Why did the NHL’s Pittsburgh Penguins hire a 22-year-old data scientist?

An NHL franchise with a track record of success on the ice is trying to embrace next-generation data analytics and technology to keep winning in the future.

On the heels NHL skates introducing the puck and player tracking in 2019, the Pittsburgh Penguins hired 22-year-old Katerina Wu, who just graduated with a bachelor’s degree in economics from the University of North Carolina at Chapel Hill, to work for the team as a data scientist.

Reporting to the Penguins’ Director of Hockey Operations and Hockey Research, Sam Ventura, Wu will design and implement new statistics to assess player and team performance.

The daughter of a research scientist, Wu interned at the company that provides the NHL with puck and player tracking data and previously worked under Ventura as part of the Hockey Graphs mentorship program during the season. 2019-2020.

“We are delighted to add Katerina to the Penguins’ organization,” said Ventura. “She is uniquely qualified to work in hockey because of her expertise in sports analysis, impressive technical skills, experience working with complex puck and player tracking data, and knowledge of the game. with Katerina over the past two years we were well aware of her skills and potential.

Wu’s hiring is just the latest example of the Penguins organization’s commitment to embracing analytics. This commitment dates back to 2015, when former Deputy Managing Director Jason Karmanos offered Ventura, who earned a degree in Computer Finance from Carnegie Mellon University, the opportunity to join the team as a consultant. Since then, Ventura’s role has grown considerably as he now heads an entire department.

Using data derived from puck and player tracking technology, Ventura and his team, which now includes Wu, attempt to find a competitive edge over their opponents by analyzing news rather than game movies.

“The data currently available publicly really focuses on specific events that occur on the ice,” Ventura said last year. “One shot. One hit. One face to face. Things like that. This data is fundamentally different. Instead of just looking at specific events, it gives you the locations and trajectories of all the players on the ice and the puck, every moment. It lets you watch things that you might never even begin to explore with data otherwise, things like the positioning of defensemen and goaltenders, the space created by particular players.

Sean N. Ayres