Computer vision in sports is rapidly transforming how sports are played, coached, officiated, and experienced. Today, AI-powered vision systems track every player in the NBA, analyze swing mechanics in MLB, assist referees in FIFA competitions, and provide real-time performance feedback in elite training facilities and home gyms alike. What once required hours of manual video review can now be done automatically, accurately, and at massive scale.
The global sports industry is undergoing a technological shift, driven by the explosive growth of AI and data-driven performance optimization. The sports technology market was valued at
$18 billion USD in 2024 and continues to grow rapidly, while AI in sports is projected to become a multi-tens-of-billions-dollar industry in the coming decade. At the center of this transformation is computer vision — the branch of artificial intelligence that enables machines to understand and analyze images and video.
In this guide, we’ll explore how computer vision is used across the sports industry, from professional leagues and officiating systems to sports training, rehabilitation, and fitness coaching. We’ll cover the most important applications, real-world examples, leading organizations, and the datasets powering modern sports AI systems.
The sports industry and its technology challenges
In addition to being an entertainment source, the sports industry boosts economies by standing behind new technical innovations and job opportunities. Key facts and figures:
Before we dive into various popular applications of computer vision in sports, it is important to know that the sports industry does not come without challenges.
- Player health and performance: Ensuring player well-being and implementing strategies to optimize player availability is crucial for sustained performance in elite team sports.
- Fan engagement in the digital age: While digital platforms have expanded reach and revenue, striking the right balance between meaningful interaction and oversaturation is crucial. The top 25 leagues in the world had a combined audience of over four billion and generated more than €2.8 billion through their digital inventory. Keeping fans engaged and fostering a sense of community requires innovative strategies to ensure that the essence of sports isn't lost in the digital noise.
- Venue evolution: According to industry experts, work must be done to make the venues themselves (stadiums, arena, and ballparks) more attractive, affordable, comfortable, safe, and technology-equipped to satisfy the needs of today’s fans and as they evolve over time.
What is computer vision in sports?
In practice,
computer vision in sports is used for player tracking, tactical analysis, injury prevention, automated refereeing, broadcast enhancements, and increasingly, sports training and performance optimization. Coaches use pose estimation to refine technique, teams use multi-camera tracking systems to analyze tactics, and athletes use vision-based systems to receive real-time feedback during workouts.
Computer vision systems enable organizations to convert video into structured, searchable, and measurable performance data, unlocking new levels of insight for coaching, scouting, officiating, and fan engagement. As adoption accelerates across professional sports, training environments, and consumer fitness platforms, these technologies are becoming foundational to how modern sports organizations operate.
Core applications of computer vision in sports
Performance analysis, player tracking and sports analytics
Sports are exhilarating for all involved — teams, players, coaches, and fans. Whether it’s a come-from-behind victory or a record-breaking play, the thrill of the game keeps people coming back for more. And when one match ends, sports pros on the field and in the back office are already thinking of ways to continue to improve performance and safety, and make the game even more exciting for fans. Data is the key to unlocking winning strategies.
The use of cameras, equipment sensors, wearables, and even radar and LiDAR scans like in the MLB, makes a variety of visual information available. Now, every jump, sprint, shot, throw, and maneuver can be captured so that the information can be organized and analyzed. Tracking players' movements, positions, speeds, and trajectories offers a rich data source. This wealth of information enables rich analytics for coaches, athletes, and sports professionals to gain valuable insights into performance — not only to advance individual and team performance at game time, but also to refine training plans, scout new talent, and for competitive analysis and strategies.
Pose estimation and object tracking are on the forefront of computer vision in sports. For example, coaches and analysts use pose estimation to determine ideal swing and pitch patterns in MLB to squeeze every ounce of performance out of their players. Soccer is also quick to adopt both of these technologies, tracking players on the pitch and seeing how they react to sudden changes in the ball's positions. Through thorough analysis of penalty kick pose estimations, goalies could get a leg up on the competition and look for tells on where the shot is likely to go, using insights only possible through computer vision.
Dig deeper with papers related to using computer vision for athletic motion tracking:
Injury prevention and rehabilitation
Using computer vision in sports has led to the development of cutting-edge ways to prevent injuries and heal from them. By analyzing athletes' movements during exercises and game-time matches, computer vision techniques like feature extraction, pose estimation and motion detection can detect improper actions that might lead to injuries. Analyzed data comes in handy for coaches and medical teams when they are putting together personalized training and conditioning programs to
prevent potential injuries. This information is also important for improving the design and construction of protective gear and equipment.
