Forward-looking professional sports franchises are increasingly relying on analytics. Our research shows that across multiple sports disciplines and organizations (ranging from professional sports teams to athletic institutions), investments in AI over the past two decades have accelerated their growth and led to demonstrable improvements in their performance on both the sports side and on the business side.
Used in combination with big data, AI can help identify players of potentially high talent. It can be used to improve in-game strategy. Or, it can be used outside of game situations to improve training program effectiveness. These are just a few examples of the many applications of AI in sports that are highlighted in this report through actual use cases ranging from baseball and football to racing.
Included in this Intelligence Brief:
- Use cases of AI for talent identification, selection, and valuation
- Use cases of AI for pre-game preparation
- Use cases of AI for optimized in-game activity
- Deep dive into sports-oriented AI service providers
- Potential improvements, challenges, and vulnerabilities of AI-enabled systems in sports
