Using Artificial Intelligence to uncover the next football superstar
6 May 2022
6 May 2022
Every year, pundits and football fans make predictions of prodigies who may become the next football superstar. Inevitably, these promising youngsters fizzle out and end up becoming squad players or worse — irrelevant.
Teams that can identify and hone the next big talent can build a strong core. So the question beckons: how to know which upcoming talent can be the next big thing.
The amalgamation of technology and sports opens new avenues for better talent recognition. As the race to scout and train prodigies heats up, artificial intelligence can speed up the identification process.
We all read about the next wonderkid in football, the next Messi or Ronaldo. With the proliferation of AI and its associated technologies, the in-depth analysis of useful metrics has become more insightful. As a result, academies can develop programs to fill gaps (if any) and extract full potential.
So how can AI help coaches and trainers stay on top of a kid's progress?
Football clubs set aside a decent chunk of money for scouting and recruitment to identify the next wonderkid. Add artificial intelligence to their arsenal, and the work of scouts becomes relatively easier.
Today, AI technologies such as computer vision can already analyse players' movements on the ground. The machine learning algorithms can predict skill levels, attacking and defending attributes, and overall potential based on the collected data.
With it, scouts can match players' ratings against their parameters to make a swift decision, make predictions on the type of training requirements and estimated time to complete those activities and work in a time-efficient manner by getting results quicker than usual.
The more data teams can serve to the machine learning model, the better it will be at predicting the outcome related to a player.
Analysing strengths and weaknesses
Every player has their own respective strengths and weaknesses. The better scouts can analyse a player's abilities, the quicker they can put players on a learning curve.
Machine learning algorithms can give scouts better clarity about a player's strength. Also, it can highlight the areas that need attention.
Scouts can then pay attention to players fulfilling the selection criteria based on the results.
It is crucial to understand that skill with the ball and the ability to read the game are essential. Deep learning strategies based on ML algorithms can uncover decision-making abilities in the information age.
By learning player attributes, scouts can then gain clarity on a talent's best position on the field and help football clubs to run training programs to make players adapt and improvise.
Training programmes to address weak areas
Suppose a player lacks confidence on his weak foot or loses aerial duels more often than not. Machine learning models can analyse the situation against large datasets and suggest a training program.
Players can then work together with their coaches to fill those gaps and minimise errors on the pitch. Since football is a fast-paced game, teams can get no time to recuperate from a player's mistakes.
The best way is to follow a rigorous training program to help players address their weak areas and boost overall performance. With AI and ML, coaches can get assistance in designing programs.
By working on the weak areas, players can achieve greater performance levels by overcoming their vulnerabilities. As a result, clubs can dedicate resources to players showing immense promise in training.
In doing so, the competition in the transfer market will intensify, and clubs can make profits by selling players as well.
Artificial Intelligence will make football better
Discovering talented kids on the block is only the first step. In today's world of technology, critical insights matter. Any kid who wants to become the next Ronaldo, Messi, or Alexia Putellas can realise his or her dream with a learning path and proper guidance.
AI, ML, and other deep learning technologies can influence how training happens in an academy. With more data to work with, unleashing the true potential of young talents is imminent.
AI applications in football are already on the rise, and adding one more possibility can do no harm.