AI Changing Sports Tech

Automation and AI are at the forefront, driving numerous industries in the pandemic world. As things slowly return to normal, they would never be the same again. In fact, the pandemic has unlocked the true potential of artificial intelligence and paved the way to a more technologically advanced society.

The Tokyo Olympics recently ended after being postponed for more than a year due to coronavirus concerns. With the new calendar, however, the increased use of artificial intelligence came on the table. Since the sports industry requires numerical computation, it is an ideal environment for artificial intelligence. Let’s see how AI changes the sports industry forever.

How Is AI Used In Sports

While many things in the world are unpredictable, there is AI for things that can be predicted using data. And the world of sports is a quantifiable thing. The use of AI in sport has gained acceptance in recent years. The positive effects it has left on the fitness industry will only keep stretching arms in sports. According to PwC research, AI-based tools are already used in almost all major sports disciplines such as cricket, baseball, soccer, and and American football, as well as non-professional recreational activities such as popular sports. These tools include sensors, wearable devices, and computer vision cameras that collect data on athletes’ performance.

In addition, natural language processing devices can use speech and text recognition to gain insight into the mood of the audience. All of this data can be processed using machine learning (ML) and deep learning (DL) systems to create predictive models and enable trainers to make better decisions. Let’s get into the details.

Recruiting New Team Members

Evaluating an athlete using quantitative metrics may not tell you much about them, but their performance can be tested. Sports organizations use this data as a measure of the athlete’s physical condition and potential. However, the data used for recruitment does not imply the use of well-known statistics of the person, but rather the use of more complex metrics that take other aspects into account as well. The process of data collection has become even easier and more reliable since big data and artificial intelligence took over sports management historical data to predict the future performance of players before they are hired. The same process is used to predict players’ market values ​​before making a contract offer to new talent.

Keeping Athletes Fully Fit

The analytical and predictive capabilities of AI go beyond just recruiting new players, they also find application in medical diagnostics, which is critical to player performance. AI-powered tools can check various physical parameters, such as athletes’ movements, to determine their condition and location. Injuries before the players even know. Gathering information with sensors is necessary for data analysis in healthcare, and according to the latest trends, health wearables are the best products for it due to their portability and low prices. They are most popular not only with professional athletes but also fitness enthusiasts. According to a study by Marketandmarkets, wearables are the largest and fastest growing part of the sports equipment market.

Broadcasting And Streaming Of Sports

In addition to making it easier for players and coaches, AI can revolutionize live streaming and affect the way viewers experience sports. Artificial intelligence can also change the way broadcasters make money from sporting events. In addition, AI systems can be helpful for automatic selection, an appropriate camera angle to provide the best viewing experience possible. It can intelligently provide subtitles for live sporting events in viewers’ preferred languages ​​based on their whereabouts. AI systems can also use reactions and emotions to determine the best ways to serve ads. This allows broadcasters to effectively make money from ad sales.

Are There Any Downsides?

As they say, “the applause does not come unreservedly,” the use of artificial intelligence systems could have some drawbacks. Data sharing can be used for gambling purposes as there is an immense amount of financial benefits associated with it. The NCAA signed a 10-year contract with a United Kingdom. IT company for collecting and selling sports data to media companies. Another challenge could be keeping human talent intact, as AI could take over sports like auto racing, where the results are more influenced by non-human elements. For example, winning an F1 race, almost anything, it is based on data including the time taken during a pit stop.

Leveraging the data collected by the built-in sensors is so important that Formula 1 teams are using Amazon’s cloud computing services. This information can be stored and sent to AI to develop the best strategies for success. This trend can spread to all other sports and lead to a conflict between human talents and artificial intelligence systems.

But we must not forget that despite the use of AI for predictions, we cannot rule out the unpredictability and surprise of sport due to the human element; Because that’s what makes sport exciting for viewers all over the world.

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