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What about getting a terminal output like this?

No      Length   Result   Luck_Adjusted  FIBS     Snowie   Date
------  -------  -------  -------------  -------  -------  ----------
1       1        1.0      79.68          1802.4   2.99     2008-08-04
2       1        0.0      51.06          1719.1   3.67     2008-08-04
3       1        0.0      37.48          1975.4   0.58     2008-08-04
4       3        1.0      56.9           1912.7   3.27     2008-08-04
5       3        0.0      52.47          2014.2   0.54     2008-08-04
6       3        1.0      68.69          1853.1   6.35     2008-08-04
7       3        0.0      59.16          1980.8   1.79     2008-08-04
8       1        1.0      51.58          1864.5   2.56     2008-08-04
9       1        0.0      35.92          1455.7   8.35     2008-08-04
10      1        1.0      56.21          1967.7   0.89     2008-08-04
 
 
Result secret_player (2): 165.0 win(s) in 276 matches. Snowie error rate: 3.68
 

 Unfortunately for the moment this is only possible on MacOS or Unix/Linux systems. I provided a script "query_player.sh" which allows you to query your database using search patterns. A script call could be:

 
#: query_player.sh goodguy

 
and the script would give you an output like shown above. Perhaps someone with deeper MSWindows knowledge is able to convert the script. You can find it either in the repository of GNU Backgammon or here (be careful, the content may change from time to time and will not always work perfectly).

There are two adjustment you have to make:

# Put the path to your database here:
DATABASE=/Users/good_player/.gnubg/gnubg.db
...
# only for getting your number of games correctly, usually you have the id 1 or 2.
if [ ${NAME_ID_RESULT} = 2 ]
    then PLAYER_ID="player_id1"
    else PLAYER_ID="player_id0"
fi
 

[Update] 

  The script now works with error rates and names of opponents. Output is slightly different to the table above.

 In the first part I showed some general information about the sqlite database in GNU Backgammon. We now start some useful queries:

sqlite> select a.session_id as No, b.length as Length,
a.actual_result+0.5 as Result,
round(a.luck_adjusted_result*100,2) as Luck_Adjusted,
round(a.snowie_error_rate_per_move*1000,2) as Snowie,
date(b.added) as Date from matchstat a, session b
where a.session_id = b.session_id and a.player_id = 2
group by a.session_id limit 10;
 

 No     Length   Result      Luck_Adjusted  Snowie   Date
------  -------  ----------  -------------  ---------- ------------
1        1         1.0       29.68          2.99      2008-08-04
2        1         0.0       1.06           3.67      2008-08-04
3        1         0.0       -12.52         0.58      2008-08-04
4        3         1.0       6.9            3.27      2008-08-04
5        3         0.0       2.47           0.54      2008-08-04
6        3         1.0       18.69          6.35      2008-08-04
7        3         0.0       9.16           1.79      2008-08-04
8        1         1.0       1.58           2.56      2008-08-04
9        1         0.0       -14.08         8.35      2008-08-04
10       1         1.0       6.21           0.89      2008-08-04
 

Explanations:

 A more sophisticated query with nicer output could be the following:

sqlite>select a.session_id as No, b.length as Length, round(a.actual_result+0.5)
as Result, round(50+a.luck_adjusted_result*100,2) as Luck_Adjusted,
round(a.error_based_fibs_rating,1) as FIBS,
round(a.snowie_error_rate_per_move*1000,2) as Snowie, date(b.added) as Date
from matchstat a, session b where a.session_id = b.session_id and
a.player_id = 2 group by a.session_id; 
 

No       Length    Result    Luck_Adjusted  FIBS      Snowie      Date
-------  --------  --------  -------------  -------  --------  ----------
267      1         0.0         53.53        1947.8    0.52      2008-08-04
268      1         1.0         44.78        1691.9    4.01      2008-08-04
269      1         1.0         37.92        1491.0    6.2       2008-08-04
270      1         1.0         49.63        1726.4    4.45      2008-08-04
271      1         1.0         58.7         1720.4    4.34      2008-08-04
272      3         1.0         36.64        1883.4    4.01      2008-08-04
273      1         1.0         67.96        1878.3    2.16      2008-08-04
274      1         1.0         57.63        1888.9    1.92      2008-08-04
275      1         1.0         61.18        1861.5    2.61      2008-08-04
276      3         1.0         57.31        1883.9    4.54      2008-08-04
 

 GNU Backgammon provides relational database support. Besides mysql and postgresql the standard database is sqlite. After the installation of gnubg you’ll find the database file in your home directory (~/.gnubg/gnubg.db on Linux and MacOS). You find the menu entry for using the database in "Analyze" – "Relational Database".

