AI and Sports: Transforming Team Plans and Fan Experience
By José F. Petrizzo M. – Engineer. Contributor at IT Business Solutions
Throughout history, high-level sports have served as a laboratory for the implementation of cutting-edge technologies that were later applied in other spaces and environments, even for different purposes.
Meanwhile, athletes, as workers, have long adopted relevant and emblematic positions on current issues. Their ability to influence children and adolescents makes them prominent examples in debates that transcend their victories and defeats on the playing field.
For more than a decade now, artificial intelligence (AI) has joined this dynamic, transforming high-level sports without exception. In recent years, AI has proven to be a true turning point and has become an indispensable tool for monitoring and evaluating team and player performance, optimizing tactical strategies, and improving health and safety.
AI technologies such as computer vision, machine learning, and natural language processing are being implemented to analyze vast amounts of data and provide valuable insights that were previously unattainable. As a result, artificial intelligence has reached nearly every sports organization, and its impact will continue to grow in the coming years.
The global market value of AI in sports was $3 billion in 2024, and by 2030, it is expected to reach $30 billion. This growth is driven by the adoption of AI technologies across all spheres and scenarios of the sports industry.
Benefits for Teams
Artificial intelligence is radically transforming the sports landscape for teams. From talent scouting to refining game strategies, AI provides coaches, managers, and players with the tools they need to make smarter decisions.
Teams can now use data to identify emerging stars, monitor player performance, and even prevent injuries before they occur, as predictive analysis systems generate alerts about muscle strain and potential injuries.
This includes biometric data, motion records, game patterns, and performance metrics, which are processed to provide real-time feedback and allow tactical adjustments. These advances help teams not only on the field but also behind the scenes, making everything run more smoothly and efficiently.
Recruitment and Scouting
Through the use of AI technologies, sports organizations have been able to improve talent scouting. Clubs no longer rely solely on scouts; they can now use big data from highlights and game recordings to determine a player’s potential success.
This shift will transform how teams approach everything from training to in-game decisions.
Game Strategies
One beneficial aspect of artificial intelligence is the speed at which statistical data can be analyzed. Players are equipped with wearable technology and optimized sports gear, allowing teams to track movements and gain valuable insights during a match.
This information enables coaches and staff to make strategic decisions based on trends. In the NFL, for example, nearly 250 trackers are present in each game, and 200 data points are collected on every play.
These data help build predictive models that influence in-game strategy and increase overall competitiveness, both for matches and leagues. Some of these programs include AlphaPlay®, AWS®, SportAI®, and Mission Cloud®.
The English club Manchester City uses the tool Slants® to analyze, in real time, each player’s position, speed, distance covered, and physical effort. This information is used not only to design tactical strategies but also to prevent injuries by monitoring workload and muscle fatigue.
Similarly, the Catapult® system is widely used in European and South American teams, collecting acceleration, speed, and heart rate data to help coaches tailor training to each player’s individual needs.
Sports Performance
Artificial intelligence is not only altering how teams strategize and operate but also changing how athletes train and recover.
By offering personalized, data-driven insights into player performance through comprehensive analysis, AI enables athletes to improve their performance, stay healthier, and recover faster.
From personalized training programs to injury prevention, AI’s impact on individual performance is transforming how sports organizations and players approach both preparation and recovery.
At the Paris Olympics, an event schedule was established through AI in collaboration with Intel, offering athletes a chat service based on technology from the French startup Mistral AI®.
Tennis is one of the sports that has adopted AI to enhance performance. IBM Watson®, used in tournaments such as Wimbledon and the US Open, analyzes a wide range of data to provide processed insights into player performance as well as information for spectators.
In sports like rugby and boxing, where the risk of concussion is high, AI has been used to develop monitoring systems that detect impacts and automatically assess their severity.
For example, Riddell InSite Smart® technology can transmit data about head impacts on athletes.
Training and Recovery Programs
Numerous sports companies are leveraging AI to offer athletes personalized training, nutrition, and recovery programs. Each athlete is unique, as is their specific role within the team. Therefore, special attention must be paid to each individual’s well-being to ensure optimal performance without the risk of injuries from extreme training.
AI and machine learning algorithms can be used to determine how and when a player should engage in reduced or non-contact practices, improving safety by adjusting training intensity and ensuring athletes remain within safe effort parameters, avoiding overtraining and reducing the risk of serious injuries.
In martial arts, training with augmented and virtual reality has been implemented. As a result, athletes can train against high-level opponents, even if those opponents are on the other side of the country or the world.
PozeAR®, a technology offered through Meta, employs augmented reality martial arts training. Computer vision, or AI-enhanced optical capture, can track motion data. This training allows athletes to learn from professionals by virtually stepping into their place.
Game Video Analysis
Machine learning algorithms can be developed to analyze game recordings. These algorithms streamline the review process by analyzing biometric data, video recordings, and performance statistics, allowing hundreds of data points about a player’s performance to be aggregated in minutes, significantly improving analysis efficiency.
When sports analysts aggregate data, they can identify player and team trends. This information helps sports teams optimize both game strategy and individual and collective performance.
