So why did our model - using basically the same data as everyone else - show such a different result? We’ve covered this question before, but it’s interesting to do so in light of the actual election results. And betting markets put Trump’s chances at just 18 percent at midnight on Tuesday, when Dixville Notch, New Hampshire, cast its votes. 1 By comparison, other models tracked by The New York Times put Trump’s odds at: 15 percent, 8 percent, 2 percent and less than 1 percent. Our final forecast, issued early Tuesday evening, had Trump with a 29 percent chance of winning the Electoral College. For most of the presidential campaign, FiveThirtyEight’s forecast gave Trump much better odds than other polling-based models. And we took weeks of abuse from people who thought we overrated Trump’s chances. If polling were perfect, you wouldn’t need to do this. But one of the reasons to build a model - perhaps the most important reason - is to measure uncertainty and to account for risk. It’s tricky to decide what tone to take in an article like this one - after all, we had Hillary Clinton favored. This isn’t just a case of hindsight bias. Given the historical accuracy of polling and where each candidate’s support was distributed, the polls showed a race that was both fairly close and highly uncertain. But it shouldn’t have been that much of a surprise based on the polls - at least if you were reading FiveThirtyEight. Based on what most of us would have thought possible a year or two ago, the election of Donald Trump was one of the most shocking events in American political history.
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