Game, Set, Match: 13 Transformative Computer Vision Applications in Sports Industry

The value in the Computer Vision market is projected to reach $22.7 billion in 2023, paving the way for its applications in several domains. Computer vision, the cutting-edge field of artificial intelligence, has emerged as a game-changer, pushing the boundaries of what was once thought possible. In 2023, its latest applications are unprecedentedly revolutionizing the sports sector, transcending traditional boundaries and propelling athletic performance to new heights.

With its ability to extract, analyze, and interpret visual data from the sporting arena, computer vision provides athletes, coaches, and spectators with an entirely new perspective on the game. Gone are the days when human judgment alone ruled the field. Today, computer vision algorithms, driven by vast amounts of data and trained with remarkable precision, are unlocking hidden insights and transforming the fabric of sports.

From real-time tracking of athletes' movements and biometrics to enhanced video analysis and officiating, computer vision seamlessly integrates into various aspects of sports. Using advanced cameras, sensors, and intelligent algorithms enables the extraction of nuanced details, empowering athletes to optimize their performance, teams to devise ingenious strategies, and referees to make more accurate decisions.

Moreover, computer vision is revolutionizing the spectator experience. Fans are no longer passive observers; they are immersed in augmented reality, enriched with real-time statistics, player profiles, and immersive visualizations. The fusion of computer vision and sports has generated a captivating, interactive environment, allowing spectators to delve further into the game and acquire previously unattainable insights.

In this article, we will explore the latest computer vision applications in the sports sector in 2023. From its impact on training and performance analysis to its influence on broadcasting and fan engagement, we will delve into the transformative power of this cutting-edge technology.

Applications of Computer Vision in Sports

The convergence of computer vision and the sports industry has paved the way for a plethora of innovative applications. Computer vision is transforming the way sports are played, coached, and experienced by harnessing the power of advanced algorithms and visual data analysis. In this section, we will explore some of the critical applications where computer vision is making a significant impact, revolutionizing everything from athlete performance analysis to fan engagement.

Player tracking

Player tracking is a widely adopted application of computer vision in sports. It involves detecting and tracking individual players or multiple players simultaneously using bounding boxes or key-point annotations. Coaches and performance analysts are particularly interested in player monitoring as it enables the analysis of player and team performance, revealing movement patterns and behavioral insights.

Anticipated growth at a compounded annual growth rate of 24.9% is projected for the global market of player tracking in the coming five years. This advancement will provide teams across various leagues, including both major and minor divisions, with access to tracking solutions that aid in comprehending their players' movements.

Beyond player tracking, computer vision systems can generate semantic information, providing context to players' actions. Through machine learning, the system can make assumptions or predictions about whether a player possesses the ball, is passing, running, defending, and more.

This integration of technology in sports offers an additional advantage - a computer vision-powered system can suggest optimal player positions and provide a visual comparison with the actual positions observed during a specific game. This allows players to identify areas for improvement and enables coaches to conduct more comprehensive performance analyses.

Athlete identification and classification

Athlete identification and classification are pivotal applications of computer vision within sports. Harnessing sophisticated algorithms, computer vision enables the accurate identification and classification of athletes in various sporting scenarios. This technology holds immense value for sports organizations, coaches, and analysts seeking to streamline data collection, enhance performance evaluation, and optimize team strategies.

Machine learning algorithms leverage aggregated data to assess players' skills and overall potential, facilitating the categorization and ranking of players across various criteria. These valuable insights enable sports teams to construct more prosperous rosters by acquiring promising talents at a lower cost and subsequently nurturing and trading them for substantial gains. An illustrative example of this strategy's efficacy lies in Brentford's accomplishment in acquiring Ollie Watkins, the striker, for approximately US$2 million, and subsequently selling him for an impressive sum of US$35 million at a later stage.

With computer vision algorithms, athlete identification becomes automated, eliminating the need for manual tagging and annotation. Computer vision systems can swiftly and accurately identify individual athletes during gameplay or training sessions by analyzing visual data, such as unique physical attributes, facial recognition, or jersey numbers.

