Speaker 2: last four years, and of course that was because one

1191
00:58:23,960 --> 00:58:27,360
Speaker 2: party got a lot of registrations perched but no, that

1192
00:58:27,560 --> 00:58:30,200
Speaker 2: state typically it always votes to the It always votes

1193
00:58:30,240 --> 00:58:33,800
Speaker 2: to the left of the GOPU registration advantage. And the

1194
00:58:33,840 --> 00:58:36,959
Speaker 2: GOPU registration advantage is thirty nine thousand. Trump has set

1195
00:58:37,000 --> 00:58:39,400
Speaker 2: thirty three thousand on average to the left of it.

1196
00:58:39,560 --> 00:58:42,320
Speaker 2: So if the registration figures hold up, Trump has a

1197
00:58:42,320 --> 00:58:44,560
Speaker 2: window to win by about five or six thousand votes.

1198
00:58:44,920 --> 00:58:47,880
Speaker 2: But I do not see either candidate likely to win

1199
00:58:47,920 --> 00:58:50,320
Speaker 2: that state by more than ten or fifteen thousand votes.

1200
00:58:51,080 --> 00:58:54,760
Speaker 2: And that's based on six election cycles worth of data.

1201
00:58:54,880 --> 00:58:58,480
Speaker 1: So you are you sound pretty bullish on Trump right now?

1202
00:58:58,560 --> 00:59:00,160
Speaker 2: Well, it's an astrosk.

1203
00:59:00,280 --> 00:59:02,560
Speaker 3: And by the way, you're pretty frustrated with doomers as well.

1204
00:59:02,600 --> 00:59:05,160
Speaker 3: It sounds like you know, like I don't.

1205
00:59:05,720 --> 00:59:10,440
Speaker 2: Doomerism is not the same as as realism, right he

1206
00:59:10,600 --> 00:59:13,120
Speaker 2: learned that, Well, what do you do if you're a

1207
00:59:13,120 --> 00:59:15,200
Speaker 2: military officer and you have a senior officer come up

1208
00:59:15,240 --> 00:59:17,600
Speaker 2: to you and you don't tell him the bad news,

1209
00:59:18,240 --> 00:59:20,520
Speaker 2: then the consequence is he may go on with a

1210
00:59:20,520 --> 00:59:22,160
Speaker 2: mission plan that gets people killed.

1211
00:59:22,520 --> 00:59:25,240
Speaker 1: Absolutely, that's exactly right.

1212
00:59:25,800 --> 00:59:28,480
Speaker 2: So that was my direct duty. I was not a

1213
00:59:28,520 --> 00:59:30,600
Speaker 2: combat arms officer. I was a staff officer. I was

1214
00:59:30,640 --> 00:59:33,640
Speaker 2: an intelligence officer. So my function was to consider the

1215
00:59:33,760 --> 00:59:37,240
Speaker 2: enemy activity, consider what our mission plan is, what tools

1216
00:59:37,240 --> 00:59:40,400
Speaker 2: and resources and weapons do we have available, what's the daylight,

1217
00:59:40,440 --> 00:59:42,560
Speaker 2: what's the illumination look like, what's the wind look like,

1218
00:59:42,600 --> 00:59:46,080
Speaker 2: what's the soil type? So all that stuff bakes into

1219
00:59:46,120 --> 00:59:48,800
Speaker 2: the mission plan, and my particular slice of that pie

1220
00:59:48,960 --> 00:59:52,520
Speaker 2: was the intelligence picture. And I have to tell that

1221
00:59:52,600 --> 00:59:55,520
Speaker 2: commander they've got this weapon system and we better not

1222
00:59:55,600 --> 00:59:57,720
Speaker 2: go right here. That would be a mistake. And a

1223
00:59:57,760 --> 01:00:00,520
Speaker 2: company commander it's different, it's a differ front side of

1224
01:00:00,520 --> 01:00:03,480
Speaker 2: the spectrum. But that commander has to tell that. That

1225
01:00:03,520 --> 01:00:06,480
Speaker 2: company commander has to tell his battalion commander when he's

1226
01:00:06,520 --> 01:00:09,400
Speaker 2: got personnel issues that are going to affect the readiness

