Which is how it is typically presented because it sounds much better than "reject a lot of candidates who would probably have worked out just fine". It is useful to perceive both the potential value in an approach like this and the shortcomings. Google can absorb the massive expense in man hours, lost opportunity, etc. that comes with trying to craft genuinely predictive interview processes, but a lot of the companies trying to emulate them can't. Too often, interviewees don't realize a process of this sort is stacked against them, and interviewers don't appreciate the negatives of adopting a still-nascent approach that sounds more reliable simply because it is quantitative - and assuming since Google does it it must work.

Its not like Google pays the best or still has the best workplace. It's a large company with large company politics and red tape.

I've met a few such people in this forum. Not many.

I'm not sure how one would even begin getting a rigorous estimate of that number. What is a credible sample of "great candidates" in this industry?

That seems to be an unproven assumption, and quite likely to be a wrong assumption. For example if good people turn out to be less interested in "honing their interview skills", adding parasitic noise to the signal.