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 [email protected] > ====================================================================================== ====================================================================================== 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 mailing list [email protected] http://lists.gnu.org/mailman/listinfo/bug-gnubg
