2013 Oscar Winners Forecasted with Farsite's Predictive Model
The 85th Annual Academy Award winners have been predicted using a proprietary data science model from Farsite, a data science firm. Predictions include Lincoln for Best Film, Daniel Day-Lewis of Lincoln for Best Actor and Jennifer Lawrence of Silver Linings Playbook for Best Actress. These categories, along with Best Director, Best Supporting Actor and Best Supporting Actress are showcased at http://www.FarsiteForecast.com. The probabilities of winning will be updated daily to account for new information such as Guild wins.
"Last year, 40 million people watched the Oscars," said Conor Gaughan , chief strategy officer of Farsite. "Given the size and cultural prominence of the entertainment industry, it is fun and relevant to apply data science to the Academy Awards and explore how the discipline can empower the media industry more broadly. This year Hollywood box office sales were over $10.8 billion. This is a huge sector where data science can help play a prominent role in growth."
To arrive at this first-of-its-kind forecasting model, Farsite leveraged its expertise in predictive and advanced analytics and the entertainment industry. The model incorporates more than 40 years of film industry and Academy Award related information to forecast probabilities for the winners. This information includes real-time data inputs and a wide array of variables such as total nominations, other Guild nominations and wins, buzz and nominees' previous winning performance. "We will adjust the forecast daily based on the key signals in our proprietary model to update the probability of any given nominee winning," said Ryan McClarren , chief science officer of Farsite.
Farsite is a data science firm that specializes in helping companies use predictive and advanced analytics to empower smart business decisions, solve their toughest challenges and gain a distinctive competitive advantage. For more information visit www.FarsiteGroup.com.