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Ever wondered what it would be like to sit behind the bench at a college basketball game—not as a fan, but as part of the team?
Through Professor Matt Bakowicz’s “Courtside Classroom,” a select group of students at Kogod are gaining real-world sports analytics experience by collecting live basketball data and using artificial intelligence to help analyze performance for the AU Eagles. Students sit behind the team bench during practices and games, track real-time statistics, and apply AI tools to understand how basketball data shapes coaching decisions.
For students who are passionate about sports—and curious about careers in sports business, analytics, or front offices for a professional team—this isn’t just a class assignment. It’s a chance to step into the world of modern sports strategy while still in college, building real skills with a real team.
What is Sports Analytics—and Why Does It Matter in Modern Sports?
Sports analytics uses data and statistical modeling to improve team performance and decision-making. Today, analytics influence nearly every major sports decision, including:
- When an NFL team should go for it on fourth down
- Which shots basketball teams should prioritize
- How teams build optimal lineups and rotations
- Player performance evaluation and scouting
Analytics has become essential across the sports industry, from college programs to professional teams. That’s why learning data analysis, AI tools, and sports strategy has become increasingly valuable for students interested in sports careers.
What Is Kogod’s Courtside Classroom?
Kogod’s Courtside Classroom allows students to work directly with the American University men’s basketball team by collecting and analyzing game data. Students essentially act as a student-run analytics team, providing actionable information that could help improve team performance. Throughout the season, students:
- Attend practices and games
- Track dozens of performance metrics in real time
- Log detailed basketball statistics into large data sets
- Use AI tools to analyze patterns and trends
- Share insights with the coaching staff
“It’s our budget-savvy solution to the growing need of analytics at the NCAA level,” Prof. Bakowicz said. “We may not have the full-time analytic staff that ‘Power 4’ programs do, but we have the data, tools, and students who can make a meaningful difference for our team.”
How Students Use AI to Analyze Basketball Performance
Students in the program have already collected thousands of data points throughout the season. Every action on the court—from contested shots to rebounding opportunities—is tracked and recorded.
Using this data, students analyze:
- Shot selection and shooting efficiency
- Defensive pressure and contested attempts
- Lineup combinations
- Rebounding percentages
- Game strategy patterns
AI tools help students process this large amount of information quickly, allowing them to deliver insights to coaches faster than traditional manual analysis.
“If a student was interviewing for an internship with the Knicks tomorrow, they could walk in and say, ‘here’s our rebounding percentage in the last couple games, here’s what it looks like when these shots are contested, here’s how I can analyze this data,’” he said. “That’s a great tangible skill that I’m super happy they have.”
How Students Use AI to Predict March Madness Outcomes
Now that the NCAA tournament is underway, students have turned their attention to using AI to predict outcomes for brackets. That’s part of class, too.
On Selection Sunday, the day the tournament seeds are drawn, students kicked off another AI analytics project that will last all March Madness long: the Bracket Battle. It’s a simple contest, much like ESPN’s Bracket Challenge, where students rack up points by correctly predicting the winners of all 67 games. It sounds like fun (and it is!), but it’s also another good example of how the statistical models and AI tools they learned how to use courtside during the season can come in handy.
How Sports Analytics Experience Helps Students Build Careers in Sports
Hands-on analytics work gives students a major advantage when pursuing internships and careers in the sports industry.
Students in the program develop skills such as:
- Data analysis and statistical modeling
- Sports performance analytics
- AI-assisted data processing
- Excel and data visualization
- Game strategy evaluation
These are the same types of skills used by analytics departments across professional sports.
What Can Students Study in Kogod’s Sports Management Program?
Students interested in sports careers can pursue a Sports Management specialization within Kogod’s Business and Entertainment program. The program is designed to prepare students for sports industry careers in 2026 and beyond, combining business education with hands-on learning opportunities like the Courtside Classroom.
The 15-credit specialization will focus on the business side of the sports industry, including:
- Front office operations
- Sales and revenue generation
- Sponsorships and partnerships
- Sports analytics and data strategy
We’re very career-driven, so we’re going to focus on: what do you need to know to work in the sports field in 2026 and beyond? Winning basketball games is great, but learning skills to land jobs is the real point of the program.”
