In 1997, IBM’s chess-playing computer Deep Blue became the first machine to beat a world champion, in Garry Kasparov. Since then, computers have become part of the fabric of the game, competing in tournaments as well as providing training assistance for players.
‘Freestyle’ tournaments have also grown in popularity, where humans compete both with and against computers. The results of these tournaments have been a little surprising; while a combination of a human consulting a computer for help generally beat a computer playing solo, a chess grandmaster with a weak process for using their computer generally lost to an amateur player with a strong process for using their computer. This slightly counter-intuitive conclusion has been dubbed Kasparov’s Law.
The parallels with football are clear. Take recruiting players, or managers:
While football is nowhere near as precise as chess, intelligent analysis of data reveals consistent themes for success – whether in recruitment, game strategy, succession planning, and so on. This is no different to a chess computer suggesting moves that improve the chances of success.
The key, however, is to get this process right. Knowing how to use the data in a smart way can triumph over both superior knowledge and the most advanced statistical models. Rather than using data to confirm our own biases, it is best used to both guide and challenge our decision-making.
Unlike chess, football’s own version of Kasparov’s Law won’t be played out in matches and tournaments – it’ll be for smart boardrooms to exploit as competitive edge.