Hello friends, we’re glad to have you with us! Today we’re going to look at:

To kick things off…

A bunch of House and Senate members left DC Thursday afternoon, jetting off to the Munich Security Conference, so, it’s going to be particularly difficult -- if not impossible -- for there to be a last-minute vote to save the day.

That said, lawmakers in the House and Senate are on notice to return if a deal seems to be on the horizon, but that probably won’t happen before midnight.

Plus, there’s a chance that the shutdown might drag on. With the exception of Senator John Fetterman, the Ds are staying united. And on Wednesday (the 11th), The White House sent the text of their offer for DHS funding, which the Ds rejected. And with folks out of town, it’ll likely be a few days before any progress is made.

So, why then, you might be wondering, are prices on Polymarket and Kalshi for “Government shutdown tomorrow?” and “Government shutdown on Saturday?” so divergent?

Well, as we’ve discussed before, it comes down to the rules and a statement by Scott Kupor, the director of the Office of Personnel Management:

And because of the difference in rules of resolution for Polymarket and Kalshi, each market responded differently.

On Polymarket, the rules state:

With the added additional context:

Kalshi’s rules state that:

In other words, Kalshi doesn’t simply come down to the OPM website, but Polymarket does. This is notable, because there is a real chance that a part of the government will shutdown this evening, and this occurs whether or not the OPM website is updated. If one of the intentions of prediction markets is to accurately reflect what will occur, then the rules of resolution need to be correctly written. Because, right now, on Kalshi people are taking positions on whether or not there will be a shutdown, and on Polymarket people are taking positions on whether a website will be updated. Those are not the same thing.

AOC spoke today at the Munich Security Conference, offering a “working class” perspective on U.S. foreign policy.

The news that AOC would speak at the conference was first widely reported around February 6, 2026, when the New York Times published the profile "Alexandria Ocasio-Cortez Steps Onto a Wider Stage."

Although she still trails Newsom on Polymarket -- who’s at 27% -- there was a small bump in the odds of AOC being the Democratic Presidential nominee in 2028 after the article broke. And professional and amateur Twitter pundits are hinting at this being a test for her on a more global stage.

Beyond AOC, Newsom, Whitmer, and Gallego -- other potential nominees -- are all also speaking at the conference.

And, even though it’s still early, they all maintain a comfortable lead over Mr. Beast, The Rock, and Hunter Biden:

I wouldn’t expect too much movement in these markets until the midterms are done, but keep your eyes out for signals in the coming months to help build your model. And if you’re not doing that, we’ll be doing some of that for you.

Below is an excerpt from our recent conversation with top Kalshi Trader Gaetan Dugas…

You talk a lot about how to build models for markets, and about really data-backed theses for these things and how to find edge with those models. Can you go into a little bit more detail about what that actually means from a practical perspective?

Sure.

Like, if you have an edge, how do you build to get that?

Sure. So, I'll walk through Spotify as an example since it's pretty easy compared to a lot of the other ones and the data is so easily accessible.

So with Spotify, they've got their whole daily history of streams of the Top 200 for global and in every country, going back to like 2017. So, you've got access to this entire database of streams. And you can pull the data and start analyzing it, and you'll start to recognize patterns.

So, there are patterns that happen when a song is released. Friday is typically the biggest day. And then Saturday, it will drop by a certain percentage. Sunday it will drop another percentage. On Monday it usually bounces back. On Tuesday it bounces back a little more. And then from there, it does a slow decay. So you can spot that type of data. And you can look for comparable songs in the history to new ones that are coming out and kind of map out what and how you think it will do.

So, when it comes to modeling, I've got different models for different types of songs. A song like "Please, Please, Please" by Sabrina Carpenter or "we can't be friends" by Ariana Grande. Those are songs that did very well; they didn't drop very much.

And then there are songs that kind of flop, like "Aperture" by Harry Styles was a recent one where it dropped a ton.

And then there's kind of the average one.

So, basically what I do is I try and come up with a range of how songs will perform, and then once I track it a couple days, then I can get a pretty good idea of which of the categories it falls into. And based on that data, I can start projecting how it's gonna do the rest of the week.

Does that make sense as an example?

Yes, I can kind of see the spreadsheet for that too, right? You sort of slot it in. When you talk about building a model, sometimes people build more of a mental model, but it seems like for you it's very numbers-based. I imagine you sort of run these songs through the Excel sheet?

Yeah, so I'll run the numbers in Excel and get a high, medium, and low range for what the streams will be throughout the week, and then I just narrow that down as more data comes in.

So, that's a fairly simple one, but for something like Rotten Tomatoes, that's actually about six models that run at different points throughout the week because the amount of data that you get is different. So, before the social media embargo lift, all you can really find is random people rating it on Letterboxd, IMDb, or sometimes Google, or pulling reactions from Twitter. But as you get closer to release, you get more and more data. And then once reviews come in, you need to account for all the reviews that you can find on websites that haven't been published yet and how likely they are to be posted to Rotten Tomatoes in time. So, I take all that information and each step of the way has a different model that applies to it.

That's very cool. I've seen you talk too, though, that sometimes you do bets for fun, kind of based on gut feel. I'm wondering if the two betting styles ever overlap. Like, you have the model, but every now and again you're like, "No, this song's a banger. I bet it actually does better than the model says."

Yeah. So, today's Thursday and at midnight Eastern they're going to drop some new songs, like the J. Cole album's gonna drop. And if something big is coming up I'll usually stay up until midnight and just listen to them. And at that point, you don't really have any data on that specific song, so it really is a matter of listening to it and seeing if it's going to be any good or perform well. But for something like J. Cole, where it's an album people have been waiting for, I'll go back and compare how he did on his last studio album, which I think was in 2021. He did a mixtape release in 2024, as well. So I'll see how he did in the past and then consider if his popularity has dropped or if it's risen. I think it's probably dropped a little, but not enough that he won't get number one for the day tomorrow. So, it's a little bit of gut and a little bit of research on how that particular artist has done.

I like that a lot. A mixture of hard data and cultural analysis.

Yeah, for sure.

But yeah, I think that's a good overview of what it means to build a model. Let's say somebody's just starting out today. They've probably lost some money gambling on sports or whatever and they're trying to get more sophisticated. Where do you think the highest upside is these days? Where are the most inefficient markets? Where could somebody actually go out and find edge, in your mind?

Read the full interview here.

Polymarket has a market on “Measles cases in U.S. by February 28?” We’ve written on measles markets in the past. This is one to watch for a late-month resolution. Currently the odds that there will be at least 1000 this month are at 97%, which seems pretty reasonable given we’re currently at 910 cases this year today.

Oscars markets -- best picture, best actor, best actress, etc. -- will resolve on March 15, 2026. These markets often have lower liquidity than some of more headline-grabbing markets in politics and the like, but many might be worth your attention. One Battle After Another leads “best picture” with odd of 75%. And Jessie Buckley (89%) and Timothée Chalamet (79%) are favorites for actress and actor, respectively.

Coming off the government shutdown “When will DHS receive full-year funding?” is another one to watch. We find this one particularly interesting because if you’ve been following these markets for the past few weeks, you can take a lot of your research and insights and apply them here. Expect more here.