Podcast Episode #6 – John Tobias – ESPN and UNC Charlotte

In our sixth episode of the Sport Analytics Podcast, host Amrit Vignesh sits down with John Tobias, an on-air TV Statistician at ESPN, Program Director of Sports Analytics at UNC Charlotte, and Founder of the Strength in Numbers nonprofit. From producing real-time metrics on ESPN broadcasts to building one of the few collegiate sports analytics internship programs in the nation, to forging open pathways for underrepresented students, John embodies how passion and purpose can reshape the field.

John explains why following your passion isn’t just a cliché but a legitimate path to long-term career success. He shares how analytics pros can blend raw data with time-pressed storytelling in live broadcasts, reveals the growing demand for college sports analytics programs, and underscores why hands-on experience is essential in a fiercely competitive industry. John also spotlights his Strength in Numbers nonprofit, which hosts free sports analytics camps at USC, Columbia, and UNC Charlotte, and is committed to expanding opportunities for women and minorities.

Whether you’re intrigued by the high-pressure environment of live TV or want to design internship programs that empower students, this conversation offers a deep look into the evolving sports analytics landscape—and how we can all help make it more diverse and inclusive.

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📧 For inquiries or collaborations, contact Dave Yount at dave@sportanalytics.com.

Amrit (Host): Welcome to the sixth episode of the Sport Analytics Podcast. Today we’re joined by John Tobias, who is a TV statistician at ESPN. John, how are you doing?

John: I’m doing great. How about you?

Amrit (Host): Doing well! Thanks again for being here. You’re also a sports analytics professor and program director at UNC Charlotte, plus the founder of the Strength in Numbers nonprofit. Could you start by telling us about your journey from UNC Charlotte to ESPN, and key steps that led you into live broadcast analytics?

John: My journey’s probably more unconventional than most. I actually didn’t major in anything sports-related in college and started in finance, working for companies like American Express and Bank of America. But I hated it. It just wasn’t my passion. I realized success means doing something you truly love. So I recalibrated, went to grad school for sports management, got an internship with the NBA in Charlotte, and that opened doors. I began as a statistician for the team, which led to ESPN in 2013, and I’ve been there ever since.

Amrit (Host): On a typical game day for ESPN, how do you prepare for a broadcast, and what does it look like from pregame production to the final buzzer?

John: A TV talent statistician sits right next to the play-by-play announcer. We feed them real-time stats, like “LeBron scored the last 14 points,” or “Joe Burrow is 9-for-9 on third down.” I also share insights with the producer, like if a QB is especially efficient late in the fourth quarter. I rely on each team’s media relations department; they release game notes 24 to 48 hours ahead. I comb through them for historical trends or interesting angles that might pop up during the game. Then during the broadcast, it’s all about reacting fast and feeding relevant data as the action unfolds.

Amrit (Host): You only have seconds to provide on-air stats. How do you pick the right numbers, and what’s your strategy to make them quick to share with broadcasters?

John: Preparation plus foresight. It’s not just “Team A is on a 6-0 run,” but also advanced metrics that might come into play—like if Luka Doncic is 30-for-40 on free throws in the last two minutes. If he’s fouled late, that’s a stat people want to hear immediately. It’s about anticipating high-impact moments and having the data ready to go.

Amrit (Host): Could you share a moment where analytics really shifted a live broadcast conversation or offered a fresh perspective to viewers?

John: ESPN’s win-probability stats sometimes show 99% when a team is up big late. Then a Hail Mary or an insane rally happens, and we have to course-correct. I did a Baylor vs. Colorado football game where Colorado had a tiny chance left, but Shadour Sanders threw a Hail Mary, forced OT, and Colorado won. It flipped the script completely and was a lesson in how analytics can’t always predict the unpredictable.

Amrit (Host): Transitioning to UNC Charlotte: you launched a sports analytics program in 2019. What motivated you, and how has it evolved since its start?

John: I saw an article about Syracuse becoming the first university to offer a bachelor’s in sports analytics. It clicked—this aligns with what I do at ESPN. I pitched the idea to UNC Charlotte’s dean, started teaching one class in Fall 2019 with just 15 students. By the next semester, it jumped to over 50. Now we have three classes, I’m the program director, and we’re on track to be the fifth school in the country offering a full bachelor’s in sports analytics. It’s been a quick and exciting growth.

Amrit (Host): Your internship program supports 17 of UNC Charlotte’s 18 team sports. Why’s it so crucial for students to work directly with college teams?

