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St. Lawrence University receives $1.2 million grant to integrate sports analytics in education

Posted 2/6/23

CANTON – Using part of a $1.2 million National Science Foundation grant, St. Lawrence University will use sports analytics as an educational tool to develop a series of materials that will prepare …

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St. Lawrence University receives $1.2 million grant to integrate sports analytics in education

Posted

CANTON – Using part of a $1.2 million National Science Foundation grant, St. Lawrence University will use sports analytics as an educational tool to develop a series of materials that will prepare the next generation of statisticians and data scientists.

"We know that sports motivate a lot of students," Michael Schuckers says. He's the Charles A. Dana Professor and chair of the Math, Computer Science, and Statistics Department at St. Lawrence. "So, we'll be using data from sports beyond those most associated with statistics. Instead of baseball or hockey, we'll analyze Olympic sports, equestrian, cross country, and others, even e-sports."

This is one way the project will break new ground.

"By analyzing these sports," Schuckers says, "we hope to bring in students who might not otherwise engage with sports data."

The NSF grant also offers opportunities for St. Lawrence students to work with high-profile athletes and sports broadcasters.

"We'll be able to hire students to conduct research and collaborate with sports personalities who are popular in the media, for example, the former head of statistics and data analysis at ESPN."

To be awarded the funding for this work, St. Lawrence is collaborating with five other institutions on this project: Yale University, Carnegie Mellon University, Baylor, University of Pittsburgh, and the U.S. Military Academy (West Point). By working together, these schools hope to engage a diverse population of faculty and students that has the potential to broaden the data science workforce.

Schuckers says the four-year grant will support the creation of data-science course materials, which will be broken down into modules.

"Each module will showcase multiple steps for working with data. Together, faculty and students will decide how to collect and parse data, build and assess appropriate models, and communicate the results. The modules will then be reviewed and refined to ensure clarity and accessibility for undergraduates at varying educational stages and within multiple disciplines."

Schuckers believes this project will have an enduring impact on St. Lawrence and current students. He says, "We should be able to take the project modules and be among the first in the country to test them and actually use them in the classroom."