Sport has become one of the most data-intensive industries in entertainment. Cameras track every player and ball movement, wearables measure athletes’ bodies, and AI turns that data into decisions — from whether a ball was in, to which player to sign, to what highlights you see on your phone.

Officiating

Hawk-Eye, a multi-camera ball-tracking system, has been used for line calls in tennis since the mid-2000s and for decisions in cricket and other sports. Electronic line calling has gradually replaced human line judges at many tennis tournaments; Wimbledon moved to live electronic line calling for all its courts from 2025.

In football, FIFA introduced semi-automated offside technology at the 2022 World Cup in Qatar. Cameras under the stadium roof track the ball and many points on each player’s body, and a sensor in the ball detects the moment it is kicked. The system alerts video officials to potential offsides and generates 3D animations to explain decisions to fans. Human officials still make the final call.

Tracking and performance analysis

Optical tracking systems in stadiums record player positions many times per second. Analysts use this data — combined with event data such as passes and shots — to measure:

  • distance covered, sprints and accelerations;
  • passing networks and team shape;
  • the quality of chances, using metrics such as expected goals (xG);
  • defensive pressure and space creation.

Tactics

In 2024, Google DeepMind and Liverpool FC published TacticAI in Nature Communications, a system that analyzed corner kicks and could suggest adjustments to player positioning. In a study, the club’s experts preferred TacticAI’s suggestions over existing tactics in most cases. It illustrated how AI could become an assistant for coaches, not just a statistics tool.

Scouting and recruitment

The “Moneyball” story — the Oakland Athletics’ use of statistical analysis to find undervalued baseball players in the early 2000s — popularized data-driven recruitment. Today, clubs use machine learning to scout players across thousands of matches worldwide, project development and estimate transfer values.

Injury prevention and training

Wearable sensors measure workload, heart rate and movement. Models flag athletes at higher risk of injury from accumulated fatigue, helping staff adjust training. Computer vision analyzes technique in sports like baseball pitching, golf and running. Evidence on how accurately injuries can be predicted is still mixed, so these tools support rather than replace medical judgment.

Broadcasting and fans

  • automatic highlight generation within minutes of a play;
  • AI-generated commentary and multilingual coverage;
  • real-time statistics and win probability graphics;
  • personalized content in apps;
  • automated production for lower-league and amateur games that would otherwise not be broadcast.

Betting and integrity

Sports betting relies heavily on models. AI is also used to detect suspicious betting patterns that may indicate match-fixing.

Concerns

  • Athlete data rights: who owns biometric data collected by clubs and leagues?
  • Fairness: wealthy clubs can afford the best analytics.
  • The human element: fans debate whether automated officiating removes drama — or finally makes decisions fair.

AI in grassroots sport

The same technologies are reaching amateur clubs: automated cameras that film and stream youth matches, apps that generate statistics from video, and AI coaching tools for individual athletes. Lower costs mean that data once available only to elite clubs can help volunteer coaches give better feedback — see our guide for amateur athletes.

What to watch next

  • Further automation of officiating in football and other sports.
  • AI coaching assistants used by professional teams.
  • Rules on ownership and use of athletes’ biometric data.
  • AI-produced broadcasts for amateur and youth sports.

Key takeaways

  • Hawk-Eye and electronic line calling have transformed tennis officiating.
  • Semi-automated offside technology debuted at the 2022 FIFA World Cup.
  • Tracking data powers tactical analysis, scouting and performance metrics.
  • TacticAI showed AI can suggest tactical adjustments that experts preferred.
  • Athlete data rights and fairness between clubs are key concerns.

Frequently asked questions

Does AI decide offside in football?

Semi-automated systems detect potential offsides and help officials, but referees and video assistant referees make the final decisions.

What is expected goals (xG)?

A metric estimating the probability that a shot becomes a goal based on factors such as distance, angle and type of chance, typically calculated with statistical models.

Can AI predict sports injuries?

Models can flag elevated risk based on workload and other data, but injuries are complex and predictions are uncertain.