Turning Video Into Physical Insight
As of March 2026, Sports AI is expanding Playlab with the launch of physical data, giving teams access to advanced physical performance metrics extracted directly from standard match footage. No new equipment. No added setup. Just deeper insight from the video you already use.
This marks a major step forward in how physical performance can be measured, contextualized, and applied across every level of the game.
Playlab's physical data pipeline uses advanced computer vision and player-tracking models to analyze any uploaded match recording, automatically detecting and tracking every player frame by frame to capture movement, speed, and workload metrics with consistent spatial accuracy across the entire match.
Crucially, this process requires no wearables, no GPS vests, and no additional hardware dependencies, removing the traditional barriers of cost, logistics, and matchday setup. As a result, physical analysis is no longer limited by equipment availability or operational complexity. If you have video, you have reliable physical data.
Key Physical Outputs That Matter
Physical data in Playlab provides a comprehensive set of objective metrics that support both match analysis and long term performance monitoring. This includes team speed and movement profiles capturing peak speed, average speed, intensity distribution, and movement volume, a measure of total distance covered across the team.
The platform also measures collective structure through metrics such as average team width and length on the pitch, offering insight into spacing and organization across different phases of play.
These metrics are complemented by heat maps and positional density maps that visualize where workload is highest across the field.
One Integrated Analysis Workflow
All physical outputs are natively built into Playlab's analysis tools and are accessible within each individual match under the Playsense tab. From there, analysts can explore and compare physical metrics alongside all other match data within the same area of the app.
They can also jump into Sequences to compare those physical outputs directly against the corresponding game footage for clear, in-context review.
There's no exporting, cross-referencing, or manual reconciliation between platforms. Everything lives in one place, reducing processing time and allowing staff to move faster from insight to decision.
Built to Scale Across Teams and Seasons
By removing hardware and per-player tracking limitations, physical data scales effortlessly across teams, competitions, and seasons. The same workflow applies to top-level professional teams, academies, and development environments, ensuring consistent data standards without increasing operational complexity.
Whether you're analyzing one squad or an entire league, the process remains the same.
Advancing Accessible Performance Analysis
The introduction of physical data reinforces Sports AI's commitment to making high-level performance analysis more efficient and accessible. By transforming video into a reliable source of physical insight, Playlab empowers teams to operate with greater clarity, consistency, and context, using tools they already trust.
Closing Note
This isn't just more data. It's smarter data, delivered exactly where it matters most: on the pitch, in the moments that define performance.