If you believe the data, there will be no Cinderella winner of this year’s NCAA men’s and women’s basketball tournaments.

Those are the findings of the students in Professor of Pharmacy Practice Chad Knoderer’s Bracket Busting class, which focuses on how to use data analytics to make decisions. Knoderer, a Pediatric Pharmacist by training, has been teaching at Butler since 2008—typically in the College of Pharmacy and Health Sciences. But after using some sports-related statistics in his Pharmacy Statistics class and seeing the students’ positive reaction to it, he created the Bracket Busting course for Butler’s Core Curriculum.

Before the class considered college hoops, they turned to the pros. Early in the semester, the students looked at five years of NBA data to determine where the best places are to shoot from and what kind of shot a player should take (is a catch-and-shoot jumper better than a dribble-drive, pull-up jumper?).

The students were able to see trends over time and better understand why so many NBA teams rely on the three-point shot, as well as shots close to the hoop, from a value standpoint.

Just before spring break, the class turned their attention to March Madness. Knoderer had everyone  predict the top four seeds in each region of the men’s bracket. But he gave them data only—no team names attached.

“They just had numbers associated with a team ID,” he says. “So Team 956 could have been Duke. It could have been Gonzaga. They didn’t necessarily know. They just knew performance data from the season. They knew the type of conference the team came from, but not the actual conference. They had to rank the team just as the selection committee would do.”

When the students had ranked teams 1-16, he released the names of each school to go along with the data. Students then could adjust their brackets, if they chose to do so.

In the men’s tournament, most of Knoderer’s students chose either Duke University or the University of North Carolina to win it all. (Knoderer picked Gonzaga, though he didn’t make his choice strictly through analytics.)

In the women’s tournament, the data pointed the students to Notre Dame or the University of Connecticut to cut down the net. (Knoderer picked Baylor, “but not too many were with me,” he says.)

“They enjoyed the activity,” he says. “A few of them said it was a lot more challenging than they thought—even when they knew which team was which.”

After the NCAA unveiled the 2019 bracket, Knoderer assigned his students to predict the outcomes of the first-round games based on data alone. There, the students picked some upsets—”There’s been some lean toward St. Mary’s over Villanova, and Murray State-Marquette was a game of interest,” he says—and learned the difference between choosing with their head versus their heart.

Jaret Rightley, a junior from New Palestine, Indiana, says the class, which combines his passions for statistics and sports, has been a great experience.

“It has changed the way I think about and watch sports, and it has been awesome to see the direct impact that the data actually plays in sports such as basketball and the NCAA tournament,” he says. “I look forward to going to this class each and every day, and I’m excited to see how this class evolves and the role analytics will continue to play in sports moving forward.”

Knoderer says he’s also enjoying Bracket Busting, especially because he has an opportunity to teach students he doesn’t normally interact with. Most of the students are from outside the College of Pharmacy and Health Sciences.

And he plans to teach the course again this summer—this time using baseball.