Zitat von
spacious_mind
So I suspect it is not Cara which probably works well but you need a number of games for each player to get a real result of ELO strength.
Indeed, a single game analysis can provide some clues about a game-scope performance; player's stats across a (hopefully large) database is required for an Elo strength estimate of a player.
Nevertheless, I double-checked the P400 King 2.55 vs Chess Gate Smyslov game and i can report slightly different outcomes, as CARA is highly flexible and setting-dependant. Using 10secs SF18, 1 core as the analysis engine, I got:
Code:
Key Statistics
==============
P400 King 2.55 (White):
Average CPL: 20.9
Accuracy: 94.0%
Est. Elo: 2517
Total Moves: 65
Best Move %: 45.5%
Top3-Move Accuracy: 87.3%
Blunder Rate: 1.5%
Smyslov (Black):
Average CPL: 9.2
Accuracy: 97.4%
Est. Elo: 2542
Total Moves: 65
Best Move %: 67.3%
Top3-Move Accuracy: 89.1%
Blunder Rate: 0.0%
And a clue about Smyslov's low-looking Elo estimate:
Code:
Phase Analysis
==============
Opening ends at move 16
Middlegame ends at move 27
Endgame type: Strong Material Imbalance
P400 King 2.55 (White):
Opening (.. move 16):
Accuracy: 95.1%
ACPL: 17.2
Middlegame (.. move 27):
Accuracy: 94.6%
ACPL: 18.8
Endgame
(Strong Material Imbalance):
Accuracy: 93.7%
ACPL: 22.0
Smyslov (Black):
Opening (.. move 16):
Accuracy: 89.0%
ACPL: 38.5
Middlegame (.. move 27):
Accuracy: 100.0%
ACPL: 0.0
Endgame
(Strong Material Imbalance):
Accuracy: 98.0%
ACPL: 7.1
As you can read, Smyslov's game as Black shew some inconsistency from the opening phase to the middlegame; and this is a criteria that matters for the Elo estimate.
Anyway, let's wait for several enough games to run player's stats.
MfG,
Eric