As promised in my first cut after the election, a more detailed walk by the numbers through the 2014 Senate and Governors race polling and my posts on the subject to illustrate that the election unfolded pretty much along the lines I projected on September 15, when I wrote that “[i]f…historical patterns hold in 2014, we would…expect Republicans to win all the races in which they currently lead plus two to four races in which they are currently behind, netting a gain of 8 to 10 Senate seats.”
This was not a consensus position of the models projecting the Senate races at the time; Sam Wang, Ph.D. wrote on September 9 that “the probability that Democrats and Independents will control 50 or more seats is 70%” and described a 9-seat GOP pickup as “a clear outlier event.” On September 16, the Huffington Post model had a 53% chance of the Democrats keeping the Senate, while the Daily Kos model on September 15 had the Democrats with a 54% chance of retaining their Senate majority. Nate Cohn at the New York Times on September 15 gave the GOP just a 53% chance of adding as many as 6 seats, with Republicans having just a 35% chance of winning in Iowa, 18% in Colorado and 18% in North Carolina, and a 56% chance of winning in Alaska. The Washington Post on September 14 had the Democrats favored in Alaska, with a 92% chance of winning Colorado and a 92% chance of winning North Carolina. Even Nate Silver and Harry Enten’s FiveThirtyEight Senate forecast, which was more optimistic than some of the others for Republicans at the time, gave the GOP just a 53% chance of making it to a 6-seat gain as of September 16.
In this case, at least, my reading of history was right, and was a better predictor of the trajectory of the race than the models or the contemporaneous polls they were based on. That won’t always be true; it wasn’t in the 2012 Presidential race. It may or may not prove true in the 2016 Presidential race, where the historical trends overwhelmingly favor Republicans. But after 2012 we were greeted with an onslaught of triumphalism for polls, poll averages and poll models, and what 2014 illustrates is not only that – as …read more