1 00:00:00,120 --> 00:00:04,040 Speaker 1: Hello everybody, Happy Friday. We have an amazing Friday Points 2 00:00:04,160 --> 00:00:07,320 Speaker 1: show for all of you, a little bit of election coverage. 3 00:00:07,320 --> 00:00:09,080 Speaker 1: I know you didn't have enough election coverage, you haven't 4 00:00:09,080 --> 00:00:11,680 Speaker 1: had enough discussion of the polls. But what you actually 5 00:00:11,680 --> 00:00:13,119 Speaker 1: have not had enough in your life is the four 6 00:00:13,119 --> 00:00:15,800 Speaker 1: of us all together. So this is a real preview 7 00:00:16,040 --> 00:00:18,240 Speaker 1: of what is to come. Andy, Ryan and Emily are 8 00:00:18,239 --> 00:00:20,239 Speaker 1: going to give some predictions that'll be fun. Chris and 9 00:00:20,320 --> 00:00:22,439 Speaker 1: I will preview a little bit of what we're going 10 00:00:22,480 --> 00:00:24,280 Speaker 1: to talk about. We've got what do we have on deck? 11 00:00:24,320 --> 00:00:26,680 Speaker 1: We have polls. We're going to like Trump and Cheney. 12 00:00:27,080 --> 00:00:28,720 Speaker 2: That's great. Well, I was just going to say it's 13 00:00:28,720 --> 00:00:30,320 Speaker 2: sort of funny because the way the first block is 14 00:00:30,360 --> 00:00:32,440 Speaker 2: set up, it's a clip of Nate Silver being like, 15 00:00:32,479 --> 00:00:34,600 Speaker 2: all these poles are bullshit, and then us proceeding to 16 00:00:34,640 --> 00:00:38,240 Speaker 2: show you every pole that exists at this point. So 17 00:00:38,440 --> 00:00:41,520 Speaker 2: that game we're going to do that. We're also, yeah, 18 00:00:41,560 --> 00:00:44,800 Speaker 2: Trump making some waves with some new comments about Loz Jeney. 19 00:00:45,560 --> 00:00:47,680 Speaker 2: We'll show you those and her response and all of that. 20 00:00:47,840 --> 00:00:50,240 Speaker 2: And then Jadie Vance on Joe Rogan. We got a 21 00:00:50,240 --> 00:00:52,279 Speaker 2: couple of clips from that that we can share with 22 00:00:52,320 --> 00:00:55,120 Speaker 2: you too, So yeah, let's go ahead and jump into 23 00:00:55,160 --> 00:00:59,280 Speaker 2: it before I show the Nate silver clip. We aren't 24 00:00:59,280 --> 00:01:01,640 Speaker 2: going to have Ryan and Emily on air again, I 25 00:01:01,680 --> 00:01:04,440 Speaker 2: don't think until election night when we're all doing our 26 00:01:04,480 --> 00:01:07,160 Speaker 2: live stream together in studio. So I wanted to give 27 00:01:07,160 --> 00:01:10,680 Speaker 2: you guys a chance for like your sort of polls 28 00:01:10,680 --> 00:01:12,759 Speaker 2: are all basically tied. It's a coin flip, so it's 29 00:01:12,880 --> 00:01:14,920 Speaker 2: just down to everybody's gut check of what they think 30 00:01:14,959 --> 00:01:16,959 Speaker 2: is going on, or reading of various tea leaves. So 31 00:01:17,560 --> 00:01:20,319 Speaker 2: what what do you guys think? Emily, which way are 32 00:01:20,360 --> 00:01:21,200 Speaker 2: you leaning at this point? 33 00:01:21,880 --> 00:01:24,399 Speaker 3: Thank you for starting with me and put you on 34 00:01:24,440 --> 00:01:25,399 Speaker 3: the spot so. 35 00:01:25,400 --> 00:01:28,240 Speaker 4: Eager to make this prediction. No, I mean, I've actually 36 00:01:28,280 --> 00:01:32,200 Speaker 4: always had a feeling that Democrats just have a better 37 00:01:32,440 --> 00:01:38,039 Speaker 4: chance in this election because the right underestimates how unpopular 38 00:01:38,440 --> 00:01:39,600 Speaker 4: Donald Trump is. 39 00:01:40,440 --> 00:01:41,959 Speaker 3: What I'm hearing from sources is. 40 00:01:41,959 --> 00:01:43,959 Speaker 4: That he's not making gains in the suburbs, but he 41 00:01:44,040 --> 00:01:46,440 Speaker 4: is making gains in rural areas. Some of them are 42 00:01:46,440 --> 00:01:48,880 Speaker 4: really excited about those big gains in roll areas, which 43 00:01:48,920 --> 00:01:51,160 Speaker 4: sounds interesting in twenty twenty four, almost a decade into 44 00:01:51,160 --> 00:01:54,880 Speaker 4: the Trump phenomena. But they're just it's a numbers game, right, 45 00:01:54,880 --> 00:01:56,720 Speaker 4: Like there aren't as many roal voters as there are 46 00:01:56,800 --> 00:01:59,480 Speaker 4: suburban voters, and as horrible of a campaign as I 47 00:01:59,520 --> 00:02:02,880 Speaker 4: think Kamala Harris's run, especially in the closing three weeks. 48 00:02:03,960 --> 00:02:06,280 Speaker 4: She's kind of gotten it together this week. But as 49 00:02:06,280 --> 00:02:10,320 Speaker 4: horrible as of a race, I think she's one. I mean, 50 00:02:10,600 --> 00:02:13,919 Speaker 4: I think anybody. I think it's anybody's guests. I think 51 00:02:13,919 --> 00:02:15,600 Speaker 4: we're all on the same page about that. But if 52 00:02:15,600 --> 00:02:19,040 Speaker 4: somebody put a gun to my head, I would probably. 53 00:02:18,760 --> 00:02:21,840 Speaker 1: Say, but I'm gonna up the stakes. It's not even 54 00:02:21,880 --> 00:02:24,600 Speaker 1: just gun to your head. Give us each state. What 55 00:02:24,600 --> 00:02:24,919 Speaker 1: do you think? 56 00:02:25,440 --> 00:02:26,200 Speaker 2: Oh, that's brtal. 57 00:02:27,280 --> 00:02:29,959 Speaker 1: Come on, you gotta call you make a call to 58 00:02:30,000 --> 00:02:30,959 Speaker 1: do it. You gotta make a call. 59 00:02:33,480 --> 00:02:34,280 Speaker 3: Make it back on. 60 00:02:35,840 --> 00:02:37,040 Speaker 1: You like my white face. 61 00:02:40,400 --> 00:02:41,560 Speaker 2: Cultural appropriations? 62 00:02:43,639 --> 00:02:46,840 Speaker 4: Well, okay, so I think the I think Kamala Harris 63 00:02:46,880 --> 00:02:50,720 Speaker 4: will will win Wisconsin. I think she'll win Michigan. I 64 00:02:50,720 --> 00:02:53,240 Speaker 4: think Trump will win Pennsylvania. And I think Kamala's route 65 00:02:53,240 --> 00:02:55,120 Speaker 4: if she wins, we'll be through the sun Belt. 66 00:02:55,440 --> 00:02:55,760 Speaker 1: Wow. 67 00:02:55,800 --> 00:02:58,519 Speaker 2: Really, so like North Carolina and Nevada. 68 00:02:58,160 --> 00:03:01,400 Speaker 1: Is going to say she'd have to do some upset there. Okay, 69 00:03:01,400 --> 00:03:03,400 Speaker 1: Interesting you and I are thinking similarly, but in a 70 00:03:03,400 --> 00:03:05,760 Speaker 1: different direction, right, Ryan, what you got? 71 00:03:05,960 --> 00:03:08,040 Speaker 5: I feel like this is that kind of election where 72 00:03:08,080 --> 00:03:11,560 Speaker 5: afterwards it will look so obvious in hindsight. 73 00:03:11,440 --> 00:03:12,160 Speaker 1: It always does. 74 00:03:12,919 --> 00:03:15,680 Speaker 5: Who wins well obviously this is That's why that happened. 75 00:03:16,120 --> 00:03:19,600 Speaker 5: But at this point, god, who knows, since I have 76 00:03:19,680 --> 00:03:24,280 Speaker 5: to pick, I think that Kamala ends up holding Pennsylvania, Michigan, 77 00:03:24,280 --> 00:03:27,320 Speaker 5: in Wisconsin and losing basically everything else. 78 00:03:27,600 --> 00:03:29,960 Speaker 1: Got it eight? Yeah? 79 00:03:30,040 --> 00:03:32,840 Speaker 5: Yeah, that would give her exactly to seventy right, yeah. 80 00:03:32,639 --> 00:03:35,640 Speaker 2: As long as she wins that one Nebraska congressional which 81 00:03:35,680 --> 00:03:38,200 Speaker 2: looks I mean, the polling there is actually looked very 82 00:03:38,480 --> 00:03:39,200 Speaker 2: strong for her. 83 00:03:39,480 --> 00:03:41,960 Speaker 5: So and then, oh man, the public will be so 84 00:03:42,000 --> 00:03:43,800 Speaker 5: mad at that one state senator. 85 00:03:44,040 --> 00:03:47,800 Speaker 2: Oh my god, that guy needs to change his name 86 00:03:47,880 --> 00:03:49,120 Speaker 2: is address for the state? 87 00:03:49,600 --> 00:03:49,760 Speaker 1: Luck. 88 00:03:50,720 --> 00:03:51,200 Speaker 4: I was just. 89 00:03:52,920 --> 00:03:57,360 Speaker 1: Political shifted that district to lean not I think lean 90 00:03:57,480 --> 00:04:00,680 Speaker 1: DEM from toss up. So they're projected that he's going 91 00:04:00,760 --> 00:04:03,400 Speaker 1: to lose his seat the Republican who does hold that district, 92 00:04:03,400 --> 00:04:05,520 Speaker 1: which is pretty interesting. That was a strong sign in 93 00:04:05,600 --> 00:04:07,360 Speaker 1: terms of Nebraska too. 94 00:04:07,640 --> 00:04:10,200 Speaker 2: Ryan, if it does, if it does work out like 95 00:04:10,240 --> 00:04:12,440 Speaker 2: you're saying, like the two seventy six eight, where she 96 00:04:12,480 --> 00:04:14,560 Speaker 2: wins through the quote unquote blue wall states, Like, what 97 00:04:14,600 --> 00:04:17,320 Speaker 2: do you think will have happened there? Strength of suburban 98 00:04:17,560 --> 00:04:18,520 Speaker 2: women or what are. 99 00:04:18,520 --> 00:04:25,800 Speaker 5: You Yeah, basically suburban women. And you know, Democrats are 100 00:04:25,839 --> 00:04:30,800 Speaker 5: still getting like, you know, high eighties with the black vote, 101 00:04:31,360 --> 00:04:33,560 Speaker 5: and so even though they're bottoming it out in rural 102 00:04:33,560 --> 00:04:36,800 Speaker 5: areas like the suburb. You know, if you have the suburbs, 103 00:04:37,320 --> 00:04:39,560 Speaker 5: if you're winning the suburbs and you're winning the cities, 104 00:04:40,040 --> 00:04:43,200 Speaker 5: you can lose rural America. You know, we were christ 105 00:04:43,279 --> 00:04:45,960 Speaker 5: Ner were joking on Twitter the other day that Trump 106 00:04:46,000 --> 00:04:51,000 Speaker 5: relying on men is quite a risky bet. Like, actually, 107 00:04:51,040 --> 00:04:52,680 Speaker 5: here's my ballot right here. I was just going to say, 108 00:04:52,680 --> 00:04:54,279 Speaker 5: I think I lost my ballot, but I just so, 109 00:04:54,360 --> 00:04:56,080 Speaker 5: I just found it, but I haven't set it in. 110 00:04:56,160 --> 00:05:00,280 Speaker 5: My wife sent hers in days and days ago. I'll 111 00:05:00,279 --> 00:05:03,320 Speaker 5: probably go on election. Uh, and most men are like, 112 00:05:03,320 --> 00:05:07,599 Speaker 5: oh shit today, God yeah, and then some bunch of. 113 00:05:07,600 --> 00:05:08,480 Speaker 1: The markets show up. 114 00:05:08,920 --> 00:05:11,360 Speaker 2: Yeah, I've I've voted when Kyle has not. 115 00:05:11,680 --> 00:05:16,240 Speaker 1: So really, my wife and I voted together. I'm actually 116 00:05:16,240 --> 00:05:17,840 Speaker 1: the one who told her. I said, Babe, we got 117 00:05:17,839 --> 00:05:19,200 Speaker 1: to go to the polls. What are we doing here? 118 00:05:19,200 --> 00:05:20,600 Speaker 1: I don't want to wait in line. So and that 119 00:05:20,680 --> 00:05:21,320 Speaker 1: was like a week ago. 120 00:05:22,160 --> 00:05:24,640 Speaker 2: Is the exception that, yes, you're an unusual creature. My 121 00:05:24,680 --> 00:05:30,120 Speaker 2: friend said with love, said all right, let's go and 122 00:05:30,160 --> 00:05:33,640 Speaker 2: get to Yeah, let's get to Nate Silver first informing 123 00:05:33,720 --> 00:05:35,719 Speaker 2: us of why everything we're about to do and the 124 00:05:35,760 --> 00:05:38,680 Speaker 2: rest of this block is worthless. But anyway, here we go. 125 00:05:38,800 --> 00:05:43,120 Speaker 2: This is Nate Silver talking about how the polsters are hurting, 126 00:05:43,360 --> 00:05:45,359 Speaker 2: meaning they're all putting their thumb on the scales to 127 00:05:45,480 --> 00:05:47,800 Speaker 2: get basically a tide result. Let's take a listen to that. 128 00:05:49,400 --> 00:05:50,760 Speaker 2: Hold on, that's way too fast. 129 00:05:51,600 --> 00:05:52,680 Speaker 1: That not too fast for me. 130 00:05:52,839 --> 00:05:53,800 Speaker 2: Let me slow that down. 131 00:05:53,839 --> 00:05:55,160 Speaker 5: All right, we already have. 132 00:05:56,279 --> 00:05:58,120 Speaker 2: Let me get my d MS on here. All right, 133 00:05:58,160 --> 00:05:58,520 Speaker 2: here we. 134 00:05:58,480 --> 00:06:03,640 Speaker 6: Go fifty five with a small chance of a tie. 135 00:06:04,720 --> 00:06:05,680 Speaker 1: It's been a little weird. 136 00:06:05,720 --> 00:06:10,640 Speaker 6: I mean, look, it's gradually drifted to trump over actually 137 00:06:11,400 --> 00:06:12,360 Speaker 6: a fairly long period. 138 00:06:12,400 --> 00:06:12,520 Speaker 1: Now. 139 00:06:12,520 --> 00:06:14,559 Speaker 6: I mean, you know, two and every three days Harris 140 00:06:14,560 --> 00:06:18,960 Speaker 6: has lost grown on the forecast since since roughly early October. 141 00:06:20,560 --> 00:06:23,400 Speaker 6: You know, it looks like you should stabilize a bit. 142 00:06:23,480 --> 00:06:24,960 Speaker 6: Maybe I don't think we're gonna don't think we're gonn 143 00:06:24,960 --> 00:06:28,599 Speaker 6: gonna learn very much in this last week of the polling. 