How to predict the Oscar winners, according to an awards statistician

Oscar pundits would probably call their work predicting the winners of the annual awards show an art, but one man has turned it quite literally into a science.

Ben Zauzmer, who by day works for the Los Angeles Dodgers as a manager of baseball analytics, has for the past eight years taken his knowledge of applied math to create a model that predicts 21 of the 24 Oscar categories (he does not predict the three short film categories). His predictions have been published in the likes of The Hollywood Reporter, The New York Times, and The Washington Post.

And now, as an early holiday present to those of us hoping to score a leg up on this year’s Oscars pool, Zauzmer has released his first book on the subject, Oscarmetrics: The Math Behind the Biggest Night in Hollywood. The book is full of insights into his model and the history of the Oscars itself, as it seeks to answer common questions about the Academy Awards using numbers put mostly in layman’s terms, no degree in applied math required. EW spoke with Zauzmer about the method to his madness and what his thoughts are on this year’s Oscar race.

ENTERTAINMENT WEEKLY: For those that aren’t already familiar with your work, can you talk a little about what you do with regards to predicting the Oscars and why you got into it?
BEN ZAUZMER: So, I predict the Oscars with math. I gather data on all of the potential contenders in over 20 categories and how they did at previous award shows, and how those categories have played out in previous years. And I use all of that data to calculate the probability that each of this year’s nominees wins the Oscars. And then I also write articles about this, I analyze it, I watch the movies, I add some color to the numbers, so it’s not just a dry recitation of statistics. 

I got into this back during the 2011 Oscar season and the Oscars in February 2012. When I was a freshman at Harvard, I was always a big fan of math and numbers and always a big fan of movies. And it occurred to me that I could try and put them together, and so I started gathering data. I spent a month in the library pulling together as much information as I could about previous years’ Oscars and that year’s nominees and started to build some formulas to try and predict the award show.

And without getting into the weeds too much, can you sort of distill a basic synopsis of how your model works? 
Sure. So the gist of it is, I look at Oscar data from previous years. And I have things like, which categories every film was nominated in, and how all of these movies did in each category at the Golden Globes and the BAFTAs and many other award shows. I have the scores of each movie on Rotten Tomatoes and Metacritic, and so on and so on. Anything that I can put into a number, I save on my computer. Then I can look at past year’s Oscars to see how well each of these different things predicted each category. So maybe in one category, it’s the guild awards that are the best predictor. And then in another category, it’s the BAFTAs that are the best predictor, and so on. That gives me a set of weights, how much weight to put on each of these predictors. The ones that have done a better job of predicting the Oscars get more weight, according to various statistical formulas. And then when all is said and done, I can take these weights and apply them to this year’s nominees. And that’s what gives me the probability that each of the 2019 contenders will come away with an Oscar in each category.

And how accurate is it usually?
Overall, in the eight years I’ve done this, the most likely nominee to win has won 77% of their races across all categories.

Whenever people ask you what things to look out for or which precursor predicts the Oscars the most, what do you tell them to look at?
It’s different by category. If I had to pick one thing to look at, across all categories, my answer would probably be the BAFTAs [the British equivalent of the Oscars]. The reason for that being that they tend to cover a large number of categories, and they tend to cover those categories pretty accurately. So they have a precursor category for just about every Oscar category. And that makes them a really good one-stop shop to sort of get a sense of the race, but there are lots of others. If we’re talking Best Picture/Best Director, then the Directors Guild and Producers Guild [Awards]. A lot of these guilds are very useful in their category. 

When you first started, was there one sort of indicator that you were most surprised by?
Yes, actually. The one thing that I looked at was the box office. You would think that, at least in some categories, there will be some sort of relationship between how the Academy feels about a movie and how audiences feel about a movie. And perhaps there was historically — I talked about this in the book, that there used to be a bit more overlap between the Academy and moviegoers — but in this day and age, there really isn’t. The box office, it turned out, was basically a useless predictor for the Oscars. And that was surprising. So that actually does not factor into my model.

How often do you adjust your model?
So the reweighting occurs every single year, because I’m always getting a new year’s worth of Oscar data, which is not negligible, because we’re really not dealing with 91 years of Oscar history in this model. And the reason is, that while the Oscars go back to 1928 — 1929 was the first ceremony — most of these predictors don’t go back nearly that far. A lot of the guild awards, we’re only talking two or three decades. And that means that the data from before those precursor awards really isn’t all that useful to me. So even just adding on one more year’s worth of data from that most recent year can sometimes move the weights around a fair amount.

It seems every year some old stat falls, such as the idea that a film has to probably be a SAG Best Ensemble nominee to win Best Picture at the Oscars (both of the last two Best Picture winners did not meet that criteria). Is there a looming stat this year that could fall and that you would tell Oscar watchers to be looking out for this year?
The couple that come to mind in terms of things that have never happened with a capital N that could fall: One is in terms of how the Academy uses its place as an American institution, but also an international film institution. So we’ve never had a foreign-language Best Picture winner, which is widely known. Roma last year was favored and failed to win. I’m sure that backers of Parasite are looking to see if Parasite can pick up where Roma left off, and it can finally be that movie that crosses that ultimate threshold for Foreign Language Film. The other one is the very way in which we consume and distribute movies has changed radically in the last few years, with the introduction and popularization of streaming movies, and so The Irishman this year is partially out in theaters but partially out on Netflix with that limited release window in theaters. That’s pretty different from how traditionally movies have been distributed and ended up winning awards. There have been other movies that have been associated with streaming platforms that have gone on to success, but it would represent a pretty fundamental shift if The Irishman were to win Best Picture and signal the full welcoming of that type of movie within the Oscar club.

It’s still early yet, but do you have any gut feelings on the state of the race this year?
Right, it’s certainly very early. So right now, I have more feelings based on my gut than I do on math because so much of that data hasn’t come in yet. It’s looking right now like a bit of a race between The Irishman and Once Upon a Time in Hollywood, in terms of who’s getting those key nominations from the groups that have already announced their nominees at least. You had a few winners, such as The Irishman won the National Board of Review, but for the most part what we have are nominees, so you have the Golden Globe nominations, and both of [those films] check that box. You have the Eddie nominations for film editing. The Irishman got that, Once Upon a Time in Hollywood was left out. And then you’ve got a number of movies that have been getting almost all of the requisite nominations. So Parasite and Marriage Story and Jojo Rabbit and Joker, all of these movies are kind of hovering around that top tier. And as we start to get to BAFTA and the Directors Guild and Producers Guild nominees, I think we’ll start to have a much stronger sense of the true frontrunners.

Oscarmetrics: The Math Behind the Biggest Night in Hollywood is available now via BearManor Media.

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