ARTIFICIAL INTELLIGENCE AND SPORTS

Artificial Intelligence is the science and engineering of making computer machines able to perform various tasks that normally require human intelligence, such as visual perception, decision-making, speech recognition and translation between languages. AI emphasizes the simulation of human intelligence processes by machines or computer systems. These processes include learning (the acquisition of information and rules for using the information), self-correction and reasoning (using rules to reach approximate or definite conclusions) .

Today’s sports world is becoming tech-savvy by bringing together athletes’ accurate analytics ,natural talent and AI. AI is successfully implemented to enhance decision-making and gain a competitive advantage over competitors. In combination with sensor systems, AI is able to analyze players’ performance and provide accurate real-time match statistics: strength, speed, scores, distance, percentages of possession, and more — depending on the type of sport.
AI-driven tools track the balls to millimeter accuracy and are adopted in many sports, including but not limited to football, tennis, baseball, and snooker. At some events, this technology is used to make the game safer, fairer and smarter. For some instance, in tennis and volleyball, players and coaches have the right to make an official call to the system if they are not sure about the judges’ decisions.

APPLICATIONS OF AI IN VARIOUS SPORTS

NASCAR

Safety continues to be a primary focus for NASCAR, the sport has averaged more than one death annually since 1950 and shows a continued trend for the last five years. Fatal crashes are both tragic and very costly.

Argo AI/Ford Motor Company has used deep learning to develop self-driving cars and is now expanding its application of deep learning to help improve safety in the world of auto racing.

Specifically, the design team recognized that its deep learning neural network was capable of identifying specific cars using images. The design team originally used a dataset containing thousands of images to train the neural network. It is unclear as to how much better the network performed but the team claims it was particularly evident in the case of blurry images. The reduced visibility is due to the high speeds at which the cars are moving.

As the network gained mastery, it reportedly provided more accurate results than humans in its ability to identify specific race cars. The ability to quickly identify and access a car that is experiencing a malfunction during a race is significant; small malfunctions can quickly lead to more serious problems such as fires, putting the driver in danger.

FOOTBALL

Football is a sport which enjoyed globally, with a large fan base in the billions. Naturally, it’s a sport that’s about to be infused with AI. AI and football are building a relationship that could change more than just the way a sport is played: They could be changing the way people engage with and understand AI. Below there are a few ways artificial intelligence and the football industry can play well together.

One of the technologies being used in football ties directly to the way goals are scored. Goal-line technology is a combination of video monitoring systems and AI tech that calls when and where a ball crossed the goal line. It helps make these calls more accurate when a referee doesn’t have a good line of sight.

Video refereeing with “Goal Line Technology(GLT)” can accurately pickup errors and mistakes whether a ball has crossed the goal line or not which human eye can’t due to positioning and blockage. Advanced GLT is AI powered and is far superior that has gained significant traction in the last few years.

Footbonaut is an advanced technique that helps training footballers to control and pass the ball instantaneously and effectively to another player in a simulated environment. Although training cost with Footbonaut is a bit on the higher side but the effectiveness of such a technique has proved to be very significant. It is said that one session of training using Footbonaut is equivalent to several weeks of rigorous passing training in the football ground.

Computer vision, which is a type of AI, helps with replay highlights and customer ticketing for the big event. This type of AI may go unnoticed by most, but it’s crucial for a smooth tournament experience on all sides.

CRICKET

DRS (Decision Review System) or UDRS (Umpire Decision Review System), a technology normally used in cricket to assist the match officials with their decision making process in a situation that may demand to challenge the decision taken by an Umpire. Some of the advanced techniques used in DRS are Hawk-Eye or Virtual-Eye which is essentially a ball tracking technique that plots the trajectory of a bowling delivery that has been interrupted by the batsman, often by the pad, and it can predict whether it would have hit the stumps.

Former India captain Anil Kumble’s technology start-up Spektacom Technologies launched the “Power Bat“: a unique tool powered by Microsoft’s Azure Cloud platform and it’s Artificial Intelligence (AI) and Internet of Things (IoT) services.

The Power Bat can provide real-time data on a player’s performance based on different parameters such as the speed of the ball on impact, a twist on impact and quality of the shot.

The vision is to bring sports closer to fans through interesting ways of engagement using real-time sports analytics.  At the core of the technology is a lightweight sticker which is stuck on the shoulder of the bat. In a live match, as soon as the batsman hits the ball, data on different parameters are captured in a new unit of measurement titled Power Speks. 

Microsoft’s Azure Sphere, an operating system for IoT applications, ensures that the data is securely captured and processed. Using advanced analytics and AI services on Azure, real-time insights are captured through the stump box and displayed via the broadcaster.

Tennis

AI used for assisting sensor systems in providing such data as serve speed and direction, ball placement, groundstroke hit points, topspin speed and rate, bounce height, and more.  

Computer vision Referee in Tennis
Bay Area-based French inventor Grégoire Gentil has designed a $199 pocket-size device called “Tennis In/Out”, which uses computer vision to detect the speed and placement of a tennis shot – including whether the ball was out of bounds.

A Smart Coach??

AI may become a professional assistant coach. By relying on data analytics, managers and coaches can enhance the winning chances of their teams. They get a possibility to track sportsmen both on and off the field and to create a database with all of the player intelligence stored in: current conditions, strengths and weaknesses, field dynamics, and more. The analysis of this information helps to improve decision making within the team.

Beyond that, coaches can benefit from a machine analysis of rivals. The obtained data may play a key role in changing the tactics and strategy for the next matches.

Conclusion

Artificial intelligence (AI) is revolutionizing sports and elevating it to a whole new level. While it is true that statistics and quantitative analysis have played a central role in sports for a long time, AI is significantly impacting the way games are strategized, played, and engaging the audience.