When AI Sees Every Move – Computer Vision in Sports and Training
In sports, success often depends on the smallest details, e.g. the angle of the arm during a tennis serve, the symmetry of a runner’s stride, or knee stability during a squat. A coach can see a lot, but even the most experienced one can’t analyze every movement angle in real time.
That’s where Computer Vision (CV) comes in – the technology that allows machines to see, track, and analyze human motion with laboratory-level precision. It’s not just an error detector but a biomechanical analysis tool available on any device with a camera.
By combining artificial intelligence and computer vision, athletes, coaches, and physiotherapists gain a systematic, objective and comprehensive picture of movement, something that previously required expensive biomechanical labs.
Why Motion Analysis Is a Biomechanical Challenge
Human movement is a complex system of joints, muscles, and compensations. Injuries rarely result from a single mistake, they usually come from repetitive biomechanical patterns that cause strain over time.
Computer Vision allows these patterns to be observed methodically and consistently. By analyzing each video frame and tracking key body points (arms, hips, knees, ankles), the system can show, for example, how a sprinter’s stride changes between repetitions or how asymmetry increases as fatigue builds.
In practice, CV reveals micro-compensations and overloads invisible to the human eye.
How Computer Vision Supports Biomechanics and Training
1. Athlete Technique Analysis
Computer Vision systems analyze joint angles and motion trajectories, for instance: the arm angle in a tennis serve, hip positioning during squats, or stride length differences between the left and right leg of a runner.
It’s not just a simple “correct/incorrect” evaluation, CV generates curves, graphs, and time-series data, allowing coaches to see how technique evolves with fatigue or training adaptation.
2. Injury Prevention
The true value of CV in sports isn’t just in measurement accuracy, but in systematic motion tracking. It identifies repeating movement patterns that can lead to overuse injuries.
This enables early intervention – improving technique, adjusting load, or strengthening specific muscle groups.
In this way, AI becomes a partner to the coach, helping athletes stay healthy and extend their careers.
3. Real-Time Training Monitoring
In fitness, Computer Vision is revolutionizing the workout experience. Instead of apps that simply count repetitions, CV-based systems evaluate biomechanics, whether the back is straight, knees are stable, or the hip angle is correct.
AI can provide instant feedback, such as:
“Hip angle 95° – correct. Knee too far forward – risk of overload.”
This is true automation of motion analysis, bringing scientific precision from biomechanics labs to everyday training.
4. Refereeing and Video Analysis
In team sports, CV supports referees in analyzing disputed plays. Instead of debating over centimeters, AI evaluates the exact body position relative to field lines, acting as a methodical, objective judge that records every detail of movement.
5. Fan Experience
Biomechanical data, once available only to coaches, is now part of the spectacle.
During broadcasts, viewers can see real-time data such as:
- shot speed,
- motion angles,
- live biomechanical analysis.
It’s a new dimension of interactive sports, where AI not only assists athletes but also engages fans.
Case Study – Sprinter Run Analysis
In a typical analysis, Computer Vision tracks body points from head to toe throughout each running phase. The system identifies:
- asymmetry between legs,
- delayed arm rotation,
- premature hip twist.
As a result, the coach receives a comprehensive biomechanical map of the athlete instead of relying solely on subjective observation. This enables not only error detection, but also data-driven training and rehabilitation planning.
Business and Organizational Benefits
Professional Sports
- Optimized training, faster recovery, longer athletic careers.
- Data-driven coaching decisions instead of intuition.
Fitness and Recreation
- CV-powered training apps act as “personal trainers” — not just counting reps but evaluating motion accuracy.
- Improved user safety and motivation.
Sports Organizations and Federations
- Objective refereeing and video analysis.
- Automated statistics, reports, and performance archives.
In this way, Computer Vision connects professional, amateur and business aspects of sports into one data-driven ecosystem.
Interactive Demo
Imagine an app that analyzes your squat or push-up and generates a report:
“Hip angle 95° – correct. Knees stable. Back slightly rounded – correct your posture.”
That’s exactly what a Computer Vision demo system does – AI that sees every move and teaches proper technique. It can analyze video in real time and generate a biomechanical report accessible from your smartphone.
Runflair – an example of Computer Vision–powered training technology
A strong real-world example of how Computer Vision can elevate training and movement analysis is the upcoming application Runflair. Although the app hasn’t yet been released to the market, its development already demonstrates how AI can meaningfully support technique improvement, injury prevention, and personalized coaching.
The comments below come from Wiktor Pastucha, the CEO of Runflair, who shares insights from the development process.
1. What are you most proud of so far?
“We’re most proud that we’ve managed to combine advanced computer vision technology with practical coaching knowledge in a truly useful way. The app won’t just analyze movement — it will translate that data into actionable insights and personalized training plans. Technology that once existed only in professional sports centers can now help anyone train more safely and effectively at home.”
2. What challenges do you see in applying AI/Computer Vision to sports?
“The biggest challenge is turning complex biomechanical data into a meaningful coach-level analysis, and then simplifying it into clear, understandable feedback for the user. Another challenge is teaching the algorithms to recognize individual differences in body structure and movement, because what is ‘correct technique’ for one person may look completely different for someone else.”
3. How do you think this technology will change training in the coming years?
We believe AI will democratize access to professional coaching knowledge. Instead of generic training plans, everyone will benefit from personalized guidance that understands their abilities and limitations. More awareness, fewer injuries, and better results, all achievable even in the comfort of one’s home.”
Conclusion and Series Preview
Computer Vision in sports is not just about detection accuracy – it’s a complete, objective biomechanical record that supports athletes, coaches, and physiotherapists alike.
From the gym to the Olympic arena, AI in sports is becoming the standard, not the exception.
Next article preview: How Computer Vision supports recycling and the circular economy by recognizing and classifying materials to make recovery more efficient and sustainable.