 Besides getting information by the GUI of gnubg you can also put queries directly into the database. I’ll describe some important stuff for terminal usage here. If you work on MSWindows systems either get a sqlite browser or the Firefox Addon "Sqlite Manager."

 In a terminal you start sqlite with:

#: sqlite .gnubg/gnubg.db (or wherever your database is located
sqlite>Loading resources from /Users/ace/.sqliterc
SQLite version 3.4.0
Enter ".help" for instructions
sqlite>
 

 Important sqlite commands:

 Gnubg stores all data into five tables (actually there is a 6th table called "control", but forget about that for now):

1. game
2. gamestat
3. matchstat
4. player
5. session

sqlite>.mode line
sqlite> select * from player limit 1;
player_id = 73
name = cdforex
notes =
 
sqlite> select * from game limit 1;
game_id = 1
session_id = 1
player_id0 = 1
player_id1 = 2
score_0 = 0
score_1 = 0
result = 1
added = 02:00:22
game_number = 1
crawford = 0
sqlite> select * from session limit 1;
session_id = 80
checksum = 112f66856248c6b6a6b0f211071b5d3d
player_id0 = 73
player_id1 = 74
result = 0
length = 1
added = 2008-08-04 05:50:07
rating0 = NULL
rating1 = NULL
event = NULL
round = NULL
place = NULL
annotator = NULL
comment = NULL
date = 2008-04-01
 

".mode" and "limit 1" are only set for displaying it here on the webpage more conveniently. The other three tables look similar but with much more rows:

game: game_id     session_id  player_id0  player_id1  score_0     score_1     result      added       game_number  crawford

gamestat: gamestat_id  game_id     player_id   total_moves  unforced_moves  unmarked_moves  good_moves  doubtful_moves  bad_moves   very_bad_moves  chequer_error_total_normalised  chequer_error_total  chequer_error_per_move_normalised  chequer_error_per_move  chequer_rating  very_lucky_rolls  lucky_rolls  unmarked_rolls  unlucky_rolls  very_unlucky_rolls  luck_total_normalised  luck_total  luck_per_move_normalised  luck_per_move  luck_rating  total_cube_decisions  close_cube_decisions  doubles     takes       passes      missed_doubles_below_cp  missed_doubles_above_cp  wrong_doubles_below_dp  wrong_doubles_above_tg  wrong_takes  wrong_passes  error_missed_doubles_below_cp_normalised  error_missed_doubles_above_cp_normalised  error_wrong_doubles_below_dp_normalised  error_wrong_doubles_above_tg_normalised  error_wrong_takes_normalised  error_wrong_passes_normalised  error_missed_doubles_below_cp  error_missed_doubles_above_cp  error_wrong_doubles_below_dp  error_wrong_doubles_above_tg  error_wrong_takes  error_wrong_passes  cube_error_total_normalised  cube_error_total  cube_error_per_move_normalised  cube_error_per_move  cube_rating  overall_error_total_normalised  overall_error_total  overall_error_per_move_normalised  overall_error_per_move  overall_rating  actual_result  luck_adjusted_result  snowie_moves  snowie_error_rate_per_move  luck_based_fibs_rating_diff  error_based_fibs_rating  chequer_rating_loss  cube_rating_loss  actual_advantage  actual_advantage_ci  luck_adjusted_advantage  luck_adjusted_advantage_ci  time_penalties  time_penalty_loss_normalised  time_penalty_loss

