In the summer of 2013, I became a freelance journalist in a rather unusual fashion.
One day, walking down the streets of Washington, D.C. (I was a college intern in town for a couple months), I received a phone call from Matt Belloni at The Hollywood Reporter, and he wanted me to write for the magazine that upcoming Oscar season.
Why the interest in a college kid? Two years earlier, during my freshman year, I began predicting the Oscars with math.
I’ve always been a math and movies fan, and after the idea came to me that someone should combine those two things, I decided to do it myself when I couldn’t find anyone who had.
I gathered data from a host of sources, such as IMDb, the Academy website, Rotten Tomatoes, Metacritic, and often even hunted for individual data points in old press releases. I built formulas that assigned proper weights to all of these factors for each category, automatically assigning more weight to those precursors that had a better track record of predicting the Oscar.
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It took a month, but I was able to publish the results on a simple WordPress website. Within a couple of years, word spread about my Oscar predictions, from film blogs around the world to mentions in The Wall Street Journal and The Economist.
I make predictions in all 21 categories that are not for short films (there isn’t enough data to predict those mathematically).
Over the eight years I’ve predicted the Oscars, my model’s favorite to win the category has gone on to win 77% of the time. In early years, I garnered attention for predicting Meryl Streep for Best Actress for “The Iron Lady” (2011) and Ang Lee for Best Director for “Life of Pi” (2012).
Now The Hollywood Reporter wanted me to write for them. I immediately said yes, beginning a relationship that continues to this day. Just this week, I yet again published my mathematical Oscar predictions in that same magazine.
And thanks to that phone call, my side career (my day job is working as a baseball analyst for the Dodgers) has further blossomed. I’ve added Tony predictions to the resume. I predict nominees for these two awards shows. I’ve written about other subjects at the intersection of data and entertainment, not just for The Hollywood Reporter but also for The New York Times, The Washington Post, and The Boston Globe. I started a Twitter account to share my love of awards trivia with the world. And most recently, I wrote a book called “Oscarmetrics” that uses math to answer a variety of questions about the Academy Awards.
My sort of awards coverage is very different from traditional forms of Hollywood journalism, and I believe that both have their place.
Mathematical predictions can uncover human biases, can properly weight various Oscar predictions and can give us an exact sense of who the favorites are and by how much.
Traditional coverage can incorporate the broad spectrum of human feelings, late-breaking news events, and the zeitgeist in Hollywood that data alone can never capture.
And to be sure, while math can estimate how a group of voters will behave, it can never tell us which film is superior to any other.
Fortunately, readers who enjoy Oscar coverage don’t have to choose. My goal in what I do is the same as the goal of traditional pundits: to provide an enjoyable, exciting form of entertainment in the run-up to the biggest awards show of the year. That is ultimately the mission of my unique brand of journalism, and one that I look forward to achieving at the 2020 Oscars and for years to come.
Ben Zauzmer (@BensOscarMath) is the author of “Oscarmetrics: The Math Behind the Biggest Night in Hollywood.”
