Top 6 Incredible Applications Of AI In Sports

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.

Applications of AI in Sports

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.

AI-Driven Sports Analysis

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:

• more profound data collection via wearables or computer vision
• using that tracking data to conduct a more in-depth type of analysis that humans would be unable to perform without AI
• deeper forecasting to produce more accurate predictions

If you are a keen reader of articles on Artificial Intelligence, you may also like to read “AI in Everyday Life.”

How AI is Being Used in Different Sports

• Basketball: The NBA has also shifted its focus to artificial intelligence and machine learning. Take HomeCourt, a computer vision and AI-based program that can aid players in honing their basketball shooting, as an illustration. After detecting the player, the hoop, and the three-point line, the app assesses whether the ball was made or missed. Additionally, it offers shooting statistics like leg angle, response time, vertical jump, and launch angle.

• Football: Information gathered by AI-powered algorithms can improve soccer. Referees can make more precise decisions by aiding technologies like Goal Line Technology and VAR. Additionally, the Madrid-based company Olocip employs machine learning algorithms to forecast the game’s outcome for the following 15 minutes on the field.

• Cricket: Cricket makes use of AI to enhance gameplay. Machine learning can accurately predict match outcomes. The analysis has improved significantly as a result of AI’s power. AI is employed in Duckworth Lewis, the Umpire Decision Review System (UDRS), and run-out analysis. Artificial intelligence can also build enclosed or indoor stadiums to play games in inclement weather.

• Baseball: Scouting new players is a significant area that has improved AI in sports. AI tracks player data such as their average speed, the angle at which they swing their bat, and how quickly they can throw an out. This aids in giving recruiters new information. Additionally, it uses VR, or virtual reality, a simulation tool that enables batters to train and hitters to master pitches from particular pitchers!

• Tennis: Wimbledon has come to life due to AI and IBM. The ability of Watson AI technology to comprehend, learn from, and communicate is revolutionary. Tennis enthusiasts may observe the game up close and personal, acquiring insightful information and enjoying a better viewing experience. The best moments of a match have been taught to IBM Watson. Everything is done by it, including listening to the sounds of the crowd, feeling their reactions, and seeing the audience’s body language. It uses each component to produce video highlights that can be posted on social media.

Conclusion

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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