How algorithms help clubs find talent
For decades, scouting was a matter of miles: a scout travelled, watched a match and wrote a report. Today, before getting on a plane, many clubs have already filtered thousands of players with data.
The basis is event data: every pass, dribble, shot, recovery or duel is recorded with its position on the pitch. With that, an algorithm can search for specific profiles, for example a left-footed full-back under 21 who carries the ball forward a lot and wins aerial duels.
Clubs such as Brentford in England and Midtjylland in Denmark became known for recruiting exactly this way: finding undervalued players in less-watched leagues and selling them on for more.
But numbers have limits. They do not show personality, how someone adapts to a new country or the tactical context of the team. That is why the common model is mixed: data makes the first list and a human scout decides with video and in the stadium.
For a young player this has a practical consequence: well-organised videos and basic data from your matches make it possible to be found even if you do not play in a big league.