No, it isn’t. There’s an obvious point to betting odds. A trade off between enticing punters to gamble and losing money, that’s the entire “game”.
And where do you think those odds come from? They aren't just thinking about what will entice punters. They are looking at the likelihood of each item happening. Again, almost certainly through analysis of huge datasets...just like xG. Defensive records, xG, injuries, form etc will all go into these things.
Your last point is what I was really getting at. A lot of fans don’t understand much about it so say things after a loss like, “Well, the xG was x for us and y for you, so we should have won”.
To be somewhat obtuse, that isn't incorrect. Football is a game of goals. If you play the other team off the park and lose 3-0 then you still lost. Saying you should have won is irrelevant. Playing the other team off the park and losing 3-0 with an xG of 3-1 in their favour says that you didn't create enough chances ergo you didn't play well in the areas that matter.
If the idea of football is to create and score chances then a metric that quite literally tracks the quality of the chances you create should tell you who wins a game more often than not... and it does. I don't know how you can argue against a metric that looks at massive amounts of historic data and derives its predictions based on that. What it is saying will happen, has happened.
This is the bit that I don't think people are getting. Its not guess work, its data. If tomorrow people starting scoring penalties at 50% instead of around 80% then the stats would soon reflect that. The stats reflect all teams as well, they aren't just looking at the very elite players, they are looking at all of them. This is how predictive modelling works. You can't say for certain something will happen but you can say what the likelihood of it happening is.
What overall xG isn't good at explaining is how it came to that figure. Was it 3 amazing chances or 15 minor ones etc.