Favoring an old-school approach, Michigan coach Tracy Smith wasn’t an early adopter of new-wave analytics.
It was some time between 2013 and 2014, before Smith was the head coach for the Wolverines, when he met this wave of change. Then, he was coaching a powerhouse Indiana team to a College World Series run. Talented and confident, but largely stuck in their ways, Smith and his team were indifferent to the emerging world of baseball analytics.
“We’re playing at Texas Tech,” Smith told The Michigan Daily. “Three weeks earlier they reached out, some data analytics companies, about ‘Hey, we plot all the bats and shifts and things like that.’ I remember I was like ‘We don’t need that. Why do we need that stuff? We know where guys are going to hit.’ ”
Smith carried that mindset into the weekend. Meanwhile, other programs evolved in this new analytics-driven era, finding a leg up. As his team got picked apart by position shifts and well-placed defense, the cost of his ignorance became painfully clear — and it stung.
“They were doing all these massive shifts based on the analytics and things,” Smith said. “They obviously had the software. … We dropped four baseball games. I remember flying back and I go ‘We are ordering that data analytics stuff.’ And we literally did it the next week.”
Over a decade later, Smith is now head coach at Michigan in a program — and a sport — where data analysis is deeply ingrained. Baseball is a numbers game, there’s no denying that, and data analytics has cemented itself as a vital tool.
But while numbers are the foundation of analytics, their implementation is what matters.
If wielded correctly, the numbers can carve out victory. But wield them with too heavy a hand and you risk cutting away the nuance, the instinct and the feel that has always guided the game. That’s where the people come in — they are the balance between spreadsheets and instincts, between code and context, between numbers and the athletes.
“You’re a fool to ignore it,” Smith said of the role of data analysis. “But I still think the human elements are important. It’s a combination.”
It’s that balance and combination that defines the role of people like Hunter Satterthwaite, the Wolverines’ Director of Data Analytics and Video Systems. He mixes interpretation and innovation, and is the invisible hand behind many decisions. Satterthwaite is tasked with finding the equilibrium between hard metrics and the unpredictable reality of student-athletes on the field.
Behind him is a team of student assistants and managers that are in charge of collecting data, setting up TrackMan, creating reports and so much more. They’re the ones setting up equipment well before a game and the ones sitting behind laptops long after practice ends.
While it makes it look like just a neatly labeled spreadsheet, each one carries a story. Decisions aren’t made in a vacuum, rather, they are forged from real human judgements and at the core every number are people who gathered it, interpreted it, and made it matter.
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Before he was the Director of Data Analytics and Video Systems, Satterthwaite was just another data science major at Michigan with a passion for baseball. And like many of the student managers now under his wing, he didn’t wait for an invitation to get involved.
“I reached out to (a mentor) and I was like, ‘Hey, I’d love to help out the baseball team,’ ” Satterthwaite told The Daily. “And so I started my sophomore year just being a student manager.”
What started as helping set up for practices, catching bullpens and doing whatever the team required quickly evolved. Working under then-pitching coach Chris Fetter and assistant coach Michael Brdar, Satterthwaite was introduced to a new frontier: How numbers, code and analysis could pave the way for a new understanding of baseball.
With TrackMan technology having been recently installed, Satterthwaite utilized his background to translate the data into something useful. His education aligned perfectly with his passions and curiosity, and he found mentors in Fetter and Brdar that valued the same balance that he now preaches — analysis and interpretation with a human touch.
“They were super smart, super passionate and really, really good with blending the analytics and baseball and kind of every facet into one easy and actionable message for the players,” Satterthwaite said. “I think the reason I enjoyed working with them so much is they would always come into the office and be like, ‘Hey, I’ve been thinking about this. I want to test that theory, can you help run the numbers on it.’ ”
The process evolved as the years went on. Now, Satterthwaite is the one guiding students through the same process — testing theories, finding patterns and building systems that turn raw information into something meaningful.
One such student manager is Karlyle Yarema. Yarema found his way to the baseball team in a similar fashion to Satterthwaite, wanting to stay close to the world of baseball even if he wasn’t playing. Four years later, he is the head student manager.
Much of the role revolves around what you may expect of a student manager, such as setting up practice and coordinating field setup. But he carries an additional responsibility in handling tools like TrackMan and BATS, two data systems that track every pitch’s movement, velocity and spin, along with multi-angle video. Staff relies on data collection and it’s the student managers who get the job done.
“It’s definitely something behind the scenes that not everybody knows about,” Yarema told The Daily. “We have a lot to do with helping, making sure everything is running properly whether it’s making sure drills are set up the way they are supposed to be or collecting the data properly so Hunter can actually use it.”
Many do not know about, or even acknowledge, this commitment, but without the work of students like Yarema, the systems don’t run and the numbers lose their meaning.
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It isn’t just the creation of data models and analytic tools that require a human touch — it’s their application as well. Understanding every player and every aspect of the team is a huge piece of things. Satterthwaite’s job covers everything from player development and lineup creation to scouting and even recruitment.
“As we’re making a lineup for the weekend…we sit and talk about ‘Are there any outliers and statistics that I maybe just don’t see visually?’ ” Smith said. “So all of that material is assembled, and then they use that…and then watching with your eyes if a guy’s having a good at-bat you may go a little against the data. It’s a combination.”
This combination and balance is central to the way Michigan baseball uses analytics. Conversations pre-game and in-game allow for the constant adjusting of strategies based on what is happening live. Whether it’s evaluating how a hitter matches up against a tough closer or deciding whether to stick with a pitcher mid-inning, these decisions are shaped by both the numbers and the on-field situation.
Much of the data work for the team centers around pitching, where a player’s control over movement and velocity allows for the most optimization. But even here, the staff makes sure to not let information become a burden.
“There’s some players that can think really analytically, that enjoy looking at that and can also perform,” Satterthwaite said. “There’s also some players who, if they get too heavy or too deep into the numbers, it’s paralysis by analysis.”
This philosophy threads through the entirety of Michigan’s analytics approach. Rather than drowning players in metrics, the staff filters information based on an individual’s learning style and mindset. While some respond to detailed breakdowns and pitch movement charts, others improve through visual cues or direct feedback.
“We’ll make it available to them… and we can use it for teaching points, but we don’t overwhelm them with it,” Smith said. “And we don’t overwhelm ourselves with it as a staff as well.”
A huge part of the job is the personalization, the understanding of who needs what and when. The numbers aren’t gospel, they are just a tool to be interpreted, questioned and molded whenever necessary.
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It isn’t just a computer in a room that runs the numbers. It’s people that drive the analysis and that drives the team’s success.
Satterthwaite pores over data from behind his laptop, while student managers like Yarema work around the clock, setting up gear and logging every pitch. And all of their contributions, plus a lot of conventional baseball wisdom, materialize into Smith’s decisions. Looking at just the intellect or just the data renders the picture incomplete.
“Sometimes you’ll make a pitching change and righty (versus) left-handed matchups are traditionally the old eyeball test,” Smith said. “But sometimes you’ll make a change and bring a right-hander to face a right-hander. You’ll hear the crowd yelling ‘Oh what are you doing?’… Well the data says he is a reverse split guy.”
It’s decisions like this — decisions that those watching may not understand — that show just how collaborative, personal and nuanced this work is. Behind the numbers, there’s an intricate balance between technology and humanity. For Michigan, that balance is embodied by people like Satterthwaite, who bridge the gap between raw data and real-world application. And the Wolverines’ success is not from the numbers itself, but from those who understand how to harness them — blending intuition, experience and teamwork to make every decision count.
