Artificial intelligence is providing players, coaches and league officials with deeper insights than ever before. Let’s take a look at some of the ways AI is taking the sports industry to the next level. <br>Professional sports are extremely competitive, with games often decided by a matter of seconds or inches, so many teams are turning to <a href="https://builtin.com/artificial-intelligence" target="_blank">artificial intelligence</a> to gain an extra edge on the competition. AI helps coaches recruit the best athletes, reduce player injuries and make better play calls. It is also used to ensure referees’ accuracy and to enhance the <a href="https://councils.forbes.com/blog/ai-in-sports-and-the-fan-experience" target="_blank">fan experience</a>.<br>Sports teams use artificial intelligence to identify top players, prevent injuries and make in-game decisions. AI is also used to double-check referee calls and to enhance live broadcasts.<br>As futuristic as these examples may seem, AI’s transformation of the sports industry has only just begun. Leagues and teams are rolling out new AI-powered tools every season, with each change elevating the game to a new level of sophistication.<br><span><span>Related Reading</span><a href="https://builtin.com/artificial-intelligence/ai-future-sports" target="_blank">Is AI the Future of Sports? </a></span><br> <br>AI is used to help coaches, players and referees perform to the best of their potential. Here are a few examples.<br>More and more, professional sports leagues are testing referees’ eyesight and snap judgments with <a href="https://builtin.com/articles/computer-vision-sports" target="_blank">computer vision</a> and high-framerate video. One of the leading companies in this space is <a href="https://www.hawkeyeinnovations.com/" target="_blank">Hawk-Eye Innovations,</a> which has developed AI-powered video technology that can detect when a soccer player is offside, a tennis ball goes out-of-bounds or a hockey puck crosses the goal line.<br>Major League Baseball is using Hawk-Eye’s technology for a new <a href="https://www.mlb.com/news/automated-ball-strike-calls-mlb-spring-games" target="_blank">“automated ball-strike challenge system”</a> that it’s testing out in 2025 spring training games. During this trial period, pitchers, batters and catchers — but not managers — are allowed to challenge an umpire’s ball or strike call. When a call is challenged, officials turn to Hawk-Eye to see whether the pitch landed within a batter’s strike zone. Each team gets two challenges per game, but successful challenges will not count against that allocation.<br>Almost every professional sports league uses sensors and cameras to gain player performance data that can then be analyzed to evaluate players and improve their weaknesses.<br>When Major League Baseball introduced <a href="https://builtin.com/articles/mlb-statcast-tech-update-hawk-eye-integration" target="_blank">StatCast</a> in 2015, for example, it opened up a new world of statistics, like the spin rate of a pitch and the “exit velocity” of a batter’s hit. Derived from <a href="https://www.mlb.com/glossary/statcast" target="_blank">Hawk-Eye video analysis</a>, these numbers add a new dimension to the game for the media, broadcasters and fans, and coaches use this data to evaluate players and look for areas of improvement. <br>The National Football League also uses AI to generate<a href="https://operations.nfl.com/gameday/technology/nfl-next-gen-stats/" target="_blank"> statistics</a> about player performance. By placing radio frequency identification (RFID) tags in players’ shoulder pads, inside the football and in endzone pylons and first-down markers, the league can track the location, speed and traveling distance of each player, as well as the football. These sensors generate data points — like probability of pass completion, for example — that can be used to evaluate players and inform coaching strategy. <br>AI can help talent scouts process large amounts of data from various sources to develop detailed profiles of players that meet their needs. These profiles can then be used to predict a player’s performance, for example, or anticipate how a given player’s skills will complement those of other players on the team.<br>There are several companies that specialize in predicting player performance. <a href="https://news.microsoft.com/source/features/digital-transformation/machine-learning-unlocking-secrets-human-movement-reshaping-pro-sports/" target="_blank">P3 Labs</a> studies the subtle mechanics of how athletes move, and then it compares those biomechanical AI models with those of existing players to predict the future trajectory of an athlete’s career. Another company, <a href="https://probility.ai/" target="_blank">Probility AI</a>, says it can predict with 90 percent confidence if a player is likely to get injured and if they will be a good match for their team.