144 00:06:29,040 --> 00:06:32,560 Speaker 6: In fact, I kind of trust polsters lest this. They 145 00:06:32,600 --> 00:06:36,880 Speaker 6: all every time a polster, Oh every state is just 146 00:06:36,920 --> 00:06:39,240 Speaker 6: a plus one if every single state's a tie. 147 00:06:39,040 --> 00:06:39,960 Speaker 1: No, you're fucking hurting. 148 00:06:40,000 --> 00:06:40,520 Speaker 6: You're cheating. 149 00:06:40,760 --> 00:06:41,320 Speaker 3: You're cheating. 150 00:06:41,440 --> 00:06:43,360 Speaker 6: Your numbers are all going to come out at exactly 151 00:06:43,400 --> 00:06:45,440 Speaker 6: one point leads. When you're staying with like eight hundred 152 00:06:45,440 --> 00:06:47,920 Speaker 6: people over dozens of surveys, you are lying. You're putting 153 00:06:47,960 --> 00:06:50,279 Speaker 6: a fucking figer on the scale. I will not name names, 154 00:06:50,320 --> 00:06:52,320 Speaker 6: but some pultures are really bad about this. 155 00:06:53,200 --> 00:06:55,440 Speaker 2: I think, yeah, you get the gist there, and this 156 00:06:55,480 --> 00:06:57,839 Speaker 2: is something a phenomenon that we've been talking about about. 157 00:06:57,960 --> 00:07:03,080 Speaker 2: And I looked Nate co tweeted out what previous accurate 158 00:07:03,720 --> 00:07:06,280 Speaker 2: polling looked like back in you know, twenty twelve, when 159 00:07:06,320 --> 00:07:09,080 Speaker 2: the polls were more accurate, and he was showing like, 160 00:07:09,160 --> 00:07:12,360 Speaker 2: in each state, here's how much of a distribution you 161 00:07:12,480 --> 00:07:14,800 Speaker 2: got In tern you'd get someone who was like, you know, oh, 162 00:07:14,800 --> 00:07:17,560 Speaker 2: it's plus five Barack Obama, Oh, actually met Romney's leading, 163 00:07:17,760 --> 00:07:20,480 Speaker 2: and the average overall was very close, but you had 164 00:07:20,600 --> 00:07:23,560 Speaker 2: a lot of variability within that. Now, you guys know, 165 00:07:23,600 --> 00:07:25,480 Speaker 2: I mean, we're about to look at a ton of poles, 166 00:07:25,520 --> 00:07:28,720 Speaker 2: most of which are like forty nine forty nine. Maybe 167 00:07:28,760 --> 00:07:31,840 Speaker 2: Kamala's got a point edge, maybe Trump's got a point edge, 168 00:07:31,880 --> 00:07:34,840 Speaker 2: And yeah, I think they're terrified. If they say it's 169 00:07:34,840 --> 00:07:38,280 Speaker 2: fifty to fifty, then they can't be too embarrassed no 170 00:07:38,320 --> 00:07:40,800 Speaker 2: matter what happens. And these are human beings with incentives, 171 00:07:40,800 --> 00:07:43,080 Speaker 2: and they do have the ability through making these likely 172 00:07:43,160 --> 00:07:46,400 Speaker 2: voter model screens, to put their thumb on the scales. 173 00:07:46,440 --> 00:07:47,720 Speaker 2: And yeah, I think they are. 174 00:07:48,120 --> 00:07:50,120 Speaker 1: Yeah, I tweeted this morning. I was like, one of 175 00:07:50,160 --> 00:07:52,600 Speaker 1: the things my biggest pulling lesson from this election is 176 00:07:52,600 --> 00:07:54,480 Speaker 1: that Polsters don't have an incentive to get it right 177 00:07:54,600 --> 00:07:56,920 Speaker 1: or even try. It's just an incentive to preserve future 178 00:07:56,960 --> 00:07:59,480 Speaker 1: business by not going out on a limb. And I 179 00:07:59,480 --> 00:08:03,640 Speaker 1: mean that's right cowardly and a problem in an industry 180 00:08:03,720 --> 00:08:07,640 Speaker 1: that is literally's entire job is forecasting. But that is 181 00:08:07,720 --> 00:08:10,440 Speaker 1: very helpful to people who are looking at this, who 182 00:08:10,440 --> 00:08:14,000 Speaker 1: are trying to use like twenty twenty or whatever type comparisons. 183 00:08:14,040 --> 00:08:15,680 Speaker 1: The truth is they have the fear of God in 184 00:08:15,720 --> 00:08:20,480 Speaker 1: them from two subsequent times of having such massive misses 185 00:08:20,520 --> 00:08:23,200 Speaker 1: in them. So we're going to show you some indicators, 186 00:08:23,200 --> 00:08:26,720 Speaker 1: but it's a lot more noisy, I think than previously. 187 00:08:26,800 --> 00:08:28,920 Speaker 1: I mean that said, there are some who are going 188 00:08:28,920 --> 00:08:30,880 Speaker 1: out on a limb, and for those we should take 189 00:08:30,920 --> 00:08:32,920 Speaker 1: we should pay attention the ones who are going out 190 00:08:32,960 --> 00:08:34,480 Speaker 1: on a limb for Trump and the ones who are 191 00:08:34,480 --> 00:08:36,760 Speaker 1: going out on a limb for KMMLA, because that actually 192 00:08:36,760 --> 00:08:38,720 Speaker 1: in the future we could look to them as well. 193 00:08:39,440 --> 00:08:40,880 Speaker 2: What do y'all think, Ryan and Emily. 194 00:08:41,800 --> 00:08:43,839 Speaker 5: It feels like a huge waste of everybody's time to 195 00:08:44,400 --> 00:08:47,079 Speaker 5: let me assign all these people to make all these 196 00:08:47,080 --> 00:08:52,040 Speaker 5: phone calls, have people sit through these surveys, then have 197 00:08:52,120 --> 00:08:55,240 Speaker 5: analysts go through all the surveys. If they're actually just 198 00:08:55,320 --> 00:08:58,600 Speaker 5: working backwards from their assumption, which is that it's now. 199 00:08:59,040 --> 00:09:01,720 Speaker 5: The way they could all be wrong is let's say 200 00:09:01,840 --> 00:09:06,120 Speaker 5: somebody wins a state by five points, and then but 201 00:09:06,200 --> 00:09:08,360 Speaker 5: then they'll say, ah, well everybody missed it, so it's 202 00:09:08,400 --> 00:09:09,160 Speaker 5: not it's not on me. 203 00:09:09,440 --> 00:09:12,120 Speaker 2: Well that's it. There's safety in numbers too. That's the 204 00:09:12,200 --> 00:09:14,840 Speaker 2: hurting part. If everyone is saying it's fifty to fifty, 205 00:09:14,920 --> 00:09:17,800 Speaker 2: then no individual polster has to be the one that 206 00:09:17,920 --> 00:09:20,160 Speaker 2: you know, what was it they said, Well, Biden's gonna 207 00:09:20,160 --> 00:09:23,240 Speaker 2: win Wisconsin by fourteen points or whatever, So no one 208 00:09:23,280 --> 00:09:26,080 Speaker 2: faces that level of reputational damage. 209 00:09:26,600 --> 00:09:29,199 Speaker 3: Yes, Brian's cat, of course, but. 210 00:09:31,360 --> 00:09:38,880 Speaker 4: There are obviously structural problems that have not gone away, 211 00:09:39,160 --> 00:09:43,239 Speaker 4: Meaning you have this like massive tech gap between hyperpensity 212 00:09:43,280 --> 00:09:46,400 Speaker 4: boomer voters and this goes back obviously years. Posters have 213 00:09:46,440 --> 00:09:48,480 Speaker 4: been dealing with this for a long time, and low 214 00:09:48,520 --> 00:09:52,840 Speaker 4: propensity zoomer millennial voters who don't have landlines and they're 215 00:09:53,000 --> 00:09:55,600 Speaker 4: adopting to the like that hasn't gone away. There is 216 00:09:55,640 --> 00:09:57,559 Speaker 4: no good way to deal with that. Everybody knows that. 217 00:09:57,600 --> 00:10:00,719 Speaker 4: So I think it's I think it's there is some 218 00:10:00,840 --> 00:10:05,800 Speaker 4: reasonable uncertainty, but I don't disagree with Nate Silver that 219 00:10:05,920 --> 00:10:08,840 Speaker 4: people are playing a little fast and loose to preserve 220 00:10:08,880 --> 00:10:11,400 Speaker 4: their themselves. And it's also because people have gotten really 221 00:10:11,440 --> 00:10:14,679 Speaker 4: pissed off about polling. Yeah, I think we used it 222 00:10:14,720 --> 00:10:17,200 Speaker 4: before it became so polarized. It used to be like, okay, well, 223 00:10:17,280 --> 00:10:19,200 Speaker 4: you know, it's it's an art, not a science. 224 00:10:19,200 --> 00:10:22,079 Speaker 2: And I was just like, man, yeah, well, And I 225 00:10:22,120 --> 00:10:25,400 Speaker 2: will say there's a lot more punishment meted out when 226 00:10:25,440 --> 00:10:29,559 Speaker 2: they underestimate Republicans than like they missed in twenty twenty 227 00:10:29,559 --> 00:10:32,680 Speaker 2: two they underestimated Dems, but they didn't get like ripped 228 00:10:32,679 --> 00:10:35,839 Speaker 2: a new one over it. So that creates certain incentives too. 229 00:10:35,880 --> 00:10:39,120 Speaker 2: And we know because of Nate Cone's analysis that they 230 00:10:39,120 --> 00:10:42,400 Speaker 2: have basically tried to clude just like we're just going 231 00:10:42,480 --> 00:10:46,319 Speaker 2: to assume that we're getting some Trump non voter response 232 00:10:46,679 --> 00:10:48,559 Speaker 2: and so we're just gonna, you know, sort of cluge 233 00:10:48,559 --> 00:10:51,520 Speaker 2: away to bump up his poll numbers. Many of the 234 00:10:51,559 --> 00:10:54,120 Speaker 2: posters are doing that, so we know they've really tried 235 00:10:54,160 --> 00:10:57,080 Speaker 2: to adjust. But they also could be that they're correct 236 00:10:57,120 --> 00:11:00,800 Speaker 2: about that, that they are missing some chunk of Trump 237 00:11:00,880 --> 00:11:02,920 Speaker 2: voters that they missed in twenty sixteen and missed again 238 00:11:02,960 --> 00:11:05,400 Speaker 2: in twenty twenty, So who knows. 239 00:11:06,480 --> 00:11:08,600 Speaker 4: I just want to quickly say the Federalist is also 240 00:11:08,880 --> 00:11:12,200 Speaker 4: an article this week that said the stigma around being 241 00:11:12,240 --> 00:11:15,160 Speaker 4: a Trump supporter is gone as and as Ryan mentioned 242 00:11:15,240 --> 00:11:17,320 Speaker 4: on our show on Wednesday, he said, you know, if 243 00:11:17,320 --> 00:11:20,640 Speaker 4: anyone would know, it's the Federalist and that is affecting polling, 244 00:11:20,640 --> 00:11:21,800 Speaker 4: There's no question about it. 245 00:11:21,840 --> 00:11:23,440 Speaker 3: And what polsters have been doing for the. 246 00:11:23,440 --> 00:11:26,440 Speaker 4: Last couple of cycles is trying to address that quote 247 00:11:26,480 --> 00:11:29,040 Speaker 4: shy Trump supporter. But what if the shy Trump supporters 248 00:11:29,120 --> 00:11:32,840 Speaker 4: totally gone and their adjustments are actually missing. That people 249 00:11:32,880 --> 00:11:35,920 Speaker 4: are now much more eager to say he only I'm 250 00:11:36,000 --> 00:11:38,360 Speaker 4: voting for Donald Trump, you know, like I heard on 251 00:11:38,440 --> 00:11:41,520 Speaker 4: theovon like the stigma is very very different this time. 252 00:11:41,559 --> 00:11:43,760 Speaker 3: Oh yeah, So I thought that was an interesting point too. 253 00:11:44,040 --> 00:11:45,760 Speaker 1: Who was it on our show that made a point 254 00:11:45,800 --> 00:11:48,240 Speaker 1: that Trump supporters these days are not all that shy 255 00:11:48,280 --> 00:11:49,600 Speaker 1: about saying they're voting for Trump. 256 00:11:49,800 --> 00:11:52,120 Speaker 2: I think it might have been Logan that said that one. 257 00:11:52,320 --> 00:11:55,160 Speaker 1: I mean, it's definitely true if you spend any time 258 00:11:55,160 --> 00:11:59,040 Speaker 1: in Trump Country during this election. The t shirts, the 259 00:11:59,200 --> 00:12:03,760 Speaker 1: truck bumpers, stickers, and the signs are more out of 260 00:12:03,800 --> 00:12:06,600 Speaker 1: control than I've ever seen ever before. And I lived 261 00:12:06,600 --> 00:12:08,520 Speaker 1: in a place that voted ninety percent for George W. 262 00:12:08,559 --> 00:12:08,800 Speaker 3: Bush. 263 00:12:08,840 --> 00:12:11,000 Speaker 2: I don't know that the shy Trump voter theory was 264 00:12:11,040 --> 00:12:13,520 Speaker 2: ever real, because I think actually the problem in twenty 265 00:12:13,559 --> 00:12:16,800 Speaker 2: sixteen was just they didn't have enough non college educated people. 266 00:12:16,840 --> 00:12:18,960 Speaker 2: It wasn't that people were like not admitting, it was 267 00:12:19,040 --> 00:12:22,960 Speaker 2: that they were not being sampled properly. But the Democrats 268 00:12:23,000 --> 00:12:26,360 Speaker 2: have a theory there's a shy Kamala voter, predominantly like 269 00:12:26,520 --> 00:12:28,720 Speaker 2: women whose husbands are voting Trump and they don't want to, 270 00:12:28,760 --> 00:12:31,680 Speaker 2: like cause marital distress by admitting they want to vote 271 00:12:31,679 --> 00:12:33,679 Speaker 2: for Kamala and they've had a whole ad series has 272 00:12:33,679 --> 00:12:38,320 Speaker 2: been very controversial, controversial, dedicated to telling women like, don't worry, 273 00:12:38,400 --> 00:12:40,360 Speaker 2: you still have your choice in the voting booth, blah blah. 274 00:12:40,480 --> 00:12:42,520 Speaker 2: I think Julia Roberts voiced one, yes, she did. 275 00:12:42,720 --> 00:12:45,719 Speaker 4: Chuck Chuck Roach told me yesterday actually and undercurrentcy said 276 00:12:45,760 --> 00:12:47,199 Speaker 4: he was like, no, that's one hundred percent real. 277 00:12:47,240 --> 00:12:49,240 Speaker 2: He said that they're really absolutely seeing him. 278 00:12:49,360 --> 00:12:51,160 Speaker 4: That's why they're putting money behind it, which I was 279 00:12:51,200 --> 00:12:54,000 Speaker 4: totally skeptical of. Maybe he's but he's under an impression 280 00:12:54,040 --> 00:12:54,760 Speaker 4: that's totally real. 281 00:12:55,160 --> 00:12:57,960 Speaker 2: All right, Well we're gonna find out. Okay they know, 282 00:12:58,760 --> 00:12:59,719 Speaker 2: How will they know after that? 283 00:13:00,480 --> 00:13:01,040 Speaker 1: If it's real? 284 00:13:02,080 --> 00:13:05,920 Speaker 5: How'd they find these women like that you told them? 285 00:13:06,080 --> 00:13:07,520 Speaker 2: Yeah, that's an interesting question. 