BABIP has no subjective probabilities, it's literally just "batting average on batted balls in play" or "what is your batting average when you hit the ball fair, but it's not a home run?". It erases things like strikeouts and home runs from the equation but still counts all of your singles, ground balls, doubles, popups, etc; as long as it is "in play".
While there's no "guaranteed BABIP" league BABIP runs, pretty standard. Let me prove that Here are the last five years league BABIP:
.291 (2025), .291 (2024), .297 (2023), .290 (2022), .292 (2021)
Basically, we know that if you hit the ball in play, you are likely going to hit like .290 regardless of the year. Even during the steroid era, BABIP was .300 (1998), and .302 (1999)! It only affected things by .10.
Where BA's dip, dive and change are in things like when we factor in strikeouts and home runs. If one player strikes out a lot versus one who doesn't, then we see the overall BA change because we were ignoring those things. If one guy has a K% of 30% and another at 20%, they can have the same BABIP but vastly different BAs. We can also increase BABIP by being fast (beat out infield singles) or lower it by being slow. And batted ball data, like launch angle, hard hit%, barrel % all can help earn it.
So what we can do is look at someone with, say, a .260 BABIP and diagnose it. If it's a big slow guy who hits a lot of weak contact, that's probably a somewhat earned BABIP. But if a fast guy makes a lot of hard contact is running a .260 BABIP, we can squint and go "hmm, that doesn't make sense". Situations like that suggest for whatever reason, he's probably *not* getting the results he should!
Things like xwOBA and xBA (the x stands for expected) are determined through statcast. These won't show up in BABIP, but in other data. Basically, statcast can take the exit velocity, tilt, launch angle, and determine, compared to what normally happens on that exact outcome, how often you should expect a ball to land for a hit. If you hit the ball 105mph on a line, that's usually a hit. If you hit it, instead, right at 3b? That's bad luck, not impossible but bad luck. It's possible for those things to add up and be meaningful, especially at lower sample sizes.
I hope that help to answer your question. Thanks for asking! It feels like it's a lot to digest, but really it boils down to our ability to use all the tools we have and figure out if you're doing the right things at the plate, you should have results that follow it. BABIP on it's own isn't super useful, but BABIP, combined with other things can help us paint a picture to help us predict what will happen next. Just because you got a single before, doesn't mean you will continue. By using these model we can more accurately predict who's going to continue to hit, and who won't. (And like I said, I promise there are 29 teams who are using predictive models).