Election Forecasts Try to Go Beyond the Polls. Are They Helping?

In 2008, Nate Silver’s election forecast model was so novel — and accurate — that it landed him on Time magazine’s list of the 100 most influential people the next year.

These days, election forecasts — which use data including polling, historical results and economic factors to predict the likelihood of an election outcome — are much more commonplace. There were at least 10 major forecasters this election cycle, though you could also find forecasts produced by high school statistics classes and Reddit users. (The New York Times has not published a pre-election forecast since 2016.)

While election polling has been around for more than a century, election forecasts have come to the forefront only in the past decade and a half. And while polls are intended to provide a snapshot in time, taking the pulse of how Americans are feeling about a race, forecasts go a step further, analyzing the polling and other data to make a prediction about who is most likely to win, and how likely.

But this year, with the polls already showing a razor-thin presidential race, the forecasts often indicated that the race was tied nationally or in swing states, or they gave one candidate or the other only a slight edge.

These results raise the question: What is the value of these election forecasts? Proponents say they help synthesize the available information and that more data is better than less. They also argue that the forecasts this year performed well, generally — capturing the uncertainty of a close race, while holding out for the possibility that Donald J. Trump could sweep the swing states, as he did.