286 00:13:07,920 --> 00:13:10,000 Speaker 5: If they're not willing to talk about it. 287 00:13:09,920 --> 00:13:12,160 Speaker 2: If they're so shy they're not admitting it, Yeah, you'd 288 00:13:12,200 --> 00:13:12,920 Speaker 2: have to just like. 289 00:13:12,960 --> 00:13:13,440 Speaker 1: It's got them. 290 00:13:13,440 --> 00:13:15,920 Speaker 5: On Monday night, while the while the dude was at. 291 00:13:15,880 --> 00:13:17,880 Speaker 2: The bar watching after the wine, had a couple of 292 00:13:18,160 --> 00:13:24,559 Speaker 2: glasses in after the kids were in bed, the book clubs. Yes, 293 00:13:27,080 --> 00:13:30,880 Speaker 2: the playgroup was infiltrated. Okay, all right, I got Polly 294 00:13:30,880 --> 00:13:32,800 Speaker 2: Market up on the screen here, Sager, tell me you 295 00:13:33,120 --> 00:13:35,319 Speaker 2: sent in this element. Tell me why this was significant 296 00:13:35,360 --> 00:13:35,520 Speaker 2: to you. 297 00:13:35,800 --> 00:13:39,120 Speaker 1: So there's been a movement there. Actually more recently it's 298 00:13:39,120 --> 00:13:42,240 Speaker 1: gone back. But Crystal, can you kit politics please out 299 00:13:42,280 --> 00:13:44,760 Speaker 1: at the top and just click the politics ones, because 300 00:13:44,760 --> 00:13:48,319 Speaker 1: I want to show people the battleground states specifically. If 301 00:13:48,320 --> 00:13:50,160 Speaker 1: you just scroll down a little bit and you look 302 00:13:50,280 --> 00:13:53,920 Speaker 1: for Michigan and Wisconsin, you can actually see that she 303 00:13:54,000 --> 00:13:56,560 Speaker 1: has taken the lead in both of those states. So 304 00:13:57,440 --> 00:13:59,800 Speaker 1: that was a huge swing that just happened in the 305 00:14:00,040 --> 00:14:02,360 Speaker 1: last twenty four hours. If you go back, the same 306 00:14:02,400 --> 00:14:05,160 Speaker 1: thing has now happened in Wisconsin just in the last 307 00:14:05,160 --> 00:14:08,680 Speaker 1: twenty four hours. Has been massive shift in both markets. 308 00:14:08,960 --> 00:14:11,440 Speaker 1: Just from a pure betting point of view. I've been 309 00:14:11,440 --> 00:14:13,319 Speaker 1: talking about this a little bit on the show. There 310 00:14:13,320 --> 00:14:16,640 Speaker 1: has been basically like an ocean of dumb money that 311 00:14:16,720 --> 00:14:20,200 Speaker 1: has come into polymarket that is purely trying to vote 312 00:14:20,320 --> 00:14:23,640 Speaker 1: based on vibes the big problem. Yeah, So there you go. 313 00:14:23,680 --> 00:14:25,960 Speaker 1: You can see Kamo at fifty two, and all of 314 00:14:25,960 --> 00:14:27,960 Speaker 1: that movement has happened literally in the last twenty four 315 00:14:27,960 --> 00:14:30,920 Speaker 1: hours and actually more like in the last six hours. Basically, 316 00:14:30,920 --> 00:14:33,400 Speaker 1: what happened is in the early days of sports betting 317 00:14:33,520 --> 00:14:36,120 Speaker 1: is that it was very similar where the sports books 318 00:14:36,160 --> 00:14:39,120 Speaker 1: didn't really know how to quote unquote price align. And 319 00:14:39,200 --> 00:14:41,560 Speaker 1: so what will happen is that you will have quote 320 00:14:41,600 --> 00:14:45,440 Speaker 1: unquote sharp betters, people who disagree with this, who will 321 00:14:45,480 --> 00:14:48,360 Speaker 1: wait until the last minute, or they will lock in 322 00:14:48,480 --> 00:14:51,440 Speaker 1: something that they see is very unfavorable to the odds. 323 00:14:51,440 --> 00:14:54,000 Speaker 1: And this is a huge problem because polymarket has been 324 00:14:54,040 --> 00:14:57,680 Speaker 1: dramatically out of step with just the basic Nate Silver model, 325 00:14:57,920 --> 00:15:01,800 Speaker 1: which was the most accurate predictor of results in twenty 326 00:15:01,880 --> 00:15:05,480 Speaker 1: sixteen and in twenty twenty, and so you can tell 327 00:15:05,520 --> 00:15:09,080 Speaker 1: that the irrational exuberance has really happened, has had now 328 00:15:09,160 --> 00:15:12,840 Speaker 1: a major correction. I wouldn't say that Trump won't maintain 329 00:15:12,920 --> 00:15:14,640 Speaker 1: the lead just because I think a ton of money 330 00:15:14,880 --> 00:15:17,160 Speaker 1: was already placed on bets his side. And of course 331 00:15:17,160 --> 00:15:19,560 Speaker 1: there's also a lot of narrative stuff going on with this. 332 00:15:19,640 --> 00:15:21,520 Speaker 1: But if you look at the state by state data, 333 00:15:21,840 --> 00:15:24,280 Speaker 1: the two seventy two sixty eight path in particular that 334 00:15:24,400 --> 00:15:27,640 Speaker 1: Ryan is laying out is becoming a big bet on 335 00:15:27,680 --> 00:15:30,360 Speaker 1: the on polymarket hot with tens of millions of dollars 336 00:15:30,440 --> 00:15:31,000 Speaker 1: behind of it. 337 00:15:31,320 --> 00:15:33,960 Speaker 2: Yeah, yeah, I mean it's also just significant because the 338 00:15:33,960 --> 00:15:36,400 Speaker 2: writer has focused so much, and Elon in particular is 339 00:15:36,400 --> 00:15:39,400 Speaker 2: pumped up poly market so much that it's like, you know, 340 00:15:39,480 --> 00:15:42,240 Speaker 2: if it's shifting some that's I don't know, maybe it 341 00:15:42,240 --> 00:15:44,200 Speaker 2: shouldn't be important, but it's interesting to look. 342 00:15:44,080 --> 00:15:47,800 Speaker 1: At billions, at least a billion five in the market. 343 00:15:47,840 --> 00:15:49,360 Speaker 1: It's not small. You know, this is a real thing. 344 00:15:49,960 --> 00:15:50,280 Speaker 3: Sager. 345 00:15:50,320 --> 00:15:53,040 Speaker 4: There was a French billionaire who was gaming it for Trump, right, 346 00:15:53,120 --> 00:15:54,480 Speaker 4: like the yeah mask. 347 00:15:54,920 --> 00:15:58,720 Speaker 1: Yeah nobody, yeah, but yeah. 348 00:15:58,040 --> 00:16:00,600 Speaker 2: I mean whether he was, you know, legitimately is really 349 00:16:00,600 --> 00:16:01,720 Speaker 2: believed in Trump was. 350 00:16:01,720 --> 00:16:04,800 Speaker 1: Altly trying to furnish you a French VPN. Okay, So 351 00:16:04,880 --> 00:16:05,720 Speaker 1: like let's send. 352 00:16:06,720 --> 00:16:11,080 Speaker 2: Very true here. I've got up the Marist final polls 353 00:16:11,080 --> 00:16:13,880 Speaker 2: from the Blue Wall. Now, maris is significant. We had 354 00:16:13,960 --> 00:16:16,800 Speaker 2: on Edinger Mentem yesterday who called the twenty two race 355 00:16:16,840 --> 00:16:20,240 Speaker 2: correctly and called the Warnock election correctly as well and 356 00:16:20,960 --> 00:16:24,120 Speaker 2: did not buy into the red wave narrative. And Marist 357 00:16:24,280 --> 00:16:26,720 Speaker 2: was one of the polls that was correct in twenty 358 00:16:26,760 --> 00:16:28,520 Speaker 2: twenty two, and it's one of the pollsters that he 359 00:16:28,640 --> 00:16:31,360 Speaker 2: sort of like, you know, looks to the most as 360 00:16:31,400 --> 00:16:35,560 Speaker 2: not falling in so much to the herding and you 361 00:16:35,560 --> 00:16:37,360 Speaker 2: know and the putting of the home on the scales 362 00:16:37,360 --> 00:16:40,040 Speaker 2: as many other pollsters. So they find here a tight race, 363 00:16:40,080 --> 00:16:42,000 Speaker 2: but pretty good for Kamala. She's up in all three 364 00:16:42,000 --> 00:16:44,040 Speaker 2: of the Blue Wall states. She's up fifty one to 365 00:16:44,080 --> 00:16:47,040 Speaker 2: forty eight in Michigan, fifty forty eight in Pennsylvania, and 366 00:16:47,520 --> 00:16:50,760 Speaker 2: fifty forty eight in Wisconsin as well. That you get 367 00:16:50,800 --> 00:16:53,640 Speaker 2: the Senate numbers here as well, but also look quite 368 00:16:53,680 --> 00:16:58,600 Speaker 2: similar for Democrats. The Senate Democrats in the Blue Wall 369 00:16:58,680 --> 00:17:02,400 Speaker 2: are no longer out for forming Kamala as significantly at 370 00:17:02,440 --> 00:17:04,960 Speaker 2: least as they were in the past, so less ticket 371 00:17:05,000 --> 00:17:07,800 Speaker 2: splitting it looks like there, but again who knows. 372 00:17:08,160 --> 00:17:11,520 Speaker 1: Yeah, the Maris one in particular was the most interesting 373 00:17:11,560 --> 00:17:15,359 Speaker 1: Maris you can actually pick in either direction because it 374 00:17:15,560 --> 00:17:18,840 Speaker 1: had big miss in twenty twenty. That's what a lot 375 00:17:18,840 --> 00:17:21,880 Speaker 1: of you know, GOP people are talking about. It actually though, 376 00:17:22,040 --> 00:17:25,440 Speaker 1: was very accurate in twenty twenty two. It was one 377 00:17:25,480 --> 00:17:28,639 Speaker 1: of the only ones that high quality so called poster 378 00:17:28,720 --> 00:17:32,080 Speaker 1: in twenty twenty two that called Fetterman up by I 379 00:17:32,080 --> 00:17:34,560 Speaker 1: think it was two or three points in the state. 380 00:17:34,680 --> 00:17:38,439 Speaker 1: So it's one to take advantage of looking for if 381 00:17:38,480 --> 00:17:41,520 Speaker 1: you're looking for the signal there, I think this and 382 00:17:41,560 --> 00:17:43,880 Speaker 1: we're I think we're about to talk about this senior 383 00:17:43,960 --> 00:17:47,200 Speaker 1: vote in Pa. Are two like flashing signs of potential 384 00:17:47,280 --> 00:17:49,800 Speaker 1: Kamala victory in all three of those states. 385 00:17:50,280 --> 00:17:53,280 Speaker 2: Yeah, that's that's exactly right. Let me see what I 386 00:17:53,320 --> 00:17:56,480 Speaker 2: got up next here. Next, I've got another. I've got 387 00:17:56,520 --> 00:17:59,200 Speaker 2: just the rundown you sent Sager of all the Pennsylvanania. 388 00:17:59,280 --> 00:17:59,720 Speaker 1: Yay, this is you. 389 00:18:00,480 --> 00:18:02,439 Speaker 2: Yeah, let me pull let me pull this up. Hold on, 390 00:18:02,640 --> 00:18:04,119 Speaker 2: let's see if I cannot screw this up. 391 00:18:04,160 --> 00:18:04,560 Speaker 1: Here we go. 392 00:18:05,520 --> 00:18:08,639 Speaker 2: Yeah, here's the rundown of all the recent Pennsylvania polling. 393 00:18:08,680 --> 00:18:11,120 Speaker 2: Among Lakely voters Maris as we said, D plus two, 394 00:18:11,240 --> 00:18:17,280 Speaker 2: Fox tie, quinnipiec R plus one, CNN tie, CBS tie. So, 395 00:18:17,520 --> 00:18:20,880 Speaker 2: and then you've got more down here Marist D plus three. 396 00:18:21,520 --> 00:18:24,200 Speaker 2: Uh oh, this is Michigan WAPO D plus one, Fox 397 00:18:24,280 --> 00:18:26,800 Speaker 2: D plus two, CNND plus five. Michigan appears to be 398 00:18:26,840 --> 00:18:31,080 Speaker 2: Commala's most certain state at this point. Wisconsin D plus two, 399 00:18:31,200 --> 00:18:34,359 Speaker 2: D plus two, D plus six, and thie North Carolina anyway, 400 00:18:34,440 --> 00:18:37,000 Speaker 2: it goes on from there a lot of uh. And 401 00:18:37,000 --> 00:18:39,439 Speaker 2: then as you get to Arizona's the state that is 402 00:18:39,480 --> 00:18:42,439 Speaker 2: the swing state that is probably the most favorable for Trump, 403 00:18:42,480 --> 00:18:45,159 Speaker 2: either there or Georgia, where the polling has been a 404 00:18:45,160 --> 00:18:49,320 Speaker 2: little bit more erratic, more of a more variability there. 405 00:18:49,760 --> 00:18:52,680 Speaker 1: Yeah. Uh, I guess let's give the Trump case. I think. 406 00:18:52,760 --> 00:18:56,000 Speaker 1: Don't you have Atlas which is listed up next? Atlas 407 00:18:56,080 --> 00:18:58,960 Speaker 1: was quite uh what was it the most accurate pollster 408 00:18:59,560 --> 00:19:02,720 Speaker 1: in tw twenty and yeah, I believe that one. That 409 00:19:02,760 --> 00:19:05,919 Speaker 1: one's listed next Crystal in the Rundown. Yeah, if right 410 00:19:06,000 --> 00:19:08,120 Speaker 1: underneath there. So yeah, there you go, and you can 411 00:19:08,160 --> 00:19:12,080 Speaker 1: see wide margin of strength for Trump in Arizona, in 412 00:19:12,119 --> 00:19:15,280 Speaker 1: North Carolina, in Nevada if he's got a couple of points. 