The best player we know
Imagine the scene. You’ve just announced your new signing. The social media team have outdone themselves with the most creative announcement yet and there are photos of the player holding aloft their new shirt plastered all over twitter. You’re satisfied. Optimism is high for the season ahead, buoyed by your confidence that you have just acquired the best available player.
But the truth is that we never sign the best player, we just sign the best player that we know. And what we know is always limited by our resources.
It is difficult for even well-resourced clubs to scout the entire market. For example, we estimate that, globally, there are around 11,000 players from 441 teams covering 61 competitions capable of playing in one of the top five European leagues. At a push, a club would therefore require around 30 scouts to feel confident that they are accessing the entire talent pool, and most clubs don’t have anywhere near that number.
Clubs must therefore make choices on where they wish to focus. If we only have four scouts in Europe for example, which leagues are we happy to ignore?
Clubs are now becoming increasingly smart in addressing this problem by using data as the first filter in the scouting process. They are coming to us to help prioritise the teams and leagues to that will yield the biggest return on their resources, and more recently through reversing the scouting process altogether. Rather like searching for a car on Autotrader, we live in a world where you can quickly scan and filter the market to provide a shortlist of options which can then be validated by the experienced eye of our scouts.
No longer limited by our human resources, we can now be confident that the best player we know is actually the best player.