No it isn't. There are some more simple ones (that are probably annotated via some sort of AI) which is the reason, why they available so fast after a match, and some more sophisticated ones. I guess, within the next 2-3 years, one model will emerge superior and will push all other models away and, with that, get rid of the discussion about differences between models.
I am not sure, if it is the best way to interpret the results of xG as scorelines. These are just sums. And they are the absolute opposite of made up: if you watch a game, you notice if somebody had a good chance or not. But maybe, because you only watch the matches of your team, your view is biased due to only knowing your teams players. There the statistical approach comes in and averages out every variance you have.
And even if I agree, that some models are too simple to make any kind of meaningful statement, the good thing is, the flaws are always consistent and therefor apply to everybody. That means that even if, for example, the understat model isn't the most perfect model, as it is applied to each time in the same way, comparing the sums over multiple matches and teams tells you a pretty good deal about how you stand in terms of chance creation and prevention.
There is no magic in that, stats are a manifestation of things you can see with your eyes. But you are not going to sit in front of your tv, stopping time while we are in possession or the number of passes we make in the final third etc.
I doubt it.