413 00:19:15,359 --> 00:19:18,159 Speaker 1: Georgia actually has tighter at one point six just for 414 00:19:18,240 --> 00:19:20,720 Speaker 1: Donald Trump. But they have Trump leads in all three 415 00:19:20,720 --> 00:19:24,800 Speaker 1: of the states, with Wisconsin actually being the tightest one 416 00:19:25,119 --> 00:19:27,320 Speaker 1: at point three. Emily, what do you make of that? 417 00:19:27,560 --> 00:19:30,560 Speaker 1: There's on the betting markets right now. Wisconsin is actually 418 00:19:31,280 --> 00:19:33,199 Speaker 1: what a lot of people have as going to be 419 00:19:33,240 --> 00:19:37,119 Speaker 1: the tightest state for battleground state. I think it was 420 00:19:37,840 --> 00:19:41,520 Speaker 1: the second tightest last time in or sorry, in twenty sixteen, 421 00:19:41,960 --> 00:19:43,400 Speaker 1: what do you think is going to happen there? 422 00:19:44,200 --> 00:19:46,840 Speaker 4: I mean, both candidates have spent a truly outrageous amount 423 00:19:46,880 --> 00:19:48,800 Speaker 4: of time there host Hillary Clinton. 424 00:19:48,800 --> 00:19:52,919 Speaker 3: Obviously there's a good reason for that, but it's I mean, 425 00:19:52,960 --> 00:19:53,440 Speaker 3: it's tied. 426 00:19:53,560 --> 00:19:56,400 Speaker 4: That's that's what I say. Like the RCP average has 427 00:19:56,760 --> 00:20:00,159 Speaker 4: actually Harris up in their national average. I'm looking at 428 00:20:00,160 --> 00:20:01,920 Speaker 4: it right now. They have her up in every blue 429 00:20:01,920 --> 00:20:05,120 Speaker 4: Wall state except for Pennsylvania. So in Wisconsin it's only 430 00:20:05,240 --> 00:20:09,080 Speaker 4: by point three though on the national RCP average. So 431 00:20:10,480 --> 00:20:14,040 Speaker 4: it's just they have a huge Senate race, and I know, 432 00:20:14,240 --> 00:20:17,120 Speaker 4: like Ryan and Crystal, you guys have covered Tammy Baldwin's 433 00:20:17,160 --> 00:20:20,080 Speaker 4: career for a long time. She's very popular in Wisconsin. 434 00:20:20,119 --> 00:20:24,040 Speaker 4: The Republican candidate has inflation and immigration going for him, 435 00:20:24,119 --> 00:20:27,720 Speaker 4: but he's kind of actually interned for him when I 436 00:20:27,800 --> 00:20:33,760 Speaker 4: was but a young student, and his other things going 437 00:20:33,760 --> 00:20:36,160 Speaker 4: against him, just being an out of state a multi 438 00:20:36,240 --> 00:20:39,119 Speaker 4: multimillionaire or someone who's pegged us out of state. So 439 00:20:39,840 --> 00:20:42,480 Speaker 4: I just it's so it's too close, and I know 440 00:20:42,520 --> 00:20:45,280 Speaker 4: that's not very useful, but I have sources saying they're 441 00:20:45,280 --> 00:20:49,200 Speaker 4: seeing in Wisconsin in particular the rural margins going up, 442 00:20:49,520 --> 00:20:52,440 Speaker 4: which again I find just fascinating. Like now people say 443 00:20:52,480 --> 00:20:54,400 Speaker 4: I'm turning out for Trump and I'm voting for Trump 444 00:20:54,440 --> 00:20:56,320 Speaker 4: in these rural areas after nearly a decade of the 445 00:20:56,400 --> 00:21:00,159 Speaker 4: Trump phenomena, but they say they're clearly not confident the 446 00:21:00,240 --> 00:21:03,440 Speaker 4: suburban margins. I feel like they're going to keep losing 447 00:21:03,480 --> 00:21:06,840 Speaker 4: in the Wow counties that's uh waukeshaw Zaki in Washington 448 00:21:06,920 --> 00:21:10,399 Speaker 4: outside of Milwaukee. And if their margin, Trump will win 449 00:21:10,480 --> 00:21:12,800 Speaker 4: all of those counties. But if he keeps losing, or 450 00:21:12,840 --> 00:21:16,280 Speaker 4: if he keeps winning by less, then that's a real disaster. 451 00:21:16,440 --> 00:21:18,320 Speaker 4: Yet I don't know that you can mathematically make up 452 00:21:18,320 --> 00:21:21,400 Speaker 4: for that with uh the rural voters. And I think 453 00:21:21,480 --> 00:21:24,760 Speaker 4: Ryan probably sees something similar as a Pennsylvania guy when 454 00:21:24,760 --> 00:21:26,960 Speaker 4: you look at the collar counties outside Philadelphia. 455 00:21:28,720 --> 00:21:32,520 Speaker 2: We got some new two new CNN battleground poles as well. 456 00:21:32,960 --> 00:21:35,919 Speaker 2: They had already released their Blue Wall polls and to 457 00:21:36,040 --> 00:21:38,840 Speaker 2: their credit, showed, you know, something other than a tie. 458 00:21:38,880 --> 00:21:41,680 Speaker 2: They showed Harris with a significant lead in Wisconsin, Michigan, 459 00:21:41,720 --> 00:21:45,560 Speaker 2: and then it tied in Pennsylvania. This time, they've got 460 00:21:45,680 --> 00:21:49,080 Speaker 2: Georgia Trump forty eight forty seven. North Carolina Kamala forty 461 00:21:49,119 --> 00:21:53,439 Speaker 2: eight forty seven. So there you go. Whatever you can 462 00:21:53,480 --> 00:21:56,800 Speaker 2: make of that, I don't really know, but you know this, 463 00:21:57,440 --> 00:22:01,760 Speaker 2: if this was all accurate, perfect accurate, I guess Kamala 464 00:22:01,800 --> 00:22:05,600 Speaker 2: would win depending on Nevada. But this Pennsylvania being a 465 00:22:05,680 --> 00:22:08,560 Speaker 2: tie really kind of PA is the really kind of 466 00:22:09,320 --> 00:22:11,400 Speaker 2: screws it up. Yeah, there to be able to make 467 00:22:11,440 --> 00:22:14,439 Speaker 2: any sort of real prediction based on any of that. 468 00:22:14,960 --> 00:22:18,520 Speaker 1: Yeah, I mean, I look, if put the polling aside, 469 00:22:18,720 --> 00:22:21,399 Speaker 1: you know, let's focus on the actual like vote and 470 00:22:21,440 --> 00:22:23,600 Speaker 1: stuff that we're seeing. Yeah, I'm glad you put this 471 00:22:23,680 --> 00:22:26,160 Speaker 1: up there on the screen. This has been the thing 472 00:22:26,240 --> 00:22:28,400 Speaker 1: I've heard. I have a few friends who are real 473 00:22:28,560 --> 00:22:31,080 Speaker 1: like gop Cassandra's like, there are one hundred percent convinced 474 00:22:31,080 --> 00:22:33,000 Speaker 1: Trump is going to lose, and I always check in 475 00:22:33,000 --> 00:22:35,000 Speaker 1: with them because it's a very good check. This is 476 00:22:35,040 --> 00:22:36,600 Speaker 1: one of the ones that they've been pointing to me 477 00:22:36,760 --> 00:22:39,520 Speaker 1: a lot. Quote. As the early results from PA reveal 478 00:22:39,560 --> 00:22:42,600 Speaker 1: an influx of first time female voters who will break 479 00:22:42,600 --> 00:22:45,679 Speaker 1: for Harris, newfound anxiety is taking hold, and in mar 480 00:22:45,720 --> 00:22:47,959 Speaker 1: A Lago they are starting to believe that the surge 481 00:22:48,040 --> 00:22:51,000 Speaker 1: last week was two weeks premature. Put the whole surge stuff, 482 00:22:51,080 --> 00:22:52,919 Speaker 1: you know, like out of it, because a lot of 483 00:22:52,920 --> 00:22:55,320 Speaker 1: this is I don't even necessarily know if like the 484 00:22:55,480 --> 00:22:58,000 Speaker 1: current vibe of the election would have affected that. I 485 00:22:58,000 --> 00:22:59,800 Speaker 1: think the truth is that the electorate has just changed 486 00:22:59,800 --> 00:23:01,639 Speaker 1: a lot. And this is one of the big problems 487 00:23:01,840 --> 00:23:05,000 Speaker 1: with the twenty twenty recall to vote waiting that a 488 00:23:05,000 --> 00:23:08,120 Speaker 1: lot of these polsters are doing. We were talking right before, 489 00:23:08,119 --> 00:23:12,359 Speaker 1: Crystal about in migration, the character of each of these states, 490 00:23:12,359 --> 00:23:16,159 Speaker 1: specifically the battleground states has changed dramatically in terms of 491 00:23:16,200 --> 00:23:20,200 Speaker 1: North Carolina, Arizona, and Georgia just population wise. Then add 492 00:23:20,240 --> 00:23:22,959 Speaker 1: on top of that that you have had not similar 493 00:23:23,080 --> 00:23:27,040 Speaker 1: changes in the blue Wall states, but demographically you had 494 00:23:27,080 --> 00:23:30,920 Speaker 1: that massive suburban swing that has happened for Kamala Harris, 495 00:23:30,920 --> 00:23:32,639 Speaker 1: it's a hidden sign of strength for her. It always 496 00:23:32,640 --> 00:23:35,840 Speaker 1: has been. Trump's major strength would be his ability to 497 00:23:35,920 --> 00:23:38,800 Speaker 1: drive out that rural vote, like Emily has said, and 498 00:23:38,880 --> 00:23:41,680 Speaker 1: one of the signs of strength for him is, for example, 499 00:23:41,680 --> 00:23:44,960 Speaker 1: in Georgia today there is actually a higher turnout amongst 500 00:23:45,240 --> 00:23:48,439 Speaker 1: rural counties. Some of these rural counties are already at 501 00:23:48,560 --> 00:23:51,919 Speaker 1: ninety two percent of their election day totals before the 502 00:23:51,920 --> 00:23:54,320 Speaker 1: ballots have even been cast an election day, and they 503 00:23:54,320 --> 00:23:57,840 Speaker 1: are much higher, some like thirty percent higher than actually 504 00:23:57,880 --> 00:24:01,720 Speaker 1: in the suburban counties in Georgia that surrounding Metro Atlanta. 505 00:24:01,800 --> 00:24:05,639 Speaker 1: So the only really way that this election will turn 506 00:24:06,480 --> 00:24:09,439 Speaker 1: for Trump is if there is, uh, there is that 507 00:24:09,600 --> 00:24:13,040 Speaker 1: similar like strength even more like one hundred and ten 508 00:24:13,080 --> 00:24:16,320 Speaker 1: percent in the rural counties and specifically also with the 509 00:24:16,359 --> 00:24:20,240 Speaker 1: black and Latino vote to offset any white suburban shift. 510 00:24:20,320 --> 00:24:22,320 Speaker 1: But this is why it is still such a very 511 00:24:22,400 --> 00:24:24,360 Speaker 1: very tight race here. That's what I really. 512 00:24:24,160 --> 00:24:27,800 Speaker 2: Saw Ryan in twenty sixteen, Schumer famously said basically like, 513 00:24:27,880 --> 00:24:31,120 Speaker 2: you know, for every voter we lose that's working class 514 00:24:31,160 --> 00:24:34,680 Speaker 2: or rural, will gain two in the Pennsylvania suburbs. And 515 00:24:35,280 --> 00:24:37,920 Speaker 2: you know, this indicates that that math may actually now 516 00:24:37,960 --> 00:24:38,600 Speaker 2: be paying off. 517 00:24:38,640 --> 00:24:43,440 Speaker 5: I guess, I mean, basically, he was running a cynical 518 00:24:44,320 --> 00:24:47,760 Speaker 5: math game that we are a country that is like 519 00:24:48,280 --> 00:24:51,159 Speaker 5: you drive around our country, we're a suburban country. Like 520 00:24:51,160 --> 00:24:54,719 Speaker 5: it's just it's suburbs from coast to coast, plus then 521 00:24:54,760 --> 00:24:56,959 Speaker 5: some cities like inside there, and then you get out 522 00:24:57,000 --> 00:24:59,680 Speaker 5: in the rural areas. Those are pretty suburban like it's 523 00:25:02,119 --> 00:25:05,240 Speaker 5: I think I think more people consider themselves living in 524 00:25:05,280 --> 00:25:10,560 Speaker 5: a rural area than actually do live in a rural area. Now, 525 00:25:10,600 --> 00:25:13,040 Speaker 5: if people vote based on how they feel and identify, 526 00:25:13,080 --> 00:25:15,240 Speaker 5: then that then it doesn't actually matter that they're wrong 527 00:25:15,240 --> 00:25:18,280 Speaker 5: about where they live. But yeah, I mean the Democrats 528 00:25:18,320 --> 00:25:21,480 Speaker 5: are going to test the theory, like how badly can 529 00:25:21,560 --> 00:25:25,880 Speaker 5: you completely bottom out among an entire kind of regional 530 00:25:26,000 --> 00:25:30,480 Speaker 5: sector of the vote and still maintain a nationwide competitiveness. 531 00:25:30,600 --> 00:25:32,800 Speaker 1: This part is so key too that you have in 532 00:25:32,840 --> 00:25:36,280 Speaker 1: front is this Trump lagging in the early vote with seniors. 