Boasting a Dunk Score of 127.7, Washington Wizards forward Justin Champagnie was credited with the top slam of the season. Meanwhile, Dallas Mavericks’ Cooper Flagg became the youngest player in National Basketball Association history (at 19 years and 105 days) to post back-to-back 45+ point games.

Leading the teams responsible for distilling NBA data points into stats that engage and educate fans, coaches, and media alike is Jarvis College of Computing and Digital Media alumnus Charles Rohlf (MS ’11), Vice President of Stats Technology Product Development for the NBA.

“We’re not telling you what should have happened on the court – that’s for the coach and players to know. We’re telling you what did happen,” says Rohlf of his team’s work.

As an undergraduate computer science student at Duke, Rohlf worked as the student manager for the university’s basketball team under the legendary Coach Mike Krzyzewski ("Coach K").  He later went on to earn his master’s in computer science at DePaul while coaching a high school basketball team. Combining his two biggest interests makes for a “perfect fit,” according to Rohlf. In fact, for one of his DePaul computer vision classes, he analyzed a video of his team playing—a project that turned into his thesis.

Today, Rohlf leads teams of software engineers, data scientists, and product managers responsible for the NBA and WNBA’s statistical infrastructure. Together, they use the latest tech and data science techniques to gather insights while keeping those insights approachable and understandable to their audience.

Learn more about Rohlf and his role in this Q&A.

Tell us a little about your role as the Vice President of Stats Technology Product Development for the NBA. 

I lead the teams that build and run the technology behind how the stats of the game are measured, understood, and ultimately experienced. At a high level, my job is to make sure every piece of data that describes what happens on the basketball court is accurate, reliable, and delivered in a way that creates value for the league, our partners, and fans.

I oversee a team of software engineers, data scientists, and technical product managers responsible for the NBA’s end to end basketball data platform. This includes ingesting live game data, applying AI/ML to create new insights, and delivering clean, scalable data across the league ecosystem.
 

What are you and your team working on currently?

Our overarching mission is to educate and engage fans with the data we have.  We have a computer vision system that gathers (x,y,z) locational tracking data on 29 body parts for every player on the court 60 times per second throughout the full game.  Add in (x,y,z) tracking on the location of the ball as well, and we have an incredible data set with which we can educate and engage fans.

We’re currently using this data to create new stats and insights for fans through our Inside the Game Platform.


How might the data sets your team gathers—or the insights based on that data—differ depending on the audience or end user? 

The game is evolving, and so are the questions people want to ask of the data — whether that’s teams looking for competitive insights, broadcasters telling more compelling stories, or fans engaging with the sport in new ways. Our goal is to create the technical foundation that makes it all possible, while ensuring data quality, consistency, and trust at every step.

Ultimately, the data is the same for each use case but we frequently use AI / ML to generate different insights tailored to each individual instance. 
 

How did your master’s in computer science from DePaul prepare you for your first role after graduation ? 

First, it gave me a strong foundation for thinking about problems the way I would eventually need to in the real world.  And it wasn’t just technical skills; it was also the soft skills needed to understand the bigger picture and propose logical solutions.  

The flexibility DePaul offered through hybrid learning allowed me to fit the course work to my schedule and identify a thesis topic that merged my passion for basketball with computer vision.  I’m forever thankful to my advisor, Dr. Daniela Stan Raicu, for her guidance and for encouraging me to explore an out-of-the-box theme.

In my current role, that foundation still shows up every day. I’m not writing code full time anymore, but I’m constantly evaluating architecture, reviewing technical decisions, and helping teams think through long term platform strategy. The ability to understand systems end to end and speak a common language with engineers, data scientists, marketing teams and product managers, among others is something I trace directly back to that graduate experience.

As the tech landscape continues to shift - including adoption of AI, increased cybersecurity threats, cloud computing and more - what advice would you give a student pursuing a computing/tech degree today?

One of the main keys to success in my view is that you’re passionate about the industry. This passion translates to curiosity that will build your knowledge base, which will help you develop effective solutions to technical challenges and make the most of the opportunities that will present themselves. This institutional knowledge will also make you a better communicator across different groups in your organization, which is paramount in any industry.