1227
01:00:09,440 --> 01:00:12,760
Speaker 2: of his unit to go into combat. So when you

1228
01:00:12,800 --> 01:00:16,480
Speaker 2: consider all this stuff, you know, like I would consider

1229
01:00:16,520 --> 01:00:20,680
Speaker 2: it not dooming to tell people to stop creating stories

1230
01:00:20,680 --> 01:00:22,520
Speaker 2: that don't work. So like the story in Michigan the

1231
01:00:22,520 --> 01:00:27,160
Speaker 2: other day, the corruption issue in Michigan, right better stated

1232
01:00:27,320 --> 01:00:29,720
Speaker 2: putting them on the spot to say why is there

1233
01:00:29,760 --> 01:00:32,160
Speaker 2: this disconnect between this record and that, because that's what

1234
01:00:32,160 --> 01:00:35,040
Speaker 2: it was. It's a transparency issue. Are you guys stuffing

1235
01:00:35,120 --> 01:00:38,000
Speaker 2: votes virtually because when we pin ourselves to this, many

1236
01:00:38,080 --> 01:00:40,240
Speaker 2: registrations cast this many fraudulent votes and we may not

1237
01:00:40,280 --> 01:00:42,400
Speaker 2: be correct. And y'all don't even agree on the numbers.

1238
01:00:42,840 --> 01:00:45,880
Speaker 2: That's a problem, all right. Or when we say that

1239
01:00:46,000 --> 01:00:48,560
Speaker 2: the male and female vote split is troublesome, okay, have

1240
01:00:48,640 --> 01:00:50,680
Speaker 2: we looked at the previous cycles, because it looks exactly

1241
01:00:50,760 --> 01:00:53,280
Speaker 2: like it looked last time. In fact, the working class

1242
01:00:53,320 --> 01:00:55,040
Speaker 2: states I just saw it right before we got on

1243
01:00:55,080 --> 01:01:00,560
Speaker 2: the call, Wisconsin and Ohio. In North Carolina, they have

1244
01:01:00,600 --> 01:01:03,000
Speaker 2: a much closer male to female split. So these working

1245
01:01:03,000 --> 01:01:06,280
Speaker 2: classmen are getting out there right now. But the male

1246
01:01:06,320 --> 01:01:09,400
Speaker 2: female vote split is simple. Minority males are not voting

1247
01:01:09,400 --> 01:01:10,880
Speaker 2: in the numbers that they usually vote for in the

1248
01:01:10,880 --> 01:01:15,040
Speaker 2: inner cities. The minority females are. And because of fewer

1249
01:01:15,080 --> 01:01:18,160
Speaker 2: minority males voting, the male count goes down as a total,

1250
01:01:18,160 --> 01:01:21,040
Speaker 2: and they're basically being backfilled by white women who, even

1251
01:01:21,080 --> 01:01:23,960
Speaker 2: if they're forty percent Republican, is a better output for

1252
01:01:24,000 --> 01:01:26,280
Speaker 2: the final vote than twenty percent Republican.

1253
01:01:27,640 --> 01:01:28,120
Speaker 1: Wow.

1254
01:01:28,840 --> 01:01:31,080
Speaker 2: And if Trump didn't think that the male vote was

1255
01:01:31,080 --> 01:01:32,800
Speaker 2: going to come out, he wouldn't be in New Mexico

1256
01:01:32,880 --> 01:01:34,880
Speaker 2: today and he would be going to the Penn State game.

1257
01:01:36,520 --> 01:01:38,200
Speaker 3: I mean, that's a great point. If you want to

1258
01:01:38,240 --> 01:01:42,840
Speaker 3: watch where a candidate is politically, you know, get a

1259
01:01:42,880 --> 01:01:45,880
Speaker 3: sense of where his priorities are. Watch what he says,

1260
01:01:45,960 --> 01:01:48,320
Speaker 3: and watch where they go and where they spend money.

1261
01:01:49,040 --> 01:01:52,040
Speaker 3: And you're right, Trump is doing rallies. I think he's

1262
01:01:52,040 --> 01:01:53,960
Speaker 3: going to do something in New Hampshire. He's definitely doing

1263
01:01:53,960 --> 01:01:57,640
Speaker 3: one in New Mexico. I think the Trump campaign sees

1264
01:01:58,200 --> 01:02:01,360
Speaker 3: Minnesota even be within striking distance.

