I got schmuchtzed once by this (#1602534) recently, and I'm definitely at risk of relying overly on Nate Silver's very fancy-schmancy models. We shall see if the Predyx degenerates beat me (#1606098, #1606435)

here's one comparison between public/traditional polls and the betting markets

To the untrained eye, prediction markets suggest the winner of the Minnesota Senate race is almost guaranteed: Kalshi odds give Democrat Peggy Flanagan a 90% chance of winning. Looking at the polls, the race might seem closer. Averages from VoteHub have Flanagan leading by just under six percentage points, a solid but not safe margin.

"Those numbers may seem contradictory. In fact, they’re really just two ways to capture a similar picture."

Despite their “truth machine” marketing, prediction markets have their limitations, just like polls. But part of the backlash against them is rooted in misguided assumptions about what they tell us — and what they don’t.

uh-hu. #1477436, #1493892, #1433466

The numbers are sort of the same thing, but "probability of victory" is not the same as "margin of victory"

While a 75-25 split in the prediction markets can look like a massive blowout next to a 5-point polling margin, those numbers are in fact largely aligned. That’s because they measure different things. A poll margin is the size of a candidate’s lead, while market odds are the chance of that candidate winning on Election Day. Compare the two across key midterm races, and the polls reflect most of where the markets land.

THREE common things that move Prediction markets but not polls:

• polls are frozen in time, a snapshot of sentiment among their respondent sample (usually) a few weeks back
• Prediction markets react in real time ("A common argument in favor of prediction markets is that they can react to shifts in voter sentiment instantaneously, while polls are inherently on a lag.")
• traders might place trades based off insider/privileged information (LOL, yea; duh #1554186)
• "Some might just be going off of vibes" -- uhuh

Nice summary:

A poll estimates who leads and to what degree at a moment in time, with uncertainty reflected in a margin of error. A prediction market translates financial wagers into an estimate of a candidate’s likelihood of winning, with uncertainty baked into the odds themselves.

...fantastic analogy:

At the recent prediction market conference, veteran political journalist Chuck Todd expressed frustration about the general public’s difficulty making this distinction. “Would you get in an airplane that only had an 80% chance of landing?” he said. “Then suddenly people start thinking about probability differently.”

Russian Roulette has better odds than that. (FUCK, what's my Kelly-sized bet for that trade?! #1606435)

Errors go both ways:

in 2016, almost every major model favored Hillary Clinton over Donald Trump. The New York Times’ Upshot model gave Clinton an 85% chance of winning going into Election Day, but swung sharply toward Trump as returns rolled in. [...] FiveThirtyEight was more cautious than most, but also underestimated Trump at a 29% chance.

...and there is overlap/feedback, too:

Polls are still one of the most important inputs for prediction markets, Sethi said. Traders follow their results closely as they place their wagers. On the flip side, a growing number of models factor prediction markets into their forecasts, creating a circular relationship that makes it tricky to draw a clear line between one and the other.

"A recent study from the Brennan Center for Justice found that prediction market odds impact voters’ views of the electoral landscape."

archive: https://archive.md/nd4St