

It’s also important to point out that the range of possible seat gains in our forecasts was wide. In fact, it’s quite close to the mean number of seats that our various forecasts projected: Classic had Democrats picking up an average of 39 seats, Lite had 38 seats and Deluxe had 36 seats.

That’s a big number, but it’s actually not that much of a surprise. If that’s the case, Democrats will wind up with a net gain of 40 House seats. I’m going to assume for the rest of this article that Cox and Harris will indeed prevail in their respective races. Two House races remain uncalled as of this writing: California 21, where Democrat TJ Cox has pulled ahead, overcoming a big deficit on election night, and North Carolina 9, where Republican Mark Harris leads but the vote hasn’t been certified because of possible fraud in absentee ballots. Here’s more detail on the numbers in that chart: Classic is the “default” forecast, but we made pretty extensive use of all three versions over the course of our election coverage, so it’s fair to evaluate and critique them all.
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Keep in mind that there are three different versions of our forecast: Lite (which uses local and national polls only, making extrapolations in districts that don’t have polling based on districts that do have polling), Classic (which blends the polls with other data such as fundraising numbers) and Deluxe (which adds expert ratings to the Classic forecasts). We’ll get back to that theme in a moment.įirst, though, I just want to look at our topline numbers for the House, the Senate and governorships. This year was sort of the opposite: terrific from an accuracy perspective, but actually somewhat problematic from a calibration perspective because not enough underdogs won. So 2016 was good from a calibration perspective but middling from an accuracy (calling races correctly) perspective. But Trump did win several key states (Wisconsin, Michigan, Pennsylvania) in which he was an underdog, and he was an underdog in the Electoral College overall. I say that because we’ve frequently argued that our 2016 forecasts did a good job because they gave President Trump a considerably higher chance than the conventional wisdom did and because our probabilities were well-calibrated. In the long run, we want our forecasts to be accurate, but we also want our probabilities to be well-calibrated, meaning that, for instance, 80 percent favorites win about 80 percent of the time. This year was one of the better years - maybe the best we’ve ever had - but it’s still just one year. Because errors are correlated, we’re going to have better years and worse ones in terms of “calling” races correctly. Not only are our forecasts for individual races probabilistic, but our model assumes that the errors in the forecasts are correlated across races - that is, if one party’s chances were overrated in one race, they’d likely be overrated in many or all races. So let’s go through how our forecast, in particular, performed: I’ll brag about what it got right, along with suggesting some areas where - despite our good top-line numbers - there’s potentially room to improve in 2020.īut before I do that, I want to remind you that our forecasts are probabilistic. Polls and forecasts, including FiveThirtyEight’s forecast, were highly accurate and did about as well as you could expect. Instead, the election we wound up with was one where everything was quite … dare I say it? … predictable. Sure, it was unlikely, but what if Republicans won the popular vote for the House, as a Rasmussen Reports poll conducted just before the election suggested? Or what if Democrats won it by about 15 percentage points, as a Los Angeles Times poll had it? What if polls were just so screwed up that there were a ton of upsets in both directions? Over the years, Sean and I have learned to stare into the abyss and play out various “unthinkable” scenarios in our head. 5, the night before last month’s midterms, I got dinner with Sean Trende from RealClearPolitics.