John: Employers want hands-on experience, not just GPAs. I wanted an in-house internship program so undergrads and grads could provide analytics for our sports—football, basketball, soccer, etc. They get tangible projects to show prospective employers. It’s helped our students land full-time roles with teams like the Panthers, Charlotte FC, Nashville SC, and MLB clubs. Real-world projects make their résumés stand out.

Amrit (Host): Strength in Numbers, your nonprofit, teaches sports analytics to underrepresented groups. What inspired this, and how have partnerships with pro teams furthered your mission?

John: I’m African American, and in over a decade at ESPN, I’ve seen very few minorities or women in similar roles. Often it’s lack of resources or awareness. So I started Strength in Numbers to run free summer camps at USC, Columbia, and UNC Charlotte. We bring in industry pros, offer behind-the-scenes tours, and show these kids real opportunities exist. Partnerships with MLB and NFL teams let students present final projects and build confidence and networking. It’s about opening doors they never knew were there.

Amrit (Host): You recently mentioned a mentorship program where students presented to the Baltimore Ravens analytics team. How did that come together, and what was the impact on the students?

John: It began with the Philadelphia Phillies, then spread to the Detroit Tigers, and now the Ravens. We create analytics projects for local college students—like UMBC, Maryland, Towson—and after a few weeks, they present at the Ravens’ Under Armour Training Facility. We had 10 students selected out of nearly 300 applicants. Being in the Ravens’ war room is mind-blowing for them. They meet real analytics staff, pitch projects, and see their place in pro sports. It’s incredibly motivating.

Amrit (Host): Fewer than 10% of minorities and women work in sports analytics. How can schools and organizations close this gap in a practical way?

John: It’s about resources and leveling the playing field. Many great camps or conferences charge thousands, which some can’t afford. If you can’t attend, you miss out on networking and insight. By offering free camps and scholarships, we expand access. It’s not about lowering standards—plenty of talented women and minorities just need that initial exposure or funding to thrive. That’s the role we aim to fill.

Amrit (Host): Managing ESPN broadcasts is chaotic. How do you stay calm when last-second data requests pop up?

John: It’s organized chaos. Being prepared is key. You won’t have days to research one team’s stats; it’s happening in real time. You keep a cool head by focusing on the storyline or data that matters right then. If something big happens—like a big run or a late fumble—you jump on relevant data that fits that moment.

Amrit (Host): Viewers range from casual fans to data geeks. How do you balance in-depth metrics with easy-to-digest stats?

John: Keep it simple. We can skip the raw scraping details or advanced modeling. Instead, say, “Steph Curry is 8-of-13 from three when he gets the ball on a curl.” That’s advanced, but framed simply. It resonates, and watchers learn something new without being overwhelmed by jargon.

Amrit (Host): Where have you seen the biggest shift in TV broadcast analytics over the past decade, and what’s next?

John: It’s not slowing down, especially with sports betting. Companies like DraftKings, FanDuel—they need data experts. Even talk shows revolve around data visuals. AI-based tracking and probability models are on the rise, and it’s all about feeding that into broadcasts instantly, so fans and commentators can see trends in real time.

Amrit (Host): For students hoping to break into sports analytics (TV or otherwise), which technical skills matter most?

John: Python, R, and SQL are the big three. But don’t overlook data viz. Coaches and producers need quick, visual insights. They don’t have time for dense code, so being able to translate advanced numbers into simple charts can be the difference in getting hired.

Amrit (Host): What’s missing in some analytics curriculums, and how can we improve them?

John: They’ve got the fundamentals, but we need more AI integration and real-world practice. Technology evolves so fast. Keeping up with new tools and having instructors who can share cutting-edge methods is vital. Hands-on projects are also crucial so students graduate with tangible experience.

Amrit (Host): Any final advice for analysts aiming to enter sports, from ESPN-like roles to team or betting firms?

John: Two things. First, get as much experience as you can—internships, side projects, free grunt work. Employers want real examples, not just GPAs. Second, follow your passion. I was miserable in finance but found happiness in sports analytics. People might say “don’t chase your dreams,” but I disagree. Doing what you love is sustainable and leads to real success. If it worked for Steve Jobs, Oprah Winfrey, Mark Cuban—it can work for you too.

Amrit (Host): Thanks, John, for joining us. Your insights are inspiring, and I’m sure many viewers will benefit.

John: Thank you! I appreciate the opportunity.