In sport, the margin between success and failure is often measured in milliseconds. A cricketer adjusting foot positioning, a runner refining sprint technique, or a footballer perfecting passing form—these small adjustments can make the difference between victory and defeat.
Traditional motion capture has long been the gold standard for analyzing athletic movement, but its limitations have restricted widespread adoption. Conventional systems require athletes to wear reflective markers and specialized suits while performing in controlled laboratory environments. These setups can cost tens of thousands of dollars, placing them out of reach for all but elite teams and well-funded research facilities.
Artificial intelligence is changing this landscape dramatically. Markerless motion capture, driven by deep learning and computer vision, allows movement to be tracked directly from video footage without physical markers. This technology is rapidly maturing, with companies like Theia leading the way with their 2025 software update 'Theia Axiom' that supports the newest NVIDIA RTX 50 Series graphics cards for enhanced processing capabilities.
"Markerless motion capture provides a practical alternative that's accessible, scalable and adaptable to real-world settings," explains Professor Habib Noorbhai, a health and sports scientist who co-authored a recent study on the technology. "It's a shift that promises to transform how athletes train, how they move, how injuries are assessed and how coaches refine performance."
The applications are far-reaching. In rehabilitation, physiotherapists can monitor movement deficiencies in real time, allowing athletes recovering from injuries like ACL tears to have their gait and knee angles monitored remotely. For performance enhancement, coaches can analyze biomechanics in natural environments rather than artificial laboratory settings.
While markerless systems still face challenges—including occlusion issues where body parts become temporarily hidden from view and variations in lighting affecting tracking accuracy—the technology continues to improve rapidly. Recent validation studies show promising results, though researchers note that further refinement is needed before these systems can fully replace marker-based setups for all applications.
The market for AI in sports is expanding dramatically, with projections showing growth from $7.63 billion in 2025 to $26.94 billion by 2030—a compound annual growth rate of 28.69%. This growth is driven by increasing adoption of AI technologies across all aspects of sports, from performance analysis to injury prevention and fan engagement.
As AI models become more sophisticated and sensor technology advances, the precision of markerless systems will continue to improve. The future likely involves integration of multiple approaches rather than one technology completely replacing another, creating a seamless framework for movement analysis that works across different contexts and needs.
For athletes at all levels, this technological revolution means that sophisticated performance analysis is becoming increasingly accessible. What was once available only to elite professionals is now within reach of college teams, developmental programs, and even dedicated amateurs—democratizing sports science and potentially leveling the competitive playing field in ways previously unimaginable.