release date July 18, 2024 |
Jamila “Just Jay” Wilkerson
AI is changing everything in the modern era, and many industries are having to adapt very quickly to the ways new technology is changing the landscape.
One industry that has no shortage of cash and is looking to leverage AI to develop better products is the sports industry. So how will AI change the sports industry? Below, we'll explore some of the ways that AI is already being used to help teams move forward.
Probability Settings
Setting odds is just one role that AI plays in the field of sports betting. Many wonder how AI and sports bookmakers will work together, but because AI has great data analysis capabilities, companies are already using it to sift through large amounts of data to determine game odds. Meanwhile, some gamblers are using AI to study statistics to get a better understanding of what will happen in upcoming games.
AI can also transform many other aspects of the gambling world: for example, AI algorithms could potentially provide people with more specific and attractive offers based on their interests and habits.
Judgment
One thing that many fans want in certain sports is refereeing assistance. In recent years, technology has been used to assist referees in soccer, with mixed results. Soccer fans aren't necessarily looking for the video assistant referee technology they've seen for the last few years.
While this isn't using AI per se, there are other systems that use the technology, such as semi-automated offside decisions in soccer tournaments.
Many sports could benefit from artificial intelligence, both in terms of accuracy and speed of decision-making. Imagine if in tennis, every “out” call was based on a camera system that could provide umpires with 100% accuracy and near-instant results.
It will take time for these to become mainstream in the industry, and the technology to evolve refereeing is only partially in place, but just like the music industry, it is expected to bring about big changes in the future.
Each sport will have to make its own decisions about how to select referees and officials, and in some circumstances this will continue to lead to more controversial calls, and some would prefer that human influence continue into the future.
Scouting
Scouting is a highly competitive part of modern sports, with many teams doing everything they can to advance. In American sports with a draft system, it's crucial for teams to know what young talent is coming out of the college system and other systems.
Large scouting teams look for players at the amateur and junior levels to evaluate whether they can make the step up to the professional level. You can see why this can mean a lot of money for teams. Some scouting teams have built reputations based on their scouting ability and their ability to buy, develop and sell young players.
Can AI really replace humans when it comes to scouting? There is undoubtedly a lot of skill involved in identifying which players have talent, but many metrics can also be measured using video footage and AI may be capable of creating a shortlist of players. In some sports, the athletic aspect of the sport is very important and AI analysis of video footage may allow scouts to know things like the distance a player traveled during a match.
This is an area where some level of human involvement is likely to always be required. There have been examples in the past of teams attempting to move to models driven by data and statistics. Famously, Billy Beane’s “Moneyball” team, the Oakland Athletics, used models to find undervalued players and tried to remove some of the human involvement from scouting. Perceptions, such as how a player looks on the field, were replaced with statistics.
training
Of course, there are many ways in which AI can be used to modify and optimize training, many of which will come from the data collected by professional sports clubs.
For example, over time, AI may be able to analyze which training schedule produces the best results and match preparation.
Another way is to incorporate VR and similar technologies. A similar technology in the world of soccer is “Soccerbot360”, which is effectively a specific 360-degree platform where the player can interact with screens around them to pass the ball to the right place, spot teammate runs, etc. This allows the player to become immersed in the recreation of the sport without actually having to play the game with 21 other players.
Ticket Security
We are already seeing AI changing the world of ticketing, which is a big issue in some sports because reselling tickets isn't always allowed, and people need to be checked as they enter the stadium.
One example is AI-powered facial recognition technology, which can help verify that the person who purchased the ticket is the one entering the stadium.
Similar technology could be used to check whether spectators are sitting in the right place or even help fans find where they should sit.
AI can also be combined with cameras to ensure different levels of fan security. AI can also be used to spot signs of unwanted activity, such as when flares are being used.
Commentary and reporting
We don't see this much yet, but it could be coming in the future. Imagine what it would be like if smaller games had AI commentators.
Using video footage and similar technology, an AI program could potentially learn who each player on the field is, which could lead to a situation where commentary is automatically generated. While this technology probably won't replace game commentary teams, it could be a good way to get play-by-play updates for smaller matches or those without commentators.
Of course, AI has the ability to transform sports coverage, offering new levels of personalization and new ways to communicate with fans.
Conclusion
There are many different ways that AI can change sports, but once Pandora's box has been opened, there's no turning back. Each sport needs to determine where and how it makes sense to deploy AI. For example, there may be a strong focus on the refereeing side, where there is a dire need for help and assistance with refereeing.
Many teams are already using AI to focus on things like training schedules, learn more about player performance, and identify potential recruits, and we're only just scratching the surface of AI's applications.
