Sports and Media
The Role of Artificial Intelligence in Sports
Shikha Negi
Contributor
According to a report by PwC, the sports industry is expected to grow a lot, mainly due to improvements in AI. By 2027, AI in sports is predicted to reach a value of $29.7 billion worldwide. The use of AI technology can improve how fans engage, enhance performance, prevent injuries, and expedite recovery. Let's explore how AI will continue to shape the future of sports.
Table of contents:
- Introduction
- What is AI in sports?
- AI in Sports: Innovations by authorities and brands
- AI in sports
- Role of artificial intelligence in modern sports
- How AI is enhancing fan engagement
- The future of AI in sports
Artificial intelligence has greatly changed the way sports are watched and analysed over the past 20 years. AI and machine learning are improving the game for players, broadcasters, sponsors, and viewers, who can now access real-time data.
The Machine Learning and Data Analytics technology used to integrate Artificial Intelligence in sports plays a key role in informed decision-making for athletes and professionals.
Some of the major highlights of how AI leverages sports:
- - Technologies such as Hawk-Eye and Statcast provide precise data on player movements and ball trajectories.
- - The National Basketball Association (NBA) employs Second Spectrum’s AI platform to offer real-time game analytics, enhancing the viewer experience.
- - AI platforms like IBM Watson have been used in tennis tournaments such as Wimbledon to predict match outcomes and provide in-depth match analysis.
- - AI betting models are estimated to power a $140 billion global sports betting industry by 2028.
- - Chatbots powered by AI, such as FIFA's chatbot for the 2022 World Cup, engaged millions of fans, providing live updates and information.
- - Research shows that 60% of sports fans use virtual assistants to access match details or stats.
- - Apps like ESPN, HomeCourt, and SmartCoach have revolutionised both the spectator experience and athlete training. HomeCourt, for example, uses AI to track basketball shooting techniques, with a 94% accuracy rate in analysing player movements.
The global sports analytics market, valued at $2.2 billion in 2022, is projected to grow at a compound annual growth rate (CAGR) of 26.5% to reach $22 billion by 2030.
What is AI in sports?
Artificial intelligence (AI) has rapidly gained popularity in many industries, including sports. AI technology is changing how teams prepare, compete, and interact with fans, as well as improving administrative tasks.
AI is now a crucial part of sports events, as it can quickly analyse large amounts of data with great accuracy, something that can be difficult for human analysts due to the volume or complexity of the data.
Sports events are fast-paced, and sometimes a single decision can completely change the outcome of a game. Therefore, real-time data processing is essential. AI is able to analyse massive amounts of data in the shortest time, providing insights that help make critical decisions during events.
AI in Sports: Innovations by authorities and brands
Sports organisations and brands around the world are using artificial intelligence (AI) to improve performance, safety, and fan experience. AI is helping to make better decisions in real time, reduce mistakes, improve player skills, and enhance the way fans enjoy sports. Below is a detailed look at how AI is being used in different sports.
1. FIFA & AI in Football
Football, the world's most popular sport, has seen major improvements with AI technology. AI helps referees make better decisions and improves the overall experience for players and fans.
Semi-Automated Offside Technology FIFA introduced AI-based offside detection at the 2022 FIFA World Cup to improve accuracy and speed in decision-making. The system uses 12 cameras in stadiums to track 29 points on each player's body, collecting data 50 times per second. AI processes this data instantly to detect offside positions, helping referees make faster and more accurate calls.
VAR (Video Assistant Referee) Upgrades FIFA has also upgraded VAR technology, which uses AI-driven video analysis to help referees make better decisions. AI analyses multiple camera angles and uses image recognition to review crucial game moments, such as fouls, handballs, and penalties. This reduces errors and makes refereeing fairer in major tournaments.
2. NBA & AI-Driven Data Analysis
The NBA has adopted AI to improve game performance, player strategies, and audience engagement.
AI-Based Player Tracking AI-powered SportVU cameras are installed in NBA arenas to track player movements, shooting accuracy, and defensive plays. These cameras collect millions of data points per game. Machine learning algorithms analyse this data to assess player performance, fatigue, and playing style. Coaches use these insights to make better decisions about substitutions, defensive tactics, and training methods.
AI-Generated Game Highlights The NBA uses AI tools to automatically create game highlights based on real-time events and crowd reactions. AI reviews fan engagement, game intensity, and key moments to generate personalised highlight reels for social media. This technology also allows teams to create custom video content for sponsors and broadcasters.
3. Tennis & Hawk-Eye Innovations
Tennis has been a leader in using AI for ball tracking, line calling, and match analysis.
