The real caveat is that 538 was a Monte Carlo model, and is only as good as its inputs. "Here's what the current spread in polling numbers is *given our model and the current polling and their reported uncertainties.*" Polling uncertainties are themselves computed under certain models, and those models are subject to errors. I don't think 538 hid this, but it's a difficult caveat for people to reason about because the sorts of modeling errors that have the most influence usually represent "unknown unknowns".

That's a core mechanic in games like Dispatch.

People don't like seeing a 95% chance of winning and then losing. The game tweaks the odds, so certain thresholds become gimmes (something like "if the displayed odds are better than 75%, treat them as 100%").

> Discussion of stats models is always complicated by the fact that a lot of people will read "30%" as a "no" prediction and claim your model is wrong if the thing happens.

I've even heard things like "70% chance of Hillary winning means she gets 70% of the votes!" (and tangentially, my far-too-long argument with someone on Reddit who insisted "there is no way in hell 50% of the people in this town make above the median income"...)

> it turned out that predicting elections is still very hard

So maybe we shouldn't be doing it. The value of predicting an election in the large out in public seems kind of dubious, and it's more like gambling than actually being useful. A candidate only runs, and continues running, if they think they can win. All predictions like these do is confuse voters leading up to election day and while they are voting. It keep candidates from making strong cases for their platform, keeps the voters from listening to the candidates' platforms, and encourages team-based partisan politics.

> FiveThirtyEight performed only slightly better than what you could find in any other reputable newspaper

FiveThirtyEight gave Trump double the odds of the next highest reputable prediction, which was The New York Times Upshot (15%). Princeton Election Consortium gave Trump less than 1%.

That is not "only slightly better" to anyone who's statistically literate.

A FiveThirtyEight reader in 2016 was significantly better calibrated regarding Clinton’s chances than a reader of other reputable newspapers.

538 was never about magically making polls more reliable, and only people that don't understand what polls are could think that (caveat: lots of people don't understand how polls work).

538 was about analyzing and communicating the information from those polls in an easily accessible form. If you came to the site for that, you weren't mad that they "predicted poorly something that was impossible to predict from the data sources they used" ... you were just mad at Trump for winning (despite polls suggesting otherwise).

Polls became much less interesting as an Entertainment category once we all had experience with how unreliable they are.

Yeah, Nate has talked a number of times about polling errors being correlated across states. In fact that's probably one of the most common mistakes models can make, treating correlated inputs as independent. There's a long history of that mistake in financial markets as well.

In 2024 the single most likely outcome his model had was trump winning all 7 swing states. The second most likely was Harris winning all 7.

They had him at 30% at a time when most reputable media had him in single digits at best. You might not remember now, but the result of that election was a real shock.

Everyone said that except for 538. That's why 538 was worth reading.

I find it interesting to blame it on the democrats. We ended up with him because enough people voted for him.

do you think nate silver is part of the problem or part of the solution?

the turnout-of-demographic-groups-based election model is surely the underlying intelligence failure here.

Democrats will not let people choose candidates because that may be too dangerous for their interests. We'll never get good candidates as long as the current leadership is in control.

Silver claimed that his model was better because it predicted a high correlation between PA/MI/WI.

A model that predicts a 30% chance of winning the election will be wrong 1 out of 3 times, which is not quite a coin flip but close enough.

Nate Silver is not a magician! He can't magically make polls reliable!

All he (or anyone) can do is interpret or analyse poll results, and then surface their findings in a way a larger audience can understand. 538 did that better than any other poll analyst ... but they all got it wrong because the polls themselves were faulty.

TLDR; You can't get water from a stone, and no one (not even Nate Silver) can get perfectly accurate predictions from (inherently flawed) polls!

So use a coin flip to predict the weather then

> But if that is the case (and it seems to be), then a coin flip is better than their models.

If a coin flip is the necessary mental model to remind you both things can happen, then sure.

People just love horse race coverage. Silver gave us the most accurate horse race coverage. Maybe the lesson is stop following horse race coverage.

But most people went back to the tea leave readers. That way when the election was over, it can justifiably be the charlatan's fault that viewers got over-invested in their predictive capabilities.

I don’t disagree, I think the tea leaf reading is ultimately pretty futile.

But at the same time I do think it’s valid to say it’s more than a coin flip. The polling data over the election cycle showed that Trump had a smaller but still legitimate chance of winning. The data was different in 2020, when he lost.

It implies a close race or a strong reason to believe there's some sort of systemic polling miss, and if it's a blowout you still look pretty bad. Especially if you don't have some kind of good explanation for the miss/you keep making those kinds of misses frequently.

Also there's more going in those forecasts besides just the "% chance to win". There's expected results in terms of %'s of the vote for the candidates, and that's what people tend to focus on for actually analyzing your performance and credibility after the fact.

You getting the outcome correct but being off by 20 points on the margin is a much worse performance than you getting the outcome wrong but being within 0.5 points of the margin. (ex: Results are 49.75/50.25, you predicted 30/70, another outlet predicted 50.25/49.75).

538 claimed that they post-checked thousands of elections and their percentages were pretty close. (E.g., 30% chances happened about 30% of the time, million to one chances happened every single time)

Of course there's more than that. Predicting higher uncertainty than warranted would be a different failure in the model. But that didn't really happen in that election.

> I know I'm being super conspiratorial here but why wouldn't all forecasters predict just between 30% - 70%? That way if they're "right" they can take the credit for it and if they're wrong they can say "well, we weren't that wrong". That's probably what I'd do anyway...

For anyone making many predictions, you can analyze the outcomes to see how accurate those percentages are.

For anyone making few predictions, you should never trust their track record even if it's technically perfect.

You're completely right, although I believe this number was not decided personally. They just happened to pick algorithms that have this "nice" property because it will lead to the same result.