1265
01:02:01,400 --> 01:02:04,640
Speaker 1: I don't know. I you sound a lot more. I

1266
01:02:04,680 --> 01:02:04,960
Speaker 1: don't know.

1267
01:02:05,000 --> 01:02:06,960
Speaker 3: I don't want to say confident. That that's not the

1268
01:02:07,040 --> 01:02:10,439
Speaker 3: right word, and I'm not. I don't lack confidence. I'm

1269
01:02:10,480 --> 01:02:13,560
Speaker 3: just used to getting punched in the face by the Democrats.

1270
01:02:13,000 --> 01:02:14,920
Speaker 2: That's all. And that's the hard part about it is

1271
01:02:14,960 --> 01:02:18,320
Speaker 2: you don't want to demoralize people. You also don't, so

1272
01:02:18,400 --> 01:02:20,240
Speaker 2: I don't. One of the reasons that none of the

1273
01:02:20,240 --> 01:02:23,840
Speaker 2: stuff that they throw at Trump works is because they

1274
01:02:23,880 --> 01:02:26,720
Speaker 2: cried wolf, like we are. The people that came before us,

1275
01:02:26,760 --> 01:02:28,920
Speaker 2: even people that wrote stories had a lot of wisdom.

1276
01:02:29,000 --> 01:02:31,400
Speaker 2: The boy that cried wolf. That's been the mainstream media

1277
01:02:31,440 --> 01:02:34,000
Speaker 2: now for for the entirety of the Trump era, and

1278
01:02:34,160 --> 01:02:36,200
Speaker 2: you know, where it used to be that people would

1279
01:02:36,240 --> 01:02:39,360
Speaker 2: care that a comedian told a joke that offended a

1280
01:02:39,360 --> 01:02:42,400
Speaker 2: group of people. Now this is just another this is

1281
01:02:42,440 --> 01:02:45,480
Speaker 2: just another Thursday, you know. Or here's another accuser of

1282
01:02:45,480 --> 01:02:48,240
Speaker 2: Donald Trump. Well this is the one of number fifty, right,

1283
01:02:48,560 --> 01:02:51,040
Speaker 2: And she waited thirty one years and his third election

1284
01:02:51,240 --> 01:02:54,160
Speaker 2: run to come out and tell this story. So now

1285
01:02:54,160 --> 01:02:56,000
Speaker 2: it's actually a really good time to put your dirt

1286
01:02:56,040 --> 01:02:59,680
Speaker 2: out there. You've been dragged through the mud, you know, right,

1287
01:02:59,760 --> 01:03:03,520
Speaker 2: And and it was political and I I look at

1288
01:03:03,520 --> 01:03:05,680
Speaker 2: this stuff like I grew up in Jackson, Mississippi, and

1289
01:03:05,720 --> 01:03:07,240
Speaker 2: in the south side of Jackson, and I went to

1290
01:03:07,240 --> 01:03:09,720
Speaker 2: a small private school. And back in those days, if

1291
01:03:09,720 --> 01:03:11,960
Speaker 2: your family got on the nightly news for some reason,

1292
01:03:12,120 --> 01:03:14,840
Speaker 2: like when my brother came back from Iraq, or you know,

1293
01:03:14,920 --> 01:03:17,200
Speaker 2: you were on uh you know they showed a football highlight,

1294
01:03:17,360 --> 01:03:19,360
Speaker 2: or your name was in the honor roll, like people,

1295
01:03:19,520 --> 01:03:21,280
Speaker 2: Hey I saw you in the paper. Hey I saw

1296
01:03:21,320 --> 01:03:23,000
Speaker 2: you on the news, almost like you're famous, Like if

1297
01:03:23,040 --> 01:03:26,680
Speaker 2: you get a parade downtown. I got my own New

1298
01:03:26,760 --> 01:03:31,080
Speaker 2: York Times hit piece written about me two weeks ago.

