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Re: [Bug-gnubg] gnubg.sql - stats from my database
From: |
address@hidden |
Subject: |
Re: [Bug-gnubg] gnubg.sql - stats from my database |
Date: |
Tue, 16 Nov 2010 17:56:23 +0000 (GMT) |
Hello Jim,
Thanks for your advice and kind offer to help. How do your
scripts run? Do you just feed it a folder of *.sgf files?
The
statistics I would be interested in are pretty much the same as the
headers from the webpage -
http://www.capp-sysware.com/analysis/octnov2010-dc-dicestudy.txt
(I've
pasted an abbreviated version of this page at the bottom of this post.)
Plus a couple of others - it would be good if there was also a column
for the 'running total all time' for each category.
+ pip-count loss
from hits / vs gnubg's stats
+ Total pip count per game / per match -
for me / GNU
+ Total number of doubles rolled whilst on the bar for me
/ GNU
+ number of occasions successfully hit a single blot when within
1 dice roll range (when you actually want to hit it i.e. not leaving
something silly open for your opponent to get of the bar and return a
hit. I know this bit sounds difficult to calculate) / vs gnubg's stats
+ number of occasions successfully hit a single blot when within 2 dice
rolls range (when you actually want to hit it) / vs gnubg's stats
Finally, I know that you are not the person to implement it, but do you
think this was an interesting idea,
> Another
> clarifying feature
would be, after I lose to gnubg (again), to be able
> to play the game
again.
> But we would swap the CPU's dice rolls with my own.
> This
would clearly show if gnubg would still win when you have his now
>
predetermined 'lucky rolls'.
or is it a waste of time for me to record
the dice rolls and try and reply the games?
P.S. Your other
suggestion sounds good too but I'm sure your round tuit list is just as
big as mine!
P.P.S. I played a lot yesterday - lost 10 games to 5
against gnubg. Today I'm winning 3-2 :)
Cheers,
djskope
>
>If you
analyse your matches and save the results as .sgf files, then
>it is
possible to extract all sorts of per-move information from an
>analysed
match. I have (when trying to settle an argument with someone
>about
"usable" doubles) written scripts which can extract almost any
>information you want - doubles, doubles from the bar, pip-count loss
>from hits, time spent dancing on the bar, you name it.
>
>Specifically, your requests:
>
>1) Given a collecton of sgf files, I
can easily generate the number of
>doubles for each player (including
if the player was able move at
>least one piece one time - a usable
double)
>
>2) I have a script which calculates pip loss from being hit,
167 - the
>loss = total pip count
>
>3) would be fairly easy to modify
an existing script to do
>
>4) would be more work, but certainly do-
able. My script for counting
>dancing reconstructs the board for each
dice roll so it would know if
>there are pieces on the bar
>
>5) The
most useful (which I will do one of these days when my round
>tuit
supply is replenished) would be to create a database of mistakes
>-
cube and checker play with an EMG loss amount (so you can choose
>what
level of mistake you want to analyse), the gnubg board and match
>ID
(so you can put the mistake back into gnubg), and an easy way for
>an
external script to input the board and match ID, allow you to play
>one
move, then stop and analyse the move afterward, reporting the
>results
back to the script. It could then tell you what you played
>before,
what you just played and what gnubg believes the best
>move/cube action
is for that position and match state.
>
>--
>Jim Segrave
address@hidden
>
======================================================================================
======================================================================================
Statistics for First Roll of a Game (Can't be a Double)
Roll
Count Expected(%) Observed(%) Difference(%) Two-Tailed p-value
(%)
======================================================================================
21 368 6.667% ( 6.88880569%, +0.22213902% )
51.037%
31 343 6.667% ( 6.42081617%, -0.24585049% )
49.290%
...
All 5342 100.000% (100.00000000%, +0.
00000000% ) -
======================================================================================
Statistics for all Regular Rolls (Excludes First Roll)
Roll
Count Expected(%) Observed(%) Difference(%) Two-Tailed p-value
(%)
======================================================================================
21 11303 5.556% ( 5.61171296%, +0.05615740% )
27.121%
31 11314 5.556% ( 5.61717423%, +0.06161868% )
22.732%
...
All 201418 100.000% (100.00000000%, +0.
00000000% ) -
Doubles 33110 16.667% ( 16.43845138%,
-0.22821529% ) 0.599%
NonDbls 168308 83.333% (
83.56154862%, +0.22821529% ) 0.599%
Average
PipCount 8.167% ( 8.13676533%, -0.02990133% )
0.179%
======================================================================================
Statistics for All Regular Rolls from the Bar
Roll Count
Expected(%) Observed(%) Difference(%) Two-Tailed p-value(%)
======================================================================================
21 2805 5.556% ( 5.49924520%, -0.05631035% )
57.876%
31 2977 5.556% ( 5.83645382%, +0.28089826% )
0.561%
...
