Oscar Nominations To Be Released Thursday At 8:30 PM EST: A Mathematical Formula For Predicting The Nominees
ByMove over Golden Globes. The Oscar nominations come out this morning at 8:30 am EST. According to a mathematical formula devised by Harvard math major Ben Zausmer, who predicted winners with 75 percent and 81 percent accuracy in 2012 and 2013, respectively, below are some of the most likely candidates to get nominated, courtesy of the Hollywood Reporter. Zausmer won't go as far to say that those most likely to be nominated are also those most likely to win. He'll compute that formula once the nominees are announced.
Of the five categories analyzed by Zausmer (basically the five most important: best picture, best actor, best actress, best supporting actor, best supporting actress), "12 Years a Slave" had the highest probability of getting a nomination at 99.9 percent, with "Gravity" at number two with 90 percent. After that, it drops considerably to "American Hustle" (77.2 percent). Likely, that foretells a two horse race between "12 Years a Slave" and "Gravity." "Gravity" had been getting most of the Oscar buzz, but "12 Years," has surpassed it as of late (and "Gravity" wasn't even mentioned in Newsday's top five, released today). Such is the complexities of the Oscars, where films can move up and down the charts even though their merits should really have already have been solidified.
The next biggest lock was Jennifer Lawrence's 96.4 percent for best supporting actress in "Amercian Hustle." Yet, she's trailed closely by three other actresses above 90 percent: Lupita Nyong'o, Julia Roberts, and June Squibb.
The closest category, if solely based on Zausmer's formula, will be best supporting actor. Four actors are within less than two percentage points of each other, with Barkhad Abi (93.2 percent) fractional points ahead of Daniel Bruhl ("Rush") and Michael Fassbender ("12 Years a Slave"). At number four is Jared Leto (91.5 percent), whom Newsday selected as its winner.
Zausmer's formula may be somewhat complex, but his methods aren't. Basically, he compiles data from all prior award shows, weighs them according to how strongly they've predicted Oscar success in the past, and tallies the results, according to the Hollywood Reporter.