How One Polling Decision Is Leading to Two Distinct Stories of the Election

In one universe, Kamala Harris leads only narrowly in the national popular vote against Donald J. Trump, even as she holds a discernible edge in the Northern battlegrounds. The numbers look surprisingly similar to the 2022 midterm election.

In the other, Ms. Harris has a clear lead in the national vote, but the battlegrounds are very tight. It’s essentially a repeat of the 2020 election.

This divide is almost entirely explained by whether a pollster uses “weighting on recalled vote,” which means trying to account for how voters say they voted in the last election.

Here’s how it works. First, the pollster asks respondents whether they voted for Joe Biden or Mr. Trump in the last election. Then they use a statistical technique called weighting, in which pollsters give more or less “weight” to respondents from different demographic groups, such that each group represents its actual share of the population. In this case, the pollster weights the number of Biden ’20 or Trump ’20 voters to match the outcome of the last election.

This approach had long been considered a mistake. For reasons we’ll explain, pollsters have avoided it over the years. But they increasingly do it today, partly as a way to try to make sure they have enough Trump supporters after high-profile polling misfires in 2016 and 2020. The choice has become an important fault line among pollsters in this election, and it helps explain the whiplash that poll watchers are experiencing from day to day.

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