Moreover, computer vision facilitates athlete classification based on predefined criteria or performance metrics. By extracting relevant data from visual inputs, such as running speed, movement patterns, or positional data, the system can categorize athletes into specific groups or skill levels. This classification aids coaches in talent scouting, team selection, and individualized training programs tailored to each athlete's strengths and weaknesses.

Avoiding Injuries

Avoiding injuries is a critical concern in sports, and computer vision has emerged as a valuable tool in this domain. In this context, one of the primary applications of computer vision is the analysis of player movements and biomechanics. Over half of the reported cases involve injuries to the Anterior cruciate ligament (ACL), which impacts approximately 200,000 people annually in the United States. Consequently, scientists have employed multi-angle video analysis to assess the potential for lower-body injuries during planned athletic motions.

By tracking and analyzing the kinematics of athletes in real-time, computer vision systems can identify potentially risky movements or biomechanical patterns that could lead to injuries. This valuable information allows coaches, trainers, and medical staff to intervene proactively, providing targeted interventions and personalized training programs to mitigate injury risks. By using this analysis, athletes and their support teams can make informed decisions about technique refinement, load management, and injury prevention strategies.

Furthermore, computer vision can assist in monitoring and assessing environmental factors contributing to injuries. For example, computer vision systems can analyze playing surfaces, such as turf or grass, to determine their condition and identify potential hazards like uneven patches or slippery areas. By detecting these risk factors, sports organizations can take preventive measures such as surface maintenance or altering training schedules to minimize the chances of injuries caused by poor playing conditions.

High-Definition Viewer Experience

One of the remarkable applications of computer vision in the realm of sports is the enhancement of the viewer experience through high-definition visuals. With advanced computer vision algorithms, sports broadcasters can provide viewers with immersive and engaging content, taking their expertise to new heights. By leveraging computer vision technology, sporting events can be captured and broadcasted with unparalleled clarity, enabling viewers to witness every intricate detail and action with astonishing precision.
An example in 2022 is from Notch VMA's Augmented Reality, for real time reflections of actual stadium data and environmental conditions.

Computer vision enables the extraction of real-time statistics, player tracking, and augmented reality overlays, enhancing the viewer's understanding and enjoyment of the game. Through sophisticated image processing techniques, computer vision algorithms can provide insightful visualizations such as player heatmaps, passing patterns, and goal probabilities. This wealth of information enriches the viewer's understanding of the game and adds an element of excitement and analysis previously inaccessible.

Moreover, computer vision can seamlessly integrate augmented reality elements into the viewer experience. Virtual graphics, player profiles, live statistics, and replays can be overlaid onto the live broadcast, offering viewers an interactive and dynamic visual display. This augmented reality integration brings a new dimension to sports broadcasting, allowing fans to engage with the game in real time and gain deeper insights into the athletes' strategies, techniques, and performance.

Referee Automation

Referee automation stands as a transformative application of computer vision in the realm of sports. With the aid of visual data analysis, computer vision technology is revolutionizing the officiating process, ensuring fair play and accurate decision-making on the field.

Traditionally, referees have shouldered the responsibility of making split-second judgments during fast-paced sporting events. However, with the integration of computer vision, referees are now equipped with intelligent tools that enhance their decision-making capabilities.

Computer vision systems can track players' movements, detect fouls, and analyze intricate details of the game with remarkable precision. This technology enables referees to access objective, real-time information, empowering them to make fair and accurate calls, ultimately elevating the integrity of the game.

The NFL employs a computer vision system known as Next Gen Stats to monitor the precise location of each player during games. This technology enables referees to make informed decisions on whether penalties should be called or not.

Adding to this, referee automation through computer vision reduces the margin of error and mitigates the influence of human bias. By leveraging data-driven analysis, the system can provide instant alerts and notifications to referees when potential rule violations occur.

This assists referees in making informed decisions while reducing the likelihood of missed calls or controversial judgments. The objectivity and consistency brought forth by computer vision technology contribute to a fair and transparent adjudication process, fostering trust among players, teams, and spectators.

Ball Movement Tracking

Accurate ball movement tracking is vital in extracting crucial information from ball-based sports, particularly in games like tennis, cricket, and badminton. Computer vision models play a significant role in capturing and analyzing the ball's movement in three dimensions, providing precise data on its location upon impact and even offering predictions on its future trajectory, such as determining whether it would hit the wicket.

