Not very long ago, most of the aspects of soccer/football were managed manually – from analyzing a player’s performance to officiating the match. However, things have been changing rapidly. 

Now, we see video assistant referees (or VAR), AI-powered players’ analysis, players’ digital avatars, and more, for a sophisticated yet fair gameplay. As a cultured soccer fan, you might not like it (and I agree) because it disrupts the emotional aspect of the game (no more Hand-of-God moments). 

But it is what it is, and it was bound to happen because the game is continually evolving. With this evolution come new ways to improve a player’s performance. That’s exactly why we see so many high-quality players across the globe. Back in the day, it was one or two names that dominated. 

All in all, I am of the view that this evolution improves the overall sport. I might not be able to convince you, but let me try harder with a more detailed look into the topic. So, let’s get into it.

Please note: Soccer is the most infused sport by AI, so I will be taking soccer as an example for this content piece. You will likely find a lot of use cases of AI around soccer here. 

What is AI in Soccer? 

AI is short for artificial intelligence, which is basically a computer’s ability to mimic human intelligence. Though not perfect, modern AI-powered tools and software can still understand much of the context behind human inputs and produce fine outputs. 

But what about AI in soccer? 

It is tools and technologies that are artificially intelligent and help improve the sport. If I go a little more into detail with my definition, take an example of VAR: it is essentially an AI-based video technology that creates a model of the player at fault and analyzes them to conclude whether a foul has been committed. 

For offside calls, it is super useful. As for other fouls like handballs and stuff, the call is made by the match officials with the help of high-definition videos. 

So, that was AI in soccer. Now, let me walk you through its practical applications that are currently implemented. 

How AI Helps Soccer Teams 

Via data-driven sports decisions

We will understand it better with the help of a comparison, so here we go (Fabrizio, if you are reading this, I admire your work): back when Manchester United was managed by Sir Alex Ferguson, he had to watch recaps on a player’s performance to identify their strengths and weaknesses. It was a very hectic job because once you lose your focus, you might miss some key details. 

Well, that has been changed. 

Those recap videos can be fed to AI-powered tools and software. They dive a lot deeper into the videos, watching every move of the player to understand their core strengths and weaknesses. Then the analyzed data is presented in a simplified form. 

With the help of data, players, managers, and behind-the-scenes teams can rectify the underlying issues of their signings. 

The same technology has trickled down to consumers as well. I mean, you can buy a wearable tailored to understanding your skills and weaknesses. I am a soccer coach at a local club in New York, and I personally use XbotGo to boost my personal and my players’ skills. 

Whenever I show up at the club facilities, I connect XbotGo to my phone, and my phone to a reliable internet connection, which I got from LocalCableDeals (an all-in-one platform for your internet, TV, and phone needs), and then start training. I sometimes miss important details of my players’ performance, but XbotGo rarely does. 

All in all, these AI-powered tools are super helpful when it comes to analyzing players’ performance. 

Improving the players’ performance

Analysis is one thing, but if it doesn’t show any results on the pitch, it’s all in vain.

So, AI has to actually help with the end result in order to be considered a genuine help. Well, it does. Let me explain how. 

It is actually related to the application of AI for player analytics, as I explained earlier. To improve, you have to know yourself first. While it would be very difficult from the first-person perspective, AI can be the third person. As I mentioned earlier, the AI wearable is basically wrapped around the cleats, and they are highly sensitive. Not as in they will break easily, but in a way that they can detect even slight movements around your cleats. 

What’s up with that detection? Well, they can actually calculate your movement, shot power, passing accuracy, impact on the ball, and more. That way, you can improve even the slightest weakness of your game. And many high-profile clubs like Real Madrid, Barcelona, Manchester United, Arsenal, Juventus, and Bayern Munich actually invest in such technologies. 

It’s not limited to just that, since every player has their own unique abilities, a one-size-fits-all kind of training program wouldn’t help gain that 1% advantage. But in reality, their training programs are unique, thanks to AI. 

Every player (apart from group training) trains according to a tailor-made program that has been built with the help of AI. This perfect training program helps improve their strengths while minimizing their weaknesses. 

Scouting talent across the globe

This is one of the most important use cases of AI in sports because of a few reasons: 

• First, it removes any bias
• provides a comprehensive overview
• and is convenient

I do understand that eye test is still very important in the game, but it does have its own limitations. 

How can those limitations be overcome? 

With a mix of AI analysis and eye test. For example, if I am a scout for a club, I will do this: I will use AI and provide it with the profiles of players I need for my club. Then I will input some players that I hear are made to fulfill my profile needs. Now, based on that data, AI will offer the output, and once I have the output, I will shortlist a player or two to see them personally in a match. That’s exactly how big clubs do it, and that’s exactly how we have young talent coming up all the time. 

Enhancing the fitness of the players

Last but certainly not least, it helps with the fitness of the players. 

It’s all about the data – an AI-powered software is more aware of the players’ physical weaknesses, which later can be used to predict and prevent injuries. 

It happened with Gavi (a young FC Barcelona midfielder who suffered a painful injury). Later on, based on the AI’s outputs, he was put in situations on selective occasions to prevent injury because the game state would cause a relapse. 

As for the injured players, you might hear news that they are training separately from the group. Well, that’s because of the tailored plan built by AI. They train according to their own plan to get back to the best of fitness as soon as possible. 

How AI Helps Match Officials?

AI is not limited to just players and clubs; it has been actively used by the match officials (people managing the games). How, exactly? Let’s talk about that in detail. 

Through video assistant referees

The first thing that was executed in games was VAR. It has been a while since we have seen VAR being used in official games. I know there have been multiple controversial issues around VAR as well, but overall, it has been helpful. 

Previously, there was no such thing, and there have been multiple occasions where the match referee made an error. That error couldn’t be rectified because the moment had passed, and there wasn’t time to deeply review. VAR solves this exact problem. 

Players can protest a decision, and a third team can use VAR and advise the on-field referee to check again. Behind the scenes, it’s AI-powered tools that are helping rectify the error. 

You will see a full model and projection of the player where it went offside, and that’s AI-powered in real time. As I said earlier, it’s not limited to just offside rules, but it can be used in many other incidents of the game, like players raising their legs too high, handballs, and more. 

Through players’ 3D avatars

This is a fairly new technology that is being tested by FIFA. What it does is it will create a 3D model of the players to pinpoint any errors when it comes to the offside. 

This was necessary because in the basic models of VAR, sometimes the tip of the cleats of a player was so big that they would also be offside. In simple words, it can be inaccurate, but with the 3D model, it can be minimized. 

Through goal line technology

Last but not least, the goal line technology helps prevent faulty goals. 

In soccer, a keeper is allowed to go inside the post to save a goal. Sometimes the ball might cross the line, and if it is halfway through the goal, it is counted as a goal. 

Goal line technology will accurately check whether half of the ball is across the goal line or not. It came in super helpful, and it is most certainly a great technology. 

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