Fit:match AI at MLS HQ: The Case for AI Bio Banding in Youth Development

This week, Fit:match AI CEO Haniff Brown and Head of Product Asna Khan joined fellow MLS Innovation Partners at the league's new New York City headquarters for a day of conversations about how technology is shaping the future of athlete development, performance, and long-term player outcomes.

Being in that room alongside some of the most forward-thinking minds in sports technology was a reminder of how much the industry has shifted. The question is no longer whether data should drive athlete development decisions. It is how to make that data more accurate, more accessible, and more equitable.

The Conversation We Came to Have

For Fit:match, the session was an opportunity to advance a topic that sits at the core of what we build: AI Bio Banding in youth soccer.

Bio banding is the practice of grouping young athletes by biological maturity rather than chronological age alone. In youth development, a 14-year-old who is physically mature can look completely different from a 14-year-old who is still two years away from their growth peak. When coaches and scouts evaluate players purely by age group, late developers are routinely overlooked, and early developers are overestimated.

QuadraScan, Fit:match's AI body scan technology, addresses this directly. In seconds, using only a smartphone, it generates body composition metrics that would traditionally require a DEXA scan and provides biological maturity indicators including Peak Height Velocity data. For the first time, clubs and academies can understand where each athlete is in their physical development journey without expensive equipment or lab visits.

That is the foundation of AI Bio Banding: pairing biological maturity data with chronological age to create more informed, more fair athlete pathways.

Why This Matters for MLS and Youth Soccer

MLS has made a significant commitment to youth development through MLS NEXT. As that pipeline grows, so does the need for standardized, scalable tools that give every player a real look regardless of where they are in their physical development.

The players who get cut at 13 because they have not hit their growth spurt yet are not necessarily the players who lack talent. They are often the players the system simply was not designed to see.

Fit:match is working to change that.

Building the Future Together

The conversations at MLS HQ reinforced what we already believe: the future of sports performance will be more individualized, more data-driven, and built on collaboration between technology partners, clubs, and the league itself.

We are grateful to MLS for the continued partnership and to every organization in that room for sharing in this vision. There is real work to do, and we are glad to be doing it together.

Want to learn more about how Fit:match AI supports youth development programs? Contact us.

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