Science student uses data analytics on the court for the Virginia Tech men’s basketball team
Numbers matter in sports. The right performance data on every player on your team and on the opposing team can help make the right decision on the court.
Sean McClurg, a senior in the Virginia Tech College of Science from Wayne, New Jersey, knows this. For the past year, McClurg has helped the Virginia Tech men’s basketball team use player data statistics to help coaches create winning court strategies.
His on-court work with data stems from a lifelong love of basketball and numbers, as well as class lessons learned by McClurg as part of the computational modeling and data analytics program, part of the Academy of Integrated Science in the College of Science.
McClurg started as a team manager collecting balls and towels, but now works the sideline of the basketball court, pen and pad in hand, carefully watching every action by players. Then he watches game footage of the Hokies and of upcoming opponents. He tracks points, possessions, offense and defense efficiencies, turnover rates, and more. “During a game, I am kind of all over the place,” said McClurg. “I am always charting something, mostly our play calls and defensive coverage.”
He started tracking detailed player data on the side as a hobby of sorts, before bring the data to Mark Embree, a professor in the Department of Mathematics and head of the computational modeling and data analytics (CMDA) program. The work by McClurg has inspired other students in the College of Science to follow in his footsteps.
“Sean’s work has been a great inspiration to his fellow CMDA majors, many of whom have an interest in sports analytics,” said Embree. “For example, after he presented his work to our freshman class, one of our students eagerly wondered if she could provide similar analysis for the softball team.”
Data analytics in sports has been growing for years, both at the professional and college levels. The book and film “Moneyball” – following a series of stunning wins by the Oakland As in the early 2000s, all using data analytics focused on individual players – have brought the practice front and center to the public.