AI is changing our understanding of sports and revolutionizing how we measure and understand the massive amounts of data available. This is because AI technology can process and interpret data in real time with high accuracy, allowing sports athletes and coaches to take advantage of this information to transform the global sports industry. For example, athletes can learn more about their abilities and limitations, whereas coaches can make data-informed decisions about training and performance. Continue reading to learn about the most exciting uses of artificial intelligence in sports.
Thanks to machine learning and deep learning algorithms, AI can offer athletes personalized training and diet plans. For instance, an AI diet plan can customize different meal plans based on the player’s current needs and schedule. For example, AI offers specific dietary recommendations based on whether the player has a match the next day or is recovering. One of the popular AI-assisted dietary apps is FoodVisor. It can identify different types of foods through object recognition and report the nutritional breakdown to the users.
In addition to AI-assisted dietary apps, athletes can also take advantage of AI-assisted fitness apps. Thanks to computer vision techniques, algorithms can detect human poses in real-time, where they can identify human joints and provide the player with guidance on how to exercise accurately. For example, FitnessAI and AlfaAI are popular AI apps that help athletes train and create a fitness schedule.
AI-powered athlete tracking systems such as wearables can also measure and improve on-field performance thanks to predictive analytics. For example, PrecisionWear is a company that engineers vests worn by athletes and equipped with multiple sensors that measure up to 21 metrics, including heart rate, total stress, and fatigue. Trainers can use these measures to monitor players’ health, develop customized training programs to optimize exercise returns, reduce the risk of injuries, and maximize their strengths.
AI in sports training can also help players improve their performance by playing against artificial intelligence. For example, a company called DeepMind has trained an AI algorithm called AlphaGo, the first computer program to defeat a Go world champion. Go is an Asian board game like chess, where two players take turns placing white or black stones on the board.
Sports teams are adding AI to their scouting and recruitment process to make competition fiercer. Thanks to machine learning algorithms and computer vision in sports, AI tracks every player’s movement and the orientation of their bodies. Then, it evaluates their skills and overall potential to help make the right recruitment decision and build a successful team. The AI utilized in recruitment is similar to machine learning in gaming. Both algorithms can predict team dynamics and chemistry based on individual player statistics and performance.
For example, AiSCOUT is an AI-based platform that professional football clubs and organizations use to find and scout players through video recognition technology. The platform analyzes and evaluates players’ performance, such as their technical, physical, cognitive, and psychometric abilities.
Even though AI can’t accurately predict the outcomes of every single match yet, it can get close. Moreover, it can predict future match results much better than humans, thanks to predictive algorithms and computer vision. For instance, Kickoff.ai is an AI/ML platform that predicts the results of football matches.
In addition, through computer vision, AI collects and analyzes data based on multiple factors such as the number of passes between teammates, chances created and passes that led to a goalscoring opportunity. Then AI uses that information and data to forecast the result of future matches.
Fans struggling to get to sporting events on time are a persistent problem at stadiums. Luckily, AI can resolve this issue. For instance, stadiums provide smart ticketing services. Moreover, Wicket uses biometric analysis and facial authentication to allow fans to enter stadiums without displaying their ticket.
In addition, AI predictive analytic tools can forecast the number of attendances in the game and the time fans might be expected to arrive at the stadium. This information also helps to improve the security and organize merchandise and food according to the number of visitors.
Journalists play a significant role in reporting sports news. Every day, there are hundreds and thousands of sports matches taking place all over the world. This can be challenging for journalists to cover in little time. As a result, to alleviate such exhaustive workloads, AI bots are being used to track multiple events, write match reports, explain critical events, and offer accurate data and statistics. For example, developed by Automated Insights, Wordsmith is an AI-driven platform that translates hard data into narratives using natural language processing.
You may have heard about a Video Assistant Referee (VAR) who watches the match through different screens and can view slow-motion replays to advise the on-field referee. However, that may soon be a thing of the past. Thanks to AI and computer vision, referees can make more accurate decisions that may change the outcomes of games and reduce the margin for errors.
Implementing AI referees in the decision-making process of sports games also helps avoid anger from coaches, players, and fans. For instance, AI computer vision can assist referees in identifying potential penalties across sports, reducing mistakes and controversies from poor refereeing decisions.
AI is also revolutionizing live broadcasting. This includes the way the audience watches sports and broadcasters monetize sporting events. For instance, when streaming a game, AI systems can automatically choose the right camera angle to display on the viewers’ screens and enhance their viewing experience. In addition, the AI system can automatically generate subtitles for live events in different languages based on the fans’ location and language preferences.
On the other hand, broadcasters can use AI to identify monetization opportunities and present relevant ads based on demographics. Moreover, AI and machine learning in sports can monitor crowd excitement levels during matches and present ads accordingly to influence their purchasing decisions based on the emotions they are experiencing at the time. This is an effective way to help advertisers drive sales.
Athletes, fans, professional recruiters, and agencies are all taking advantage of the surging popularity of artificial intelligence in sports. As a result, there is no doubt that the future of sports technology lies with AI, and we’re only at the beginning. With the enormous potential for AI, from dietary recommendations to wearables and athlete tracking systems, experts expect artificial intelligence in sports to grow faster than ever while enhancing efficiency and improving decision-making.
