After seeing the match of Japan vs. Spain in Football Worldcup 2022, VAR has peaked up a hike. VAR (Video Assistant Referee) is an AI-based technology that utilizes 12 dedicated tracking cameras to generate 3D models of an athlete’s body to analyze whether any part of their body is offside. Baseball, Football, and cricket are among the the sports that have utilized this technology.
But understanding VAR raised a query what are other applications of AI in sports that we don’t know of?
Artificial intelligence is being utilized in sports to plan strategies, coach athletes, market, and much more, from football/soccer to Formula 1. In other words, AI significantly impacts how people watch and consume sports information. According to research, the market of AI sports is expected to be worth $1.8 billion in 2021. The study adds that this market will reach around $19.9 billion by 2030.
1. AI Referee
The robot or apparatus serving as the AI referee is not required to stand with the participants on the ground. With the availability of cameras from various perspectives, AI may create the player’s 3D view to comprehend the environment better. This video will enlighten you precisely about VAR.
2. AI Ticketing
An AI ticketing system uses automation and AI technology to resolve tickets quickly. Self-serve and ticket categorization is made possible by an AI ticketing system in a sporting venue, increasing productivity and patron satisfaction.
3. Personalized training with AI
Using AI for individualized training is a technique that focuses on creating a movement to match each athlete’s specific needs. One way to see it in all of its glory is through the lens of tailored training. Each player receives personalized training that is adapted to their particular needs.
4. Automated sports journalism
Automated sports journalism is a computer program known as algorithmic journalism. Instead of using human reporters, artificial intelligence (AI) software generates news automatically using computers.
5. Fitness, Health, and Safety
One of AI’s most potential applications for occupational safety is computer vision. This technology may be used for various things, including keeping an eye on employee behavior, spotting potential risks, and sending out instant alerts. Thermal cameras, for instance, can detect heat exhaustion in employees.
6. Match predictions
While estimating the possibility of a particular occurrence, such as whether a batter in cricket would score above 50 runs and whether that would help the team to win, such prediction requires the AI algorithm trained on past data integrated with the current data.
Sports analysis has traditionally been based on box score and event data, from Bill James’ grassroots project Project Scoresheet, which aimed to create a network of baseball fans to gather and distribute information, to Daryl Morey’s integration of advanced statistical analysis in the Houston Rockets in 2007.
Tracking data paved the way for fresh approaches to sports analysis in the 2010s. A new era of sports analysis has developed over the past ten years, enhancing the utility of conventional box-score and event data by combining it with deeper tracking data. Thanks to tracking data, the revolution of AI in sports has concentrated on three main areas:
If you are a keen reader of articles on Artificial Intelligence, you may also like to read “AI in Everyday Life.”
Aiding AI in sports, it has become a lot more competitive than ever before. It can forecast competition results better with better sensors and algorithms. Advertisers, sports organizations, franchise owners, coaches, and game designers will all be impacted by AI. Given the scope of implementation, it is likely that every sector of the sports industry will look to adopt AI to outperform its competitors.
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