The Academy Awards telecast is still a few days away, but data scientists at Farsite claim to already know who will take home the Oscars on Sunday night.
Farsite, the advanced analytics division of ICC, specializes in helping companies use big data and predictive analytics to empower smart business decisions, solve their toughest challenges, and gain a competitive advantage, and it claims to use the same sophisticated, predictive modeling it uses in industries like retail and healthcare to predict Oscar winners quite accurately.
According to the firm’s predictions, the Oscar this year goes to….
- Matthew McConaughey for best actor in Dallas Buyers Club;
- Alfonso Cuaron for best director for Gravity;
- 12 Months a Slave for best picture;
- Jared Leto for best supporting actor in Dallas Buyers Club;
- Cate Blanchet for best actress in Blue Jasmine; and
- Lupita Nyong’o for best supporting actress in 12 Years a Slave.
Last year, Farsite correctly predicted Christoph Waltz would win best supporting actor for Django Unchained and Argo would win for best picture. In fact, the company was right in five out of the top six categories for the 2013 Oscars. Either its data modeling is sound, or it’s very lucky.
“Our predictions are far more than lucky guesses. Most people are surprised to hear that the same sophisticated predictive modeling we use in industries like retail and healthcare can predict Oscar winners quite accurately,” Ryan McClarren, ICC’s chief science officer, boasted in a statement.
Farsite’s data modeling tool analyzes more than 40 years of film industry and Academy Award-related information to forecast probabilities for the winners. This information includes real-time data and an array of variables, including total nominations, industry and media buzz, and nominees’ previous winning performances. It also factors in voting results from other awards contests, including the Critic’s Choice, Golden Globes, the Producers Guild, the Screen Actors Guild, the Writers Guild, and the Directors Guild, among others.
According to Farsite data scientists, the first factor to consider is that during awards season there are other award winners that can provide insight into likely Oscar winners. The second factor to consider is the momentum or buzz behind particular nominees. Since Oscars are at the end of awards season, if the results of previous awards and other buzz by the glitterati are strong enough to sway the votes of some members of the academy, then signals that historically point to the “correct” nominee could be hijacked. The third factor is the history or prior performance of the nominees. Some nominees may have an edge given their past.
We’ll have to tune in on Sunday to see how all that data did. Will it be a hit or will it stumble right there on the red carpet? The envelope, please…..