Even at the semi-professional soccer level, coaches are making use of analytics. For example, they get information about where other teams are - or who is - losing the ball.
Then, the game was pushed toward extreme (and boring) control of ball possession largely by analytics. When I played at a decent level, it was considered "criminal" to pass the ball in close proximity (up to 20 yards) to the net while being "pressured" by the other team. Nowadays, it is very rare to see a team that gives up possession easily.
AC Milan had been using "Milan Lab" since the early 2000s and it was whispered that it used neural networks to predict the probability of injury. It was a largely unsuccessful experiment at the time-players were very often injured (also, Milan's head of the medical/performance team, Meersseman https://www.jpmchiropratica.it/en/studio/jeann-pierre-meerss..., was pulling players' teeth because he believed that some teeth could give postural problems and thus increase the likelihood of injury, see Seedorf).
The analytics/data science revolution has already arrived in soccer, but the reasonably large effects have been, due to the nature of the game, less visible than those in American football and baseball.
AC Milan had been using "Milan Lab" since the early 2000s and it was whispered that it used neural networks to predict the probability of injury. It was a largely unsuccessful experiment at the time-players were very often injured (also, Milan's head of the medical/performance team, Meersseman https://www.jpmchiropratica.it/en/studio/jeann-pierre-meerss..., was pulling players' teeth because he believed that some teeth could give postural problems and thus increase the likelihood of injury, see Seedorf).
The analytics/data science revolution has already arrived in soccer, but the reasonably large effects have been, due to the nature of the game, less visible than those in American football and baseball.