Artificial Intelligence Could Be About To Change Soccer Player Scouting

It’s a scout’s worst nightmare, spending half the day traveling to watch a soccer player recommended to them, only to find out that the player is well below the required standard. But soon, artificial intelligence could save scouts the trip.

From this season, several clubs including Chelsea, Nottingham Forest and Olympiacos will start using a mobile application called AiSCOUT to help them search for new players.

The app gives scouts data on soccer players’ athletic, cognitive and technical skills so that they can refine their searches. Players upload videos of themselves performing drills set by the club. These drills have been done by the club’s own players so it has a benchmark to judge the scouted players against.

AiSCOUT’s COO and Head of Sports Science, Richard Felton, says in the past, Chelsea were often sent game footage, but that footage was basically useless without knowing the level of the opponents the player was up against. By benchmarking against players already at Chelsea, the club can know if the players on the app are worth looking at more closely.

He says professionals are signed for millions of pounds based on so much data, but that data only doesn’t get collected until the player has already turned pro. This app will help give scouts data on amateur players so they can find anybody the current system has missed.

The drills on the app can range from dribbling at speed to cognitive tests that measure concentration or reaction time. All a player needs to complete them is a smartphone, a soccer ball, something to use as a set of cones, and a space to perform the drills. Felton says the app has been tested on a wide range of mobile phones and can compensate for different surfaces, from smooth artificial turf, to dribbling around rocks and jumpers on a sandy pitch.

Clubs using the app can decide exactly what attributes they are looking for, Chelsea, for instance focus on power and pace at this early stage of the scouting process. Players who lack those characteristics will never be a Chelsea player, but perhaps their other attributes make them a good fit for another club.

As well as acting as a pre-screening tool, it can help scouts find any players they might have missed.

The early tests of the app unearthed a player called Ben Greenwood who Chelsea then invited for a one-day trial. In the end, he stayed at Chelsea for ten weeks and is currently at Bournemouth, where he has played with the first team and has been capped at youth level for Ireland.

Greenwood lived just a few miles from Chelsea’s training ground but had never been watched by Chelsea, or any other professional club, before using the app.

With all Chelsea’s talented youngsters, they probably don’t need much help searching for new players. The real way AI could change scouting is through helping teams without the same scouting resources.

Small international teams, such as the Caribbean islands that compete in CONCACAF, have many people around the world who are eligible to play for them, but don’t have the scouting resources to find those players. Even the likes of Chile only discovered Blackburn Rovers striker Ben Brereton Diaz after fans reportedly found out about his Chilean ancestry through the Football Manager computer game.

Such national teams could use this app to find potential new players to invite to training camps. Around the world there are millions of talented youngsters who don’t play organized soccer but could have all the attributes to make it in the game. If artificial intelligence can tap into these places where scouts would never look at on their own, who knows what talent it could find.

One cliché seen in many soccer movies involves a player leaving some important event to rush to a match for a once-in-a-lifetime chance to be seen by a scout for Manchester United. If AI becomes widespread in scouting, that player would already be on the club’s radar and would simply be invited down for a trial.