From U-M to the Big Leagues: How a data science alum became a baseball analytics pro

U-M alum Danny Vargovick is leveraging his data science degree to build prediction systems for the Detroit Tigers.
Danny Vargovick (torso up) wearing a black button-up shirt, smiles at the camera. He is sitting on a wooden bench in the Detroit Tigers dugout.
Danny Vargovick, pictured at Comerica Park. Photo credit: Allison Farrand / Ilitch Sports.

From the halls of “the Dude” on University of Michigan’s North Campus to Comerica Park, home of the Detroit Tigers, alum Danny Vargovick’s (BSE Data Science 2017) professional trajectory has been anything but typical. His path from an ambitious data science student at U-M to a key player in data analytics for a Major League Baseball team showcases a blend of technical mastery and a lifelong love of the game. We recently spoke with Danny about his journey in baseball analytics, a testament to the transformative impact of a U-M education in sports and beyond.

Can you briefly summarize your background (e.g., where you’re from, your educational background including U-M, your career trajectory)?

I’m from Northville, MI and went to Detroit Catholic Central High School in Novi, MI. At Michigan, I was a Data Science Engineering major and a Ross Business minor. I did the Engineering Honors Program as well. 

The Data Science program prepared me incredibly well for working in baseball analytics. Classes like EECS 281 give you the reps you need writing code—even if you never use C++ again, and classes like EECS 445, Machine Learning, provide much of the technical knowledge you need in an entry level position. 

I was also involved in The Michigan Daily and was a member of the baseball beat for one season. This helped me convince ML organizations that I had a passion for baseball which is important to separate yourself from other applicants. It was also a great way to meet friends with similar interests. During welcome week freshman year—over ten years ago—I actually met my current roommate who now works for the Tigers as well in Communications. 

In baseball, it’s common to take internships after graduation. It was a bit disconcerting to be making minimum wage after graduation, but I’m lucky enough to have a great support system to allow me to take risks like that, and I shared a bedroom to keep costs down. 

When I joined the Tigers, the analytics department was very young. By pure luck, I happened to graduate at the perfect time to be given a ton of responsibility early in my career. This fall I was promoted to Assistant Director of R&D and now have other analysts reporting to me. 

Can you describe your current job?

My main job is to build projection systems to predict player performance for use in player evaluation and acquisition. I used to build models for both the amateur draft and pro evaluation, but since our team has grown I now lead our team working on our pro projection system and focus most of my effort there.

Did you always know you wanted to go into the sports industry? What made you interested in this area?

This has been my dream job since middle school. As a senior at Michigan, working in baseball was my reach goal but I truly didn’t believe it would happen for me until I got an offer. 

I’ve always been fascinated by player evaluation and roster building. Baseball, with 162 games, discrete events, and the importance of the batter-pitcher matchup, has always been the major sport that could most easily benefit from statistical methods. I read baseball analytics sites like FanGraphs voraciously in high school which intensified my passion for the game and desire to work in baseball analytics. 

What were some highlights of your time at U-M?

The best part of my Michigan experience was the people. Michigan is a special place filled with people ready to challenge you, push you, and support you at any moment. And it’s a big enough place that no matter what you’re looking for, there’s some sort of club or group of people looking for the same thing. 

I really enjoyed being a part of The Michigan Daily, MECC Consulting Group, and the Engineering Honors Program. The summer after my junior year, I went with Honors to Peru for three weeks to do rainforest conservation volunteering and then hike Machu Picchu. We had a great group and it was a ton of fun—even though I made a pit stop in a Cusco emergency room. 

With The Daily, we played MSU’s student paper in a flag football game every year before the actual football game. Unsurprisingly, we took it way too seriously. My senior year, we were losing at halftime, and then I went in as quarterback and we came back to win. We sang The Victors at Munn Field in East Lansing and afterwards current Red Wings beat reporter Max Bultman hung up my shirt from the game at The Daily to retire my jersey. While we all knew it didn’t actually matter who won a pickup football game between a bunch of student journalists, it’s a memory that means so much to me.