AI-Powered Ball Tracking (Hawk-Eye Technology) Hawk-Eye is an AI-driven system that provides real-time line calls and ball tracking in tournaments like Wimbledon, the US Open, and the Australian Open. High-speed cameras track the ball’s movement with millimetre accuracy. This AI technology has replaced human line judges, reducing errors and improving fairness in matches.
AI-Based Match Predictions AI models analyse historical match data, player statistics, and real-time performance metrics to predict match results. AI-powered platforms like IBM Watson assess player speed, stamina, and shot accuracy to provide insights for fans, commentators, and analysts. Betting companies and sports experts also use these AI predictions to evaluate player performance and match odds.
4. Formula 1 & AI in Racing
Formula 1 teams use AI and machine learning to optimise race strategies, car performance, and safety measures.
AI-Optimised Race Strategy AI-driven race simulations help teams like Mercedes, Red Bull, and Ferrari make quick decisions on pit stops, tyre choices, and fuel management. Machine learning models analyse weather conditions, track temperatures, and past race data to suggest the best strategies. AI also predicts the impact of pit stop timings and tyre changes on race outcomes.
AI-Based Car Performance Analysis Formula 1 cars are equipped with thousands of sensors that collect real-time data on engine performance, aerodynamics, and tyre wear. AI analyses this data to optimise car setups, reduce drag, and improve fuel efficiency. AI has also helped reduce mechanical failures and improve driver safety.
5. NFL & AI in American Football
The NFL uses AI to enhance game analysis, injury prevention, and play strategy.
AI-Based Injury Prevention The NFL works with AI research teams to study helmet impact data and design better safety gear to reduce concussions. AI-driven injury prediction models examine player movement, collisions, and fatigue to prevent injuries. Wearable sensors also track athletes’ workloads to optimise training and recovery.
AI in Play Calling AI-driven analytics help coaches predict opponent strategies based on past play patterns and game situations. AI-assisted scouting platforms analyse defensive formations and offensive plays, providing real-time tactical recommendations. This allows teams to make more data-driven decisions about play calls and defence strategies.
6. Adidas & AI-Driven Sports Gear
Adidas has integrated AI into footwear and clothing design to improve athlete performance and innovation.
AI-Powered Shoe Design Adidas uses AI to create high-performance sports shoes by analysing data on athlete movement, running style, and pressure points. AI helps design custom soles and grips to improve traction, comfort, and durability. The Adidas 4D Run series is an AI-designed running shoe made using 3D printing and biomechanical data.
AI in Apparel Manufacturing AI-powered body scanning technology enables Adidas to produce custom-fit jerseys and compression wear for athletes. AI algorithms optimise fabric cutting to reduce waste and improve material efficiency.
7. Nike & AI-Powered Performance Analytics
Nike uses AI to improve athlete training, product personalisation, and sports science.
Nike AI Coaching Apps The Nike Training Club app uses AI-driven coaching to offer personalised workouts, recovery plans, and fitness tracking. AI analyses user data to provide real-time feedback on running efficiency, stride patterns, and workout intensity.
AI-Based Shoe Personalisation Nike uses AI-driven gait analysis to create custom footwear for professional athletes. AI-powered motion sensors help design shoes that adapt to different playing surfaces and movement styles.
8. Wimbledon & IBM Watson AI
Wimbledon has partnered with IBM Watson AI to enhance fan engagement, match analysis, and content creation.
AI-Generated Highlights IBM Watson uses AI to automatically generate match highlights by analysing crowd reactions, player expressions, and key moments. AI identifies the most exciting moments in a match and creates highlight reels for fans and broadcasters.
AI-Powered Match Insights AI processes millions of data points from historical and live match data to provide predictive insights on player performance. AI-powered dashboards offer real-time strategic insights for commentators, analysts, and coaches.
AI in sports
AI is no longer just used for looking at data; it has become a valuable tool for helping teams improve their performance, enhance player health, and change the way fans experience the sport.
1. AI-driven training programs
In the past, athletes relied on their coaches' expertise to improve. Now, AI takes this a step further. During training, data is collected on an athlete's running speed, endurance, and reaction times. AI systems can process this data and create personalised training plans that focus on each athlete’s strengths and weaknesses.
For example, a sprinter may need to work on their start, while a basketball player may focus on agility and spatial awareness. AI can identify these areas for improvement much faster and more accurately than a coach. This allows athletes to reach their full potential while avoiding overtraining or injuries.
2. Fatigue and stress monitoring
Injuries are common in professional sports, but AI can help prevent them. By tracking an athlete’s movements and biomechanics, AI can spot patterns that indicate an injury might occur before symptoms appear.
