Artificial Intelligence has been improving the sports we watch and analyze for nearly the past 20 years, but the latest generation of ultra-modern AI tools is revolutionizing every aspect of sports, from improving player and team performances to ensuring safety along with fan engagement and the experiences.

AI can process and store large amounts of data, which allows us to gain insights that we couldn't see before. This capability is at the center of the revolution. For the players, this brings improved strategies, varied training methods, and a significantly lower risk of injury.

The fans enjoy a whole new level of engagement in the game, thanks to Al-powered platforms providing content tailored to them, such as virtual reality experiences and more.

The massive impact of AI in the Sports Industry

Artificial Intelligence is revolutionizing the Sports Industry rapidly by offering solutions to common problems such as individual performance, tactical requirements, injuries and recoveries, variations in training, etc.

The capacity of AI and GenAI tools to analyze complex data and provide instant insights is ushering in a new era of athletic performance and fan engagement as well.

From predictive analytics that improve player safety and performance to AI-powered viewing experiences for fans, the influence of artificial intelligence is setting the bar higher across the industry.

1. Player and team performance

AI in Sports – How is AI Transforming the Sports Industry? — (Image Credit | Markovate)

GenAI can analyze team and player behavior to reach conclusions that would contribute to improved training and coaching. For example, they can monitor and analyze the movements of players with computer vision.

In this way, they can assess whether an athlete is moving wrongly or could be injured. Machine learning algorithms can watch game videos to identify patterns of the opposing team. Sports coaches can be made to develop wiser game plans and strategies by artificial intelligence.

Some techniques, including motion tracking and motion analysis, can capture changes in the posture, movement, or technique of a player that indicte fatigue or poor motor control.

According to a study by Grand View Research, the sports analytics market size was valued at $1.9 billion in 2020 and is expected to reach $5.2 billion by 2028, showcasing the rapid growth and demand for advanced analytics tools in sports.

The following two tools are widely applicable to player and team analysis:

SportVU: This system tracks detailed player and ball motion in a game with computer vision and machine learning. It can analyze shot mechanics, accelerations and decelerations, speed, and distance.
KINEXON: This system tracks positional and motion data in real-time by equipping players with sensors.

2. Injury Prediction and Prevention

Predictive modelling and its use to identify injury risk - Sportsmith — (Image Credit | Sportsmith)

Injuries occur regularly in professional sports. Identifying and preventing injuries before they even occur is likely one of the most thrilling applications of AI.

Teams can utilize AI algorithms to monitor an individual's motion as they move their joints and strain their muscles. It can search for patterns or instabilities that signify an injury before the symptoms themselves appear.

AI can recognize a slight deviation in the amount of strain a soccer player puts on their knee joint and warn the coaches or medical staff. Way before the injury became acute enough to cause the player to miss games, the team could either give them rest or do exercises to help them recover.

A report by MarketsandMarkets estimates that the global sports medicine market, which incorporates AI-driven health monitoring solutions, is projected to reach $9.3 billion by 2026, underlining the significant role of AI in athlete well-being.

The following two tools could be used in the AI-powered prediction and prevention of injuries:

Sparta Science: It uses computer vision and motion sensing in analyzing movement patterns of an athlete. Based on motion data, biomechanical deficiencies, and especially risks of increased injury, machine learning models are able to identify those.
Zone 7: It measures injury risk using factors such as workload, degree of fatigue, and others through artificial intelligence and research in sports science. Their methods take age, position, body composition, and medical history into account.

3. Training Through AI-Powered Analytics and Wearables

10 ways how Artificial Intelligence will impact sports in a big way — (Image Credit | Sports Tomorrow)

Smartwatches and fitness trackers are examples of wearable technology that have become essential for tracking many of the parameters mentioned earlier.

Wearable GPS devices that can track athletes' speed and location, overall distance traveled, and movement patterns are available to provide relevant information.

Wearable heart rate monitors use optical sensors to measure blood flow in real-time, tracking the heart rate. This is an important aspect of monitoring heart health, fitness levels, and recovery. It also helps in tracking blood oxygen levels, which is another important component of modern-day fitness trackers. They use optical sensors to track the oxygen saturation level of blood.

Since the 2010s, Inertial Measurement Units (IMUs), such as GPS tracking vests, have been commonly used in professional sports. Such vests are offered with discrete and effective GPS tracking and sensors located on the back and shoulders; they are typically worn as tank tops.

