Suddenly, Biden leads in Iowa!

Differentiator 1: We adjust state polls based on trends in national polls

A hallmark of our general election forecasts, dating all the way back to our first versions in 2008, is what we call a “trend line adjustment.” Basically, in states that haven’t been polled recently, we make inferences about what’s going on there using national polls or polls from other states that have been surveyed recently. If President Trump gained 3 percentage points in national polls, for instance, but North Carolina hadn’t been polled recently, you could probably infer that he’d also gained 3 points, or thereabouts, in North Carolina.

We apply this adjustment for a good reason: Trend-line-adjusted averages have been quite a bit more accurate, historically. That is, once someone does get around to polling North Carolina, it usually turns out that Trump did gain about 3 points. Trend-line-adjusted averages have also been insightful so far this cycle — they anticipated, for instance, that Sen. Elizabeth Warren’s numbers would decline in state polls in November and early December once she began to slump in national polls.

So we’re now applying a slightly simplified version1 of the trend line adjustment to the primaries. (Note that all polling averages you see on our state polling pages reflect this trend line adjustment.) Say that Sen. Cory Booker has surged by 5 points in national polls, for instance, but we haven’t seen a recent poll in Nevada. Our average would assume that he’d also improved his standing by 5 points in Nevada, other things held equal.

There are a few complications: For instance, the adjustment is nonlinear, which can have meaningful effects if a candidate is polling in the low single digits. But in short, the trend line adjustment can have fairly large effects if a state hasn’t been polled much recently. It doesn’t affect our numbers much, conversely, if there are a lot of recent, high-quality polls from that state.