Game Management

Krannert’s data analytics strengths muscle the school into the sports industry

As the Purdue men’s basketball team was about to begin its improbable run to the Elite Eight in this season’s NCCA Tournament, Boilermakers everywhere took part in an annual exercise of sports analytics when they filled out their brackets predicting the winner of each game and the eventual champion.

For beginners or collegial fans who often follow their hearts while making March Madness picks, school pride can easily override logic, but a growing number of more invested spectators consider every available data point no matter how obscure — from a team’s performance in night games against non-conference opponents to an individual player’s stats while staying on the court with four fouls in end-of-game or overtime scenarios.

And that’s just among the team’s frenetic followers and the burgeoning betting public.

The billion-dollar business side of data analytics has brought new jobs and strategic decision-making tools to the front office of virtually every professional sports team, as well as a growing number of intercollegiate programs.

More recently, it’s also entered the lucrative and growing market for online gaming and esports, spawning both a new industry and a new type of competitor, one whose skills bridge multiple disciplines driven more by data than athletic prowess.

Winning prognosis

Sports analytics guru “Dr. Dave” Schrader, who earned a PhD in computer science from Purdue and was named a School of Science Distinguished Graduate in 2004, made his latest visit to the West Lafayette campus last September for a fast-paced talk in Krannert Auditorium on the field’s latest trends.

“Big data has been a driving force in every industry for many years, but sports analytics is clearly the hot topic,” he said. “That’s what everyone wants to talk about.”

Although cost can be a deterrent for hiring professional analysts at the college level, Schrader said there are numerous ways that universities can draw from their existing talent base of students in data science, business analytics and sports.

He presented several college case studies where students helped tackle and solve interesting analytics problems for coaches, trainers, and athletics business staff, including:

At the professional level, there are ample job opportunities in sports analytics for those who are ready to take their skills to the next level.  “It is no different from the world of analytics in the business world,” Schrader said. “There’s more data than most teams know how to use, but you can’t just put a bunch of analysts in a basement and expect them to work magic. You have to be strategic.”

Getting past the “geeks and jocks” stereotype is another challenge for data analytics in the sports industry, he said.

“What you really want to do is treat the analytics people like translators,” Schrader explained. “They need to absorb the problems identified by the team and translate possible solutions.

“Talking about an algorithm or regression model isn’t going to get a coaching staff’s attention, but using data to help with roster construction, knowing who you should have in the game in different scenarios against different opponents, and what plays you should run in critical situations — that’s the vocabulary they want to hear.”

Next: Playing in the big leagues

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