1299
01:03:31,120 --> 01:03:33,600
Speaker 2: I'm talking. It wasn't like I was named in the

1300
01:03:33,680 --> 01:03:36,520
Speaker 2: hit piece I'm talking about. It was literally my own

1301
01:03:37,160 --> 01:03:37,680
Speaker 2: hit piece.

1302
01:03:38,120 --> 01:03:39,800
Speaker 1: I mean, this is this is.

1303
01:03:39,760 --> 01:03:41,760
Speaker 2: This is end of level boss stuff right there.

1304
01:03:41,920 --> 01:03:44,160
Speaker 1: Wait meet the election denial forcat.

1305
01:03:44,920 --> 01:03:50,120
Speaker 2: Wait, how did you get I'm sitting here in a

1306
01:03:50,120 --> 01:03:55,040
Speaker 2: freaking shadow. I mean, come on, you know. So I

1307
01:03:55,120 --> 01:03:56,640
Speaker 2: was in the New York Times and I was on

1308
01:03:56,680 --> 01:03:59,720
Speaker 2: the cover of the business section in print that Saturday.

1309
01:04:00,200 --> 01:04:04,080
Speaker 2: And I'm not not one person in my life or

1310
01:04:04,120 --> 01:04:08,160
Speaker 2: in my military past or my professional career said hey, Seth,

1311
01:04:08,280 --> 01:04:10,640
Speaker 2: I saw you on the cover of the Business section

1312
01:04:10,720 --> 01:04:12,680
Speaker 2: of the New York Times. That's really crazy. The most

1313
01:04:12,680 --> 01:04:15,520
Speaker 2: widely spread publication in the world. Nobody reads it anymore.

1314
01:04:16,680 --> 01:04:22,200
Speaker 3: That is a really interesting point. Good lord, that is crazy.

1315
01:04:22,440 --> 01:04:24,600
Speaker 2: Right. So that's why nothing sticks to Trump is because

1316
01:04:24,600 --> 01:04:26,960
Speaker 2: something happens. I mean, nobody even talks about the guy

1317
01:04:27,000 --> 01:04:28,160
Speaker 2: getting shot anymore.

1318
01:04:28,400 --> 01:04:30,880
Speaker 1: It's insane. I mean we talk about that all the time, Like.

1319
01:04:31,520 --> 01:04:33,920
Speaker 2: Trump getting shot. We had JD. Vans getting picture as

1320
01:04:33,920 --> 01:04:36,680
Speaker 2: a VP. Then we had there were several major news

1321
01:04:36,800 --> 01:04:39,600
Speaker 2: articles within days of him being shot, where within three

1322
01:04:39,680 --> 01:04:41,520
Speaker 2: or four days it was like, oh yeah, Trump got shot.

1323
01:04:43,560 --> 01:04:46,600
Speaker 3: Holy smokes man, I Seth, you got to tell us

1324
01:04:47,040 --> 01:04:49,640
Speaker 3: what kept you over time. But tell everybody that's watching

1325
01:04:49,680 --> 01:04:52,520
Speaker 3: and listening how they can support you and where they

1326
01:04:52,520 --> 01:04:53,280
Speaker 3: can find you.

1327
01:04:54,320 --> 01:04:56,959
Speaker 2: Well, if people want to keep up my work, I'm

1328
01:04:57,080 --> 01:05:00,560
Speaker 2: all over the place these days. I did think i'd

1329
01:05:00,600 --> 01:05:03,080
Speaker 2: be using X much, but that's guess where the information

1330
01:05:03,160 --> 01:05:05,920
Speaker 2: space is right now. My X and true social are

1331
01:05:05,960 --> 01:05:09,160
Speaker 2: at real s Keshel. I'm on telegram Captain Keshel's twenty

1332
01:05:09,200 --> 01:05:12,320
Speaker 2: twenty four election headquarters, and my substack is where I

1333
01:05:12,360 --> 01:05:15,000
Speaker 2: go into long form deeper analysis, a different mode of

1334
01:05:15,000 --> 01:05:17,120
Speaker 2: reading what I've got stuck in between my ears, and

1335
01:05:17,120 --> 01:05:19,920
Speaker 2: that's Skeshel dot substack dot com right there in my window.