matchstat: matchstat_id  session_id  player_id   total_moves  unforced_moves  unmarked_moves  good_moves  doubtful_moves  bad_moves   very_bad_moves  chequer_error_total_normalised  chequer_error_total  chequer_error_per_move_normalised  chequer_error_per_move  chequer_rating  very_lucky_rolls  lucky_rolls  unmarked_rolls  unlucky_rolls  very_unlucky_rolls  luck_total_normalised  luck_total  luck_per_move_normalised  luck_per_move  luck_rating  total_cube_decisions  close_cube_decisions  doubles     takes       passes      missed_doubles_below_cp  missed_doubles_above_cp  wrong_doubles_below_dp  wrong_doubles_above_tg  wrong_takes  wrong_passes  error_missed_doubles_below_cp_normalised  error_missed_doubles_above_cp_normalised  error_wrong_doubles_below_dp_normalised  error_wrong_doubles_above_tg_normalised  error_wrong_takes_normalised  error_wrong_passes_normalised  error_missed_doubles_below_cp  error_missed_doubles_above_cp  error_wrong_doubles_below_dp  error_wrong_doubles_above_tg  error_wrong_takes  error_wrong_passes  cube_error_total_normalised  cube_error_total  cube_error_per_move_normalised  cube_error_per_move  cube_rating  overall_error_total_normalised  overall_error_total  overall_error_per_move_normalised  overall_error_per_move  overall_rating  actual_result  luck_adjusted_result  snowie_moves  snowie_error_rate_per_move  luck_based_fibs_rating_diff  error_based_fibs_rating  chequer_rating_loss  cube_rating_loss  actual_advantage  actual_advantage_ci  luck_adjusted_advantage  luck_adjusted_advantage_ci  time_penalties  time_penalty_loss_normalised  time_penalty_loss
 

 
A simple query could now be:

sqlite> select * from player where name = "ace";
player_id   name        notes
----------  ----------  ----------
12          ace
 

 
And now you have one of the most important information about a player, his "player_id" which is necessary for further queries. It’s also possible to deliver a search string:

sqlite> select * from player where name like "%ace%";
player_id   name        notes
----------  ----------  ----------
12          ace
26          Acepoint
 

 
As you can see the search is not case sensitive.

 If you want gnubg doing some batch rollouts you can prepare a file like:

set gnubg Position ID ...
rollout =cube
export position html filename.html
set gnubg Position ID ...
hint
rollout =1 =2 =3
export position html filename.htm
...

 

and start gnubg with the following command:


#: gnubg -t -c [file].txt
 

Command line

Setup a position:
set board simple 0  2 4 2 2 3 0  0 -1 0 0 0 0  0 1 0 -2 0 -2  -2 -3 -3 1 0 -1  1

GNU Backgammon  Position ID: cbcZIEB72wEECA
                Match ID   : cAngAAAAAAAA
+13-14-15-16-17-18------19-20-21-22-23-24-+     O: gnubg
|    X     O     O | O | O  O  O  X     O |     0 points
|          O     O |   | O  O  O          |
|                  |   |    O  O          |
|                  |   |                  |
|                  |   |                  |
|                  |BAR|                  |     7 point match (Cube: 1)
|                  |   |                  |
|                  |   |             X    |
|                  |   |    X        X    |
|                  |   |    X  X  X  X  X |     On roll
|             O    |   |    X  X  X  X  X |     0 points
+12-11-10--9--8--7-------6--5--4--3--2--1-+     X: ace

From an online match 

The score (after 2 games) is: gnubg 1, ace 1 (match to 3 points)

Move number 6: gnubg to play 61

Pip counts: gnubg 84, ace 112
Position ID: bHsTEEBrtxkAIA Match ID: EQFnABAACAAA

From Woolsey, BG Encyclopdia, 04-10

The score (after 0 games) is: gnubg 0, ace 0

move number 8:ace doubles to 2

Pipcounts: gnubg 105, ace 108
Position ID: trsDAGDbtgEgMA Match ID: cBEAAAAAAAAA

• gnubg takes

From  Robertie, Modern Backgammon,  05-11

Der Spielstand (nach 0 Partie) ist: gnubg 0, ace 0

Zug Nr. 26:ace muss 65 spielen

Pipcounts: gnubg 119, ace 143
Position ID: cjeDwQDYPQMwDA Match ID: cAkXAGAAMAAA

• ace zieht 8/2 6/1

Achtung: Zug schlecht ( -0,095)