In a Stanford study, Researchers ran multiple configurations of the pos-N-M model on a manually labeled set of 4,000 frames and achieved an 85.5% accuracy on a test.

The applications of computer-vision-powered ball tracking systems encompass various aspects, including ball detection, trajectory tracing, and game result prediction. However, the complexity of tracking ball movement intensifies in sports like basketball, volleyball, and soccer. In these scenarios, the ball can be obscured from view due to players obstructing its visibility, or the rapid and unpredictable nature of player interactions with the ball presents additional challenges.

According to a study by L Chen, CNN+RNN algorithms achieved an accuracy of 76.5% for four types of actions in basketball videos.

Effectively tracking ball movement in these dynamic sports requires advanced computer vision algorithms that can handle the complexities associated with occlusion and rapid motion, enabling accurate analysis of ball trajectory, player interactions, and overall game dynamics. These advanced tracking systems hold the potential to provide valuable insights for coaches, analysts, and players, leading to enhanced strategies, performance evaluation, and overall game understanding.

Increased Security at Stadiums

Increased security at stadiums is a critical application of computer vision in the sports industry. With large crowds gathering at stadiums during sporting events, ensuring attendees' safety and security is paramount. Computer vision systems equipped with advanced surveillance cameras and intelligent algorithms can enhance security measures by providing real-time monitoring and threat detection capabilities.

The incident that occurred during the Halloween Seoul crowd crush in 2022 was a tragedy, resulting in the loss of over 158 lives and causing numerous injuries. It serves as a stark reminder of the risks posed by overcrowded spaces. Nevertheless, the implementation of CV technology holds the promise of averting such calamities and enhancing overall stadium safety:

Computer vision can automatically identify and track individuals by analyzing live video feeds and flagging suspicious behavior or unauthorized access. Facial recognition technology can match faces against watchlists, allowing security personnel to identify threats or individuals with restricted access quickly. This proactive approach to security minimizes risks and enables rapid response in case of any security breaches or incidents.

Furthermore, computer vision can assist in crowd management by monitoring crowd density and flow patterns. The system can detect overcrowded areas or bottlenecks by analyzing video footage, allowing stadium staff to take necessary actions to maintain crowd safety and prevent potential stampedes or accidents. This real-time monitoring ensures attendees a smooth and secure experience and reduces the likelihood of security-related incidents.

Video Assistant Referee

Video Assistant Referee (VAR), an application of computer vision in sports, has emerged as a transformative tool in officiating. With its advanced capabilities, VAR has revolutionized how decisions are made in sports events, bringing increased accuracy and fairness to the game. By utilizing computer vision algorithms and video analysis, VAR provides referees with an enhanced perspective, allowing them to review critical incidents and make more informed judgments.

In the realm of research applications, deep learning models designed for match outcome prediction demonstrated commendable performance in accurately forecasting the FIFA World Cup 2018 matches, achieving a notable prediction accuracy of 63.3%.

In essence, VAR serves as an additional set of eyes for referees on the field. It analyzes high-definition video footage from multiple camera angles, enabling officials to revisit contentious moments such as goals, penalties, offside calls, and potential fouls.

Using computer vision algorithms, VAR can detect and track player movements, precisely measure distances, and identify subtle infringements that may have been missed in real-time. This technology assists referees in making accurate and fair decisions, reducing the margin of error and minimizing controversies that can arise during matches.

Moreover, VAR benefits referees, promotes transparency, and enhances the overall integrity of sports competitions. The system provides a platform for objective decision-making, ensuring that crucial judgments are based on verifiable evidence rather than subjective interpretations. This fosters a sense of trust among players, coaches, and spectators as they witness a more robust and accountable officiating process. By leveraging the power of computer vision, VAR has genuinely transformed the landscape of sports officiating, delivering a higher level of accuracy and fairness to the game.

Identifying Exercises

A Mayo Clinic study found that, on average, people are likely to suffer up to 9 injuries per 1,000 training hours, so it is clear that having the correct feedback and specific exercise can significantly reduce this incident rate.