All 51007 100.000% (100.00000000%, +0.
00000000% ) -
Doubles 8327 16.667% ( 16.32521027%,
-0.34145640% ) 3.852%
NonDbls 42680 83.333% (
83.67478973%, +0.34145640% ) 3.852%
Average
PipCount 8.167% ( 8.12498285%, -0.04168382% )
2.850%
======================================================================================
Statistics for all Die values (First rolls included)
Roll
Count Expected(%) Observed(%) Difference(%) Two-Tailed p-value
(%)
======================================================================================
1 69392 16.667% ( 16.78080867%, +0.11414200% )
4.889%
2 68994 16.667% ( 16.68456181%, +0.01789514% )
75.749%
...
All 413520 100.000% (100.00000000%, +0.
00000000% ) -
======================================================================================
Statistics for bringing one checker in off the bar
Total # Times # Times Observed Expected
Difference Two-Tailed
Against Moves Danced Success
Success (%) Success (%) (%) p-value(%)
===================================================================================================
0-pt board 46 0 46 100.00000000% 100.00000000%
+0.00000000% -
1-pt board 5961 155 5806
97.39976514% 97.22222222% +0.17754292% 43.050%
2-pt board
8469 918 7551 89.16046759% 88.88888889% +0.27157870%
43.658%
...
===================================================================================================
Statistics for bringing two checkers in off the bar
Total # Times # Times Observed Expected
Difference Two-Tailed
Against Moves Danced Success
Success (%) Success (%) (%) p-value(%)
===================================================================================================
0-pt board 1 0 1 100.00000000% 100.00000000%
+0.00000000% -
1-pt board 779 226 553
70.98844673% 69.44444444% +1.54400228% 37.106%
2-pt board
1058 570 488 46.12476371% 44.44444444% +1.68031926%
27.895%
...
===================================================================================================
Statistics for consecutive rolls that are doubles
# in a row
Count Expected(%) Observed(%) Difference(%) Two-Tailed p-
value(%)
==============================================================================================
1 doubles 33110 16.66666667% ( 16.43845138%, -0.22821529% )
0.599%
2 doubles 5414 2.77777778% ( 2.68794249%,
-0.08983529% ) 1.415%
...
==============================================================================================
Statistics for consecutive identical rolls
[ 2 in a row
] [ 3 in a row
] [ 4 in a row
] [ 5 in a row ]
Expected Diff. From Two-Tailed
Expected Diff. From Two-Tailed Expected Diff.
>From Two-Tailed Expected Diff. From Two-Tailed
Roll Count (%) Expected(%) p-value(%) Count
(%) Expected(%) p-value(%) Count (%) Expected(%)
p-value(%) Count (%) Expected(%) p-value(%)
=========================================================================================================================================================================================================
21 641 0.30864198% ( +0.00960168%, 43.724%) 40
0.01714678% ( +0.00271242%, 35.252%) 4 0.00095260% ( +0.
00103332%, NeD ) 0 0.00005292% ( -0.00005292%, NeD )
31 657 0.30864198% ( +0.01754536%, 15.573%) 38
0.01714678% ( +0.00171946%, 55.561%) 2 0.00095260% ( +0.
00004036%, NeD ) 0 0.00005292% ( -0.00005292%, NeD )
...
All 868 0.46296296% ( -0.03201836%, 3.428%) 20
0.01286008% ( -0.00293048%, 24.612%) 0 0.00035722% (
-0.00035722%, NeD ) 0 0.00000992% ( -0.00000992%, NeD
)
=========================================================================================================================================================================================================
* NeD = Not Enough Data (npq < 5). Sample size is too small for
binomial test to be accurate
- [Bug-gnubg] gnubg.sql - stats from my database, address@hidden, 2010/11/14
- RE: [Bug-gnubg] gnubg.sql - stats from my database, Ian Shaw, 2010/11/15
- Re: [Bug-gnubg] gnubg.sql - stats from my database, Michael Petch, 2010/11/15
- Re: [Bug-gnubg] gnubg.sql - stats from my database, Michael Petch, 2010/11/15
- Re: [Bug-gnubg] gnubg.sql - stats from my database, address@hidden, 2010/11/15
- Re: [Bug-gnubg] gnubg.sql - stats from my database, Jim Segrave, 2010/11/15
- RE: [Bug-gnubg] gnubg.sql - stats from my database, Ian Shaw, 2010/11/15
- Re: [Bug-gnubg] gnubg.sql - stats from my database,
address@hidden <=
- Re: [Bug-gnubg] gnubg.sql - stats from my database, Jim Segrave, 2010/11/24
- RE: [Bug-gnubg] gnubg.sql - stats from my database, djskope, 2010/11/24
- Re: [Bug-gnubg] gnubg.sql - stats from my database, Jim Segrave, 2010/11/24