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Data analytics opening new doors for sports teams and business students

Sports analytics expert Dave Schrader discussed “The Golden Age of Sports Analytics” at a presentation in the Krannert Auditorium on Feb. 23 that highlighted the practical application of analytics and how those applications help teach and practice business skills.

“Sports is a big business that generates $145 billion worldwide,” said Schrader, who earned a PhD in computer science from Purdue and was named a School of Science Distinguished Graduate in 2004. “That’s made sports analytics a hot area because of the vast amount of data generated that teams use to create insights to improve their decision-making.”

The presentation was part of a Data Mining course taught by Matthew Lanham, a clinical assistant professor in Krannert’s quantitative methods area whose analytics courses often have external speakers whom are experts in certain topical areas.

Dr. Ron Menich, chief data scientist at Infor, spoke about “Retail Analytics” as part of Lanham’s Predictive Analytics course last semester. Dr. Chuck Bower, chief scientist at Edj Analytics, also spoke to students about how NFL teams use his ZEUS simulation software for situational game planning. 

According to Lanham, “The best way to learn business analytics is for the students to see how the methods and technologies we teach are being used right now by industry’s best to support decision-making.” 

Schrader, known as “Dr. Dave,” retired after 30 years of industry experience at high-tech database companies and serves on the board of directors for the Teradata University Network, which sponsored the talk. 

Among the topics Schrader addressed were:

• What is happening around the world to collect and analyze data for recruiting, player development, game planning and injury prevention?

• How are analytics being used to improve business operations — ticket pricing, sales and sponsorships?

• What analytics do leading pro teams and leagues use for basketball, baseball, football, and soccer? How quickly are teams adopting analytics?  Who is leading? What are they doing?

• How do analytic techniques used in business apply to sports?  Where are there gaps? What are interesting research problems in sports analytics?

• How can universities collaborate with their sports programs to provide analytics for teams?  What are good first projects to launch? 

The biggest data challenge facing sports teams is often one of “feast or famine,” Schrader said. “There’s either not enough data or too much data. With multiple vendors come multiple systems, which means the data isn’t integrated and lacks actionable recommendations,” he said.

Another issue facing the industry is the “jocks vs. geeks” stereotype in which those who lead the business of sports have different skills, backgrounds and attitudes toward math and science than those who analyze the data. 

“There can be insufficient communication in both directions,” Schrader said. “The jocks need help integrating the data, building the systems and identifying how new data sources can augment their decision-making, while the geeks need to learn the working vocabulary to become part of the team.” 

Lanham recalls similar sentiments shared by Chuck Bower in last semester’s course. 

“Chuck told the students a story of when he was sitting in a room with the head coach of an NFL team demonstrating the capabilities of ZEUS. The coach did not deny the accuracy of the data-based play recommendations, but stated that at the end of the day, he alone must follow accepted play calling decisions because the media and owner would kill him if a non-traditional play was called and did not go in his favor during a critical junction in the game.”

Despite those challenges, the “big data” phenomenon in sports has created a lucrative market for students who know business analytics. “Collectively, sports teams invested $125 million in analytics in 2014, and some studies say it could reach $4.7 billion by 2021,” said Schrader.

“I expect there are Krannert students who are very interested in landing a job in sports,” adds Lanham. “The best way to do that is to work on a project that uses data to examine a sports-related problem. We have a plethora of data sources that are just waiting to be combined, cleaned and analyzed.”

For more information, contact Matthew Lanham, clinical assistant professor, Purdue University Krannert School of Management, at lanhamm@purdue.edu or 765-494-4419.