Famed Iowa Pollster Ann Selzer Announces Retirement Weeks After Her Staggering Miss in 2024 Election
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Trusted political pollster Ann Selzer announced she’s retiring from the Des Moines Register following a devastating misread of which way the political winds blew in Iowa at the end of the 2024 presidential election.
Selzer had predicted a win by Democratic presidential nominee Kamala Harris in the state, which turned out to be a full 16 points off the mark, according to CNN.
CNN reporter Liam Reilly wrote that Selzer’s final poll before election day, “delivered a bombshell result showing Vice President Kamala Harris leading Donald Trump 47-44% among likely voters in the state, raising speculation that Harris could mount a stunning upset. While other surveys had found Trump comfortably ahead of Harris in the state, Selzer’s poll raised Democrats’ hopes in the final days of the race and was widely reported by other outlets.”
Selzer wrote an op-ed for Sunday’s Des Moines Register, explaining that her exit from the Register was pre-planned, even before her mortifying misstep.
“Over a year ago I advised the Register I would not renew when my 2024 contract expired with the latest election poll as I transition to other ventures and opportunities,” Selzer wrote, continuing:
Would I have liked to make this announcement after a final poll aligned with Election Day results? Of course. It’s ironic that it’s just the opposite. I am proud of the work I’ve done for the Register, for the Detroit Free Press, for the Indianapolis Star, for Bloomberg News and for other public and private organizations interested in elections. They were great clients and were happy with my work.
There were shocking polls for each, to be sure. In the end, my findings looked good. Over 30 years of polling led to an A+ rating in Nate Silver’s analysis of pollsters’ track records of accuracy. I earned that rating in Silver’s first list, and my grade never dropped. Maybe that history of accuracy made the outlier position too comfortable.
Polling is a science of estimation, and science has a way of periodically humbling the scientist. So, I’m humbled, yet always willing to learn from unexpected findings.
