These data scientists think they can predict who’ll win at the Oscars

Data or, more specifically, increasingly open and accessible data has completely changed the way we look at the world. Far from being a record of what has happened, it’s become an increasingly good indicator of what might happen.

Heck, data has been used to predict everything from the Rugby World Cup to US presidential elections and now… the Oscars.

At least that’s Pricipa, the company that beat the vast majority of SuperBru players during the 2015 Rugby World Cup, is hoping to do.

The results? Well, it looks like Leonardo DiCaprio could finally get his hands on one of those prized little gold trophies.

According to a press release sent to Memeburn, the Principa team collected and analysed data spanning back to 1935 to find patterns which could help identify strong predictors of the winners. Some of the best predictors identified have tended to be winning other awards, critics’ ratings and bookie odds. Other predictors have been genre and box office revenue before and after Oscar nominations.

Using probability analysis, Principa predicts the following winners in the following four main categories:

1. Best Picture: The Revenant – winning by a very slim margin over Spotlight
2. Best Actor: Leonardo DiCaprio – winning by an 8 fold margin over Matt Damon
3. Best Actress: Brie Larson – winning by a 6.7 fold margin over Saoirse Ronan
4. Best Director: Alejandro González Iñárritu – winning by a very slim margin over George Miller

Betting on the bookies

As was the case during the Rugby World Cup, Principa sees serious value in the odds provided by bookmakers.

“Thanks to the predictive power we’ve observed within the bookie odds and previous wins, we can make our predictions with a high-level of confidence,” says Thomas Maydon, Head of Data Analytics at Principa.

“Our predictions are similar to what experts are saying, with Best Actors and Best Actress awards almost a dead certainty and Best Director and Best Picture going either way due to the slim margin. However, the bookie odds are changing every day and as they hold high predictive power in our own predictions, our predictions may change as we get closer to the night of the Oscars.”

As with the Rugby World Cup initiative, the team are using this as a way to test the applicability of the same data analytics principles used in determining the likelihood of an individual to pay back a loan or respond to a marketing campaign to another area: predicting the voting behaviour of 7 000 Academy Award members.

The team have applied lessons learned from their Rugby World Cup initiative to improve the quality and accuracy of their Oscar predictions. “We learned from our Rugby World Cup initiative that when we build different models off data sources and then combine them, our predictions tended to be more accurate. As a result, for our Oscars initiative we’ve built a model off 80 years of data and then a model off more recent data and combined the two instead of using one model,” continues Maydon.

The truth will out

And that’s a potentially more interesting area of analysis than trying to predict future outcomes. One pattern identified in the analysis of the data going back to 1935 has been a growing affinity towards films that are based on true stories. In fact, more than half of films nominated this year for an Oscar in any of the four main categories are based on a true story. This is the highest percentage of nominees in this genre to date and this percentage has steadily been increasing through the decades.

“Regardless of how accurate our current predictions end up being on Oscar night, we have identified some very interesting patterns and trends, which reveal how our tastes are changing and how certain variables or characteristics tend to make up an Oscar winner. The data tells a story and as data scientists, we serve as story tellers,” concludes Maydon.

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