Just in time to finalize your Oscar betting pools, a Harvard sophomore has cracked the code to predicting the 2013 Academy Award winners. Well, sort of.

Ben Zauzmer may be a statistics whiz, but he's also a major film buff who has closely studied the ever-shifting patterns that have historically led to Oscar night victory. He knows better than most how difficult it can be to forecast the voting preferences of the Academy.

Still, Ben – like many other 2013 Oscar prognosticators – is counting on “Argo” to take the Best Picture trophy home. The applied mathematics major uses a liner regression model that weighs the importance of dozens of predictors – like a Golden Globe win, a high rating on Rotten Tomatoes, or the total number of nominations a particular film receives – and plugs them into a statistical formula the reveals the percentage odds of a nominee's chance of winning.

“These are not 100 percent predictions, they are 60 or 70 percent predictions,” he said. “It's very possible that quite a few of these end up being wrong.” But if last year's predictions are any indication, they probably won't be: Zauzmer correctly predicted all eight major categories of the 2012 Oscars.

According to Zauzmer's 2013 Oscar forecast, “Argo” has a 60 percent chance of winning the Best Picture award – despite Ben Affleck's notorious Best Director snub – and Best Documentary award nominee “Searching for Sugar Man” has the best chance – 80 percent – of winning among all the nominee categories. The Best Supporting Actor is the closest race: Tommy Lee Jones and Christoph Waltz are neck and neck, with the other nominees not too far behind.

Zauzmer took some time this week to talk to IBTimes about his Oscar predictions, and explain why the Academy's decision to expand the Best Picture nominee pool in 2009 has significantly impacted the already-complicated mathematical process of predicting Oscar victory.

IBTimes: At what percentage point does a predicted victor become a lock?

Zauzmer: Nothing is truly ever a lock. That’s why even the very highest -- “Searching for Sugar Man,” the Best Documentary nominee that’s just cleaning up everything – only ends up at 80 percent. And I say “only” because it’s really dominated so far in just about every way a documentary can. “The Gatekeepers” has taken a little bit, but nothing much.

There’s only so much data around the Academy Awards, and the math accounts for that. The more data you put in to the linear regression model, the more accurate the results will be. Since the Oscars only have so much data – it’s not really a data-driven business – no one nominee can every truly become a “lock.”

But that said, there are two things I look at to determine which predictions are pretty sure bets. One is – is the predicted winner above 50 percent? Because if the winner is below 50 percent -- like Best Director Ang Lee is at 48 percent, or Tommy Lee Jones is at 43 -- that means that if you were to ask me if I would bet for or against them, I would actually bet against them. Even though they are the favorites.

Just to be clear, you would bet against Tommy Lee Jones winning the Best Supporting Actor Oscar even though your model predicted him to win?

If you said to me, “do you think it’s more likely that he wins or he loses?” and those were the only two choices -- right now, it’s at 43 percent that Tommy Lee Jones wins, which means it’s at 57 percent that he loses.

Anytime a predicted winner is below 50 percent, I’d say you can’t call a lock. Anything above 50 is looking a bit safer. If someone is sending out their Oscar pool, they should still go with the highest percentage.

The other thing I look to is: what’s the difference between who is leading the race and who is in second? That makes a big difference. If you have something where two nominees have a high percentage chance of winning – even if one is above 50 percent, they might be really close to each other. For example, Jennifer Lawrence is predicted to have a 60 percent chance of winning the Best Actress Oscar. That happens to be the same as “Argo” for Best Picture. But for “Argo,” everybody else is below ten percent – because there are more nominees in the Best Picture category than Best Actress, where not everyone is below 10 percent. As a matter of fact, both Jessica Chastain and Emmanuelle Riva are above 10 percent.

Which nominees this year come closest to being a true lock?

Daniel-Day Lewis is going to win, Anne Hathaway is going to win, “Brave” is pretty close to being a lock. “Amour” [for Best Foreign Film], “Searching for Sugar Man,” “Life of Pi” for effects, “Argo” for film editing – that’s about it as far as saying, “I’d bet the bank on this one.”

According to your blog, you factor in pretty heavily a nominee’s performance at prior award shows, which makes sense. But I feel like “Argo” is an unusual position as far as this goes.

