AI and Football: Revolutionising the beautiful game

IKE UME 

Ike Ume is a project professional and AI researcher with experience in the Telecoms, Finance, and Travel industries. He holds an MSc in Project Management from the University of the West of Scotland and a bachelor’s degree in Business Administration from the University of Abuja. His current research interests include ‘The trends influencing the adoption of AI-based technologies by PMOs in the United Kingdom’. He can be reached at ike.ume14@gmail.com

We’ve heard about it and are now experiencing it, and we are wondering where the next advancements in artificial intelligence (AI) will take modern life. Microsoft Azure defines Artificial Intelligence as a consistent process where a machine detects, imitates, and responds to human behaviour and intelligence through recognition, learning, reasoning, and action based on pre-set data inputs. The impact of AI permeates almost every aspect of modern-day life, from its advancements in Health to how it’s changing how we move from point A to B, to even Helping us decide what to eat. Artificial intelligence has eaten into one of the oldest and most heavily guarded industries, Professional Football. As AI relies heavily on data, it is not surprising that it has revolutionised the Analytical aspects of Football.

Player monitoring: Scouting, performance analytics and player improvement strategies.

The core tasks in football are one of the few fields in the world where AI cannot replicate (or is this author speaking too soon?). These tasks refer to physical movements carried out by the primary protagonists, the players. AI (in its most advanced iteration at the time of writing) powered robots cannot kick or head a football with precision or make individual moments of dribbling and trickery that make high-level football the world’s most loved and popular sport. However, it has given the coaches a helping hand in two key areas.

• Scouting:

The latest example of the AI revolution in football is its application in scouting. Scouting in the 20th Century and the first decade of the 2000s primarily involved managers, sporting directors, scouts, and coaches making long trips and even missing games to watch football matches involving players they were interested in buying. Conversely, aspiring footballers who need to register with an academy or club need help to afford the funds and required documentation to travel and attend football trials. But this logistic headache has been alleviated by AI-powered scouting apps. One example is the AI sports analytics company ai.io. Their flagship product, “aiScout”, has partnered with English clubs Chelsea and Burnley. The app allows amateur players to take and upload videos of themselves participating in specifically designed football training drills. These videos are analysed to create insights based on desirable attributes that clubs consider when unearthing new talent. It seems that aiScout is here to stay as the USA’s Major League Soccer has signed an agreement to partner with the company, giving more aspiring players a chance to be scouted by MLS teams for free. aiScout’s parent company, ai.io, was invited to be featured on the world stage in FIFA’s innovation programme.

While this advance in AI scouting is still in the early phase, its results are still in the early stages, and there have been a few success stories. However, this method isn’t quickly replacing traditional counting methods, as many coaches still gauge players by some aesthetic qualities (sometimes called “eye test”). However, with the combination of these AI videos easing the stress on scouts, the battle for the brightest prospects among the most prominent clubs will intensify in the coming years.

• Performance analytics and player improvement strategies.

Due to football’s physical and contact-heavy nature, injuries are part and parcel of the game. And the more common ones (like Hamstring and thigh strains, fractures, and dislocations) are unpredictable due to the contact-heavy nature of the sport. However, AI-powered wearable inventions (Undervests, watches) have helped sports science departments use predictive analytics (generating and using data to predict future trends) to prevent more mental injuries like burnout and fatigue. By using data from minutes, sprints, match actions, and recovery time in between matches, players take over a certain period before specific injuries to create insights. These insights can lead to sports science teams creating recovery plans for players to prevent them from entering “red zones”, where fatigue can impact performance.

With Augmented Reality (AR) and Virtual Reality devices (like glasses and headsets), players and coaches get real-time views from different angles of their teammates and opponent’s positioning during training. This advancement increases coaches’ speed and decision-making processes during training sessions instead of relying on eye tests and recorded tapes. While Meta Quest headsets and Apple Vision Pro headsets compete in this space, Google Glass was one of the first mainstream uses of AR in a live game. In 2014, Atletico Madrid’s assistant coach wore a Google glass, receiving live scores and statistics during a 2-0 La Liga win over Getafe, which helped the team get an advantage over their rivals. Google shelved the Headsets, but conversations are going on about how to incorporate other forms of VR and AR into the Fan and Matchday experience.

With all these advancements in player scouting and analytics, the next step would be for grassroots footballers and smaller clubs in the food chain to use these methods to tailor training programmes that can transform the roughest diamonds to the next world-beater.

As AI grows, especially with Microsoft partnering with Open AI’s “Chat GPT” and Google pushing hard with their AI offering, Gemini, football won’t be left behind. And the beautiful game we love might look different in the next decade.

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