Is a perfect March Madness bracket possible?

The Probability of a Perfect Bracket

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Nine quintillion is such a big number that it’s practically meaningless. Let’s put this number—and your odds—into perspective.

Pennington explains that there are 64 teams in the Big Dance, and one team is eliminated per game, leading to 63 total games in the tournament. Since each game has two possible outcomes, win or lose, that means there are two to the 63rd possible brackets: 2⁶³ or 9.2 x 10¹⁸.

For scale, Pennington continues, the universe is approximately 13.8 billion years old, or 4 x 10¹⁷ seconds old. “If you took 20 people back to the beginning of the universe,” he says, “and had them build a bracket every second, they would get every possible bracket by about now.”

This helps show how unbelievably rare it is to pick the correct bracket by chance.

Statistical Modeling—Your Best Bet (But Not a Perfect One)

Let’s forget pure chance and your 1-in-9-quintillion odds for a moment. We know you’re thinking there’s got to be a better way.

And there is—with statistical modeling!

If your goal is to pick more correct winners than most people, Pennington says statistical modeling is your best tool—it’s what gamblers and analysts rely on. Models like KenPom (Ken Pomeroy’s analytics) and random number generation can improve accuracy and help your bracket outperform the majority.

Why Statistical Models Improve Your Odds

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By analyzing historical tournament trends, using seeding and high-value upset picks and more, statistical models help reduce randomness and improve your chances of making accurate predictions—however, says Pennington, “there is no tool that’s going to give you a perfectly accurate tournament outcome."

Since March Madness is a one-time event, you can’t test your bracket over and over to refine the model. It’s also random—with 10 players making specific decisions every second, resulting in upsets, momentum, injuries and pure luck—something for which models can’t account.

Even with creating better odds than the comical 1-in-9-quintilian, the odds of anyone picking a perfect bracket with a statistical model are still virtually impossible.

As Pennington puts it: “Not every game’s outcome has an equal probability. Predicting every game correctly is so difficult, even with data and analytics.”

On the other hand, Pennington says, “If you want to fill a bracket out scientifically, you’re going to beat people doing it for fun.”

Watch Nathan Pennington, PhD, Video

The Science of Bracketology

A perfect bracket and bracketology are two different things. A perfect bracket is nearly impossible, but bracketology is about maximizing your points in a pool by using a mix of statistics and strategic decision-making.

This results in two-three approaches to increase your chances of winning your pool:

1. Improving your overall accuracy and optimizing more correct choices throughout your bracket using statistic models
2. Using bracketology with strategy and social cues, as well as taking calculated risks, to predict key games (especially the championship) in a way that maximizes your edge over competitors
3. A combination of the two.

Balancing Risk & Reward

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For most brackets, later-round games are worth more points; often, picking the championship game correctly is worth as much as the entire first round combined. That’s why your strategy could focus on making smart championship picks rather than just maximizing total correct picks, says Pennington.

• If you pick the same winner as everyone else, either the most likely to win or the “fan favorite,” you may break even—even if you’re right
• If you take a calculated risk and pick a less popular champion—and they win—you could win your pool outright

Using Social Cues: The Creighton Example

In a Creighton-heavy pool, many people will pick Creighton to win. If Creighton wins and you picked it, you’re still tied with everyone else—no advantage gained. If you pick a different winner, and that team wins, you could dominate everyone else in your pool.

Key Insight:

“If you’re asking about the best way to make a bracket to win, you’re looking for a sweet spot of something that is likely, but not what everyone else is going to pick,” Pennington says.

You can find sweet spots where you think the predictive models are wrong, or where you think others might make a different, more obvious choice. That’s what’s going to give you an edge over others.

The 2025 March Madness Tournament poses a unique opportunity over the 2024 tournament. In 2024, the two most likely teams to win were Purdue and UConn. "Picking anybody but one of those two to win was probably sufficiently unlikely that it would not have been a good strategy,” says Pennington.

In 2025, there are about 4-6 teams who have similar probabilities to win. “Picking one that is the least likely to be picked by other people in your pool is then a good strategy,” he continues.

Ultimately, it comes down to your goal and the route you think will make you more likely to win your pool—creating as perfect of a bracket as possible with stats, or maximizing your points with strategy, decision-making and risk.

Statistics at Creighton

At Creighton, we recognize the importance and applications of statistics—beyond March Madness!

Every degree on campus requires completing a designated statistics course. No matter what area of study students are interested in, from business to pre-health to social science, they are required to take at least one course that is statistically oriented.

Specifically, the Business Intelligence and Analytics program and the Data Science program dive deep into statistics. In introductory courses for data science, a final project may look like students building a predictive model and testing how well it works.

Pennington explains that data science has been on the forefront of the business industry for a handful of years. “Now that all commerce is getting pushed toward the internet, advertisers can track actual outcomes of their ads," he says. “These sites are generating an enormous amount of data, and companies do not know what to do with it.” He adds data scientists are in demand because organizations hire them to pore through their data to make better, more informed decisions.