Rolled 65 (-0.087):
     1. Rollout          22/11                        Eq.:  -0.531
       0.348 0.094 0.003 – 0.652 0.246 0.009 CL  -0.445 CF  -0.531
      [0.001 0.001 0.000 - 0.001 0.002 0.001 CL   0.003 CF   0.007]
        Full cubeful rollout with var.redn.
        1296 games, Mersenne Twister dice gen. with seed 2939214018 and quasi-random dice
        Play: world class 2-ply cubeful prune [world class]
        keep the first 0 0-ply moves and up to 8 more moves within equity 0.16
        Skip pruning for 1-ply moves.
        Cube: 2-ply cubeful prune [world class]
     2. Rollout          8/3 8/2                      Eq.:  -0.577 ( -0.046)
       0.339 0.073 0.002 – 0.661 0.181 0.007 CL  -0.414 CF  -0.577
      [0.001 0.001 0.000 - 0.001 0.002 0.001 CL   0.004 CF   0.008]
        Full cubeful rollout with var.redn.
        1296 games, Mersenne Twister dice gen. with seed 2939214018 and quasi-random dice
        Play: world class 2-ply cubeful prune [world class]
        keep the first 0 0-ply moves and up to 8 more moves within equity 0.16
        Skip pruning for 1-ply moves.
        Cube: 2-ply cubeful prune [world class]
*    3. Rollout          8/2 6/1                      Eq.:  -0.650 ( -0.120)
       0.319 0.069 0.002 – 0.681 0.175 0.006 CL  -0.452 CF  -0.650
      [0.001 0.001 0.000 - 0.001 0.003 0.001 CL   0.004 CF   0.009]
        Full cubeful rollout with var.redn.
        1296 games, Mersenne Twister dice gen. with seed 2939214018 and quasi-random dice
        Play: world class 2-ply cubeful prune [world class]
        keep the first 0 0-ply moves and up to 8 more moves within equity 0.16
        Skip pruning for 1-ply moves.
        Cube: 2-ply cubeful prune [world class]
     4. Cubeful 0-ply    22/16 6/1                    Eq.:  -0.522 ( +0.009)
       0.350 0.111 0.002 – 0.650 0.287 0.016
     5. Cubeful 0-ply    22/16 8/3                    Eq.:  -0.656 ( -0.125)
       0.327 0.113 0.002 – 0.673 0.352 0.032

From Robertie, Modern Backgammon, 05-15

The score (after 0 games) is: gnubg 0, ace 0

move number 38:ace to play 11

Pipcounts: gnubg 125, ace 65
Position ID: tm1BAA7f2GwAAA Match ID: QYkEAGAAMAAA

• ace moves 9/8(2) 6/5(2)

Rolled 11 (+0.270):
*    1. Rollout          9/8(2) 6/5(2)                Eq.:  +0.279
0.653 0.064 0.000 – 0.347 0.042 0.002 CL  +0.341 CF  +0.279
[0.002 0.002 0.000 - 0.002 0.002 0.000 CL   0.005 CF   0.006]
Full cubeful rollout with var.redn.
369 games, Mersenne Twister dice gen. with seed 2939214018 and quasi-random dice
Play: world class 2-ply cubeful prune [world class]
keep the first 0 0-ply moves and up to 8 more moves within equity 0.16
Skip pruning for 1-ply moves.
Cube: 2-ply cubeful prune [world class]
2. Rollout          9/6 9/8                      Eq.:  +0.223 ( -0.056)
0.623 0.076 0.000 – 0.377 0.049 0.001 CL  +0.286 CF  +0.223
[0.002 0.002 0.000 - 0.002 0.003 0.000 CL   0.005 CF   0.005]
Full cubeful rollout with var.redn.
368 games, Mersenne Twister dice gen. with seed 2939214018 and quasi-random dice
Play: world class 2-ply cubeful prune [world class]
keep the first 0 0-ply moves and up to 8 more moves within equity 0.16
Skip pruning for 1-ply moves.
Cube: 2-ply cubeful prune [world class]
3. Rollout          9/7(2)                       Eq.:  +0.219 ( -0.060)
0.630 0.065 0.000 – 0.370 0.051 0.002 CL  +0.286 CF  +0.219
[0.002 0.002 0.001 - 0.002 0.003 0.001 CL   0.005 CF   0.006]
Full cubeful rollout with var.redn.
368 games, Mersenne Twister dice gen. with seed 2939214018 and quasi-random dice
Play: world class 2-ply cubeful prune [world class]
keep the first 0 0-ply moves and up to 8 more moves within equity 0.16
Skip pruning for 1-ply moves.
Cube: 2-ply cubeful prune [world class]
4. Cubeful 2-ply    9/8(2) 5/4(2)                Eq.:  +0.178 ( -0.101)
0.611 0.079 0.000 – 0.389 0.065 0.000
5. Cubeful 2-ply    8/6(2)                       Eq.:  +0.178 ( -0.101)
0.602 0.095 0.001 – 0.398 0.061 0.000

From Woolsey, BG Encyclopedia, 03-07

The score (after 0 games) is: gnubg 0, ace 0

move no. 19:ace doubles to 2

Pipcounts: gnubg 114, ace 104

Position ID: ttuAAQzY3Q0GAA Match ID: cBEAAAAAAAAA

• gnubg takes

Alert: wrong take ( -0,041)!