Statistician Nate Silver predicts the Oscars
Nate Silver Predicts the Winners of the 2009 Oscars -- New York Magazine
First Baseball then Politics and now the Oscars? Is nothing sacred Silver?
His picks are:
Supporting actor: Heath Ledger
Nate explains the statistical reasoning behind each choice in the article.
Supporting actress: Taraji P. Henson
Lead actor: Mickey Rourke
Lead actress: Kate Winslet
Best director: Danny Boyle
Best film: Slumdog Millionaire
fter spending most of 2008 predicting the success of political actors—also called politicians—it’s only natural that Nate Silver (FiveThirtyEight.com) would turn his attention to the genuine article: the nominees in the major categories for the 81st Annual Academy Awards (Feb. 22 at 8 p.m. on ABC). Formally speaking, this required the use of statistical software and a process called logistic regression. Informally, it involved building a huge database of the past 30 years of Oscar history. Categories included genre, MPAA classification, the release date, opening-weekend box office (adjusted for inflation), and whether the film won any other awards. We also looked at whether being nominated in one category predicts success in another. For example, is someone more likely to win Best Actress if her film has also been nominated for Best Picture? (Yes!) But the greatest predictor (80 percent of what you need to know) is other awards earned that year, particularly from peers (the Directors Guild Awards, for instance, reliably foretells Best Picture). Genre matters a lot (the Academy has an aversion to comedy); MPAA and release date don’t at all. A film’s average user rating on IMDb (the Internet Movie Database) is sometimes a predictor of success; box grosses rarely are. And, as in Washington, politics matter, in ways foreseeable and not.
