[BoxFour]

Disclaimer: I have only extremely limited exposure to this topic (I worked in sports analytics, attached to a team, quite awhile ago), so take it all as heavy speculation:

1) It seems like there’s a natural resistance to change driven by loss aversion; you see a similar pattern in the NFL with decisions like punting vs. going for it on fourth down. Even if the expected value is positive, the failures are given far more weight than the successes.

2) In general, there's a lot of skepticism toward analytics until they reach a tipping point where they’re impossible to ignore, at which point they take over completely and introduce shifts like the ones shown here.

Moneyball, for example, has plenty of anecdotes about front office staff and coaches dismissing analytics in favor of “gut instincts”—and that was in 2002! In baseball, a sport which adopted advanced analytics far faster than others (obviously in no small part due to teams like that As roster).

Even today, plenty of NBA personalities push back against analytics—Reggie Miller, for example, has been pretty vocal about his distaste for them. He's obviously increasingly alone in that opinion, but it can be really hard to break old habits.

[dleink]

Baseball lent itself to advanced analytics even before player tracking became a thing, since the sport consists of a series of discrete one-on-one matchups with limited possible outcomes.