533 00:25:36,600 --> 00:25:39,120 Speaker 1: And I was thinking about it. If Kamala is given 534 00:25:39,160 --> 00:25:42,200 Speaker 1: the White House in two seventy two sixty eight by 535 00:25:42,280 --> 00:25:46,200 Speaker 1: boomers in PA, but Trump wins the black Latino vote, 536 00:25:46,200 --> 00:25:49,280 Speaker 1: and he actually wins all the most economically dynamic states, 537 00:25:49,480 --> 00:25:51,840 Speaker 1: which is across the Sun Belt, will have like one 538 00:25:51,880 --> 00:25:55,679 Speaker 1: of those reverse twenty sixteen situations where what did Hillary 539 00:25:55,720 --> 00:25:58,040 Speaker 1: say she was like I won all the places? What 540 00:25:58,040 --> 00:25:58,960 Speaker 1: does she say that she was. 541 00:25:58,960 --> 00:26:01,520 Speaker 2: Like our dynamic growing or doing well? 542 00:26:01,520 --> 00:26:01,680 Speaker 7: That? 543 00:26:01,840 --> 00:26:03,720 Speaker 1: Yeah, and he and all the places they are doing bad. 544 00:26:04,040 --> 00:26:06,120 Speaker 1: It actually would be the opposite this time around, which 545 00:26:06,320 --> 00:26:09,600 Speaker 1: kind of fits if you think about my whole barsool 546 00:26:09,960 --> 00:26:14,360 Speaker 1: conservative thesis about like you know, libertarian economics and specifically 547 00:26:14,400 --> 00:26:15,920 Speaker 1: the type of people who would move to a sun 548 00:26:15,960 --> 00:26:18,680 Speaker 1: belt state where the election, you know, where the economy 549 00:26:18,760 --> 00:26:21,720 Speaker 1: is the pre eminent one, as opposed to PA where 550 00:26:21,800 --> 00:26:23,879 Speaker 1: it's pretty clear like a lot of the people who 551 00:26:23,920 --> 00:26:26,600 Speaker 1: are coming in for common the Democrats are coming on 552 00:26:26,680 --> 00:26:28,920 Speaker 1: the back of abortion and it's just like one of 553 00:26:28,920 --> 00:26:32,960 Speaker 1: the number one catalysts for that surgeon suburban vote and 554 00:26:32,960 --> 00:26:34,240 Speaker 1: specifically also with women. 555 00:26:34,760 --> 00:26:36,600 Speaker 4: And let me just quickly put some numbers on this, 556 00:26:36,680 --> 00:26:38,320 Speaker 4: because I have them in front of me. This is, 557 00:26:38,359 --> 00:26:42,639 Speaker 4: according to Pew, to just visualize the difference between rural, 558 00:26:42,680 --> 00:26:46,280 Speaker 4: suburban and urban voters, forty six million Americans live in 559 00:26:46,280 --> 00:26:50,200 Speaker 4: the nation's rural counties, one hundred and seventy five million 560 00:26:50,320 --> 00:26:53,000 Speaker 4: in its suburbs and small metros, and then about ninety 561 00:26:53,000 --> 00:26:55,719 Speaker 4: eight million in its urban core counties. So I mean, 562 00:26:55,760 --> 00:26:57,159 Speaker 4: it's really just it's not even close. 563 00:26:57,760 --> 00:27:00,840 Speaker 2: Yeah, yeah, And I guess that's the other question with 564 00:27:00,920 --> 00:27:02,879 Speaker 2: the early vote that people have been raising, you know, 565 00:27:02,920 --> 00:27:06,200 Speaker 2: where there's huge early turnout in these rural counties, is 566 00:27:06,720 --> 00:27:08,920 Speaker 2: at the end of the day, where these just people 567 00:27:08,920 --> 00:27:10,480 Speaker 2: who were going to show up an election day, another 568 00:27:10,600 --> 00:27:14,400 Speaker 2: showing up early, you know, so it doesn't really impact 569 00:27:14,440 --> 00:27:17,199 Speaker 2: the turnout margin, et cetera in these counties, and you know, 570 00:27:17,440 --> 00:27:20,080 Speaker 2: still very much too early to tell on any of that. 571 00:27:20,880 --> 00:27:23,879 Speaker 2: Next we have another you know, if you're making the 572 00:27:24,080 --> 00:27:28,080 Speaker 2: bowl case for Democrats, this is the enthusiasm numbers, and 573 00:27:28,119 --> 00:27:33,000 Speaker 2: you can actually see that they have maintained. Now, Democrats 574 00:27:33,040 --> 00:27:35,800 Speaker 2: have actually slid a little bit since basically like Kamalo's pick, 575 00:27:35,880 --> 00:27:40,480 Speaker 2: but still they have maintained very high enthusiasm numbers, higher 576 00:27:40,480 --> 00:27:43,800 Speaker 2: than the Republicans. And you know, I feel like you 577 00:27:43,800 --> 00:27:45,399 Speaker 2: can get that vibe a little bit at some of 578 00:27:45,400 --> 00:27:47,520 Speaker 2: Trump's rallies are a little bit more low energy than 579 00:27:47,520 --> 00:27:50,159 Speaker 2: they used to be. Certainly massive turnout for Kamala in 580 00:27:50,160 --> 00:27:53,359 Speaker 2: the places where she is popular on the you know, 581 00:27:53,800 --> 00:27:56,600 Speaker 2: the Ellipse where you guys were the other night. I've 582 00:27:56,640 --> 00:27:59,000 Speaker 2: also seen numbers which are kind of wild to me 583 00:27:59,160 --> 00:28:02,919 Speaker 2: that she's as possular with Democrats as Barack Obama was 584 00:28:03,119 --> 00:28:06,119 Speaker 2: at his like peak in two thousand and eight, which is, 585 00:28:06,320 --> 00:28:07,560 Speaker 2: you know, surprising, but. 586 00:28:08,240 --> 00:28:12,760 Speaker 5: In any case, primary people hated him. 587 00:28:13,320 --> 00:28:15,600 Speaker 2: That is true. You also at that point had more 588 00:28:15,680 --> 00:28:19,159 Speaker 2: people who are in that, like, you know, Appalachian in particular, 589 00:28:19,200 --> 00:28:21,199 Speaker 2: I still identify as a Democrat, but I'm really not 590 00:28:21,240 --> 00:28:24,879 Speaker 2: a Democrat outside of maybe like voting for county officials, 591 00:28:25,320 --> 00:28:32,240 Speaker 2: and most of that realignment has all shaken out. Yeah, 592 00:28:32,320 --> 00:28:34,040 Speaker 2: all right, let me see what I got here next. 593 00:28:34,280 --> 00:28:39,040 Speaker 2: This is interesting about where the turnout is, that rural turnout. 594 00:28:39,400 --> 00:28:42,280 Speaker 2: This is from Greg Bluestem down in Georgia, great reporter 595 00:28:42,480 --> 00:28:45,640 Speaker 2: at Atlanta Journal Constitution. He says, the highest early voting 596 00:28:45,640 --> 00:28:49,080 Speaker 2: turnout in Georgia is not in Democratic strongholds like Dacabb 597 00:28:49,160 --> 00:28:52,360 Speaker 2: County or the fiercely contested suburbs that surround Metro Atlanta. 598 00:28:52,400 --> 00:28:57,240 Speaker 2: It's in sparsely populated rural counties where Republicans dominate. So 599 00:28:57,840 --> 00:29:00,520 Speaker 2: this is what what you guys have been talked about. 600 00:29:00,600 --> 00:29:02,880 Speaker 2: You know, Like I said, the Democratic cope here is 601 00:29:02,880 --> 00:29:04,520 Speaker 2: that okay, But those people are just going to vote 602 00:29:04,520 --> 00:29:06,280 Speaker 2: on election day, so no big deal. And also, by 603 00:29:06,280 --> 00:29:08,400 Speaker 2: the way, there's not enough of them. But it can 604 00:29:08,440 --> 00:29:12,200 Speaker 2: also be an indicator of hey this, you know, your 605 00:29:12,200 --> 00:29:14,959 Speaker 2: opponent is really fired up, Like they are turning out 606 00:29:15,000 --> 00:29:18,440 Speaker 2: to vote early in potentially unprecedented numbers. 607 00:29:19,360 --> 00:29:22,800 Speaker 4: It's totally what I'm hearing from Republicans. That's really where 608 00:29:22,800 --> 00:29:25,400 Speaker 4: they're getting their source of hope from right now, is 609 00:29:25,440 --> 00:29:27,760 Speaker 4: what they're seeing in early voting in rural areas. 610 00:29:27,840 --> 00:29:30,920 Speaker 2: And Emily, is there a nervousness there though, Like there's 611 00:29:30,960 --> 00:29:34,600 Speaker 2: a lot of bravado publicly, But are you like we 612 00:29:34,600 --> 00:29:38,240 Speaker 2: we showed the reporting I believe from Puck News earlier 613 00:29:38,280 --> 00:29:41,080 Speaker 2: that said there was anxiety in particular about Pennsylvania. Is 614 00:29:41,080 --> 00:29:43,280 Speaker 2: that accurate to the best of your knowledge? 615 00:29:43,800 --> 00:29:44,240 Speaker 3: Totally? 616 00:29:44,360 --> 00:29:47,320 Speaker 4: And that said, and Sager, you're probably seeing this too. 617 00:29:47,960 --> 00:29:52,440 Speaker 4: It's it's almost polarized within like geop circles, where you 618 00:29:52,480 --> 00:29:55,760 Speaker 4: have some people who are feeling jittery because of that, 619 00:29:56,240 --> 00:29:58,240 Speaker 4: and then you have other people who are like, actually, 620 00:29:58,280 --> 00:30:00,160 Speaker 4: we're gonna see Trump win the popular vote. He's going 621 00:30:00,160 --> 00:30:03,120 Speaker 4: to sweep the blue wall, and he's been surging the 622 00:30:03,200 --> 00:30:04,000 Speaker 4: last few weeks. 623 00:30:04,400 --> 00:30:05,320 Speaker 3: She's been struggling. 624 00:30:05,800 --> 00:30:09,240 Speaker 4: We've just seen him be underestimated in those national averages, 625 00:30:09,240 --> 00:30:11,760 Speaker 4: and the fact that he's tied means that he's probably 626 00:30:11,920 --> 00:30:14,120 Speaker 4: up by three or four points. And so election day 627 00:30:14,160 --> 00:30:16,400 Speaker 4: comes around and you see him win Wisconsin by two, 628 00:30:16,480 --> 00:30:18,800 Speaker 4: you see him win Pennsylvania by three, you see him 629 00:30:19,120 --> 00:30:23,240 Speaker 4: just absolutely crushed North Carolina and Georgia, and we know 630 00:30:23,320 --> 00:30:26,280 Speaker 4: the answer pretty early. So people are like in one 631 00:30:26,320 --> 00:30:27,960 Speaker 4: of two camps. There aren't a lot of people in 632 00:30:27,960 --> 00:30:31,719 Speaker 4: the middle. People are either like, who these numbers have 633 00:30:31,800 --> 00:30:34,920 Speaker 4: this feeling a little uncomfortable because of the suburban vote, 634 00:30:35,040 --> 00:30:37,440 Speaker 4: or people like, actually, he's being underestimated. 635 00:30:37,600 --> 00:30:39,680 Speaker 1: The other caution I would throw out for people out 636 00:30:39,680 --> 00:30:42,600 Speaker 1: there is there's a real public private game happening right now. 637 00:30:42,720 --> 00:30:46,200 Speaker 1: So I noticed this with like democratic election experts, like 638 00:30:46,280 --> 00:30:49,680 Speaker 1: everything is about like, well, actually, here's why the Democratic 639 00:30:49,680 --> 00:30:52,240 Speaker 1: turnouts like not that bad, or actually, here's why you 640 00:30:52,240 --> 00:30:54,320 Speaker 1: know the Democratic turnout is going to be okay. And 641 00:30:54,360 --> 00:30:57,200 Speaker 1: there's also a huge I mean because Twitter right now 642 00:30:57,240 --> 00:31:00,400 Speaker 1: is signal boosting like so much pro Trump content. There's 643 00:31:00,440 --> 00:31:02,680 Speaker 1: a real effort to try and just like demoralize the 644 00:31:02,760 --> 00:31:04,760 Speaker 1: left by saying like, oh, it's going to be a 645 00:31:04,800 --> 00:31:08,200 Speaker 1: Trump blowout victory. It's going to be this. The smart ones, 646 00:31:08,320 --> 00:31:11,120 Speaker 1: the smarter ones, I will say, are people like Mike 647 00:31:11,160 --> 00:31:14,160 Speaker 1: Cernovich and Charlie Kirk, who I noticed, you know, we're 648 00:31:14,200 --> 00:31:17,520 Speaker 1: originally doing that, but when they got the data in, 649 00:31:17,640 --> 00:31:19,800 Speaker 1: they were like, Okay, we have a problem here. Men 650 00:31:19,800 --> 00:31:21,840 Speaker 1: are not voting. We need to get our asses out, 651 00:31:21,840 --> 00:31:23,880 Speaker 1: we need to go vote right now. But there is 652 00:31:23,960 --> 00:31:27,320 Speaker 1: still I have noticed, like a commentator or a polling 653 00:31:27,320 --> 00:31:29,800 Speaker 1: analysis types which have grown up on the right, which 654 00:31:29,800 --> 00:31:33,800 Speaker 1: are very, very obviously geared to trying to demoralize the left. 655 00:31:34,520 --> 00:31:37,040 Speaker 1: And so you I'm what I'm saying that is for 656 00:31:37,080 --> 00:31:39,200 Speaker 1: people who are out there who are just scrolling, you 657 00:31:39,240 --> 00:31:41,440 Speaker 1: may not know that is you should really like think 658 00:31:41,480 --> 00:31:44,200 Speaker 1: about the motivations also of the poster, because sometimes a 659 00:31:44,240 --> 00:31:46,280 Speaker 1: lot of it is not honest analysis. I saw a 660 00:31:46,320 --> 00:31:48,520 Speaker 1: lot of this back in twenty twenty. Oh Trump, you know, 661 00:31:48,600 --> 00:31:50,760 Speaker 1: Virginia is in play. It's like, no, it's not. You know, 662 00:31:50,880 --> 00:31:53,720 Speaker 1: it's not like we just saw a rowneck pole this 663 00:31:53,800 --> 00:31:57,160 Speaker 1: morning has carry us up by ten points. Or remember 664 00:31:57,440 --> 00:32:00,000 Speaker 1: in twenty twenty, New Mexico is in play. Like again, 665 00:32:00,280 --> 00:32:02,600 Speaker 1: no it's not. You know, Trump lost it by more 666 00:32:02,640 --> 00:32:04,840 Speaker 1: than twenty twenty than he did in twenty sixteen, and 667 00:32:04,880 --> 00:32:07,040 Speaker 1: he'll probably be lose it by I mean, pols just 668 00:32:07,040 --> 00:32:09,440 Speaker 1: saw this morning in New Mexico he's down by twelve. 