For example, AI might detect a slight difference in the stress placed on a soccer player's knee joint and alert coaches or medical staff to the issue. They can then adjust the athlete’s training or give them rest before a serious injury happens. AI also helps monitor recovery, making sure training plans are adjusted as needed to aid healing.
3. Monitoring stress and fatigue
Fatigue and stress can seriously affect an athlete’s performance. AI sensors, often in wearable tech, monitor an athlete’s heart rate, oxygen levels, muscle strain, and stress hormones. The AI systems use this information to determine when a player is approaching physical or mental exhaustion.
This allows teams to adjust training intensity and the number of games a player competes in. By monitoring fatigue proactively, teams can help players stay in top condition, especially during critical times like tournaments or playoffs.
Role of artificial intelligence in modern sports
1. Improving performance and training: AI-powered tools are being used more and more to help athletes improve their performance and training. Advanced motion-tracking systems analyse the way athletes move, helping them improve their techniques and avoid injuries. Wearable devices, which work with AI, track real-time data like heart rate, speed, and muscle activity. This information helps both athletes and coaches design training plans that give the best results. For example, football clubs use AI to predict when players might be tired or at risk of injury, which helps in creating better recovery plans.
2. Making decisions with data: AI has had a big impact on how decisions are made in sports. AI models can process large amounts of data to offer insights into game plans, player performance, and how the opponent is playing. In cricket, for example, AI tools can help identify patterns in batting and bowling, giving teams an advantage. In basketball, AI studies shooting techniques and defensive moves, helping teams adjust their strategy during the game.
3. Changing how fans engage: AI is changing the way fans interact with sports. AI helps deliver personalised content, making sure fans get updates, statistics, and highlights that match their interests. Chatbots are used by sports organisations to improve customer service, ticketing, and selling merchandise. Virtual reality (VR), enhanced by AI, allows fans to experience the game as if they were there, no matter where they are.
4. Making officiating more accurate: AI is improving the accuracy of refereeing in sports. Technologies like Hawk-Eye and Video Assistant Referee (VAR) use AI to review decisions in sports like tennis and football. These systems reduce the chance of human error, ensuring that the game is fair and upholding the integrity of the sport.
5. Finding new talent: AI is also playing an important role in finding and recruiting new talent. Machine learning models look at player statistics and performances from different leagues to spot potential stars. Teams and clubs use this information to make smarter recruitment decisions, saving time and resources.
How AI is enhancing fan engagement
Sports fans, whether they are into racing, tennis, football, or cricket, all want to feel involved. Whether a racing team manager is deciding when to change tires or a football coach is picking their next substitute, fans often wish they could share their opinions. Big sports competitions and leagues are using AI in the gaming world to offer detailed real-time data on player performance and match insights, bringing fans closer to the decisions that coaches might make. As a result, fans are enjoying better viewing experiences thanks to the use of technology in sports. They can also learn from the comfort of their homes.
AI systems are helping sports organisations provide more personalised experiences and recommendations for fans. If a venue doesn't meet fan expectations, the excitement of being at a live sports event can quickly fade. To improve the overall experience for spectators, many stadiums are now using AI-driven technologies. Fans are passionate and devoted, and they have a strong desire for sports-related products and services.
AI can process huge amounts of data to identify patterns, unusual activities, and even new types of fraud, as it learns from billions of transactions worldwide. It can also help analyse tournament ticket sales and use advanced analytics to offer insights into customer behaviour and buying habits. When used properly, AI enhances the fan experience by ensuring safety at live events and offering more personalised interactions.
The future of AI in sports
In the future, teams and coaches will be able to create better strategies by studying data on their opponents and making real-time changes. As AI technology becomes more advanced and accurate, and as more data is collected, it will help teams make better decisions. With the right use of historical data, past events, and other factors, AI models will be able to predict incidents with greater accuracy.
Sports are not only a source of entertainment but also help build teams and support businesses. As AI becomes more important in sports, people are paying close attention to what the future holds. By 2030, the AI industry in sports is expected to grow quickly, reaching a value of US $19.2 billion. This suggests that there is a lot of potential for major breakthroughs in the future.
Thanks to AI, we are living in a time where robots can report games and change how the media covers sports. Media outlets can now share stories using AI, without needing to physically be at the event or set up cameras. By using AI to cover every moment of the game, content sharing will grow, leading to more fan engagement.
Data-sharing will also help players and teams predict the next move of their opponents, which will improve how strategies are developed. Virtual Reality (VR) and Augmented Reality (AR) are expected to see massive growth. By 2031, the global VR industry for sports and entertainment is predicted to reach $56.7 billion. Sports teams in the NFL and NBA, as well as networks like ESPN, are already using AR and VR to enhance fan engagement and show how AI is transforming sports.
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