Basketball fans have one more day to fill out their March Madness brackets. They'll need to predict not just the champions and their route to victory, but also the paths of all the losers. It's not easy. In fact, no person or computer has yet been able to do it.

But that's not for lack of trying. Andy Dieckhoff has been working on his NCAA basketball ranking system for more than a decade. He's a senior at Portland State University studying applied linguistics. But in his spare time he studies basketball.

"I get really excited," he says. "I tend to think of Bracket Day as more enjoyable than my birthday most years."

Dieckhoff started watching games with his dad when he was 5 or 6, and he ran his first bracket pool in middle school.

"I wanted to give myself kind of an advantage," he says.

So he poured a bunch of win-loss stats into a spreadsheet and used some basic equations to try to predict the winners.

"It was nothing sophisticated or anything like that when it started," Dieckhoff says.

But since that first year, when Dieckhoff beat all of the 11-year-olds in his pool, his system has become a lot more complex. The spreadsheet has grown to include not just scores but also rebounds, assists, three-point shooting percentages and numerical values for some qualities that are harder to define, like hustle, discipline and even luck. The system is all about using intuition to interpret the stats.

"The weighting of everything is done on completely gut feeling," Deickhoff says. "I've picked up things I feel are important in the game."

Dieckhoff's system correctly predicted 66 of the 68 teams that made it into this year's tournament. But that doesn't necessarily mean it will help him predict winners in the tournament.

"There's no making sense of it," Dieckhoff says. "I'm trying pretty hard to make sense of it. But at the end of the day, any team can win any game."

Dieckhoff isn't alone. More than 3 million people filled out brackets on ESPN.com last year.

Keith Lipscomb, a senior editor at ESPN Fantasy Games, says no one got a perfect bracket; the best anyone did was guessing 52 out of the 64 games. Raw knowledge of basketball doesn't count for that much when it comes to filling out brackets.

"The NCAA tournament happens to be my favorite thing in the world," Lipscomb says. "But that doesn't mean I have any better grip on it than anybody else just because I watch a lot of games. I feel like you're sometimes better off not knowing too much, because that way you don't overthink it."

So what if you know nothing? What are the odds of randomly predicting the outcome of every tournament game?

According to Mike Weimerskirch, a math professor and sports fan at the University of Minnesota, those odds aren't good: about 147 quintillion to one (that's 147,000,000,000,000,000,000:1). The odds get slightly better (about 9 quintillion to one) if you ignore the play-in games and just look at the field of 64.

"It's going to be more likely for Phil Mickelson to get a hole in one on all four of the par threes in the opening round of the Masters than it is to fill out a perfect bracket," Weimerskirch says.

But what if you take a slightly smarter approach to filling out your bracket and always pick the teams that are seeded higher?

"You bring it down to about 150 billion to one," Weimerskirch says.

But in the age of Google, shouldn't we be able to get closer than that? Shouldn't we be able to use all our computational power to correctly predict all the winners and create the perfect bracket?

That's the question behind a very special March Madness pool run by Danny Tarlow, a postdoctoral student at Microsoft Research Cambridge. His pool has just one serious rule: no humans.

Computer programs fill out the brackets.

It started a few years ago when Tarlow entered a March Madness bracket and wanted to give himself a bit of an edge. He hijacked the basic structure of a program he was working on (it was designed to anticipate a reader's book selection) and used it to predict winners.

"It worked surprisingly well," Tarlow says. "I won the pool, so it wasn't behaving completely crazily."

The next year he invited other programmers to enter their own bracket-building algorithms.

Each competitor enters a program that must learn about basketball by chewing through the stats from past games. It's similar to voice recognition software learning speech. The programs guess the outcome of a game, then refine their algorithms based on the actual results. Then they repeat the process, guessing and checking, with all the games on record.

"It can take quite a long time to do this initial learning phase — several hours to even a day," Tarlow says.

So are these programs any good at filling out brackets?

"Looking at the group of algorithms, it's probably not that much different than you would expect to see out of your group of friends," Tarlow says.

It turns out that the cold statistical precision of a computer program is just as unsuccessful as human intuition. Weimerskirch says there just isn't enough data to overcome the randomness of college basketball.

"No matter how much computer analysis you do, you're still stuck with the way the ball bounces," he says.

"That's the beauty of college basketball," Dieckhoff says. "There are upsets all the time. Maybe sometimes it's better to just put on a blindfold and pick the teams."

Or you could try a more creative strategy.

"Somebody apparently won their office pool basing their picks on who would win the game if the mascots fought," Weimerskirch says.