1336
01:05:20,360 --> 01:05:22,880
Speaker 2: So that's where you can support me. I offer a

1337
01:05:22,880 --> 01:05:25,000
Speaker 2: lot of free work on there. I also offer paid

1338
01:05:25,040 --> 01:05:28,000
Speaker 2: articles and that has been good enough to keep me rolling.

1339
01:05:28,800 --> 01:05:31,160
Speaker 2: Other than that, you know, you can support everybody by

1340
01:05:31,280 --> 01:05:33,920
Speaker 2: making sure that you're getting everybody you know out to vote,

1341
01:05:34,000 --> 01:05:37,120
Speaker 2: getting eyes and ears out there, using your phone when

1342
01:05:37,120 --> 01:05:39,680
Speaker 2: you're in line at the polling centers, using your phone

1343
01:05:39,680 --> 01:05:41,560
Speaker 2: when you're collecting stuff. Because now we have a lot

1344
01:05:41,560 --> 01:05:44,840
Speaker 2: more power behind us thanks to X. And really, what

1345
01:05:44,880 --> 01:05:46,959
Speaker 2: happened to Bucks County the other day within twenty four

1346
01:05:47,000 --> 01:05:49,840
Speaker 2: hours was amazing the power of being able to put

1347
01:05:49,840 --> 01:05:50,840
Speaker 2: these folks on blast.

1348
01:05:51,720 --> 01:05:54,240
Speaker 3: Absolutely, man, Seth, we got to have you back. Man,

1349
01:05:54,320 --> 01:05:57,479
Speaker 3: You're fantastic. I think the audience loves you, man, and

1350
01:05:57,520 --> 01:06:00,000
Speaker 3: I appreciate you being so generous with your time, my friend.

1351
01:06:01,040 --> 01:06:03,400
Speaker 2: All right, Sean, well, hey, great job out there. Thanks

1352
01:06:03,440 --> 01:06:04,840
Speaker 2: for what you do. Thanks for what you do for

1353
01:06:04,880 --> 01:06:07,040
Speaker 2: the representing the veterans community. You know a lot of

1354
01:06:07,040 --> 01:06:09,880
Speaker 2: people took notice of your actions out there in Butler,

1355
01:06:10,320 --> 01:06:12,000
Speaker 2: so keep being a light out there.

1356
01:06:12,240 --> 01:06:13,680
Speaker 1: Yeah. Thanks, brother, We'll see you soon.

1357
01:06:14,280 --> 01:06:14,760
Speaker 2: Copy that.

1358
01:06:15,160 --> 01:06:18,160
Speaker 1: All right, that is the great, Seth Cashal. I really listen.

1359
01:06:18,240 --> 01:06:20,120
Speaker 3: I try to bring you all some of the smartest

1360
01:06:20,120 --> 01:06:24,720
Speaker 3: people around that are truth tellers, actually courageous truth tellers,

1361
01:06:24,760 --> 01:06:27,320
Speaker 3: and man, that dude is smart. People in the live

1362
01:06:27,400 --> 01:06:30,120
Speaker 3: chat saying bring Seth back, bring Seth back. Yeah, we're

1363
01:06:30,120 --> 01:06:33,040
Speaker 3: gonna do that if Phil, if he will have us.

1364
01:06:33,640 --> 01:06:36,600
Speaker 3: But yeah, man, he is fantastic. So hey, go support

1365
01:06:36,600 --> 01:06:39,640
Speaker 3: his substack, go following him on X, do whatever you

1366
01:06:39,680 --> 01:06:43,440
Speaker 3: can to help him out, because we've got to support

1367
01:06:43,480 --> 01:06:46,320
Speaker 3: our people. We got to make sure that the good

1368
01:06:46,320 --> 01:06:49,840
Speaker 3: people are supported so that they can remain independent. Make

1369
01:06:49,920 --> 01:06:52,000
Speaker 3: sure you smash that like button, that little green thumb

1370
01:06:52,000 --> 01:06:55,760
Speaker 3: beneath the video. All right, folks, thank you for tuning in.

1371
01:06:56,160 --> 01:06:59,600
Speaker 3: We are five days from election day, and man, I

1372
01:06:59,640 --> 01:07:01,600
Speaker 3: wish we had more time with Seth because I could

1373
01:07:01,600 --> 01:07:03,560
Speaker 3: talk to him about this stuff for a long time.