In football and rugby, the vest is mainly utilized to track the location and movement of a player and, thereby, report strengths and weaknesses.

4. Sports Commentary and Reporting

Sports commentary and reporting can automatically be generated from match events and live data by employing natural language processing (NLP) methods like GPT-3. Artificially intelligent commentary not only comments on a strategy but also summarizes the critical events of match play.

Similarly, GenAI can create such highlights, summaries, and post-match data reportage for viewing audiences as well.

NLP methods can make the commentary more dramatic and interesting by taking into account the game statistics and situations in real-time data. With the use of generated personalities and tones, it is possible to accommodate various fan interests in the coverage.

Automated GenAI reporting enhances sports coverage and commentary without losing interesting and captivating stories.

5. Sports Officiating

The Role of AI and Computer Vision in Sports | Griffon Webstudios — (Image Credit | Griffon Webstudios)

The use of AI in sports officiating is not without controversy, including traditional backlash and concerns regarding technology's influence on the game. Yet, the improvements it introduces, such as real-time analysis and decision support, are dramatically enhancing the accuracy and fairness of officiating.

Its capabilities to review plays from multiple angles and analyze them in seconds are proving invaluable in high-level games where every call matters.

Despite initial doubts, the use of AI in officiating is increasingly being accepted, with many seeing its potential to eliminate human error and ensure a level playing field.

As the technology improves and its uses extend, its role in assisting fair play and accuracy in sports is poised to increase, ushering in a new era in the use of technology and sportsmanship.

6. Player Scouting

AI in Sports: Practical Uses, Impacts, Examples & Trends — (Image Credit | Intuz)

Team owners are using artificial intelligence to review the performance of the players. To determine the most skilled people to invest in, they use data analysis using artificial intelligence. It takes millions of dollars to find talent in the sports world.

So, team owners would like to ensure that scouting one player is the best decision. Artificial intelligence is used widely in scouting players for any sport, be it cricket, football, or basketball.

AI-powered Change in Fan Engagement and Experiences

1. Personalized Fan Engagement

To provide customised fan experiences, GenAI algorithms can model the preferences and behaviours of audiences. Sports teams and broadcasters can use these insights to optimize engagement across media channels.

For example, social media platforms can deliver tailored video highlights, personalized promotions, and AI-recommended content to resonate with each fan.

The NBA revealed 'NB-AI', allowing fans to activate "movie mode" and watch live games animated like popular films, such as Spider-Man

pic.twitter.com/zb2IYT2YBX
— Dexerto (@Dexerto) February 16, 2024

Based on their past interactions and activities, the Generative AI identifies what content types, sports stats, and topics each fan finds most appealing. It creates and sends personalized content for each person. This level of customization, enabled by GenAI in sports, helps sports organizations connect more deeply with their audiences.

2. Viewing Experiences

GenAI can process live video to generate augmented reality (AR) overlays and graphics that enhance broadcasts or live streams.

For example, shot trajectories, real-time player stats, and situational analysis can be visualized and overlaid onto the gameplay footage. For virtual reality (VR), GenAI can create real-world simulated environments for an immersive in-game perspective.

The key innovation is using Generative AI to dynamically generate and adapt AR/VR overlays and environments on the fly, customized to each moment. As the narrative and action of the game shift, the GenAI-powered augmented experiences shift with them, elevating viewing to multidimensional engagement.

A survey conducted by PwC found that 65% of sports fans are interested in using AR or virtual reality (VR) devices to watch sports, indicating a growing appetite for immersive experiences enabled by AI-driven technologies.

Conclusion

AI collaboration with sports is making the place safer as well as fairer. Predictive modeling and algorithms in AI are becoming a must for injury prevention. AI guarantees that more accuracy and fairness can be introduced in the outcome of a game by enhancing officiating. Both the aspects of performance and integrity are vital components in ensuring the prosperity and popularity of sports continue.

The impact of AI reaches sports journalism, advertising, and the creation of next-gen sports equipment, beyond the field or court. These innovations create new revenue streams and provide more exciting ways for fans to engage with their beloved sports and teams.

In this sense, artificial intelligence in the sports field could be said to be, by itself, a change not only for the athletes or for the coaches but for the sports system in general. With AI, the sports of the future could easily be foreseen because technology would harmoniously mix with manly athleticism at its highest levels.

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