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Problem is, the same thing applies to regular "stats" like rebounds. Lots of times teams designate one guy as the defensive rebounder and everyone else as transition players. So that guy ends up with 10+ easy rebounds a game, but does that necessarily make him a good rebounder? Stats like the one I provided do a lot more to judge a player in isolation. Not perfect, granted, but better.
I get your point -- I really do. But the same "judgment" aspect that potentially makes your stat better also leaves it open to being worse. Your stat being "better" is dependent upon two pretty big "ifs" -- consistency, and accuracy. Even though the basic rebounding stat doesn't tell you exactly how good a rebounder someone is, we can rely on the fact that they are actually counted the exact same way every time (consistency) and that the number we're given accurately reflects when a rebound is actually corralled. It's a close to objective as you can get.
We have no way of knowing whether that applies to the "rebounding opportunity." stat. First, we don't know if the guy who is compiling that data is applying his standard consistently every time. And second, even if he is applying his standard consistently, we may not agree with his standard. It may be that he routinely classifies as a rebounding opportunity something that others would say was a player deferring to someone else, heading out on a break, whatever. Not everyone will draw that distinction in the same place, so it is a judgment call. And we have no idea whether we agree with that guy's judgment or not.
In other words, he may be consistent, but consistently applying the wrong standard. We just don't know. That's not really an issue with the basic rebounding stat, which is pretty objective.
I personally think that once you get to the point of wanting to look beyond the objective rebounding stat, you're better off just watching the guy actually play and rendering a judgment that way, rather than relying on some other guy's judgment that inherently includes his subjectivity/bias.