In Friday's Wall Street Journal was an econometric analysis of the upcoming Oscars. article here (reg. required).

The upshot of the article is the probit analysis by Andrew Bernard at Dartmouth, he of winter Olympics medal predictions. His analysis suggests that the best picture award is more likely to go a movie that is not a comedy, has more nominations, and has more Golden Globe awards. Other fields had a significantly insignificant impact on the odds of a film winning the top award.

The journal explained the probit analysis as such:

The science behind the Weekend Journal formula is, well, science. Math geeks, read on.

We started by collecting some two dozen fields of data on the 100 Best Picture nominees for the past 20 years, expressing each as a number (Oscar nominations, length of each film in minutes) or, in the case of plot elements, as a binomial (movies in which a main character rode a horse were designated a 1; others were given zeros in the category). We turned our data over to Andrew Bernard, an economics professor at the Tuck School of Business at Dartmouth, who used a form of regression analysis, which is a way to examine how well a variable or combination of variables predicts an outcome.

More precisely, Prof. Bernard used a "binary probit" statistical model, which seeks to find a correlation between a group of explanatory factors and a given outcome. It's binary because the outcome is expressed as one of two variables -- a 1 for a movie that wins Best Picture, and a 0 for one that is nominated but does not win. He expressed that as an equation, above, which produces the probability that a given movie will win. All the probabilities were between one and zero -- a one representing a guaranteed win, and a zero representing a guaranteed loss.

His final formula used three variables: a film's total number of Oscar nominations, its number of Golden Globe wins, and whether or not the film was a comedy. Each of the three variables includes a coefficient (beta, gamma, delta) that essentially provides a weighting. The formula also includes a constant (it balances out the equation, and is the same year after year). The final term, mu, represents factors we haven't identified but also affect a film's probability of winning. Because no comedy has won a Best Picture Oscar in the past 20 years, those films, such as this year's "Sideways," were statistical zeros in our model.

When he ran the model, each Oscar nomination increased a film's probability of winning Best Picture by an average of 4.5 percentage points. And for the typical film, each additional Golden Globe increased the probability of winning by about 10.2 percentage points.

Pretty decent explanation of the probit approach. Econometrics might become more "maintstream" thanks to Dr. Bernard.