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.
Turning Video Into Physical Insight
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 delivers a comprehensive set of objective metrics that support both match analysis and long-term performance monitoring, including detailed player speed profiles that capture peak speed, average speed, and intensity distribution, alongside movement volume and workload indicators that quantify total distance covered and physical effort over time. It also includes team shape metrics, such as average team width and length on the pitch, providing insight into collective spacing and physical structure in different phases of play.
These outputs are complemented by heat maps and positional density maps that clearly visualize where physical demands are highest across the field. Physical data is fully contextualized, linking effort directly to tactical phases, game states, on-ball events, and team structure. Because physical and tactical data exist within the same environment, analysts can evaluate physical performance in direct relation to the moments that truly decide matches, rather than viewing physical output in isolation.
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.
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.