Nobody could have imagined that a little over a decade ago, that AI would have such a rising growth in the sports industry. Started with the movie Moneyball and its exciting use of artificial intelligence. Spoiler alert for Moneyball, but the general gist of it is that Billy Beane, the manager of Oakland Athletics, used artificial intelligence to make a dream team against all odds. The perfect blend of athleticism and technology is possible thanks to advancements in the field of sports AI.
In 2021, this evolution has only improved. In a way, the remote situation forced onto athletes has made these advancements a necessity. We are long past the days of Moneyball’s clever use of statistics. Now AI is being used for things such as game planning, conditioned training, dietary plans, audience engagement, and athlete recruitment. Sports AI has improved so much that it’s even used at the Olympic level.
Of course, the origins of sports AI started at the professional scene first and foremost, and it is there that it flourishes to this day. The positive change brought by the use of sports AI cannot be understated, and with time, it will only get better.
Today, let’s talk about the specific areas where AI has been implemented in the field of sports.
VR Sports Advancements
VR Sports are a relatively new branch of sports AI technology, but the implications are exciting. With the use of a VR headset, athletes and enthusiasts alike can compete virtually from anywhere on Earth. The virtual platform needs a lot of refinement, but VR technology is one of the hottest fields right now and it will only get more advanced with time. Plus, with the improvement being made over wireless connections, its versatility and interactivity can change the field of sports training forever.
Broadcasting
One of the most popular advancements in recent years for AI is in broadcasting and streaming. AI has managed to train cameras to follow the action in such a way that it will never miss the action. In addition, automatic subtitles are constantly improving, giving even non-native speakers an idea of what the announcers are talking about.
Another one often not noticed by the average sports fan, is the use of 60fps AI to create smooth slow-motion playback. This has been crucial in analyzing plays and quick tactics employed by athletes and looks plain cool.
Match Predictions
Through the use of machine learning, AI has been used to predict the outcome of matches. By using training data and official sports records, the AI makes an educated guess of what the result will be. This is incredibly useful for training purposes as it gives the coach and players an objective view of where their strengths lie and where their opponents’ weaknesses are, and vice versa.
AI Coaching
AI can be a great tool for making game plans and tactical decisions on the fly. AI sensors are used to calculate the micro details such as the distances a ball can be thrown by certain players, to reaction times of players. It’s a very strong asset for coaches who want to make the most out of every game planning session. When paired with match predictions, coaching has never been more efficient and advanced.
Audience Engagement
Through the use of AI, networks can find out which sports are gaining a ton of viewership, and which ones are struggling. In this way, networks can know which sports to push more for their audience. More importantly, it can help struggling sports know what kind of audience they appeal to and find out how to be more accessible to a wider audience.
Performance Reviews
Not only AI can be used on consumer research, but also for tracking a player’s performance. While match predictions focus on the macro, performance analysis focuses on an individual athlete’s statistics and abilities. By recording their performance after every game and inputting it into specialized apps, the player can review their skills and find what skills they should pay special attention to. For example, sharpshooters may find that while they are near perfect at the 2-point line but notice difficulty on the 3-point line, the app can let them know the variance between them.
Player Recruitment
AI has made it possible for a virtual platform that recruits athletes to exist, and they have been used by major sporting institutions to streamline the selection process. By using AI to analyze the statistics of up-and-coming athletes, sporting institutions now have a much easier time finding the athletes that fit best.
Not only that, it provides athletes who have difficulty getting scouted a chance to be found by the AI, and giving them the chance, they deserve. On the recruiter’s side, the AI eases a lot of their workload. The best thing about AI is that it’s easy for coaches to add it to their current training regime. Instead of looming over paperwork for days, all of your prospective player choices are already gathered for you.
