Here are some specific examples of companies using AI in sports analytics and strategy, with numbers:
- Player Tracking and Performance Analysis:
- STATS Perform uses computer vision and machine learning to track player movements and generate advanced analytics. They track over 3.6 million events per game across 400,000 matches per year.
- Second Spectrum, acquired by Genius Sports, provides AI-powered player tracking and analytics for the NBA, Premier League, and other leagues. They track over 3.6 million events per game.
- Injury Prevention:
- Kitman Labs uses AI and machine learning to predict injury risk for professional sports teams. They work with over 100 professional teams across the NFL, NBA, NHL, and Premier League.
- Fan Engagement:
- IBM developed an AI system to automatically generate video highlights during Wimbledon, reducing the time to create highlights from hours to minutes.
- The San Francisco Deltas soccer team introduced an AI-powered smart ticketing system to personalise the fan experience.
- Game Strategy and Player Selection:
- Moneyball, the analytics-driven approach pioneered by the Oakland Athletics baseball team, used statistical models to identify undervalued players, leading to a record-breaking 20-game winning streak in 2002.
- Kick-off is an AI-powered system that predicts match outcomes using machine learning on large datasets.
- Automated Sports Journalism:
- Automated Insights uses natural language processing to generate game summaries and reports for the Associated Press, covering over 10,000 minor league baseball games per year.
Leading sports organisations and technology companies are leveraging AI across player tracking, performance analysis, injury prevention, fan engagement, game strategy, and automated content generation, demonstrating the transformative impact of AI in sports analytics and strategy.