Yeah, it’s bizarre.

As you know, Ben Affleck wasn’t nominated for Best Director, and as everyone has been talking about, it’s unusual for a film to win Best Picture when the director has not been nominated. If politics are why he was shut out of the Best Director pool, could the fact that he’s pretty much won everything he could win since he was snubbed by the Academy work against him?

Yes, from an anecdotal/political perspective, but I don’t really have a way of accounting for that with one’s and zero’s. Personally, I agree with what you are saying. What I can try to do is shed some light on why the math still likes him.

Basically, the Best Director snub does hurt him. Had he cleaned up as much as he has done at other award shows and gotten a Best Director nomination, “Argo” would be at much higher than a 60 percent likelihood of winning.

Affleck has basically won everything that matters as a predictor. … The key is the Best Director thing. That's why two out of five times with this setup, you can say “Argo” is going to lose, and three out of five times “Argo” would win.

The other interesting thing about the Best Director nomination is that it hasn't been as great a predictor as people might expect, historically. Because for most years, just about all of the nominees for Best Picture are getting nominated for Best Director – because there were five of each. So getting nominated for Best Director, mathematically speaking, means you're likely to win [Best Picture]. It also means you're likely to lose, because the losers are also getting nominated for Best Director. It's a strange thing to think about.

It is! I am having a hard time grasping what you just said.

When there were five Best Picture nominees, let's say four out of five were also nominated for Best Director as well – which was pretty common until they doubled the number of Best Picture nominees. In that case, you have a movie that got a Best Director nomination and won Best Picture. You also have three movies that got a Best Director nomination and they lost. So when you look at the math, it shows that a Best Director nomination can help you win, but it also helps you lose.

That said, the Best Director nomination still helps, overall ... but the key difference is when they doubled the number of nominees. Now, there are going to be a lot of Best Picture nominations that don't get a Best Director nomination. It's going to start to matter a lot more as the years go on. But right now, the math doesn't fully account for that.

To be clear, the math doesn't account for the fact that there are far more Best Picture nominees than Best Director, yes?

Right – at least it only accounts for three years' worth of that difference, and I'm using 15 years' worth of data.

I had a choice this year, which was to only use three years' worth of data or to use 15 years' worth. And what I determined was that everything else would become extremely inaccurate if I only used three years, so I decided to stick it out with this method. But it's very possible that this method is undervaluing the significance of having twice as many nominees. And it could be that the Best Director nomination is more important than the math is letting on, and that it's a closer race than the math is reflecting.

So in a few more years, the math will better be able to account for the differences in the number of nominees between those two categories.

Yes – what I will eventually do is stop using any data before 2009. But we're not at the point where there is enough data to do that yet.

Right now, your data goes back to 1996. Why that year?

I wanted a consistent standard, so I looked across all the different indicators for all the awards and when they started – for example, Metacritic and Rotten Tomatoes. Also when different award shows and guild awards got started, and when they started to become good predictors.

We know you don't consider your personal preferences when you are making these predictions, but what are some of your personal preferences? Do you want any of your predictions to be wrong?

From a personal perspective, I'd love to see “Les Mis” pull off Best Picture, but I know it's not going to happen. I'm just such a big musical fan, and particularly of that one, even if there were some issues with how it was made.

Among the acting awards, I'd be more inclined toward Jessica Chastain than Jennifer Lawrence.

I was surprised to see that Naomi Watts came in so low in your predictions (a 1% chance of winning the Best Actress Oscar).

Let's take a look at what hurt her. If your movie is nominated for Best Picture [“The Impossibles” was not], that slightly helps you. She didn't win a Golden Globe, she didn't win Screen Actors Guild, she did not win a BAFTA. Emmanuelle Riva won the BAFTA, so Riva is over Watts.

The SAG win is an excellent predictor, which is what put Jennifer Lawrence over the top. The Golden Globes are also good predictors – and Lawrence and Chastain each won a Golden Globe.

You must be a big fan of Nate Silver.

Absolutely. I'm also a big fan of the people who do saber metrics – the fancy name for baseball stats. The “Moneyball” thing.

Are you a betting man?

I'm not. The most I've ever bet is $3 dollars on a March Madness pool. That's about as high stakes as it gets for me.

RELATED STORIES