In some years that could bring up some tricky questions.

"If, say, Ohio State plays Stanford, you've got a nut going against a tree," Weimerskirch says. "I'm not quite sure how I would call that one."

That kind of unpredictable match-up is what makes March Madness so ... maddening.

Copyright 2015 NPR. To see more, visit http://www.npr.org/.

Transcript

STEVE INSKEEP, HOST:

Basketball fans have one more day before the NCAA tournament to complete a spring ritual - they finalize their March Madness brackets. People try to pick the winners round after round. And by necessity, they also try to pick the losers, which turns out to be a nearly impossible task to do perfectly.

As NPR's Adam Cole reports, neither man nor computer has been able to do it.

ADAM COLE, BYLINE: If anyone could fill out a perfect bracket, you'd think it would be Andy Dieckhoff. He's a senior at Portland State University studying applied linguistics - but in his spare time he studies basketball.

ANDY DIECKHOFF: I tend to think of Bracket Day as more enjoyable than my birthday, most years.

COLE: He started watching games with his dad when he was five or six, and he ran his first bracket pool in middle school.

DIECKHOFF: But I wanted to give myself kind of an advantage.

COLE: So he poured a bunch of win-loss stats into a spreadsheet, and used some basic equations to try and predict the winners.

DIECKHOFF: It was nothing sophisticated or anything like that when it started.

COLE: But since that first year - when Dieckhoff beat all the 11-year-olds in his pool - his system has become a lot more complex. The spreadsheet has grown to include not just scores, but rebounds, assists, three-point shooting percentages; and numerical values for some qualities that are harder to define, like hustle, discipline, even luck. The system is all about using intuition to interpret the stats.

DIECKHOFF: The weighting of everything is done on completely gut feeling.

COLE: Dieckhoff's system correctly predicted 66 of the 68 teams that made it into this years tournament. But he doubts it will help him that much when he's filling out his bracket.

DIECKHOFF: There's no making sense of it. I'm trying.

(LAUGHTER)

DIECKHOFF: I'm trying pretty hard to make sense of it. But it's just such a crapshoot that even when you know everything, you really don't know anything.

COLE: OK, so what if you know nothing? What are the odds of randomly predicting the outcome of every tournament game?

MIKE WEIMERSKIRCH: One hundred and forty-seven quintillion to one.

COLE: That's Mike Weimerskirch, a math professor and sports fan at the University of Minnesota.

WEIMERSKIRCH: You're far more likely to win the lottery than you are to hit up on the perfect bracket.

COLE: But what if you take a slightly smarter approach and always pick the team that is ranked higher?

WEIMERSKIRCH: You bring it down to about 150 billion to one.

COLE: But in the age of Google, shouldn't we be able to get closer than that? Shouldn't we be able to use all our computational power to create the perfect bracket? Daniel Tarlow is a computer scientist, and he's trying to do just that. He runs a very special March Madness pool.

DANIEL TARLOW: So really, there's only one serious rule.

COLE: No humans allowed. In this pool, computer programs complete the brackets. Programmers write a few lines of code and the programs must learn about basketball by chewing through the stats from thousands of games. It's similar to voice recognition software learning speech. The programs guess the outcome of a game, then refine their algorithm based on the actual results. Then they make a new guess on a new game and refine again - thousands of times.

So are these programs any good at filling out brackets?

TARLOW: Looking at the group of algorithms, it's probably not that much different than you would expect to see out of your group of friends.

COLE: The cold statistical precision of a computer program is just as unsuccessful as human intuition. Weimerskirch there just isn't enough data to overcome the randomness of college basketball.

WEIMERSKIRCH: No matter how much computer analysis you do, you're still stuck with the way the ball bounces.

COLE: So you might as well try a creative strategy.

WEIMERSKIRCH: Somebody apparently won their office pool by basing their picks on who would win the game if the mascots fought.

COLE: In some years, that strategy could bring up tricky questions.

WEIMERSKIRCH: If, say, Ohio State plays Stanford, you've got a nut going against a tree - I'm not quite sure how I would call that one.

COLE: And that kind of unpredictable match-up, that's what March Madness is all about.

Adam Cole, NPR News.

(SOUNDBITE OF MUSIC)

INSKEEP: I predict that we are about to say: It's MORNING EDITION, from NPR News. I'm Steve Inskeep.

RENEE MONTAGNE, HOST:

And I'm Renee Montagne. Transcript provided by NPR, Copyright NPR.

300x250 Ad

Support quality journalism, like the story above, with your gift right now.

Donate