The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

by Nate Silver

Wasserman’s knowledge of the nooks and crannies of political geography can make him seem like a local, and Kapanke was happy to talk shop about the intricacies of his district—just how many voters he needed to win in La Crosse to make up for the ones he’d lose in Eau Claire. But he stumbled over a series of questions on allegations that he had used contributions from lobbyists to buy a new set of lights for the Loggers’ ballpark.40 It was small-bore stuff; it wasn’t like Kapanke had been accused of cheating on his wife or his taxes. But it was enough to dissuade Wasserman from changing the rating.41 Indeed, Kapanke lost his election that November by about 9,500 votes, even though Republicans won their races throughout most of the similar districts in the Midwest. This is, in fact, the more common occurrence; Wasserman will usually maintain the same rating after the interview. As hard as he works to glean new information from the candidates, it is often not important enough to override his prior take on the race. Wasserman’s approach works because he is capable of evaluating this information without becoming dazzled by the candidate sitting in front of him.