When it comes to rehabilitation, computer vision is an essential asset. The healing journey of athletes can be monitored to make sure that rehabilitation exercises are done correctly to lower the risk of reinjury. Techniques such as
marker-less human pose estimation are particularly promising, allowing for cost-effective and reliable telerehabilitation services without additional equipment. Digitizing rehabilitation not only improves accuracy but also holds the potential to speed up recovery, making the process more organized and data-driven.
Explore papers on computer vision-based sports technologies for player health:
AI referee assistance
AI referee assistance aids human referees in overseeing sports games. Through computer vision and machine learning, AI referees can make precise calls in real time, reducing human errors. They can detect goals, misconduct between players, and other rule infringements swiftly and accurately. This not only enhances the credibility of the game but also alleviates the pressure on human referees.
In soccer for example, an AI refereeing system can use multiple cameras to capture the field from different angles. These images are then analyzed in real time to detect events like fouls or offside situations. For example, in an offside scenario the system can calculate the positions of players, the ball, and the last defender at the moment the ball is played. If a player is found in an offside position, the system instantly alerts the
human referee and can provide a visual representation of the scene on a sideline monitor for verification, ensuring that the call is accurate and fair.
For more information enjoy these papers related to using computer vision in sports refereeing:
Fan experience and sports broadcasting
Enhancing fan experiences and fueling new ones are exciting applications of computer vision in sports. While there are more ways unfolding to inform and engage fans further than ever before, in this article we’ll focus on two prominent use cases: augmenting the broadcast experience and new ways to engage via Augmented Reality (AR) and Virtual Reality (VR).
1. Augmenting the broadcast experience
Computer vision is paving the way for enhancements to sports broadcasting to create a richer viewing experience. It’s now possible to analyze live and recorded content in real time in order to extract insights to pair with the broadcast. For example, vision-based AI can provide real-time statistics and player information, real-time ball tracking, the ability to generate on-screen graphics, as well as
identify key moments in matches. All of these new possibilities help fans develop deeper connections to the game.
2. Immersive AR and VR experiences
With the combination of AR and VR, the traditional stadium experience is evolving, making sports events more engaging and interactive for fans. Fans can virtually explore stadiums, get the latest player profiles, enjoy 3D game rewinds, and live chat with other fans. Computer vision sports technology captures and analyzes the game as it happens, turning complex on-field actions into digital data. This data then powers the AR and VR applications, making spectators feel like they’re part of the game. Moreover, renowned football teams and leagues have already begun experimenting with AR/VR technologies.
Through interactive apps and other digital platforms, fans can
virtually immerse themselves in live games, accessing features like panoramic camera angles, real-time stats, and on-demand replays. With the continued advancement in
AR, VR, and computer vision sports technologies, the boundaries of how fans experience sports are set to expand further, potentially leading to features like holographic player projections and live streams of remote audiences, offering a new level of engagement and excitement for sports enthusiasts worldwide.
Computer vision in sports training and fitness coaching
Computer vision is revolutionizing the realm of personalized fitness and sports training. Advancements in AI and ML make it possible to analyze human movement with remarkable accuracy, providing real-time feedback and tailored guidance to people pursuing their fitness goals. Popular use cases include:
- Posture and form tracking and correction: By monitoring body positions, angles, and movements, computer vision systems can detect deviations from proper form, providing immediate feedback to help people correct their technique and prevent injuries.
- Personalized workout recommendations: Data-driven approaches enable users to receive workout recommendations tailored to their specific needs and abilities, helping them achieve their fitness goals.
- Virtual coaching: With the ability to remotely monitor and assess user movements, fitness professionals and coaches can provide personalized guidance and support in virtual settings.
Organizations using computer vision in sports
The United States Tennis Association (USTA)
The
USTA is using AI to level up player performance. With an increasing amount of data available from court cameras, video recordings, and wearables during practice, AI plays a significant role in bringing performance insights to the forefront for the entire performance team of athletes, coaches, mental skills staff, and strength and conditioning professionals.
At the heart of USTA’s AI-driven performance management system is data: the x-y coordinate of the player on the court, every shot of the rally, the speed of the shots, the spin, the number of changes in direction, and more. Being able to access and analyze critical data is important in evolving player strategies and winning more matches. AI-powered systems for sport enable athletes to analyze competitor performance, and analyze their own matches once they’re over, so they can swiftly and continuously tune and improve.
AiSport
AiSport is building an AI fitness platform to give users real-time feedback on their workout techniques, all from the convenience of their smartphones. AiSport’s platform uses AI and computer vision to analyze and correct people’s posture while they are exercising to maximize effectiveness and prevent injuries. With AiSport, fitness clubs can provide their members with not only equipment and a location, but also with a personal AI fitness trainer.