669 00:32:09,640 --> 00:32:12,200 Speaker 1: So now why is Trump in both of these states 670 00:32:12,520 --> 00:32:17,480 Speaker 1: in the last week of the election. Beats me, you know, it's. 671 00:32:17,320 --> 00:32:19,520 Speaker 2: All politics is national, so it kind of doesn't really 672 00:32:19,560 --> 00:32:21,719 Speaker 2: matter where he does the rally at this point, if 673 00:32:21,720 --> 00:32:25,080 Speaker 2: the rally gets coverage, Ryan, do you get any vibes 674 00:32:25,120 --> 00:32:27,800 Speaker 2: from the Democratic side or they're too mad about you 675 00:32:27,840 --> 00:32:29,000 Speaker 2: opposing their genocide to talk? 676 00:32:29,160 --> 00:32:29,200 Speaker 1: No? 677 00:32:29,680 --> 00:32:39,280 Speaker 5: No, their vibe is nervous, with some cautious optimism that 678 00:32:39,320 --> 00:32:40,560 Speaker 5: they're in it like they've. 679 00:32:40,680 --> 00:32:42,840 Speaker 2: Isn't the Democratic vibe always nervous though. 680 00:32:42,720 --> 00:32:45,960 Speaker 5: Yes, I agree with that, except twenty sixteen they were, Yeah. 681 00:32:45,920 --> 00:32:52,320 Speaker 2: Yeah, famously not nervous in twenty sixteen competent again. Yeah, yeah, 682 00:32:52,440 --> 00:32:54,840 Speaker 2: I was there, man, at the Davit Center. It was sad. 683 00:32:55,000 --> 00:32:57,160 Speaker 2: It was a sad place to be. Let me tell you, 684 00:32:57,400 --> 00:32:59,280 Speaker 2: it was a sad place to be, all right. We 685 00:32:59,320 --> 00:33:02,120 Speaker 2: got some dueling endorsements here. Let me just quickly go 686 00:33:02,200 --> 00:33:06,920 Speaker 2: through these. We got Lebron James sharing some Tony Hinchcliff 687 00:33:06,960 --> 00:33:09,960 Speaker 2: and endorsing Kamala Harris. I won't play the video, but it's, like, 688 00:33:10,000 --> 00:33:14,200 Speaker 2: you know, a compilation of basically like hateful comments from 689 00:33:14,480 --> 00:33:17,680 Speaker 2: Trump and various supporters. We also, though, got on the 690 00:33:17,720 --> 00:33:24,920 Speaker 2: other side, Jake Paul endorsing Donald Trump, and I actually didn't. 691 00:33:25,000 --> 00:33:26,880 Speaker 2: I'm not sure what the content is of this video. 692 00:33:26,880 --> 00:33:30,800 Speaker 2: It did in eighteen minutes of Jake Paul's explanation for 693 00:33:30,880 --> 00:33:33,440 Speaker 2: his endorsement. Maybe maybe somebody else here can share some 694 00:33:33,480 --> 00:33:34,280 Speaker 2: more insight there. 695 00:33:35,240 --> 00:33:38,120 Speaker 1: No, I mean it's you know, as an original Team 696 00:33:38,200 --> 00:33:41,240 Speaker 1: ten person, this is of course shocking to see somebody 697 00:33:41,600 --> 00:33:43,840 Speaker 1: who I used to watch during prank videos now literally 698 00:33:43,920 --> 00:33:47,880 Speaker 1: endorsing Trump. But look, Jake Paul Logan Paul is not 699 00:33:47,920 --> 00:33:50,400 Speaker 1: a surprise. There were two who were original, like from 700 00:33:50,520 --> 00:33:53,000 Speaker 1: some of the early influencers who were kind of flirting 701 00:33:53,000 --> 00:33:56,880 Speaker 1: with and or endorsing Trump interviewing him. It's if you 702 00:33:56,960 --> 00:34:00,120 Speaker 1: look at the world that they swim in from crypto 703 00:34:00,000 --> 00:34:04,760 Speaker 1: go to boxing, UFC, like the bro sphere online, it's 704 00:34:04,880 --> 00:34:08,760 Speaker 1: very obvious what that trend in direction is. For example, 705 00:34:08,800 --> 00:34:11,600 Speaker 1: like Jake was a big vivig Ramaswami guy, right, so 706 00:34:11,840 --> 00:34:14,359 Speaker 1: there you go, like where does that come from? It's 707 00:34:14,520 --> 00:34:17,839 Speaker 1: very much like the podcast world. And so, I mean, 708 00:34:17,880 --> 00:34:19,480 Speaker 1: this is a big bet, and that's Ryan what you 709 00:34:19,560 --> 00:34:22,080 Speaker 1: just talked about. The bet is is these people will 710 00:34:22,400 --> 00:34:25,000 Speaker 1: come out to vote. Now, statistically it doesn't really happen, 711 00:34:25,120 --> 00:34:28,480 Speaker 1: but twenty twenty was a very high turnout election. We 712 00:34:28,600 --> 00:34:31,480 Speaker 1: don't think that twenty and twenty four will reach twenty 713 00:34:31,520 --> 00:34:35,040 Speaker 1: twenty levels, but it'll probably be higher than twenty sixteen. 714 00:34:35,360 --> 00:34:37,760 Speaker 1: I think the youth vote was higher in twenty twenty 715 00:34:37,800 --> 00:34:39,719 Speaker 1: than it had been in quite a long time. So 716 00:34:39,880 --> 00:34:41,960 Speaker 1: you know, if you see people who are jazzed up 717 00:34:41,960 --> 00:34:44,760 Speaker 1: and potentially you know, this could be something that swings 718 00:34:44,840 --> 00:34:48,799 Speaker 1: in their direction. So I don't I wouldn't dismiss it 719 00:34:48,960 --> 00:34:51,960 Speaker 1: because if their theory of the male turnout and the 720 00:34:52,000 --> 00:34:55,680 Speaker 1: gender grap is correct, especially in terms of enthusiasm getting 721 00:34:55,680 --> 00:34:58,200 Speaker 1: people out to vote, it will be like genuinely a 722 00:34:58,280 --> 00:35:02,239 Speaker 1: landmark moment, especially some of those swing states where if 723 00:35:02,239 --> 00:35:04,520 Speaker 1: that's what the margin of victory is, it'll be pretty crazy. 724 00:35:05,040 --> 00:35:07,520 Speaker 5: Yeah, and it's a huge long term problem for Democrats 725 00:35:07,719 --> 00:35:11,680 Speaker 5: regards even if they eat this one out. Just not 726 00:35:11,719 --> 00:35:15,960 Speaker 5: having Democrats even be part of the conversation among like 727 00:35:16,080 --> 00:35:20,960 Speaker 5: one of two genders is insane. Every Like pretty pretty 728 00:35:21,000 --> 00:35:24,800 Speaker 5: much everything that that that men do ends up being 729 00:35:24,920 --> 00:35:29,440 Speaker 5: coded as Republican and right wing, whether it's like exercise, 730 00:35:29,520 --> 00:35:33,719 Speaker 5: trying to stay healthy, watching sports, like just you know, 731 00:35:33,800 --> 00:35:35,920 Speaker 5: talking about like talking about sports, whatever it is, like 732 00:35:36,320 --> 00:35:40,440 Speaker 5: it it drifts into like the world of conservative podcasting, 733 00:35:40,880 --> 00:35:43,880 Speaker 5: and they're just other than like Hassan Piker. There's like 734 00:35:43,960 --> 00:35:45,000 Speaker 5: nobody there. 735 00:35:45,160 --> 00:35:50,120 Speaker 2: You're there, Ryan me other than me, and I don't 736 00:35:50,120 --> 00:35:55,640 Speaker 2: know that I'm really helping. But of course, I mean 737 00:35:55,680 --> 00:36:00,160 Speaker 2: the flip side of that is obviously Republicans struggling with 738 00:36:00,280 --> 00:36:03,000 Speaker 2: women in the bet that's being placed in this particular 739 00:36:03,080 --> 00:36:08,440 Speaker 2: election is Republicans think the motivation of like the podcast 740 00:36:08,520 --> 00:36:12,000 Speaker 2: circuit and Trump going on Rogan and Dake Paul endorsing 741 00:36:12,040 --> 00:36:16,520 Speaker 2: and whatever will be sufficient motivation and energizing enough on 742 00:36:16,560 --> 00:36:20,040 Speaker 2: the bro side to overcome the sense among many women 743 00:36:20,080 --> 00:36:23,520 Speaker 2: and young women especially that they have lost a right 744 00:36:23,600 --> 00:36:25,040 Speaker 2: that they previously took for granted. 745 00:36:25,600 --> 00:36:28,360 Speaker 5: And it's kind of incredible that she it's kind of 746 00:36:28,400 --> 00:36:32,040 Speaker 5: incredible she didn't take up the Joe Rogan opportunity. And 747 00:36:32,080 --> 00:36:33,919 Speaker 5: I wonder if she'll kind of be the last one 748 00:36:33,920 --> 00:36:35,040 Speaker 5: that blows them. 749 00:36:34,960 --> 00:36:38,399 Speaker 1: Doesn't If she loses, that will be a huge That'll 750 00:36:38,440 --> 00:36:43,320 Speaker 1: be one of those like, I'm. 751 00:36:41,480 --> 00:36:44,640 Speaker 2: Just not as sold on it because Number I just 752 00:36:46,320 --> 00:36:47,960 Speaker 2: there's a lot of risk there for her right. 753 00:36:48,600 --> 00:36:52,480 Speaker 5: We visually may not just probably equipped for three hours 754 00:36:52,520 --> 00:36:53,919 Speaker 5: of that exactly fair. 755 00:36:54,160 --> 00:36:57,120 Speaker 2: Yeah, And then it's like how many of these people 756 00:36:57,200 --> 00:37:02,640 Speaker 2: are winnable, motivatable, et cetera. I don't really disagree with 757 00:37:02,760 --> 00:37:05,520 Speaker 2: their analysis of basically like, hey, if you'll do an 758 00:37:05,520 --> 00:37:07,080 Speaker 2: hour and come to us, I guess we'll make it work. 759 00:37:07,120 --> 00:37:10,120 Speaker 2: But in the home stretch we've got other fish to fry. 760 00:37:10,239 --> 00:37:12,440 Speaker 5: I think a lot of them would have been winnable, 761 00:37:12,680 --> 00:37:16,120 Speaker 5: but not necessarily by her. True what they need as 762 00:37:16,160 --> 00:37:19,000 Speaker 5: a candidate who can sit down for three or four hours. 763 00:37:19,160 --> 00:37:22,680 Speaker 2: Yeah, like I think, you know, Bernie did, like you know, 764 00:37:22,800 --> 00:37:24,840 Speaker 2: Rogan's audience. I think at that point in Rogan himself 765 00:37:24,880 --> 00:37:28,000 Speaker 2: was ideologically different when Bernie sits down with him. And 766 00:37:28,000 --> 00:37:30,360 Speaker 2: Bernie also, by the way, didn't do three hours, but 767 00:37:30,440 --> 00:37:32,799 Speaker 2: I people liked it on that podcast, and he was 768 00:37:32,840 --> 00:37:35,160 Speaker 2: able to you know, go with the flow and like 769 00:37:35,640 --> 00:37:36,640 Speaker 2: do his Bernie thing. 770 00:37:37,560 --> 00:37:39,919 Speaker 4: Just But yeah, Lex, Well, I was just gonna say quickly, 771 00:37:40,160 --> 00:37:42,080 Speaker 4: it's a problem for Democrats obviously, but it's a huge 772 00:37:42,120 --> 00:37:45,760 Speaker 4: problem for Republicans. There are abortion referendums on the ballot 773 00:37:45,840 --> 00:37:47,760 Speaker 4: when people are going to vote all over the country 774 00:37:47,840 --> 00:37:50,239 Speaker 4: right now. So the gender gap, which literally as we 775 00:37:50,239 --> 00:37:52,080 Speaker 4: were talking, I had a GOP source say we will 776 00:37:52,080 --> 00:37:55,160 Speaker 4: see the largest gender gap in an election in decades. Well, 777 00:37:55,320 --> 00:37:57,040 Speaker 4: it gets us right back to the same math that 778 00:37:57,040 --> 00:37:59,839 Speaker 4: we're doing between rural and suburban. It's like, you can 779 00:38:00,080 --> 00:38:03,120 Speaker 4: in all of the bros. But Megan Colli and Nikki Hayley, 780 00:38:03,200 --> 00:38:05,799 Speaker 4: even this week after the Madison Square Garden rally, We're like, dude, 781 00:38:05,840 --> 00:38:06,200 Speaker 4: you are. 782 00:38:06,239 --> 00:38:07,800 Speaker 3: Turning off women. 783 00:38:07,960 --> 00:38:09,920 Speaker 4: So it's not even just abortion, it's just the bro 784 00:38:10,080 --> 00:38:12,400 Speaker 4: coded stuff like you can try to amp up the 785 00:38:12,400 --> 00:38:14,160 Speaker 4: Meal voters, just like you can try to amp up 786 00:38:14,160 --> 00:38:17,040 Speaker 4: the Royal voters for turnout, but then does it go 787 00:38:17,080 --> 00:38:19,359 Speaker 4: too far in that direction and do you hurt your 788 00:38:19,360 --> 00:38:20,640 Speaker 4: margins in other places? 789 00:38:20,920 --> 00:38:22,720 Speaker 1: All right, we're going to turn out of Liz Cheney. 790 00:38:23,040 --> 00:38:26,000 Speaker 1: Donald Trump did an event last night with Tucker Carlson 791 00:38:26,719 --> 00:38:29,680 Speaker 1: made some quote unquote eye popping comments. We can debate 792 00:38:30,320 --> 00:38:33,759 Speaker 1: what exactly said, whether it even should be all that controversial, 793 00:38:33,800 --> 00:38:35,000 Speaker 1: but Christal, do you have it? 794 00:38:35,320 --> 00:38:39,719 Speaker 2: Hid? Let me pull this up here, here we go. 795 00:38:39,880 --> 00:38:43,280 Speaker 2: This is getting a lot of attention on cable news 796 00:38:43,320 --> 00:38:47,240 Speaker 2: and with Democrats in particular. So here, let's take a listen. 797 00:38:47,440 --> 00:38:51,479 Speaker 7: And Cheney was so fair. He said, I really want 798 00:38:51,480 --> 00:38:53,920 Speaker 7: to thank you. He said, Now, I'm so glad that 799 00:38:53,960 --> 00:38:57,360 Speaker 7: I actually endorsed you. It's amazing, but that you would 800 00:38:57,360 --> 00:38:59,399 Speaker 7: do this, And I didn't speak to him about it, 801 00:39:00,680 --> 00:39:03,680 Speaker 7: But then, you know, go a couple of years forward 802 00:39:03,760 --> 00:39:06,920 Speaker 7: to go now, and I don't blame him for sticking 803 00:39:07,040 --> 00:39:10,600 Speaker 7: with his daughter. But his daughter is a very dumb individual, 804 00:39:10,840 --> 00:39:16,440 Speaker 7: very dumb. She's a radical war hawk. Let's put her 805 00:39:16,480 --> 00:39:19,800 Speaker 7: with a rifle standing there with nine barrel shooting at her. Okay, 806 00:39:19,920 --> 00:39:22,439 Speaker 7: let's see how she feels about it. You know, when 807 00:39:22,440 --> 00:39:25,879 Speaker 7: the guns are trained on her face. You know, there 808 00:39:25,880 --> 00:39:28,279 Speaker 7: were a war Hawks when they're sitting in Washington in 809 00:39:28,320 --> 00:39:32,319 Speaker 7: a nice building saying, oh, gee, will let's send Let's 810 00:39:32,320 --> 00:39:35,240 Speaker 7: send ten thousand troops right into the mouth of the enemy. 