MSA Alumni Spotlight
Chris Mast (’17)
CEO & Founder, Lean Basketball Analytics
Atlanta, Georgia
About Chris
Hi, I’m Chris Mast, CEO and founder of Lean Basketball Analytics, based right here in Atlanta. My core mission is to help coaches make smarter, data-driven decisions. I’ve developed a patented analytics platform that gives coaching staffs the tools to strategize more effectively by logging in and accessing actionable insights.
But it’s not just about the platform—I also work directly with coaches on a consulting level. I dive into the data alongside them, using custom scripts and analysis to help identify the best strategic paths for their teams.
And it’s not only for coaches. Just before March Madness, I launched the AI Bracket Calculator—a tool designed for fans to make smarter picks and track their brackets with the help of data and predictive modeling.
How do you use analytics or data science in your day-to-day work?
In my day-to-day work, I use analytics to help coaches turn raw data into actionable strategy. One of the most rewarding parts is working directly with them—whether they’re reviewing the data themselves or I’m walking them through it during a consulting session. There’s always that moment when things just click—when they suddenly see how the numbers can inform their next move. It’s exciting to witness that shift in thinking, where data starts to drive strategy in a very real way.
What’s even more powerful is seeing the impact on the court. Recently, I worked with a coaching staff at a smaller Division I program. They ended up winning their conference and made it to the national tournament. After that season, both coaches landed head coaching roles at larger programs.
Now, I’m not saying analytics was the only factor in their success—but it absolutely contributed. My goal is to provide insights that help coaches make better decisions—whether it's adjusting matchups, fine-tuning game plans, or spotting patterns that give them an edge. Data science in my world is all about enabling smarter, faster, and more confident decision-making.
What do you enjoy most about your job, especially when it comes to working with data?
What I enjoy most is seeing the direct impact data can have in a real-world setting — especially in sports. For example, right before I graduated, I collaborated with the Phoenix Suns on a lineup data analysis project, which was part of my own startup as well. It was an amazing experience to combine innovation and real team strategy like that.
Later, through Lean Basketball Analytics, I sponsored a practicum project for the MSA cohort focused on calculating expected points per shot. Basically, as soon as a game ends, our code runs an algorithm that estimates the probability of each shot going in — giving us a quality metric for every shot attempt. Coaches use this data to refine their strategy, and it’s incredibly rewarding to know that something we built is influencing coaching decisions across the globe.
That connection between technical work and meaningful, tangible outcomes — that’s what I love most about working with data.
What MSA skill, class, or project helped you get your job or grow in your career?
One of the most impactful classes I took was a data visualization course. On the surface, it was about best practices—how to present data clearly and effectively to stakeholders. But what I really took away was a deeper understanding of how to match the right type of data with the right kind of visual. That insight ended up saving me a lot of time down the road.
For example, when I was working for the Hawks team, I knew exactly how to present performance data to the training staff in a way that was both clear and immediately actionable. And now, with Lean Basketball Analytics, that lesson carries over into how I build reports and dashboards for coaches—translating complex metrics into visuals that actually drive decisions.
What surprised me most was how practical and long-lasting that course turned out to be. I didn’t expect it at the time, but it fundamentally shaped how I communicate analytics every day.