AI in Sports: 5 ways in which AI is transforming the sports industry
AI has made the headlines of many publications in recent months, especially since the release of ChatGPT. Even more, we’re seeing how it is rapidly integrated into the sports industry, day by day!
So let’s get ready to catch up on the latest trends!!
What is AI?
AI stands for Artificial Intelligence. In simple words, AI combines computer science and complex datasets, to enable problem-solving (IBM, 2033).
But how does it relate to sports and what are the key areas in which AI is revolutionising the sports industry at the moment?
1. Injury Prevention
Many athletes careers end ahead of time due to injuries. Even if an injury doesn’t completely end an athlete’s career, it can still have long-term implications for their physical and mental health.
By using predictive analysis, AI can help teams better understand if an athlete is, for example, overtraining or if they’ve been skipping warm up sessions, and provide further recommendations for getting back on track safely.
2. Athlete Performance
National Football League (NFL) has been using AI to analyse game film and improve player performance (Imaginovation Insider, 2023). AI can also be used to create tailored training schedules for athletes based on individual needs.
3. Training Development
AI can be used to reduce the amount of film that needs to be reviewed by coaches, by recognising patterns.
Such advancement are making sports more accessible and improving the chances of smaller teams and players in less favourable circumstances to succeed in their careers, by giving them the necessary resources, data, and tools to be more competitive against larger teams.
Since we mentioned ChatGPT earlier (how couldn’t we), we should also talk about the improvements in the area of communications in sports.
ChatGPT, alongside other similar chat services, may help in a number of areas, such as: allowing a better understanding of sports through Q&A; game & training data analysis; assisting with training plans development & sharing; improving sports marketing communications (e.g., through fan behaviour analysis, marketing copy generation, CMS automations, etc.).
We’ll be talking more about this in our next article!
5. Scouting & Recruitment
The NBA is using AI to continuously improve their scouting process, while MLB uses this technology to help teams with the decision-making surrounding player personnel (NBA, MBL, 2023).
By analysing a player’s profile (e.g., skills, past performance, physical attributes) AI systems are able to make a selection of the most suitable candidates, again, reducing the scouting & recruitment timeframes. This way, it can be assessed more objectively whether a new team member will keep up with the training and performance requirements, or even the team culture and dynamics.
With all these being said, what are the points that surprised you the most, or that you’re most excited to see developing in the near future?!
Let us know in the comments section below!!