Revolutionary Uses of Artificial Intelligence in the Sports Industry

Artificial intelligence is gaining traction across the sports business, with applications ranging from post-game analysis to in-game activity—and even the fan experience.

FREMONT, CA: For the last two decades, coaches have used data science in sports to assist their players in performing better. They've been utilizing big data to assist them in making split-second on-field judgments, as well as relying on sports analytics to assist them in signing the "next big thing." Meanwhile, referees in football now use Video Assistant Technology (VAR) to assist them in making more precise assessments on major decisions such as penalties, free kicks, and red cards. And now that AI, notably Deep Learning, is engaged, the sports experience will undergo further transformation. This article discusses some of the fascinating applications of artificial intelligence in sports, as well as the technology that powers them:

Individualized training and nutrition plans

Professional athletes' training and eating regimens have improved considerably throughout the years. In 1990s Britain, it was not uncommon for a British player to visit a bar following training, consume several beers, and then stop for a kebab on the way home. It was perfectly natural.

However, incorporating artificial intelligence into sports can further personalize training and diet routines. Numerous studies have already demonstrated promising results in the usage of AI in weight training.

In essence, an AI diet plan uses machine learning to tailor different plans to different players based on their demands and present circumstances.

Not to mention the plethora of AI-assisted fitness applications that have flooded the market. Sports personnel can now train algorithms capable of detecting human poses in real-time using the computer vision technique known as human pose estimation. This technology has been found in online yoga and pilates, where keypoint skeleton models may be used to identify human joints and instruct users on proper exercise techniques.

Predictions for matches

For years, bettors have attempted to process massive amounts of data to forecast the outcome of future matches and win large sums of money. They analyzed first and second served percentages in tennis and the amount of aces and backhand winners in an attempt to forecast sports results.

However, a human cannot comprehend the amount of data that an AI-driven football program can, nor can they properly forecast enough matches to become millions. Their human limits always constrain them—and as a result, the majority will never become millionaires.

AI is also incapable of precisely predicting the outcome of every single match. However, using a predictive algorithm can get far closer than a human can.

When computer vision is properly trained as a ball possession model, it can assist in forecasting future match outcomes. For instance, computer vision is used to determine the duration of ball possession. Using this data, the algorithm can forecast whether a team will win, lose, or draw a future match.