Funny thing about pseudoscientific metrics: they will inevitably fail
Nate Silver, 2012: "no precedents..for a candidate losing with two or three-point lead"
FiveThirtyEight, 2023 "Races within 3 points in the polls are little better than tossups...been shouting it for years"
Which is it? Those two observations are incompatible.
Their approach, because it's not scientific, can't explain sh*t.
*Mine literally predicts this is what we should see*
Gray = L
Black = W
Notice anything?
👇
If your response is “lol holy shit” you'd be in good company.
Notice what happens when a candidate's poll average - regardless of their “lead” clears 48%. And 49%. And 50%.
If “spread” were a valid metric - if it was sufficient to predict election outcomes (which the worldwide consensus of experts say it is!) then this observation would not exist.
Richard Feynman once said: if it disagrees with observation, then it's wrong.
And this “spread” obsession is wrong. QED
The question isn't IF it is wrong, it's what do we do about it?
I outline those steps in my book, which (insert Bernie Sanders meme here) I am once again asking you to preorder, please.
The publisher has requested that I not share too much content directly from the book, so I'll leave you with these posts from 2020:
But you know.
The new Iowa poll reminds me of what you said about Tim Ryan in Ohio; Kamala’s ceiling is probably 47% but that isn’t enough to win. There are a lot of good underlying numbers in the poll that help confirm trends in other polls, but that doesn’t mean she’s ahead in Iowa. Am I right?