Key excerpt (But it's worth reading the full thing):
But the real value-add of the model is not just in calculating who’s ahead in the polling average. Rather, it’s in understanding the uncertainties in the data: how accurate polls are in practice, and how these errors are correlated between the states. The final margins on Tuesday were actually quite close to the polling averages in the swing states, though less so in blue states, as I’ll discuss in a moment. But this was more or less a textbook illustration of the normal-sized polling error that we frequently wrote about [paid only; basically says that the polling errors could be correlated be correlated between states]. When polls miss low on Trump in one key state, they probably also will in most or all of the others.
In fact, because polling errors are highly correlated between states — and because Trump was ahead in 5 of the 7 swing states anyway — a Trump sweep of the swing states was actually our most common scenario, occurring in 20 percent of simulations. Following the same logic, the second most common outcome, happening 14 percent of the time, was a Harris swing state sweep.6
[Interactive table]
Relatedly, the final Electoral College tally will be 312 electoral votes for Trump and 226 for Harris. And Trump @ 312 was by far the most common outcome in our simulations, occurring 6 percent of the time. In fact, Trump 312/Harris 226 is the huge spike you see in our electoral vote distribution chart:
[Interactive graph]
The difference between 20 percent (the share of times Trump won all 7 swing states) and 6 percent (his getting exactly 312 electoral votes) is because sometimes, Trump winning all the swing states was part of a complete landslide where he penetrated further into blue territory. Conditional on winning all 7 swing states, for instance, Trump had a 22 percent chance of also winning New Mexico, a 21 percent chance at Minnesota, 19 percent in New Hampshire, 16 percent in Maine, 11 percent in Nebraska’s 2nd Congressional District, and 10 percent in Virginia. Trump won more than 312 electoral votes in 16 percent of our simulations.
But on Tuesday, there weren’t any upsets in the other states. So not only did Trump win with exactly 312 electoral votes, he also won with the exact map that occurred most often in our simulations, counting all 50 states, the District of Columbia and the congressional districts in Nebraska and Maine.
I don't know of an intuitive test for whether a forecast of a non-repeating event was well-reasoned (see, also, the lively debate over the performance of prediction markets), but this is Silver's initial defense of his 50-50 forecast. I'm unconvinced - if the modal outcome of the model was the actual result of the election, does that vindicate its internal correlations, indict its confidence in its output, both, neither... ? But I don't think it's irreconcilable that the model's modal outcome being real vindicates its internal correlations AND that its certainty was limited by the quality of the available data, so this hasn't lowered my opinion of Silver, either.
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Notes -
Massive cope. His model got a few small things right, it got the big things people actually care about wrong. As usual he will hide behind the “things with <50% probability still happen!” defense, but this is just sophistry as it was never 50/50
He liked to tout how in 2016 he allowed the errors of different polls to be correlated, rather than being purely independent experiments. But at the end of the day all this does is increase the uncertainty and expand the error bars. If you keep doing this and allowing for more error here or there it tends your “prediction” towards throwing up its hands and saying “idk it’s a coin flip”, which is what happened to Nate and why he had to shut off his model so early on election night. He did plenty of bitching about “herding” of polls while he himself was herding towards coinflip. His big brag in 2016 was ultimately that he had herded towards 50/50 harder than anybody else.
In the prediction thread I called this for Trump with high confidence and said it was an “easy call” because there was ample evidence there for those with eyes to see. 2020 was an extremely close election and by every metric (polls, fundamentals, vibes, registration, mail in voting) Trump was better positioned this year than he was then. Nate can call everything a coin flip and cope all he wants but his credibility is shot
A child, when introduced to the concept of probability, gives equal weight to the possible outcomes. Two choices means 50/50 (a coin flip.) A pollster that isn't better than a coin flip is useless. You might as well ask a child. (I believe the children's election - 52/48 in favor of Harris - being +2 D, while being wrong, was more accurate than any of the left-leaning pollsters could muster.)
It's not useless if it's actually 50-50.
If it was actually 50-50, why did he take down his real time election result projection?
He admitted well before E-day that anything more than a very crude real time projection needed far more resources than he had - he borderline told people to just go and look at the NYT needle, and probably only did his thing because it wasn't known until the last minute whether the needle would be active.
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