Danny Vargovick wears a neon yellow t-shirt and sunglasses and faces the camera, smiling. Behind him is a mountainous landscape. In the middle ground is Macchu Picchu, a collection of stone ruins.
Danny pictured at Macchu Picchu, which he hiked as part of his volunteer trip to Peru with the Engineering Honors Program at U-M.
A group of about two dozen students stands in front of.a large wooden sign in Spanish, smiling at the camera. The front four people are holding a dark blue flag with a yellow block M on it and the words "Engineering Honors Program"
Danny pictured with the rest of his Engineering Honors Program during a trip to Peru, where they volunteered on a rainforest conservation project.
Danny, mid-sprint, in a yellow shirt, black shorts, and holding a football. He is pursued by a man in a black shirt who is lunging after him with an arm outreached.
Danny (right) played on the The Michigan Daily’s flag football team in their annual match against the Michigan State student paper. He helped the team secure a thrilling victory his senior year.
A crowd of around 40-50 people, all wearing Maize and Blue clothes, sitting, kneeling, and standing. They are smiling at the camera, some holding up peace signs with their hands.
Danny pictured with The Michigan Daily flag football team

What made you interested in data science/why did you choose to major in data science?

I came to Michigan not knowing what I wanted to do. Both of my parents are Michigan mechanical engineers, and I wanted to do something in STEM, so they pushed me to start in engineering thinking that was the most likely fit. At the end of my sophomore year, I was a computer science (CS) and industrial and operations engineering (IOE) double major. Without knowing what type of role was right for me, I had some understanding that coding ability was going to be a skill I needed even though I was sure I didn’t want to be a software engineer. Data science then became a major at the start of my junior year, allowing me to drop both CS and IOE. I was so eager to get into the DS program that when I went to declare during Welcome Week my counselor told me he was pretty sure I was the first student to declare DS. 

Looking back, an analyst role in any industry would have been a good fit for me since I have an obsessive personality and end up liking things a lot better when I can dive into the details of a complex system such as the sport of baseball. Data science gives you a great toolkit to model how something fundamentally works. I’m lucky that my dream of working in baseball pushed me into the perfect major for me.

How did a degree from U-M help you get to where you are now? Do you use knowledge or skills you learned in the data science program at U-M in your current position?

The data science program at Michigan was instrumental in helping me find a career in baseball. The position is first and foremost data science work, and I spend the majority of my time developing models. The CS core through EECS 281 was valuable to get reps writing and debugging code, and Machine Learning taught me concepts I use constantly. The data science program also allowed me to sample classes from other departments which I thought had real value. Even though I may not directly use my Decision Analysis or Economics classes often, I think the ways that those classes teach you to think have parallels to solving baseball problems. 

Why is data science important? How is it applicable to baseball and other sports?

Data science turns art into science in baseball and many other industries. Fundamentally, it’s a set of tools that can be used to gain knowledge that had been unobtainable before the age of modern computing. 

How does data analysis change how decisions are made in baseball/sports more generally?

In baseball specifically, we had over 53,000 games in 2023 across all levels—the majors, minors, international, and amateur. Without this data, we would be making decisions based only on the small fraction that front office members and scouts could actually observe. Then with this data, we can also use data science to control for variables exogenous to player talent such as ballpark or opponent. 

Making decisions without this data and the modeling we do would be an inefficient outcome for both the teams trying to win and the players spending a sizable portion of their lives dedicated to the game trying to make a living.

You’ve been with the Tigers for several years now. How have you seen the role of data analysis change over that period?

We do have richer datasets now than we did when I started with the installation of Hawk-Eye optical tracking systems in MLB. Hawk-Eye, which is also used in other sports such as tennis, provides us with ball, bat, and skeletal tracking.

The department is also much more mature than it was when I started. As our capabilities have expanded and more employees are working on an ever-increasing number of projects, model interpretability only grows in importance.

What are your goals and plans going forward?

Right now, I still fall asleep most nights and wake up most mornings thinking about how we can better model baseball. While I’m proud of the work I’ve done so far, there’s so much more we can do that it’s hard to have any goals beyond to keep plugging away at what we’re working on right now. More recently since I’ve been promoted, it’s been rewarding to see what we can accomplish with more personnel. 

Since I joined the Tigers, we’ve largely been rebuilding. I know everyone in the organization has a goal of bringing a winner to Detroit soon.