A lot of Baseball teams are using data-driven approach and computer modelling to help them better succeed in games. The most famous example being Billy Beane of Oakland Athletics (2001-2003), popularized by the film Moneyball.
My question is why soccer or football is very slow to warm up to this approach? In an interview Billy Beane said that :
“It’s a very dynamic sport. Baseball is very stop-start and it lends itself to measurement, but on the flip side there are a lot more events going on during a football match than there are in a baseball game - and anybody who is well versed in modelling, whether from a computer science background or a mathematics background, will tell you the more data you have, the better you are able to put the models together.
“So it may be different and there’s certainly a correlation of an interaction between players that may not exist in baseball – but there are a lot of events, and the more events you have the better you should be at predicting things.”
I've no idea what these words mean. On one moment he said that football has a lot more events, and on the other moment he said that the more data the better for data driven approach. So I guess more events should lead to more data which means that football should be amenable to data-driven approach, right?
In addition to whatever he was saying, is there any other reasons why football is slower to warm up to data-driven approach?
Edit: the question How are football players are objectively rated is related, but not necessarily a duplicate as suggested. Reason being, data-driven approach is not necessarily limited to sports where individual players can be objectively rated. In fact football is a collective sport where individual talents are less important than team dynamics. I can easily imagine that we find other team-related metrics, as opposed to individual metrics, that are more amenable to data-driven analysis.
So no, it's not a duplicate at all.