Opening Day 2026 arrived with a guest that’s been arguing its way into baseball for years: the Automated Ball-Strike Challenge System. Twelve Hawk-Eye cameras per stadium now track the strike zone. Players challenge calls by tapping their helmet. In the first 47 games, 94 calls were overturned.
Meanwhile, FIFA announced that every player at the 2026 World Cup will be digitally scanned, a one-second process that creates a precise 3D avatar for semi-automated offside technology. Their “Football AI Pro” system will analyze millions of data points per game in real time.
And according to the Global SportsTech Report 2026, 82% of sports organizations are now deploying AI, with 98% planning to expand their use within 12 months.
This isn’t hype. This is the current state of play.
I’ve been on the field for this
From 2015 to 2019, I worked as an NFL Game Day Operator for Zebra Technologies at every Jacksonville Jaguars home game. My job was to set up RFID chips in players’ shoulder pads and ensure the antenna array was functioning before kickoff. During games, I added metadata to each play as part of NFL Media’s data package that fed broadcast and stat partners.
That experience gave me a perspective that most people building sports tech don’t have: I’ve literally been on the sideline watching data flow from a player’s body to a broadcast truck in real time. I know what it takes to make that work reliably when 70,000 fans are watching and a $200 million quarterback is about to take the field.
The NFL’s player tracking system was early. What’s happening now across all sports is orders of magnitude more ambitious.
Where the opportunity is
The 82% stat from the SportsTech report is impressive, but it masks something important: most of that AI deployment is happening at the top, in professional leagues with massive budgets. The technology is trickling down, but slowly.
Here’s where I see the real opportunity:
Youth and travel sports are underserved. There are roughly 45 million kids playing organized sports in the US, supported by a sprawling ecosystem of travel ball organizations, tournament operators, and club programs. Most of them run on spreadsheets, group texts, and a patchwork of apps that don’t talk to each other. That’s the problem we’re tackling with the CBU App, building a platform that brings modern team management, scheduling, and communication to competitive youth sports.
Video is the gateway. With Winsight, I built a video streaming ecosystem for sports, letting parents and athletes record, share, and review game footage from their phones. The startup exited, but the thesis holds: video is how sports organizations first experience the value of technology, and AI-powered video analysis is the next step. Automatic highlight reels, coaching review tools, and performance tracking are all becoming feasible for organizations that couldn’t afford it two years ago.
The data layer is missing. MLB has Hawk-Eye and Statcast. The NFL has Zebra’s RFID tracking. But youth and amateur sports have almost no structured data. The organizations that figure out how to capture, organize, and surface useful data for non-professional sports will build something valuable.
Building for sports in the AI era
The AI in sports market is projected to grow from $8.9 billion in 2024 to $27.6 billion by 2030. That kind of growth creates opportunity at every level, not just for the teams and leagues deploying the technology, but for the companies building the tools they deploy.
At Londonberry, sports tech isn’t a vertical we picked from a strategy deck. It comes from standing on an NFL sideline in the Florida heat, making sure the tech works before kickoff. It comes from building Winsight and learning what parents and coaches actually need versus what tech companies think they need.
The robot umps are just the beginning. The real transformation is happening everywhere else in sports, and most of it hasn’t been built yet.