Duke University business professor Otis Jennings likes tackling problems with data. Whether it's in the manufacturing or health-care sectors, or how to improve call center operations, Jennings is a disciple of the data analytics gospel. He's never met an industry that can't be made better by amassing data, sifting through the data and implementing changes based on what only the data can show a business manager.

One unexpected problem that arose: As a visiting scholar, Jennings was asked to teach first-year engineering students at Columbia University an introductory analytics course without making it overly complicated. It just so happened that Jennings had been thinking about analytics and bowling, and a bizarre anomaly in amateur bowling tournaments.

Handicaps in bowling tournaments are used to encourage people with various skill to participate, but there was a counterintuitive result of the handicap method. When you rank everyone from the best to the worst bowler, take the average score and develop a handicap based on the distance between the worst player and the average, it should help to level the playing field, and in theory, the winner could end up being anyone.

But it turns out that the winner more often than not comes from the top half of the rankings, even after leveling the playing field with the handicap, and the bias to the top half happens with unusually high frequency.

Thinking about a data problem in the context of something as "American" as bowling led Jennings to believe that sports might be a good topic for an introductory course on data analytics. Yet Jennings' "teaching tool" is an area he thinks will be a viable career option for MBA students.

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"You can make a career of this. Every organization has to have analytics personnel on board. Businesses will uncover that these people end up paying for their own salaries," Jennings said, and that includes professional sports leagues and teams.

Data analyst has already been dubbed the "sexiest job" of the 21st century. And professional sports leagues and teams, from Nascar to Major League Baseball and the NFL, are ramping up their data efforts. For MBAs looking to capitalize on the big data wave—and whose dreams of being a professional athlete petered out about the eighth grade—there is a way to athletic stardom yet.

Jennings's course ended up attracting a mix of engineering majors and MBAs, and the ideas that began flowing related to sports were all over the place. Jennings, though, said it was the MBA students who showed the greater creative, strategic flair in thinking about sports analytics, while the engineering students crunched the numbers.

One student created a fictitious golf course and worked their way backward to figure out every point on the course and the wind conditions and skills of each player so a tablet computer could tell the player exactly which club to use—the caddie of the future—half man, half machine. "If this was really refined, the software would generate on the fly the best clubs to use," Jennings said, which would probably make stodgy PGA officials shudder.

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