AiSport’s tech analyzes and provides real-time recommendations to maximize performance while keeping workouts injury-free. Computer vision techniques at the center of AiSport’s platform include: 3D body pose and shape recognition, biomechanical analysis, pattern matching, and deviation estimation. AiSport was co-founded by two Ukrainian women and long-time sports enthusiasts, Anna Stepura and Dariia Hordiiuk. Development of the AiSports platform continues today in Silicon Valley.
Hawk-Eye Innovations
Hawk-Eye Innovations, a pioneering UK-based company and part of the Sony group, focuses on applying computer vision to sports. With a team of dedicated professionals, Hawk-Eye has become a household name in the sporting world, delivering precise and real-time tracking, analytics, and officiating assistance in a wide variety of sports, including tennis, cricket, and soccer. Their key technologies include the Synchronized Multi-Angle Replay Technology (SMART) for enhanced video capture, review, clipping, and distribution, the TRACK systems for Performance Tracking, Ball Tracking, and Object Tracking, and the INSIGHT suite, which provides data collation, storage, aggregation, delivery, and visualization capabilities.
Founded in 2001, Hawk-Eye has grown into a thriving company with a global presence. Not only have they partnered with Major League Baseball (MLB) for optical tracking and vision-processing technology and the National Basketball Association (NBA) for deploying 3D optical tracking technology, they have achieved international recognition and are an integral part of sports events in more than 90 countries worldwide.
Sportlogiq
Based in Montreal, Quebec,
Sportlogiq initially focused on professional hockey and then expanded its reach to collaborate with major sports teams and data providers around the world. Numerous NHL clubs, more than 150 professional and amateur hockey teams worldwide, media outlets, content producers, top performance research firms for soccer and football, as well as amateur sports and video companies, all rely on their data and insights.
The company is supported by prominent investor Mark Cuban and the TandemLaunch incubator. Sportlogiq is made up of a team of 13 AI researchers. They have been granted 180 patents and publications and have 75 full-time professionals onboard. Sportlogiq is helping to shape the future of AI in sports by providing creative solutions for improving athletic performance and training.
Ludimos
Ludimos, a smartphone-based cricket training app, is transforming the world of cricket coaching. Founded by Madan Rajagopal, an Indian cricket enthusiast living in the Netherlands, Ludimos was born out of his frustration with inconsistent coaching advice and a lack of tools to track players' progress. As a data scientist and AI engineer, Rajagopal developed Ludimos to address these challenges. The app has gained widespread popularity, with over 19,000 users across 15 countries, including national cricket associations and teams like Royal Challengers Bangalore.
What sets Ludimos apart are its specialized features aimed at cricket training. It offers multi-angle video analysis, allowing a thorough look at player techniques from different viewpoints. The app excels in ball and bat tracking, giving a data-driven insight into player performance. Additionally, it provides a communication platform for coaches to assign drills and give feedback, making the coaching process more interactive and efficient. While ball tracking is its strong suit for now, Ludimos has plans to expand into bat tracking and biomechanics analysis, showing a promising trajectory for evolving cricket coaching and player analysis.
Track160
Track160 is changing the way soccer is coached and analyzed. Founded and chaired by Miky Tamir, a pioneer in sports computer vision, Track160 combines cutting-edge technology with a deep understanding of the game to provide valuable insights to soccer clubs and academies. At the core of Track160's offerings is an AI-based solution that utilizes multiple cameras tethered to a single base. These cameras, equipped with computer vision and deep learning algorithms, capture a wealth of data related to player performance and team tactics. What sets Track160 apart is its commitment to data accuracy, earning FIFA certification for its data quality from a single installation point.
Tonal
Tonal is an AI-powered home gym system that combines strength training equipment, personalized fitness coaching, and live and on-demand classes. It was founded by Aly Orady, a supercomputer engineer who wanted to create a more effective and convenient way to strength train at home.
Tonal's main piece of equipment is a wall-mounted device with two electromagnetic pulleys that can provide up to 200 pounds of resistance. The device also has a touchscreen display that shows you how to perform each exercise and tracks your progress. Tonal uses AI to dynamically adjust the resistance for each exercise based on your individual strength and fitness level in order to provide you with your most effective workout.
The future of computer vision in sports
Computer vision has moved from experimental technology to core infrastructure in modern sports. From professional leagues and elite training centers to consumer fitness apps and rehabilitation platforms, vision-based AI systems are now fundamental tools for analyzing performance, preventing injuries, improving officiating, and enhancing the fan experience.
As AI models, camera systems, and real-time processing continue to improve, the role of computer vision in sports will only grow. At
Voxel51 we are helping innovators move toward a future where every movement on the field, in the gym, or in rehabilitation can be measured, understood, and optimized. For teams, coaches, athletes, and developers alike, computer vision is no longer a futuristic add-on — it is becoming a competitive necessity.
