By Tim Chartier, Davidson College
I’m a professor of mathematics and computer science who specializes in sports analytics. Professional teams and national media outlets call to get help from my students and me. Sound like a dream job? It is to me. But the best part isn’t the bright lights—it’s the everyday work of using mathematical thinking to answer real questions and, importantly, doing that work alongside students. Whether you’re a student wondering how to turn your interests into impact, or a professor helping students connect math to the wider world, here are a few lessons from my path that can help you get your career into the game.
Tip 1: Know your position—and play it well
People often assume I must be a walking encyclopedia of player stats. I’m not. I enjoy sports for the athleticism and the drama more than the box score. I’ve missed many games to play with my kids or take a walk with my wife—although she’s not always eager to miss the game. Still, professional teams call, and I founded a student group that delivers analytics to our college coaches.
How? I play my position. I analyze numbers and build models—that’s where I excel. Domain knowledge matters, and I’ve played enough sports to speak the language, but I don’t try to be everything. My research group is intentionally diverse: some students barely follow sports but love math and code; others can recall lineups from memory—and some do both. That mix is a strength. Deep domain knowledge frames the right questions, while fresh mathematical eyes spot patterns others might miss.
For students: Take stock of your strengths and limits. Are you the model-builder, the domain translator, the communicator, the coder, or the visualizer? Claim that role and develop it until coaches—or any stakeholder—can trust you with it. Wish you had a different role? Study it. Practice it. Build it into a strength that becomes part of your game.
For professors: Build teams with complementary roles. In a data analytics project, one student might lead feature engineering, another manage data cleaning, and another present results. Design grading to reflect both individual contributions and team outcomes—just like a well-coached roster. Learning to play a role and to grow within that role are both vital lessons for life after college.
Tip 2: Late-round draft picks have incredible careers
If you were ranking candidates for their promise in a sports analytics job early in my career, I would not have been a first-round pick. My research area was numerical partial differential equations. I moved into sports analytics through work on ranking methods with my collaborator, Dr. Amy Langville of the College of Charleston. We built new algorithms and tested them by generating March Madness brackets. Those models performed in the top few percent out of millions of brackets—enough to make people take notice. Every March now brings calls from TV, podcasts/radio, and newspapers—and, more importantly, new opportunities for students to contribute.
The point isn’t that you need a viral bracket. It’s that careers rarely move in straight lines. A project you do for fun or to test an idea might be the unexpected tryout that lands you on a new team.
For students: Don’t self-select out because you think you’re “late to the game.” Start small and specific: in data analytics, scrape one season of data, reproduce a published method, or re-create a visualization you admire. Share your process—you’re building tape for your highlight reel.
For professors: When possible, design assignments that can become public artifacts—reproducible notebooks, short technical blogs, polished posters. Help students see how coursework can become portfolio work. That highlight might just spark the conversation that opens a door in a future interview.
Tip 3: It takes skill and luck to play the game
Life, like sport, contains both skill and randomness. Your preparation, creativity, and persistence matter. So does serendipity—the email you didn’t expect, the coach who happens to ask a question you can answer, the dataset that appears at just the right time. Our bracket work required skill to design the method and luck that our approach matched that particular tournament. The methods have continued to perform well—often landing in the top percentiles—but not with stop-the-presses results every year.
What do you control? Your readiness. If luck is the ball bouncing loose at midfield, skill is being in position to collect it. Keep learning, ship small projects, reflect on mistakes, and stay coachable. That way, when opportunity rolls your direction, you’re already moving toward it.
For students and professors: Normalize the role of chance. In debriefs, ask: What did we do well? What was lucky? How could we make that luck more likely next time? This mindset builds resilience and reduces the fear of trying ambitious work.
Tip 4: Have a game plan—and call timeouts to re-plan
“Who do you want to be?” is a far more useful question than “What job title do you want?” Two goals shape my professional life: (1) work closely with students so they become independent creators of knowledge, and (2) be active in my family life. Sports analytics fits that plan. Students co-lead our group, meet with coaches, and present to teams. Shifting to applied analytics also created local collaborations that simplified family logistics, especially in summers. The work is fulfilling at the office and at home.
Plans, however, need timeouts. Circumstances change, interests evolve, and new opportunities emerge. Pause, check the score, and redraw the play. Early in my career, that meant stepping from PDEs toward rankings; later, it meant broadening from rankings to player evaluation and strategy. The throughline wasn’t a title—it was a set of values.
For students: Write down three “north stars” (e.g., creativity, impact, collaboration). Use them to choose electives, internships, and side projects. If an opportunity doesn’t move at least one star forward, think twice.
For professors: Make reflection an assignment. Ask students to submit a short “work statement” with a project: what they tried, why it mattered to them, and what they’d change next time. These reflections can help the project “stick” — becoming one of the lessons that lasts, among the memories of the class that don’t fade.
Tip 5: Play to win—by defining what a win looks like
Careers consume time and shape well-being. I try to make choices I can count as wins in more than one way. If a media appearance doesn’t happen, can the preparation become a class activity? If a project doesn’t interest a pro team, can it still help our college coaches? I rarely bet on a single outcome. I set up the work so progress—technical, educational, or personal—counts as success.
For students: Before you start a project, define two win conditions: one external (e.g., in data science, presenting to a coach or submitting to a data-viz challenge) and one internal (e.g., learning a new research skill or trying a new way to communicate your work). If the external win doesn’t land, the internal one still will.
For professors: Design projects that can be meaningful beyond the class—and make that possibility visible. Model how to evaluate an assignment’s value: why it’s a positive for the course and how it might also serve students beyond it. Share your own win-win thinking so students learn to apply the same mindset to their work.
So, what will be your dream job? It depends on who you are—and who you’re becoming. I expect to be in sports analytics for a long while, but the joy isn’t in holding onto a label. It’s in treating life like research: dive in, study, get confused, discover, and keep exploring. That habit of mind travels well—from sports analytics to data science, from academia to industry, from math classrooms to locker rooms and back.
If you know your position, embrace late-round starts, respect the roles of skill and luck, revisit your plan, and define wins that truly matter to you, you won’t simply “get into the game.” You’ll help shape it. And whether your game is in PDEs, rankings, or analytics you can move in the direction of a big win.
Tim Chartier is the Joseph R. Morton Professor of Mathematics and Computer Science at Davidson College. He specializes in sports analytics and works with students on projects with professional teams, while also collaborating with and supporting Davidson Athletics.