Identifying exercises is a notable application of computer vision in sports. With the aid of advanced algorithms and visual data analysis, computer vision systems are capable of recognizing and categorizing different exercises performed by athletes. This technology brings a new level of precision and efficiency to training programs, benefiting athletes and coaches.

By utilizing computer vision, athletes can receive real-time feedback on their exercise technique and form. The system can accurately identify exercises such as squats, lunges, or bench presses and provide instant feedback on factors like body alignment, range of motion, and timing. This allows athletes to make necessary adjustments and optimize their workout routines to achieve better results while reducing the risk of injury.

For coaches, computer vision-powered exercise identification offers valuable insights into athletes' training sessions. Coaches can track the performance of individual athletes or an entire team, analyzing exercise data to identify strengths, weaknesses, and areas for improvement. This data-driven approach enables coaches to tailor training programs more effectively, providing personalized guidance and ensuring that athletes are executing exercises correctly for maximum benefit.

Automated Sports Journalism

In the ever-evolving landscape of sports journalism, a groundbreaking application of computer vision has emerged: automated journalism. Automated journalism is transforming the way sports news and updates are generated and disseminated. By analyzing visual data from sporting events, this cutting-edge technology enables the creation of real-time, data-driven articles and reports without human intervention.

In the realm of sports, where every second counts and fans crave immediate updates, automated journalism fills a crucial gap. Computer vision algorithms can process vast amounts of visual information, extract relevant statistics, analyze player movements, and interpret game dynamics. This wealth of data is the foundation for generating detailed and engaging sports content.

The platform called Wordsmith, which utilizes artificial intelligence, employs natural language processing to transform data from Minor League Baseball (MiLB) into written stories. This technology has proven beneficial for the Associated Press (AP) by expanding its reporting capabilities to encompass 13 leagues and 14 teams affiliated with Major League Baseball. Another example is the Dutch regional media group NDC, which uses AI to help cover 60,000 soccer matches in one year, which amounts to every local game.

Through automated journalism, sports enthusiasts can access up-to-the-minute match summaries, player performance analyses, and even personalized news tailored to their favorite teams or athletes. This technology empowers media outlets to provide comprehensive coverage of various sports events simultaneously, regardless of their geographical locations.

Additionally, the use of computer vision in sports journalism ensures a standardized and objective approach to reporting, eliminating potential biases and enhancing the overall credibility of the news generated.

Automating Ticketing

One of the significant applications of computer vision in the sports industry is automated ticketing. Traditional ticketing methods often involve manual processes, which can be time-consuming, prone to errors, and lead to long venue queues. However, with the integration of computer vision technology, the ticketing process is being revolutionized, streamlining operations and enhancing the spectator experience. A famous example is Columbus Crew uses facial recognition to allow their fans to enter the stadium without having to display their ticket.

Computer vision algorithms can automatically scan and validate tickets as spectators enter the venue. Utilizing advanced cameras and image recognition techniques, the system can quickly and accurately verify the authenticity of tickets, ensuring smooth and efficient entry for attendees. This eliminates the need for physical ticket validation and minimizes the risk of fraudulent activities, enhancing security measures.

Furthermore, automated ticketing systems powered by computer vision can offer real-time insights and analytics. By capturing and analyzing data on ticket sales, attendance patterns, and crowd flows, event organizers can gain valuable information to optimize venue layouts, improve crowd management strategies, and enhance overall event planning. This data-driven approach enables organizers to make informed decisions that enhance the spectator experience, maximize revenue, and ensure the safety and satisfaction of attendees.

Life-threatening situations

Computer vision has emerged as a crucial tool in sports for preventing life-threatening situations and ensuring the safety of athletes. With its ability to analyze real-time video feeds and detect potential risks, computer vision systems contribute significantly to maintaining a secure environment during sporting events.

The use of smart surveillance systems, backed by top-of-the-line computer vision and AI technologies, is seen as a promising way to enhance safety and security measures.

One key application is the detection of concussions and head injuries. Computer vision algorithms can track player movements and identify abnormal behavior or impacts that may indicate a potential head injury. By promptly alerting medical personnel and coaches, these systems enable swift intervention and appropriate medical attention, potentially preventing severe consequences.