<br><span><span>Related Reading</span><a href="https://builtin.com/articles/football-analytics" target="_blank">Is Football Ready for a Tech-Driven Revolution? </a></span><br>Coaches can leverage the power of probability models to inform real-time decision-making, like which play to call out or which player to put in. Liverpool FC, a soccer team in England’s Premier League, has leveraged <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC10951310/" target="_blank">TacticAI</a> to decide on an optimal strategy for corner kicks.<br>In baseball, these models can tell fielders where a batter is most likely to hit the ball, and it can tell pitchers which types of pitches will be most effective against each batter. In the future, technologists <a href="https://www.economist.com/science-and-technology/2025/02/12/how-artificial-intelligence-is-changing-baseball" target="_blank">hope to develop </a>a similar tool for pitchers as well. Such a model might detect how subtle differences in a pitcher’s wind-up might foreshadow whether they’re about to throw a changeup, a curveball or a slider.<br>Artificial intelligence can be used to analyze data obtained from trackers and sensors to determine an athletes’ workload limit, and then alert coaches when a player is reaching that limit. From there, coaches can adjust the player’s training to prevent injury from overuse. <br>AI can help prevent injuries that result from poor technique, too. Companies like <a href="https://www.p3.md/" target="_blank">P3 Labs</a> that analyze biomechanical models of athletes can identify which types of movements are more likely to lead to an injury, and then work with athletes to correct their form.<br>The NFL has also developed an AI-powered injury prevention program, called <a href="https://www.nfl.com/playerhealthandsafety/equipment-and-innovation/aws-partnership/revolutionizing-player-health-and-safety-with-the-digital-athlete" target="_blank">The Digital Athlete</a>, which analyzes practice and game footage, running millions of simulations to determine when players are at the highest risk of injury. That information is used to help players prevent and recover from injuries. It’s also used to develop rule changes, like the league’s new <a href="https://operations.nfl.com/the-rules/rules-changes/dynamic-kickoff-rule-explainer/" target="_blank">dynamic kickoff</a> configuration.<br>AI technology is also incorporated into Riddel’s <a href="https://content.riddell.com/InSite/" target="_blank">smart helmet technology</a>, which can detect the location and severity of impacts to a player’s head. This data can be used to correct players’ techniques and adjust their position and playing time.<br>AI-powered <a href="https://builtin.com/robotics" target="_blank">robots</a> are starting to be incorporated into professional sports, providing a tireless practice companion when there’s a shortage of human players. For example, the Golden State Warriors <a href="https://www.youtube.com/watch?v=Qv4FxFDHJTA&t=149s" target="_blank">practice with two types of AI robots</a> — one can rebound and pass balls back to players during shooting practice, while the other is trained to play defense, pouncing on the slightest hesitation in a player’s movement.<br><span><span>Related Reading</span><a href="https://builtin.com/articles/big-data-companies-sports" target="_blank">Sports Analytics: What It Is, How It’s Used </a></span><br><span><span><span><span><span><span><span>Artificial intelligence is used to evaluate players, inform coaching decisions, double-check referee calls and reduce injuries.</span></span></span></span></span></span></span><br> <br><span><span><span><span><span><span><span>The NFL uses AI to reduce injuries through The Digital Athlete program. It also uses sensors to generate “next generation statistics,” helping teams evaluate players and refine coaching strategies.</span></span></span></span></span></span></span><br><span><span><span><span><span><span><span>The future possibilities of AI in sports are endless. Researchers hope to generate more accurate and personalized insights in a more timely manner. They also hope to refine their biomechanical AI models to learn what sets all-star players apart from others.</span></span></span></span></span></span></span><br><br><a href="https://news.google.com/rss/articles/CBMiZ0FVX3lxTE9mbkEybk5XMnZac1VTRW0tZzhlUkFudG44b01aU3BoaElQaGxna1ZRYkhxdWVpbmpSaGd0YV8zTjBsanRXay1EOEFrd01SODJrVUdjdkhYVlQ3S1k1eVJWemtQbHhoYzA?oc=5">source</a>
