Genius Sports Innovation & Technology Culture

How does your team stay ahead of emerging technology trends while scaling fast?

My team at Genius Sports sits at the heart of sports data, fan engagement and advertising, which gives us a unique vantage point. While technology cycles move fast, our partners need to build lasting connections with fans. We focus on the products and platforms that power brands, broadcasters, leagues and teams to connect with them at exactly the right moment.

By aligning the team around these trends, experimentation becomes focused rather than random. New technologies are evaluated based on whether they accelerate those shifts or create measurable value for partners. That helps us innovate quickly without chasing every new tool or trend.

What recent product or feature are you most proud of — and what impact has it had?

The product I’m most proud of recently is the Moment Engine, because it changes how advertising works in live sports. Almost nowhere else do millions of fans react to the same play at the same time. Historically though, advertising hasn’t been built to respond to that, with media bought in advance and ads running regardless of what’s happening in the game. 

The Moment Engine translates live game events into real-time advertising signals using official sports data. Key moments like a red zone drive, buzzer-beater or comeback scenario can trigger signals that influence bidding, activate contextual deals, or power dynamic ad experiences. 

The impact has been twofold. First, it creates new premium inventory and moment-based deals that brands actually want to align with. Second, it connects the game, the fan and the advertising marketplace in real time. Ultimately, it moves sports advertising from static placements to moment-driven activation, allowing brands to show up when fan attention and emotion are at their peak.

How do you create a culture where innovation and experimentation are encouraged daily?

Innovation tends to happen when teams feel both ownership and safety to try things that might not work. We encourage this by making experimentation part of the daily workflow, rather than something reserved for special projects. 

First, we anchor teams around clear strategic problems instead of rigid feature roadmaps. When people understand the outcome we’re trying to drive, whether that’s improving fan engagement or unlocking new advertising value, they have room to explore different ways to solve it. 

Second, we encourage fast, lightweight experimentation. Not every idea needs a full product cycle. Prototypes, partner pilots and small tests allow us to learn quickly and scale what works. 

Third, we keep tight feedback loops with customers and partners. When engineers, product managers and commercial teams see how their work performs in the real market, it naturally drives curiosity and iteration. 

Finally, leadership reinforces that smart risks are valued. If teams know thoughtful experimentation won’t be punished when something fails, they’re far more likely to push boundaries and innovate consistently.

What’s it like to work on the AI and machine learning team at your company?

As a software engineer on the Soccer AI team my work is centered around GeniusIQ, our next-generation data and AI platform.

In particular, I focus on data generation, or what we call soccer semantics: turning the raw materials from our high-resolution event and tracking data into real soccer meaning.

I have the opportunity to work with what I believe is the most detailed, advanced tracking and event data in the industry. With this, we work on some of the most interesting and challenging problems in the field for the biggest leagues and teams in the world.

In my role, new modeling development is especially interesting. My process heavily utilizes historical games and exploring the results of a new run within the context of Performance Studio, our data and video platform for top-level video analysis.

Typically, I'll have code on one monitor and a constant stream of match footage on another. That's something I certainly wouldn't do in another job!

How is your team applying emerging technology in practical, business-relevant ways?

Our goal is to be the "operating system of modern sport," so our work is naturally wide-ranging in scope: from team performance, to media, broadcast and betting.

There are over 3 million center-of-mass tracking data points in a single game and our skeletal tracking increases this by an order of magnitude. From that data, we provide detailed physical metrics for all players and referees throughout each game.

These have numerous applications powered by GeniusIQ, from player performance, to fantasy games and even evaluating refereeing performance. The possibilities are limitless and our software needs to be highly accurate and flexible to extend to any number of new use cases.

What should candidates know about the tools, collaboration or problem-solving involved in AI work at your company?

Our systems are expected to run live at low latency with high accuracy, all integrated into a large, distributed architecture. That means stream processing is a key part of our work. We manage race conditions, asynchronous updates and state management across distributed workers, all at low latency.

Cooperation is massively encouraged here. Every team member brings their own unique skills and interests and some of the most interesting ideas lie in the connections between seemingly unrelated domains. We've drawn ideas from other sports, chess engines and even cancer biology. We're encouraged to take initiative and explore problems that we find important.

Most importantly, our teams are composed of not only talented, but passionate engineers. It's hard not to be passionate about working in sport and Genius is full of people who take initiative in driving not only our company's technology forward, but also the field as a whole.