Rebel wrote:In the past I have written a PGN utility that produces all kind of statistics from an eng-eng match. Among
other things it for instance produces a statistic in which game phase a game is lost.
Code: Select all
Phase LOST DRAWS WON
Overview MIDG END1 END2 END3 MIDG END1 END2 END3
190 202 4 157 90 816 335 10 221 75 1054.0 (55.0%)
186 335 10 221 75 816 202 4 157 90 864.0 (45.0%)
Late Endgame LOST DRAWS WON
Overview QUEEN ROOK LIGHT PAWN QUEEN ROOK LIGHT PAWN
190 17 23 27 0 514 18 20 23 0
186 18 20 23 0 514 17 23 27 0
The abbreviations in the Phase Overview stand for:
•MIDG: Opening and Middle Game.
•END1: No Queens on the board.
•END2: Real Endgame. Sum black&white <= 26 using the Pawn=1, Knight=3, Bishop=3, Rook=5, Queen=9 formula.
•END3: Late Endgame. Sum black&white <= 10 using the above formula, so Rook, Bishop, Knight and pawn endings.
The second overview (Late endgame overview) further splits the ending in Queen | Rook | Bishop/Knight | Pawn endings.
I want to improve here and further split the Late endgame overview more specifically in a third overview. But before investing time I want to ask first if something similar already is in the open.
It's a long time ago I made this feature (part of Protools) before cutechess-cli saw the light (or became popular) and surprisingly it seems to work with cutechess-cli scores and depths as well. Saves me some trouble. Other supported formats are Chessbase and Arena score+depth PGN's.
Pgn-extract is capable of extracting games from any material configurations. Example p vs p, q vs q, rn vs rbp, etc. I have this tool (dos batch files) where given a pgn, I will extract games involving material config that I want to examine. Say games with positions where there are no queens. Once extracted I run ordo to see how engines would look in these type of material config.
Example from Gauntlet test, at tc 300s + 100ms - queenless. My engine is D2015.1.262.
Code: Select all
# PLAYER : RATING ERROR POINTS PLAYED (%) CFS(next)
1 HIARCS 14 WCSC : 173.5 201.5 5.0 7 71.4% 52
2 Quazar_0.4_x64 : 166.5 202.0 5.0 7 71.4% 87
3 Gaviota v1.0 64bit : 23.4 142.8 5.0 10 50.0% 58
4 D2015.1.262 : 8.7 51.4 46.0 87 52.9% 51
5 Hannibal 1.1 64bit : 6.5 144.8 5.5 11 50.0% 53
6 Spark 1.0 x64 : -3.5 234.1 2.0 4 50.0% 52
7 DiscoCheck 5.2.1 : -12.2 154.3 5.0 11 45.5% 59
8 Cheng_4.39_x64 : -38.7 160.5 4.0 9 44.4% 60
9 Hakkapeliitta 3.0 x64 : -68.1 150.6 3.5 9 38.9% 54
10 Arasan_18_x64_popcnt : -81.2 176.6 3.0 8 37.5% 78
11 SmarThink v1.7 : -174.9 147.2 3.0 11 27.3% ---
White advantage = 24.48 +/- 32.04
Draw rate (equal opponents) = 54.90 % +/- 5.96
Code: Select all
4) D2015.1.262 8.7 : 87 (+24,=44,-19), 52.9 %
vs. : games ( +, =, -), (%) : Diff, SD, CFS (%)
HIARCS 14 WCSC : 7 ( 1, 2, 4), 28.6 : -164.8, 106.9, 6.2
Quazar_0.4_x64 : 7 ( 1, 2, 4), 28.6 : -157.8, 108.6, 7.3
Gaviota v1.0 64bit : 10 ( 2, 6, 2), 50.0 : -14.7, 75.0, 42.2
Hannibal 1.1 64bit : 11 ( 2, 7, 2), 50.0 : +2.2, 74.8, 51.2
Spark 1.0 x64 : 4 ( 1, 2, 1), 50.0 : +12.3, 127.9, 53.8
DiscoCheck 5.2.1 : 11 ( 3, 6, 2), 54.5 : +20.9, 78.8, 60.5
Cheng_4.39_x64 : 9 ( 2, 6, 1), 55.6 : +47.5, 84.7, 71.2
Hakkapeliitta 3.0 x64 : 9 ( 3, 5, 1), 61.1 : +76.9, 81.4, 82.7
Arasan_18_x64_popcnt : 8 ( 3, 4, 1), 62.5 : +89.9, 97.6, 82.2
SmarThink v1.7 : 11 ( 6, 4, 1), 72.7 : +183.6, 78.8, 99.0