Impact of Artificial Intelligence in the Sports Industry

Kalyani Tangadpally
4 min readFeb 19, 2021

Image Source: forbes

There are countless things in the world. Everything that can be measured, can be accurately tracked using data analytics and artificial intelligence. The sports world is rich in such quantitative elements that it is ideal for the use of artificial intelligence. Applications of Artificial Intelligence in sports have become a common sight in recent years. Considering the positive impact they have brought through their growing abilities, they continue to enter the sport. The following are some areas in sports where artificial intelligence may be a major factor:

The sports industry has used statistics and data analysis since ancient times. Everything that can be measured is measurable in sports, which has become fertile ground for the use of artificial intelligence. Artificial intelligence affects us every day and the impact on sports is constant. Here are some places where AI has influenced the sports industry:

#1. AI to improve learning and efficiency:

The combination of sensor technology and AI improves the practice of AI players in sports training. It is used to provide real-time feedback and create personalized training programs for players, thus improving the performance of their workouts. Each exercise for each person

Predictive analytics by AI can be applied in sports to improve health and fitness. The wearable app can also provide players with information on tears and stress, helping prevent athlete injuries. The AI can be used to identify patterns in tactics, tactics, and weaknesses during NBA games.


That uses AI to analyze player health data to inform teams about injuries and other setbacks, Arcos caddy, an artificial intelligence platform that provides players’ virtual caddy inputs based on wind direction, which club to choose. Pressing the direction and location buttons and other important information

#2. Assisting AI Coach:

Artificial intelligence has a big impact on strategy before and during games. Making decisions on lineups before and during games is now influenced by computer analysis. Artificial intelligence can be used to improve athletic performance by understanding metrics such as rotation, speed and serving, position, and movement of a player.

In this regard, AI helps managers/coaches make better decisions for different competitions. And for an important competition

#3. AI can provide a rich experience:

AI can provide real-time analysis for sports such as Find clips or visual analysis of each player’s winning strategy. Helps players and coaches develop counter strategies and have a more realistic experience. For Roland Garros, Infosys has developed a series of statistics that will reorder the record in live matches. This direct feature is based on AI / ML principles to enhance the experience of fans and players.

#4. AI is used for better advertising:

Artificial intelligence is also used to identify the most relevant ad opportunities based on audience numbers. Brands will get better advertising opportunities based on key moments of the game, according to AI. Automated learning algorithms will monitor player actions, audience emotions, and expressions to identify them.

The most exciting moment of the game. Use it for AI streaming and broadcast: With the help of the AI platform, the camera records the event, broadcasters can choose which highlights to distribute, which hinder the monetization of sports events. Subtitles for the live broadcast are also available based on the venue’s language. Artificial intelligence in sports marketing is used to determine the best camera angles during matches and headlines/replays.

The AI also provides information on statistics for commenters to help critics use live captions better. And Opta Sports has entered into a collaboration agreement to create, manage and distribute real-time video clips for fans at events using AI.

#5. Scouting and recruiting:

AI can also be used to understand the performance of a potential recruit in the sports industry. Sports companies can use AI to track the performances of various players, and companies can analyze these records before investing in sports. Ability to recruit personnel Performance data can use more complex metrics than open statistics. (Running, Passing, Goals, etc.) Big data and AI in sports management make the process of recording and measuring future success indicators much easier.

Want to know cost to develop AI?

#6. AI in Referees:

Referees are one of the earliest examples of the use of AI in sports. In cricket, Hawk-Eye technology was used to determine if a batsman is in the LBW case. The technology makes the game no odd. Expensive and law-compliant, NASCAR has adopted AI to streamline the task process by using cameras to detect racing violations.

#7. AI in Sports Journalism:

Adding the Power of NLP Could Completely Change the Face of AI Journalism. Automated journalism is about to hit the market, and sports journalism is heavily influenced by it.AI uses sports data to write readable information about sports events.

Final Thoughts:

AI in sports is here, and as technology improves through better sensors, processors, and algorithms, it becomes even more important. Either through an internal IT organization or via an external AI platform, sports require AI to be successful at the highest levels of competition.

USM Business Systems is one of the leading service provider in Artificial Intelligence, HR Management systems, App Development, Data Quality solutions, Work Force Service to build interactive experiences for all major platforms. As a prominent Mobile development company, we are delivering top-notch and high-quality App development services to various brands and businesses irrespective of the industry.


Kalyani Tangadpally

SEO Executive and a Content Writer interested to write on Artificial Intelligence, Mobile App development, Machine Learning, Deep Learning, HRM & tech Blogs



Kalyani Tangadpally

SEO Executive and a Content Writer interested to write on Artificial Intelligence, Mobile App development, Machine Learning, Deep Learning, HRM & tech Blogs