1374
01:07:04,360 --> 01:07:07,680
Speaker 3: Make sure look at gaming too long, first time ever

1375
01:07:07,760 --> 01:07:10,480
Speaker 3: knowing of Seth. Well, listen, I'm really glad that to

1376
01:07:10,600 --> 01:07:12,720
Speaker 3: have you all. Look at how the audience has grown.

1377
01:07:14,160 --> 01:07:16,080
Speaker 3: Make sure you smash that like button. Always try to

1378
01:07:16,080 --> 01:07:17,960
Speaker 3: get the four hundred likes before the show. We're so

1379
01:07:18,080 --> 01:07:21,120
Speaker 3: close to it now, smash the like button. Don't forget

1380
01:07:21,120 --> 01:07:25,320
Speaker 3: about official Sean Parnell. Support Seth Cashell in any way

1381
01:07:25,320 --> 01:07:28,240
Speaker 3: that you can. Wholock, I see you in the live chat.

1382
01:07:28,400 --> 01:07:30,439
Speaker 3: I know you're a new addition to the battle Crew,

1383
01:07:30,480 --> 01:07:33,360
Speaker 3: but we're lucky that we're here. Cindy Wiser, Animal Dory,

1384
01:07:33,560 --> 01:07:39,280
Speaker 3: Don Grandpaul, Myron, Mama, Bear Hockey, Love Wildlife Watch or Trinity.

1385
01:07:39,560 --> 01:07:44,520
Speaker 1: Listen, g I, Jenny, Hammerhead, Dory, you all have.

1386
01:07:44,960 --> 01:07:47,440
Speaker 3: You all are just the best audience in the world.

1387
01:07:48,120 --> 01:07:50,040
Speaker 3: So many OG members of the battle Crew have been

1388
01:07:50,040 --> 01:07:53,600
Speaker 3: with us since day one. Tomorrow, folks, do not forget

1389
01:07:53,640 --> 01:07:57,280
Speaker 3: to be here. I know Fridays can be Typically they're

1390
01:07:57,280 --> 01:07:59,280
Speaker 3: tough for people. Right people like to get their weekend

1391
01:07:59,320 --> 01:08:02,760
Speaker 3: started a little bit early. But tomorrow we have Right

1392
01:08:02,920 --> 01:08:06,960
Speaker 3: Night with Brian Dean Wright in the arena, also one

1393
01:08:06,960 --> 01:08:11,400
Speaker 3: of the smartest dudes around. Look, I'm a knuckle dragger,

1394
01:08:11,520 --> 01:08:14,880
Speaker 3: you know, That's who I am. That's how it's it's

1395
01:08:14,920 --> 01:08:17,840
Speaker 3: who I am. It's it's it's it's who I've always been.

1396
01:08:18,720 --> 01:08:20,880
Speaker 3: I try to surround myself with people that are a

1397
01:08:20,880 --> 01:08:22,960
Speaker 3: hell of a lot smarter than me. Brian Dean Wright

1398
01:08:23,040 --> 01:08:24,720
Speaker 3: is one of those people. Rich Barris is one of

1399
01:08:24,760 --> 01:08:26,720
Speaker 3: these one of those people. Seth Cashall is one of

1400
01:08:26,720 --> 01:08:30,599
Speaker 3: those people. But Right Night is tomorrow, So be here

1401
01:08:30,960 --> 01:08:35,439
Speaker 3: live on Rumble at five pm Eastern Standard Time. In

1402
01:08:35,520 --> 01:08:38,040
Speaker 3: the meantime, folks, God bless you all, keep the faith,

1403
01:08:38,080 --> 01:08:41,000
Speaker 3: work your ass off, sprint to the finish. We have

1404
01:08:41,200 --> 01:08:44,400
Speaker 3: a country to save. God bless you all, and God

1405
01:08:44,439 --> 01:08:48,679
Speaker 3: bless this amazing country that we call home. Take care,

1406
01:08:48,760 --> 01:08:51,240
Speaker 3: good night, and I will see you tomorrow night in battle.

1407
01:08:51,240 --> 01:08:51,920
Speaker 1: Crew, Take care