Around the world, sports teams are always on the lookout for ways to improve their game and gain a competitive edge. Traditionally, coaches and players have relied on intuition, personal experience, and gut feelings to make decisions. However, with the increasing applications of big data and artificial intelligence (AI), sports teams are now able to gain data-driven insights that can help them make more informed decisions. Teams and players across various sports such as tennis, football, baseball, lacrosse, hockey, and others have been using these new technologies. Following the diagram below, we will unpack the practical ways in which big data and AI are increasingly being used in sports. 

One way we are seeing big data and AI being used in sports is through the way we experience major sporting events. For example, during the 2022 World Cup there were AI-powered cameras and real-time data analysis providing athletes, coaches, and fans with valuable insights. The 15,000 cameras were able to track athletes’ movements and provide real-time data on their performance, in addition to providing the official ball report, which is precise location data on the ball that is updated 500 times per second. This not only allows coaches and analysts to make more informed decisions and commentary, but also helps referees to make the best calls. This is true across many more sporting events, where several other applications such as online betting, predictive tools and news content  have allowed fans to engage more actively with their favorite sports.

Another key use of big data and AI is for scouting and recruiting. Some examples include the Major League Baseball (MLB), which is using AI to help teams make better decisions about hiring players, and the National Basketball Association (NBA), which is using AI to improve its scouting process. An advantage of adding AI into scouting is that it has allowed for a democratization in the process, where smaller teams who do not have the resources to hire a scouting team to go over countless hours of footage can now use an AI system to facilitate the scouting process. For example, AiScout, a platform that allows all players (even those in remote areas) to upload videos of themselves doing drills that can then be then analyzed by professional football clubs to scout amateur players from all over the world.

In terms of pre-game preparation, another of the most significant applications of big data is performance analysis. Teams can now use this data to track player performance, monitor injuries, and optimize training routines. It can also be used to create personalized training programs that are tailored to individual players, helping to reduce the risk of injury and improve overall performance. For example, three NHL teams (the Eagles, the Sixers and the Flyers) are using wearable technology to monitor player performance and health through technology developed by Catapult, an Australian-based company developing performance technology. In the same way, companies such as Seattle Sports Sciences and Sparta Science provide teams with machine learning (ML) tools that analyze athletes’ movements to improve their form and even predict injuries. The demand for this type of information on players performance has grown exponentially and it is predicted to continue to grow with a Compound Annual Growth Rate (CAGR) of 24.9% over the next 5 years.

Additionally, there is also the in-game activity component that allows coaches to use data to analyze their opponents’ strengths and weaknesses, identify patterns, and make informed decisions about game strategies. There is also a vast amount of data collected in every game related to passes, goals scored, rebounds, movement speeds, ball trajectories, shot accuracy and others, giving coaches and their teams the ability to analyze these metrics in detail and extract valuable insights. These technologies are already being used, including at the 2022 Winter Olympics, and they can give sport players around the world that extra competitive advantage.

Overall, the use of big data and AI in sports presents many opportunities for teams to improve performance, recruit new players, engage with fans, and optimize strategies. Join us in this edition of Links We Like as we highlight the ways in which these technologies continue to evolve, and their innovative uses in the world of sports.