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A bad move should not be marked "good" just because the player who did it is losing horribly.

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Fr3nchToastCrunch

A bad move is bad. Period. Marking it as "good" because the player is getting absolutely decimated is not a good way to help people improve. It's a good way to make a downright awful game seem way less terrible than it was, which is not good.

It goes the other way too — a blunder should not be just an "inaccuracy" because the player is losing. A blunder is a blunder, no matter how the game is going.

It's fine when there is no good move to be played, but I'd argue that it should be marked as a "zugzwang" move and not given an evaluation as a result.  If you've reached the point where bad moves are somehow considered OK, you most likely should have resigned at least ten moves ago anyway.

justbefair

Remarks like "good" or "bad" or "blunder" are left over from the "human descriptive" period or pre-engine period of chess analysis. They were often used imprecisely, even if surrounded by loads of adjectives.

Computer evaluations have always needed to be simpler. Things had to be reduced to fit a formula. Human evaluations and early computer evaluations often used simple material gain or loss to value moves. Beginners and programmers decided that a blunder was anything that changed the material balance by more than 2 points. Moves that caused little change in the material balance were deemed excellent or good.

Material change was often a good indicator. However, there were problems. For example, a sacrifice leading to some later gain or checkmate must be valued differently.

Newer programmers came up with a statistical measure of winning chances called the expected points model. Expected Points employs data science to calculate a player's probability of winning by considering their rating and the engine's evaluation of the position

Simply put, any move other than the best move will make you somewhat more likely to lose.

https://support.chess.com/en/articles/8572705-how-are-moves-classified-what-is-a-blunder-or-brilliant-etc

In this model, a blunder is not always a blunder. A blunder is a move that materially alters winning chances.

The old human/ early computer evaluations were clumsily mapped over to the new expected points model. This often produced situations like the ones you mentioned.

Is it perfect? Far from it?

Is it better than the old model? I think so.