Whenever we see data like this, a number of hyp email lists australia otheses arise. The one we like best internally right now is that the URL path/filename data may be skewed by the root domain keyword usage. Essentially, when a root domain name already employs the keyword term, the engines may see those who also employ it in the path/filename as potentially keyword stuffing (a form of spam). It may also be that raw correlation sees a large number of less-well URL-optimized pages performing well due to other factors (links, domain authority, etc.
It's also true that most sites that employ the keyword in the path/filename don't use it in the root domain as well, so the negative of the one may be mixed-in with the positive of the other. and why a greater depth of analysis - and much more sophisticated models - are critical to getting more value out of the data. Can We Build a Ranking Model that Gives more Actionable Takeaways? To get to a true representation of the potential value of any given SEO action, we need a model that imitates Google's.