> Helmut Norpoth aka the Primary Model (primarymodel.com).That website's subtitle is "forecasting presidential elections since 1912". What does that even mean? Is Helmut 120+ years old? Or does he mean "fitting" instead of "forecasting"?
BTW: Helmut's model was jut wrong in 2016. Its prediction -- the actual statistical forecast the model actually made -- was that Trump had an 87%-chance of winning the popular vote. That was its forecast -- of the popular vote, not of the electoral college. Its electoral college forecast was then conditional on its popular vote forecast. The actual core quantitative prediction the model made was in fact wrong. Literally, the primary model got the right result by accident.
Of course, Helmut retroactively claims that because he got the EC right it doesn't matter. Which would be somewhat reasonable if:
a) that's how the model actually worked (it isn't -- the model's core prediction was about the popular vote and it was wrong), or
b) he didn't make exactly the OPPOSITE corrective about his model's performance whenever he talks about 2000, where he always stresses that it at least got the popular vote right even though it got the EC wrong.
Why does this matter?
First, Helmut's model isn't as good as he claims it is even on historical data. He moves the goalposts from year to year.
Second, Models that get the right answer for the wrong reason are usually over-fit to historical data. They should be taken with a grain of salt in years where their core feature set might behave differently that in previous years. (E.g., a year in which the model's main predictive feature -- primary results -- were cut short due to a 1-in-100-year pandemic).
Anyways, there are a lot of other contrarian/first-principles models that back-test well and predict a (D) win. Of course, no one cares about those this year. But they might next time around if the polling-based methodologies predict an (R) win.
FWIW, I tend to agree that the polling aggregation models are "meh" and should have way more uncertainty than they currently do. Mostly because a) I think turnout is much more correlated between swing states than those models typically assume and b) I don't think aggregating polls is actually all that useful.
Basically, everyone in election polling is making educated guesses and everyone in election polling over-sells their certainty.
Also, re: betting markets. Through a combination of bets on state-level results, you can construct positions that pay out if EITHER Democrats win the popular vote OR Republicans win the electoral college. The odds of Republicans winning the popular vote but losing the college are basically zero. I guess my point is just that there are lots of idiots betting on elections and you can trivially construct (small) sure-to-win positions.