811 00:39:36,040 --> 00:39:38,600 Speaker 7: But she's a stupid person. And I used to have 812 00:39:39,560 --> 00:39:42,719 Speaker 7: I have meetings with a lot of people, and she 813 00:39:42,800 --> 00:39:46,280 Speaker 7: always wanted to go to war with people. So whether 814 00:39:46,320 --> 00:39:49,239 Speaker 7: it's her, whether it's sick. I was surprised a little 815 00:39:49,239 --> 00:39:51,000 Speaker 7: bit with Dick Cheney. I didn't know him at all. 816 00:39:51,520 --> 00:39:53,880 Speaker 7: I only had essentially the one or two phone calls, 817 00:39:53,880 --> 00:39:56,960 Speaker 7: and it was only a call saying thank you very 818 00:39:57,040 --> 00:39:59,399 Speaker 7: much for doing that for Scooter Libby. That was nice. 819 00:39:59,400 --> 00:40:03,800 Speaker 7: And Scuda, by the way, was beyond that, he couldn't 820 00:40:03,840 --> 00:40:06,720 Speaker 7: believe that it happened. Nobody would do it. They should 821 00:40:06,719 --> 00:40:09,560 Speaker 7: have done that for him years before. But I was 822 00:40:09,600 --> 00:40:12,680 Speaker 7: a little surprised because I actually thought that Dick Cheney 823 00:40:13,160 --> 00:40:15,960 Speaker 7: would go with me over his daughter and he didn't. 824 00:40:16,200 --> 00:40:18,200 Speaker 7: And you know what, I understand it. It's your daughter 825 00:40:18,239 --> 00:40:21,800 Speaker 7: and you go, but she's a bad person. 826 00:40:22,800 --> 00:40:27,200 Speaker 2: So to me, well, I'll let I'll let the rest 827 00:40:27,239 --> 00:40:28,880 Speaker 2: of you guys react. But it's kind of wild to 828 00:40:28,920 --> 00:40:30,560 Speaker 2: me that he was sad that he didn't get the 829 00:40:30,600 --> 00:40:31,759 Speaker 2: Dick Cheney endorsing. 830 00:40:32,200 --> 00:40:35,839 Speaker 1: Se Cable keeps talking about that. For me, I'm like, bro, 831 00:40:36,120 --> 00:40:39,080 Speaker 1: we don't want the Dick Cheney endorsement. That's the whole point. 832 00:40:39,239 --> 00:40:42,680 Speaker 2: Like Dick is way worse than Liz Way, Like she's 833 00:40:42,719 --> 00:40:45,759 Speaker 2: got the bad ideology, like he did the thing like 834 00:40:45,880 --> 00:40:47,960 Speaker 2: and you're still like, gosh, I wish Dick Cheney had 835 00:40:48,000 --> 00:40:51,520 Speaker 2: endorsed me. It just shows you to me. And then 836 00:40:51,560 --> 00:40:53,520 Speaker 2: well you can talk about the comments that you know, 837 00:40:53,560 --> 00:40:57,319 Speaker 2: I think for for reasons that are you know, not unreasonable, 838 00:40:57,360 --> 00:40:59,080 Speaker 2: that got picked up on where he was saying, you know, 839 00:40:59,200 --> 00:41:01,880 Speaker 2: let's see her with the guns pointed at her face 840 00:41:01,960 --> 00:41:06,000 Speaker 2: or something like that, but you know it shows you 841 00:41:06,400 --> 00:41:10,000 Speaker 2: all of this, Oh, the neo cons are with Kamala 842 00:41:10,120 --> 00:41:13,920 Speaker 2: and Trump is anti war and whatever. None of this 843 00:41:14,000 --> 00:41:17,640 Speaker 2: is ideological for him. He still loves Mike Pompeo. He's 844 00:41:17,920 --> 00:41:20,400 Speaker 2: Mike Pompeo might be the Secretary of Defense. Tom Cotton 845 00:41:20,480 --> 00:41:23,080 Speaker 2: might be the Secretary of Defense. He's still pining after 846 00:41:23,160 --> 00:41:26,560 Speaker 2: the Dick Cheney endorsement. He campaigned with Liz Cheney last 847 00:41:26,560 --> 00:41:30,080 Speaker 2: time he ran, and she supported him throughout his entire 848 00:41:30,600 --> 00:41:33,400 Speaker 2: term in office. So for him, it's just all about 849 00:41:33,680 --> 00:41:36,719 Speaker 2: number one, Like how sort of prestigious he thinks you are. 850 00:41:36,760 --> 00:41:39,120 Speaker 2: So he thinks Dick Cheney because he was vice president 851 00:41:39,160 --> 00:41:41,399 Speaker 2: and he's well known, blah blah blah, it's prestigious, even 852 00:41:41,400 --> 00:41:43,240 Speaker 2: though he's like, to me, one of the most evil, 853 00:41:43,560 --> 00:41:47,600 Speaker 2: most nefarious politicians we've ever had in American politics. But 854 00:41:47,680 --> 00:41:51,400 Speaker 2: then number two, and most importantly, it's not about ideology. 855 00:41:51,480 --> 00:41:54,960 Speaker 2: It's about how do you feel about me personally? And 856 00:41:55,000 --> 00:41:58,000 Speaker 2: did you come through for me personally when I needed 857 00:41:58,000 --> 00:41:58,600 Speaker 2: and wanted you. 858 00:41:58,719 --> 00:42:01,600 Speaker 1: If you're looking for ideologic coherence from Donald Trump and 859 00:42:01,640 --> 00:42:04,799 Speaker 1: your Republican voter, I've got some bridges to sell you 860 00:42:05,480 --> 00:42:08,680 Speaker 1: in terms of the cable comments. So I will quote 861 00:42:08,680 --> 00:42:11,799 Speaker 1: from Zach Bouchamp, who can we all agree Zach Bouchamp 862 00:42:12,120 --> 00:42:16,760 Speaker 1: is a major liberal Kamala Harris type figure. He says, folks, 863 00:42:17,040 --> 00:42:19,520 Speaker 1: Trump did not threaten to execute Li Cheney. He actually 864 00:42:19,520 --> 00:42:22,080 Speaker 1: was calling her a chickenhawk, something liberals have said about 865 00:42:22,080 --> 00:42:24,960 Speaker 1: her for ages. Look at the context Trump is talking 866 00:42:24,960 --> 00:42:27,560 Speaker 1: about giving her a weapon. Typically people put in front 867 00:42:27,560 --> 00:42:31,120 Speaker 1: of firing scarms aren't armed. Trump does so many offensive things, 868 00:42:31,320 --> 00:42:34,680 Speaker 1: He makes so many anti democratic promises, it is counterproductive 869 00:42:34,680 --> 00:42:37,759 Speaker 1: to get outraged about fake ones. That and if you 870 00:42:37,800 --> 00:42:41,360 Speaker 1: also combined Glenn Greenwald's long list there of all the 871 00:42:41,440 --> 00:42:44,240 Speaker 1: chickenhawk comments that people have made throughout the two thousands 872 00:42:44,280 --> 00:42:46,879 Speaker 1: about the Chinese, that is one of the most sane 873 00:42:46,880 --> 00:42:49,759 Speaker 1: things that Trump has actually said about Liz Cheney. So 874 00:42:49,840 --> 00:42:50,520 Speaker 1: I'll leave it at that. 875 00:42:50,960 --> 00:42:53,560 Speaker 4: I think he's making a legitimate point, but it's somewhat 876 00:42:53,600 --> 00:42:56,320 Speaker 4: amusing that he's making the point as they are saying 877 00:42:56,360 --> 00:42:59,240 Speaker 4: that Kamala Harris calling him a fascist and a Nazi 878 00:42:59,360 --> 00:43:03,120 Speaker 4: is incitement to another assassination attempt. So if we're playing 879 00:43:03,200 --> 00:43:06,239 Speaker 4: this game, I mean, obviously am the political candidates to this. 880 00:43:06,480 --> 00:43:09,240 Speaker 1: Thank you for saying that, and like, can you sound 881 00:43:09,280 --> 00:43:12,560 Speaker 1: off on this this? What did Mark Cuban say something 882 00:43:12,600 --> 00:43:16,480 Speaker 1: about like stupid women? He was like, no intelligent women sport. 883 00:43:16,719 --> 00:43:19,760 Speaker 4: But I've had an all time Hall of Fame level 884 00:43:20,000 --> 00:43:21,200 Speaker 4: tweet at yes. 885 00:43:21,160 --> 00:43:22,839 Speaker 1: I saw that. Yeah, where he's like he doesn't even 886 00:43:22,880 --> 00:43:25,680 Speaker 1: have club speed. This is two where let's let's float 887 00:43:25,880 --> 00:43:31,000 Speaker 1: slow clue, let's talk about golf. Republican Republican snowflakes on this, 888 00:43:31,080 --> 00:43:34,120 Speaker 1: They're like, I'm a strong woman and I support Trump. 889 00:43:34,160 --> 00:43:36,040 Speaker 1: I'm like, you are just as much of a loser 890 00:43:36,080 --> 00:43:39,000 Speaker 1: then as those possy hat wearing liberals if you're out 891 00:43:39,040 --> 00:43:41,960 Speaker 1: there like sorry, like you know, like do we reject 892 00:43:42,000 --> 00:43:44,880 Speaker 1: identity stuff or not? Like are we getting offended at 893 00:43:44,920 --> 00:43:47,840 Speaker 1: things or not? And it's like the selective bias on 894 00:43:47,880 --> 00:43:51,800 Speaker 1: this drives me crazy because they're like, Mark Cuban doesn't 895 00:43:51,840 --> 00:43:55,280 Speaker 1: respect women because you said smart women don't surround themselves 896 00:43:55,280 --> 00:43:57,279 Speaker 1: with Trump. And they're like, I'm a swart woman who 897 00:43:57,480 --> 00:43:59,760 Speaker 1: works for Donald Trump. I'm like that's like Hillary Clinton, 898 00:44:00,320 --> 00:44:02,880 Speaker 1: like bullshity. 899 00:44:03,440 --> 00:44:05,719 Speaker 4: It's it's well, no, I mean it's virtue signaling, right, 900 00:44:05,760 --> 00:44:08,759 Speaker 4: Like it's it's what's so insufferable about virtue signaling on 901 00:44:08,800 --> 00:44:10,960 Speaker 4: the left is that there's a sanctimony to it, and 902 00:44:10,960 --> 00:44:12,919 Speaker 4: it's the same thing when it's on the right. Now, 903 00:44:13,239 --> 00:44:15,359 Speaker 4: Mark Cuban said something really dumb, by the way, from 904 00:44:15,440 --> 00:44:17,520 Speaker 4: the interior of what appeared to be his private jet. Well, 905 00:44:17,520 --> 00:44:20,800 Speaker 4: he was beaming into his view and assuring everybody that 906 00:44:20,880 --> 00:44:22,920 Speaker 4: Kamala Harris would be the best president for them. So 907 00:44:22,920 --> 00:44:25,280 Speaker 4: it's it's amusing all around, Like there are real, no 908 00:44:25,440 --> 00:44:28,239 Speaker 4: real winners here in this situation. But I do think 909 00:44:28,280 --> 00:44:30,800 Speaker 4: it is a little bit precious to defend Donald Trump 910 00:44:30,840 --> 00:44:33,880 Speaker 4: saying let's see Liz Cheney with a gun in her face. 911 00:44:34,640 --> 00:44:37,319 Speaker 2: And by the way, the reason because you know, if 912 00:44:37,480 --> 00:44:42,200 Speaker 2: Kamala or Tim Walls or Mark Cuban or whatever said 913 00:44:42,239 --> 00:44:46,480 Speaker 2: that about let's say Tulci Gabbard or Trump himself, there 914 00:44:46,520 --> 00:44:51,000 Speaker 2: would be quite a reaction, you know, coming coming from 915 00:44:51,000 --> 00:44:53,240 Speaker 2: that side with that level of like, you know, visceral, 916 00:44:53,960 --> 00:44:55,120 Speaker 2: violent type rhetoric. 917 00:44:55,280 --> 00:44:59,040 Speaker 1: I mean, again, though it's a warhawk comment, it's like, hey, 918 00:44:59,200 --> 00:45:01,640 Speaker 1: she doesn't work, that's a chicken hawk point, that's you know. 919 00:45:01,760 --> 00:45:04,680 Speaker 1: I mean, I remember saying shit like that about George W. Bush, 920 00:45:04,760 --> 00:45:08,279 Speaker 1: right like, and I think it was fine. Anyway, Look, 921 00:45:08,320 --> 00:45:09,120 Speaker 1: and what do you think. 922 00:45:09,560 --> 00:45:13,279 Speaker 5: I think it's not fair for people to want descriptions 923 00:45:13,280 --> 00:45:16,440 Speaker 5: of war to be more sanitized like that, because that's 924 00:45:16,440 --> 00:45:19,080 Speaker 5: basically what they're saying. They're saying, it's okay to call 925 00:45:19,160 --> 00:45:22,000 Speaker 5: somebody at chicken hawk, Uh, but you should leave it 926 00:45:22,040 --> 00:45:23,919 Speaker 5: at chicken hawk and say they should go to war. 927 00:45:24,000 --> 00:45:26,480 Speaker 5: But but when you get into the grizzly details of 928 00:45:26,480 --> 00:45:29,440 Speaker 5: what war is like, that's that's a little bit too much. 929 00:45:30,280 --> 00:45:33,520 Speaker 5: But that is the essence of the chicken hawk critique 930 00:45:33,520 --> 00:45:37,560 Speaker 5: that war is hell and that nobody who's ever experienced 931 00:45:37,640 --> 00:45:40,759 Speaker 5: the hell of it would think it is anything other 932 00:45:40,840 --> 00:45:43,200 Speaker 5: than hell. Now, some people who've experienced it still think 933 00:45:43,200 --> 00:45:45,440 Speaker 5: it's necessary to create the world that we want to 934 00:45:45,440 --> 00:45:48,360 Speaker 5: live in, et cetera. But the idea is that it 935 00:45:48,480 --> 00:45:51,520 Speaker 5: is hell, and it is grizzly, and people do have guns, 936 00:45:51,840 --> 00:45:53,880 Speaker 5: you know, pointed at their pointed at their face, and 937 00:45:53,920 --> 00:45:57,040 Speaker 5: bullets that you know, ripped through their skulls and their lives. 