Data Scientists Predict Oscar Winners
A data scientist can generate a multitude of insightful analyses with enterprise technology solutions and challenging big data opportunities. But who will win the major awards at the Oscars? Farsite data scientists have the answers.
February 25, 2014
oscars
The Academy Awards are Sunday. Can data crunching predict the winners? (Photo: Oscars.org)
A data scientist can generate a multitude of insightful analyses with enterprise technology solutions and challenging big data opportunities - coupling statistics, computer science and business acumen. But what about a more pressing question: who's going to win at the Oscars?
Data scientists at Farsite, the advanced analytics division of ICC have done just that, using data to predict the winners in major categories this Sunday night at the Oscars.
“Our predictions are far more than lucky guesses," says Ryan McClarren, Chief Science Officer at ICC. "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. And while social media buzz may be high this week for Leo DiCaprio, sadly, our data shows he is not going home with a statue on Sunday.”
Farsite made Oscar predictions last year as well, and picked winners in five of the six major categories - including surprise best supporting actor winner Christoph Waltz, and best picture winner Argo. Farsite uses a first-of-its kind data-modeling tool to predict Oscar winners. The model 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, other Guild nominations and wins, buzz and nominees’ previous winning performances. For the 2014 Oscars, Farsite is predicting the following winners:
Matthew McConaughey for best actor for Dallas Buyers Club
Alfonso Cuaron for best director for the movie Gravity
12 Years a Slave for best picture
Cate Blanchett for best actress for Blue Jasmine
Jared Leto for best supporting actor for Dallas Buyers Club
According to Farsite data scientists, the first factor to consider in the model for predicting 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. The third factor is the history or prior performance of the nominees. Some nominees may have an edge given their past.
Follow the @FarsiteForecast Twitter account for learning the details behind science of their predictions.
ICC (Information Control Company) is a Columbus, Ohio provider of enterprise technology solutions. Its Farsite advanced analytics division specializes in helping companies use big data and predictive analytics to empower smart business decisions and solve tough challenges.
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