It’s a scout’s worst nightmare, spending half a day on the road to see a player he recommended, only to find out that the player is far below the required standard. But soon artificial intelligence was able to save the scouts from the trip.
Starting this season, several clubs including Chelsea, Nottingham Forest and Olympiacos will start using a mobile app called AiSCOUT to find new players.
The app provides scouts with data on football players’ athletic, cognitive and technical skills so they can refine their search results. Players upload videos in which they perform exercises set by the club. These drills were performed by the club’s own players, so it has a standard by which divorced players can be judged.
AiSCOUT COO and head of sports science Richard Felton says Chelsea have often sent game footage in the past, but that footage was mostly useless unless one knew the level of opposition the player was up against. By comparing players already playing at Chelsea, the club can find out if it’s worth taking a closer look at the players on the app.
He says professionals sign up for millions of pounds based on a lot of data, but that data isn’t collected until a player is a professional. This app will help scouts get data on amateur players so they can find anyone who is missed by the current system.
The exercises in the app can range from dribbles for speed to cognitive tests that measure concentration or reaction time. All the player needs to complete them is a smartphone, a soccer ball, something that can be used as a set of cones, and a place to do the exercises. Felton says the app has been tested on a wide range of mobile phones and can compensate for a variety of surfaces, from smooth artificial turf to dribbling around rocks to jumpers on a sandy pitch.
Clubs using the app can decide exactly what attributes they need, with Chelsea focusing on strength and pace this early in the search process, for example. Players who lack these characteristics will never become Chelsea players, but perhaps their other qualities make them suitable for another club.
In addition to acting as a pre-screening tool, it can help scouts find players they may have missed.
The first tests of the application found a player called Ben Greenwood whom Chelsea then brought in for a one-day trial. He ended up staying at Chelsea for ten weeks and is currently at Bournemouth where he played for the first team and was capped by Ireland at youth level.
Greenwood lived only a few miles from Chelsea’s training ground, but neither Chelsea nor any other professional club had ever followed him before using the app.
With all of Chelsea’s talented youngsters, they probably don’t need a lot of help finding new players. The real way AI can change scouting is by helping teams that don’t have the same scouting resources.
Small international teams like the Caribbean that compete in CONCACAF have many people around the world who are eligible to play for them but lack the scouting resources to find such players. Even people like Chile only discovered Blackburn Rovers forward Ben Brereton Diaz after fans reportedly learned of his Chilean heritage through the PC game Football Manager.
Such national teams could use this application to find potential new players to invite to the training camp. There are millions of talented youth around the world who do not play organized football but may have all the qualities to excel in the game. If AI can get into places where scouts would never go on their own, who knows what kind of talent it might find.
One cliché that can be seen in many football films involves the player leaving some important event to rush to the match for a once in a lifetime chance of being spotted by a Manchester United scout. If AI becomes widespread in scouting, this player will already be on the club’s radar and will simply be called in for a tryout.