938 00:45:57,800 --> 00:46:00,839 Speaker 5: And that's that's seeing it change Seeing it and being 939 00:46:00,880 --> 00:46:03,400 Speaker 5: part of it changes you. So I think it's just 940 00:46:03,480 --> 00:46:06,919 Speaker 5: kind of unfair to say, like, you can call someone 941 00:46:06,960 --> 00:46:09,960 Speaker 5: a chicken hawk, but you can't like describe the grizzly 942 00:46:10,000 --> 00:46:12,040 Speaker 5: details of war because that that's the whole Yeah, well 943 00:46:12,520 --> 00:46:13,919 Speaker 5: at all is the whole. That's the whole point. 944 00:46:14,120 --> 00:46:16,160 Speaker 2: There's of course another element to this, which is that 945 00:46:16,200 --> 00:46:21,520 Speaker 2: Trump himself used bots birth to get down observing liberals. 946 00:46:22,239 --> 00:46:24,760 Speaker 1: Liberals, he's a draft dodger. 947 00:46:25,000 --> 00:46:28,040 Speaker 2: It's true. 948 00:46:28,080 --> 00:46:29,759 Speaker 1: It's a totally fine thing to say too. 949 00:46:30,200 --> 00:46:33,080 Speaker 4: Yeah, but his own his own Vietnam you guys all know. 950 00:46:33,080 --> 00:46:41,480 Speaker 5: Oh yeah, not getting STDs and thank you for So. 951 00:46:41,640 --> 00:46:44,040 Speaker 2: This is Liz Cheney's response. She says, this is how 952 00:46:44,080 --> 00:46:47,000 Speaker 2: dictators destroy free nations. They threaten those who speak against 953 00:46:47,040 --> 00:46:49,239 Speaker 2: them with death. We cannot entrust our country and our 954 00:46:49,239 --> 00:46:52,320 Speaker 2: freedom to a petty, vindictive, cruel, unstable man who wants 955 00:46:52,360 --> 00:46:54,960 Speaker 2: to be a tyrant. And so, you know, I think 956 00:46:54,960 --> 00:46:57,600 Speaker 2: Democrats feel, like, you know, while they're trying to lay 957 00:46:57,640 --> 00:47:01,160 Speaker 2: the fascist charge at his feet, and they're also trying 958 00:47:01,160 --> 00:47:03,640 Speaker 2: to change the topic from a news cycle about whether 959 00:47:03,719 --> 00:47:07,200 Speaker 2: or not Joe Biden said that Trump's supporters are quote 960 00:47:07,239 --> 00:47:11,160 Speaker 2: unquote garbage. I think they are happy to seize on 961 00:47:11,200 --> 00:47:14,759 Speaker 2: these comments as well, and as a reminder that of 962 00:47:15,000 --> 00:47:17,800 Speaker 2: some of the things that people really don't like about 963 00:47:18,080 --> 00:47:21,880 Speaker 2: Donald Trump. And you know, I've been thinking about this 964 00:47:21,880 --> 00:47:23,600 Speaker 2: hour because we've been going back and forth a little 965 00:47:23,640 --> 00:47:27,000 Speaker 2: bit on this. But part of what has made Trump 966 00:47:27,160 --> 00:47:30,040 Speaker 2: hold up so well in this election is that his 967 00:47:30,080 --> 00:47:32,560 Speaker 2: approval rating is significantly higher than he used to be, 968 00:47:33,200 --> 00:47:36,359 Speaker 2: and so he's still underwater in most polls, you know, 969 00:47:36,880 --> 00:47:39,880 Speaker 2: some amount, but not nearly where he used to be. 970 00:47:40,160 --> 00:47:43,680 Speaker 2: And so Democrats paid advertisements are by and large going 971 00:47:43,719 --> 00:47:45,920 Speaker 2: after like it's more of like a class war message. 972 00:47:45,920 --> 00:47:49,360 Speaker 2: But obviously Kamala Di the Ellipse speech, they amplified the 973 00:47:49,600 --> 00:47:51,799 Speaker 2: comments from John Kelly saying, Hey, I serve with this guy, 974 00:47:51,840 --> 00:47:54,160 Speaker 2: and he is a fascist. And so they feel like 975 00:47:54,280 --> 00:47:59,000 Speaker 2: this very visceral invocation of violent rhetoric kind of fuels 976 00:47:59,040 --> 00:48:02,640 Speaker 2: and serves to people of some of the elements of 977 00:48:02,680 --> 00:48:05,840 Speaker 2: him that they don't like and plays into their argument 978 00:48:05,840 --> 00:48:06,560 Speaker 2: about who he is. 979 00:48:06,640 --> 00:48:09,120 Speaker 1: Ultimately, Okay, I'll give it to them. I mean, because 980 00:48:09,120 --> 00:48:11,080 Speaker 1: they've got the media on their side. Basically, they are 981 00:48:11,080 --> 00:48:13,319 Speaker 1: literally saying on CNN all morning, they're like, oh, if 982 00:48:13,360 --> 00:48:15,200 Speaker 1: he wants to put Trump or Liz Cheney in a 983 00:48:15,200 --> 00:48:18,320 Speaker 1: firing squad, if I combined with that with the senior figure, 984 00:48:18,400 --> 00:48:20,560 Speaker 1: I will say yeah, that's a problem. Now again, I 985 00:48:20,560 --> 00:48:23,120 Speaker 1: don't think I think it's a dishonest presentation by CNN 986 00:48:23,400 --> 00:48:26,640 Speaker 1: and MSNBC based on that. But if the senior vote 987 00:48:26,680 --> 00:48:29,680 Speaker 1: is correct the numbers they're coming out right now. I mean, 988 00:48:29,719 --> 00:48:33,319 Speaker 1: just anecdotally, seniors who I've spoken to, they bring up 989 00:48:33,360 --> 00:48:35,839 Speaker 1: the wildest shit. You know, They'll be like, oh, did 990 00:48:35,840 --> 00:48:39,080 Speaker 1: you see Trump called you know, veteran suckers and loser. 991 00:48:39,120 --> 00:48:42,040 Speaker 1: I'm like, bro, what, Like this's a bullshit store. And 992 00:48:42,080 --> 00:48:43,480 Speaker 1: then but they don't want to hear it, like that's 993 00:48:43,480 --> 00:48:46,799 Speaker 1: the type of stuff that they take in or the 994 00:48:46,840 --> 00:48:48,560 Speaker 1: type of things that piss them off. More. What I'll 995 00:48:48,560 --> 00:48:50,279 Speaker 1: say is just so different than I think a lot 996 00:48:50,320 --> 00:48:53,200 Speaker 1: of people who watch our show. So I could see 997 00:48:53,520 --> 00:48:57,320 Speaker 1: this presentation by CNN and MSNBC and all that feeding 998 00:48:57,320 --> 00:49:00,440 Speaker 1: into that crystal because that is specifically the that is 999 00:49:00,480 --> 00:49:04,080 Speaker 1: the strategy of the Harris Cheney voter. I mean, like 1000 00:49:04,160 --> 00:49:08,160 Speaker 1: we see this for example in PA at that event. 1001 00:49:08,239 --> 00:49:10,279 Speaker 1: It was not an accident, Ryan, You'll know. It was 1002 00:49:10,280 --> 00:49:13,640 Speaker 1: in Malvern, one of the wealthiest, I believe, the wealthiest city, 1003 00:49:13,800 --> 00:49:17,360 Speaker 1: one of the wealthiest in the mainline suburban Philadelphia area. 1004 00:49:17,440 --> 00:49:19,160 Speaker 1: So I could see it, and that you know a 1005 00:49:19,160 --> 00:49:21,640 Speaker 1: lot of older voters there in that In that respect, 1006 00:49:21,960 --> 00:49:22,399 Speaker 1: it's true. 1007 00:49:22,440 --> 00:49:25,640 Speaker 2: Look, I think there are decorum voters absolutely, you know, 1008 00:49:25,840 --> 00:49:27,640 Speaker 2: not just older. I think I don't. I don't think 1009 00:49:27,719 --> 00:49:30,560 Speaker 2: just older. I think, you know, the suburban women vote 1010 00:49:30,560 --> 00:49:33,439 Speaker 2: that they're chasing very hard. Like I think there are 1011 00:49:33,920 --> 00:49:38,400 Speaker 2: who you know, respectless Cheney for whatever reason, whether they 1012 00:49:38,440 --> 00:49:40,680 Speaker 2: should or not as actually I don't even think that's 1013 00:49:40,680 --> 00:49:43,680 Speaker 2: a question. They shouldn't. But but yeah, I think there 1014 00:49:43,760 --> 00:49:47,080 Speaker 2: is a decorum voter out there who feels like these 1015 00:49:47,120 --> 00:49:50,080 Speaker 2: comments are too far, who don't want the visceral description 1016 00:49:50,320 --> 00:49:52,319 Speaker 2: of war, even though that should be put in our 1017 00:49:52,320 --> 00:49:54,520 Speaker 2: face more often. To your point, Ryan. 1018 00:49:54,400 --> 00:49:55,640 Speaker 5: Yeah, I'm in the minority on this. 1019 00:49:56,360 --> 00:49:57,960 Speaker 4: Yeah, I mean, I was just gonna say the reason 1020 00:49:58,000 --> 00:50:01,880 Speaker 4: that list Cheney is being deployed specifically for women voters 1021 00:50:01,920 --> 00:50:04,000 Speaker 4: and so the bro code thing, you know, you know, 1022 00:50:04,120 --> 00:50:06,880 Speaker 4: JD Vance on Joe Rogan yesterday, and I think soccer 1023 00:50:06,920 --> 00:50:09,640 Speaker 4: and I probably agree that he did a good job 1024 00:50:09,640 --> 00:50:11,120 Speaker 4: for a number of reasons, and that that will be 1025 00:50:11,160 --> 00:50:13,319 Speaker 4: helpful for a number of reasons. Although people probably don't 1026 00:50:13,360 --> 00:50:16,719 Speaker 4: elect vote to elect vice presidents. But this Cheney is 1027 00:50:16,719 --> 00:50:20,920 Speaker 4: specifically being used by Democrats to get this very small 1028 00:50:21,000 --> 00:50:25,960 Speaker 4: slice of the electorate pie, which is suburban swing women 1029 00:50:26,120 --> 00:50:29,319 Speaker 4: voters who might be persuaded by Liz Cheney to vote 1030 00:50:29,320 --> 00:50:30,240 Speaker 4: for Kamala Harris. 1031 00:50:30,239 --> 00:50:31,840 Speaker 3: And so it's not a huge group of people. 1032 00:50:32,160 --> 00:50:34,880 Speaker 4: But Trump then saying, yeah, you see what happens if 1033 00:50:34,920 --> 00:50:37,400 Speaker 4: she gets blasted in the face or you put a 1034 00:50:37,560 --> 00:50:40,320 Speaker 4: rifle in her fashion. Misrepresent the comments, but put a 1035 00:50:40,680 --> 00:50:43,959 Speaker 4: gun in her face. Those people are probably already leaning 1036 00:50:43,960 --> 00:50:48,200 Speaker 4: towards Kamala Harris. But it's definitely not helpful because the 1037 00:50:48,239 --> 00:50:50,759 Speaker 4: media is going to run with it all dancy, and 1038 00:50:50,760 --> 00:50:51,319 Speaker 4: then it will. 1039 00:50:51,320 --> 00:50:55,919 Speaker 2: Just not Probably the closing argument of the Republicans dreams. 1040 00:50:55,719 --> 00:50:57,120 Speaker 1: Yeah, I mean, we're not going to cover j D 1041 00:50:57,200 --> 00:50:59,279 Speaker 1: because we're out of time. But I mean, this is 1042 00:50:59,280 --> 00:51:01,120 Speaker 1: the problem with having somebody who just talks a lot 1043 00:51:01,280 --> 00:51:04,160 Speaker 1: like and you know, it's like, if you compare the appearances, 1044 00:51:04,160 --> 00:51:07,040 Speaker 1: I challenge I challenge people out there listen to Trump 1045 00:51:07,040 --> 00:51:10,040 Speaker 1: and JD on Rogan back to back, same interviewer, you know, like, 1046 00:51:10,120 --> 00:51:12,520 Speaker 1: same studio and all that, and you tell me who 1047 00:51:12,520 --> 00:51:14,920 Speaker 1: has a better command to the facts, a better articulation 1048 00:51:15,000 --> 00:51:18,320 Speaker 1: of the case, a better like cares about you like 1049 00:51:18,960 --> 00:51:21,600 Speaker 1: better on every single thing that people say that they like. 1050 00:51:21,800 --> 00:51:24,360 Speaker 1: But then also we know that, you know, Trump is 1051 00:51:24,360 --> 00:51:26,680 Speaker 1: the person who won the GOP primary, so that also 1052 00:51:26,719 --> 00:51:29,000 Speaker 1: tells us quite a bit about what those voters want 1053 00:51:29,040 --> 00:51:30,200 Speaker 1: from him. So there you go. 1054 00:51:30,520 --> 00:51:34,000 Speaker 2: Yeah, well, I think we'll probably maybe cover on Monday. Sorry, 1055 00:51:34,080 --> 00:51:36,320 Speaker 2: you and I can talk more about the JD Van's interview. 1056 00:51:36,400 --> 00:51:40,520 Speaker 2: But I mean, he has positioned himself very well within 1057 00:51:40,560 --> 00:51:43,280 Speaker 2: the Republican Party, you know. But now it all comes 1058 00:51:43,280 --> 00:51:47,319 Speaker 2: down to Trump. How this election goes. What does he win, 1059 00:51:47,400 --> 00:51:49,279 Speaker 2: does he lose? What does the stop this? What is 1060 00:51:49,360 --> 00:51:51,440 Speaker 2: the flavor of the stop the steal this time? If 1061 00:51:51,440 --> 00:51:53,719 Speaker 2: Trump does lose, does JD go along with it? Like 1062 00:51:53,760 --> 00:51:55,799 Speaker 2: there's still a lot of trip wires for him, but 1063 00:51:56,520 --> 00:51:59,319 Speaker 2: no doubt in terms of like the conservative base, he 1064 00:51:59,320 --> 00:52:01,000 Speaker 2: has done himself a lot of favors there. 1065 00:52:01,320 --> 00:52:04,640 Speaker 1: Very true. All right, that's a good tease, Ryan M. 1066 00:52:04,719 --> 00:52:07,520 Speaker 1: Thank you for joining us, guys. This was fun, good time. 1067 00:52:07,800 --> 00:52:09,960 Speaker 4: Like you guys opened up by saying it was a 1068 00:52:10,040 --> 00:52:11,960 Speaker 4: Friday points or points Friday, because that. 1069 00:52:11,880 --> 00:52:13,399 Speaker 2: What you do. Yeah, He's a Friday points. 1070 00:52:13,960 --> 00:52:19,560 Speaker 4: Are they breaking or are they countering? Nobody knows the Judge, 1071 00:52:19,760 --> 00:52:23,080 Speaker 4: we report you decide A. 1072 00:52:23,640 --> 00:52:25,280 Speaker 2: Sorry, have a good weekend y'all. Bye.