IBM Brings AI Limb-Tracking to the US Open With New Serve Metric
The enterprise tech giant tracks 21 points on a player's body 50 times a second to grade serve mechanics in real time.
Key highlights · 1 min read
- IBM has introduced an AI-driven biomechanical analysis system at this year's US Open, aiming to quantify the mechanical execution behind every serve delivered throughout the tournament.
- The system relies on computer vision and limb-tracking technology developed with IBM Bob.
- By measuring technical variables ranging from wrist flexion to the transfer of kinetic energy from the legs through the torso, IBM estimates the setup will generate roughly 1.2 billion data points…
The Scale ReportIBM has introduced an AI-driven biomechanical analysis system at this year's US Open, aiming to quantify the mechanical execution behind every serve delivered throughout the tournament.
The system relies on computer vision and limb-tracking technology developed with IBM Bob. During each motion, the platform captures 21 distinct spatial points across a player's body and racquet at a frequency of 50 times per second.
By measuring technical variables ranging from wrist flexion to the transfer of kinetic energy from the legs through the torso, IBM estimates the setup will generate roughly 1.2 billion data points across the two-week event.
Those measurements feed an algorithm that computes a single Serve Quality score in near real time. The resulting metric gives broadcast partners and viewers a breakdown of mechanical efficiency rather than just standard radar-gun speed.
Tennis analytics have historically relied on outcome-based measurements such as velocity, spin, and court placement. Moving deeper into kinetic tracking represents a logical evolution for sports telemetry, though boiling down complex athletic movement into an automated, single-digit fan score always risks oversimplifying individual technique.
Reporting based on coverage from @sportico on Instagram.