Numerous nations are employing computer vision-enabled facial recognition systems to apprehend fugitives, even in situations where masks are worn.

Moreover, computer vision technology aids in identifying hazardous situations such as collisions or falls during sports events.. By continuously monitoring the playing field, computer vision systems can recognize dangerous scenarios and provide instant alerts to officials, allowing them to take immediate action and prevent accidents before they escalate.

The integration of computer vision in sports also extends to outdoor activities, such as extreme sports or outdoor adventures. In these contexts, computer vision can assist in monitoring environmental conditions and detecting potential dangers like avalanches, rockfalls, or weather changes. By providing timely warnings to athletes, instructors, or event organizers, computer vision systems contribute to mitigating risks and ensuring the well-being of participants.

Sports Retail

Computer vision technology has found a remarkable application in the retail sector within the context of sports. Retailers are increasingly leveraging computer vision to enhance the customer shopping experience, optimize inventory management, and drive sales in the sports industry. Computer vision is transforming the presentation, monitoring, and sale of sports-related products, revolutionizing the industry.

According to a Forbes report, retail establishments can leverage computer vision technologies to monitor customer activity, yielding valuable insights into consumer behavior and the efficacy of merchandise placement strategies. This, in turn, can optimize customer traffic and overall shopping experience.

One significant area where computer vision is transforming retail in sports is through intelligent visual merchandising. Retailers can utilize computer vision algorithms to analyze customer behavior, identify popular product categories, and optimize product placement on store shelves. By understanding customer preferences and buying patterns, retailers can create visually appealing displays that attract customers and maximize sales potential. Computer vision algorithms can also track inventory levels in real time, ensuring that popular sports products are always available, while automated alerts can be triggered when stock needs replenishment.

Let's take an example "SportStar," (a hypothetical sports retailer), which has implemented computer vision technology within its stores. They've set up smart cameras that keep an eye on customer behaviors, foot traffic, and product interest. For example, if customers frequently examine running shoes, the computer vision system takes note. It provides this information to the store management, leading to these shoes being displayed more prominently or engagingly.

Furthermore, this system isn't just looking at customer interest—it's also keeping tabs on inventory levels. Suppose the system detects that football jerseys, a hot commodity, are running low. In that case, it instantly alerts the store management to restock. Thus, this technology ensures customer favorites are always available and improves the overall shopping experience, contributing to increased customer satisfaction and a rise in sales.

By understanding customer behavior and preferences, retailers can make informed decisions on product assortment, pricing, and targeted marketing campaigns, ultimately driving customer satisfaction and increasing sales in the sports retail sector.

Conclusion

Computer vision has emerged as a transformative force in the sports industry, revolutionizing various sectors. From monitoring athlete movements and recognizing workout patterns to enhancing spectator experiences with high-definition visuals and driving automated sports reporting, computer vision technology is continually expanding the realm of possibilities in the world of sports. Computer vision applications in sports extend beyond the playing field, impacting areas such as retail, security, and ticketing.

The adoption of computer vision in sports brings numerous benefits. Athletes can optimize their performance through real-time analysis of their movements and techniques, while coaches gain valuable insights for strategic decision-making. Fans enjoy an immersive and interactive viewing experience enriched with real-time statistics and augmented reality elements. Retailers leverage computer vision to enhance the customer shopping experience and drive sales. Security measures are strengthened, and ticketing processes are streamlined, ensuring a safe and seamless experience for spectators.

As computer vision continues to advance, it presents exciting opportunities for growth and innovation in the sports industry. Leveraging this cutting-edge technology can improve athlete performance, enhance fan engagement, and increase operational efficiency for sports organizations. To stay ahead of the curve and harness the full potential of computer vision in sports, partnering with a knowledgeable consulting firm is crucial.

At Cogent Infotech, we specialize in delivering comprehensive strategic counsel and proficient implementation services for integrating cutting-edge computer vision solutions within the sports industry. Our highly adept team of professionals stands ready to collaborate closely with you, empowering your organization to harness the full potential of computer vision technology.

Take the decisive step towards transforming your sports enterprise in the fast-evolving landscape, contact us.