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12) That might make up something like 5% difference between them, but I doubt it's 13% vs 33%. And note--prediction markets get to read 538; 538 doesn't model based on FTX. Prediction markets are at 33% *after adjusting down* for 538's information. Otherwise they might be 40%.

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13) So what's really going on here? My best guess, roughly: There are known unknowns; models capture those. There are unknown unknowns; models try to model the distribution of those.

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14) And then there are intuitions -- something like "yeah, but COVID". The unknown unknown unknowns -- the model's uncertainty about how many unknown unknowns are likely to happen this year, relative to others. Those were high in 2016. They're way higher now.

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15) What are the odds that mail-in voting turns out very different than expected in an election blowing through records in mail-in voting? What are the odds there's $5b of Super PAC spending coming on November 2nd? What are the odds COVID delays the election in some states?

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16) 2012 was a pretty 'standard', boring election. Incumbent with average popularity, slightly unpopular challenger, decent economy. 2016 was weird: a candidate unlike what we'd seen before. Almost everyone was off by a bunch there--a few % of the popular vote.

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17) How much wackier is 2020 than 2016? IDK -- probably a lot more. I sort of think that volatility here should be something like 9x the baseline and 3x 2016. So, idk, I think my model would be a fair bit less certain than 538 etc.'s, in ways that aren't reflected by polling.

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18) And then, take a step back. How surprised would you be if Trump won--if it turns out polls were off by 5%, Trump lost popular vote but won Electoral college? IDK -- I wouldn't be shocked. And if you say the odds Trump wins are 10%--

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19) idk, I guess I feel like the odds all these models are just kinda busted and this is a wacky election are greater than 10%. It can be dangerous to trust intuition above numbers, and so I'm definitely fading to the models here. But 10% kind of fails my smell test.

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20) But, who knows, I might be wrong. I guess we'll find out.

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21) to be clear here, I think Biden is the heavy favorite -- and *very* heavy favorite for the popular vote. I think the odds Trump wins aren't that much higher than the odds he loses but tries to say he won. But I think both of those are above 10%.

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22) Both sides are doubling down, e.g. twitter.com/NateSilver538/ If

is right that

@realDonaldTrump

's COVID strategy sucks, then Trump very likely loses. But the public secretly liking it more than they let on is an example of a possible systematic bias.

Quote Tweet

Trump doubling down on a series of extremely unpopular messages about COVID—after having caught COVID, and at a time when COVID cases are rising again nationally—is about the worst possible closing pitch, and one has to wonder about how downballot GOP candidates feel about it.

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1:09 PM · Oct 13, 2020Twitter Web App

Adam Cochran (adamscochran.eth)

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1/2 As a data science guy, I frequently cringe at election odds reporting. Most polls reflect the popular vote, and fail to capture turn out, suppression risk, vote friction (who believes strongly enough to stand in line for 3 hours) &

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Adam Cochran (adamscochran.eth)

Replying to

2/2 most importantly if the voters are new voters or switch voters vs just the reporting base. This election comes down to moderates, independents, and former Republicans switching + who wants it the most. Polls need that quantify voter determination to overcome friction.

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Does ftx have a gambling license...!?

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thank you for your insights SBF

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and

I don't think systematic lying in polls should be underestimated either. Trump supporters have a clear incentive to skew the data to further blame "fake news" while praising their own sources. It feels like the polls will be more skewed than ever for this election.

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i am not afraid of the elections but rather of the people's and markets reaction if covid worsens

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My guess about the discrepancy is that prediction market pricing is influenced by a relatively small number of users who each have siloed media consumption that skews their perception of election odds. I'd trust 538's prediction model more

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and

@realDonaldTrump

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