It's not really an answer to the question, but I once read something along these lines.
From memory, a game with an even score will have an expected result of 0.5 (total of 0 for a loss, 1/2 for a draw, 1 for a win).
A game with score of +1 (eg
a pawn advantage) will have an expected result of 0.6.
A game with a score of +2 (eg
a couple of pawns up, or
a rook versus minor piece exchange) will have an expected result of 0.7.
A game with a score of +3 (eg
a minor piece advantage) will have an expected result of 0.8.
A game with a score of +4 (eg
a rook for a pawn, or
a minor piece plus pawn) will have an expected result of 0.9.
And by the time you are 5 points ahead, the game is almost certainly won.
I don't remember the article which had this information.
It was a bit more precise than my rule of thumb created from it, which is 10% per pawn.
- Code: Select all
Result
1,0 ************************** WIN
0.9 *****
0.8 ***
0.7 **
0.6 *
0.5 <---- pawns behind 54321*12345 pawns advantage ---->
0.4 *
0.3 **
0.2 ***
0.1 *****
0.0 ************************** LOSS
I imagine a graph with this sort of shape, 0 at the bottom and 1 at the top of the
result axis and the graph having a gradient of 10% per pawn in the steep linear-looking part lying between [-4,4] pawns score on the x axis. Don't take the graph as being anything too realistic - I just did a couple of FOR loops in BASIC and printed a '*' if there was an arctan relationship between the X and Y figures. So my text is more accurate than the graph, and the text is just a from-memory recollection of some article I once read.
I had thought of trying to use this information to help with playing strategy in my chess program - for example, what is the fascination with trying to find the best move? When a game is fairly level at the start, maybe it is more important to make sure that a move that looks good actually is, rather than to spend time looking for a better move. Also, when a chess engine appears to be beating its opponent, the statistics seem to show that the game gets easier to play. It's more important therefor to avoid mistakes than to spend time trying to recover from one afterwards. And extra thinking time spent early on can pay for itself in reduced thinking time required later. In my last match for my local chess club, the time controls were 30 moves in the first hour and a quarter. I spent 15mins on my 20th move - my opponent threatened a rook and I replied with a knight sacrifice which caused my opponent to resign after move 25.
I don't know how to calculate the ideal amount of time a program should spend thinking about a move, but it seems to me that there should be some advantage to over-thinking when a game is level and playing moves more casually (quickly) once an advantage has been gained over the opponent.
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For the original question, about how the score during the game correlates with the final outcome, I wonder ...
The score at what point in a game?
During the game the score (as reported by a chess engine) is going to change.