I was patiently waiting to see who if anyone would answer Ariis.
After 5 days, Zorba offers the same old pathetic BS. Incredible!
The only thing the free fudge called GnuBG is good for is doing
experiments using its Python interface. Otherwise it's worthless.
It looks like Ariis is trying to verify for himself what I had shown
with my mutant experiments and my arguments that went along
with them. Good for him.
We'll see who if anyone responds to Zorba...??
BTW: This is not DailyGammon owned by your "control freaks"...
You may get deservedly slapped for any garbage you spew...
MK
On 9/28/2025 3:35 PM, Robert-Jan Veldhuizen wrote:
Hi Francesco,
Your formulas are correct.
But luck evaluations/analysis uses a fundamentally different approach than error
evaluations/analysis, regardless of any ply-depth.
Only when the backgammon engine would produce perfect numbers for all positions, would the two
different methods always lead to the same conclusions about the % skill and % luck.
An important distinction between error analysis and luck analysis, is that the latter is
unbiased. Which means that in the long run, the luck analysis numbers will approach the real
values (inaccuracies of the bot will cancel out).This is not the case for error analysis, where
inaccuracies of the bot may not cancel out and sometimes even pile up.
With GnuBG, I believe the default luck analysis is unfortunately (still) set to 0-ply and not
changeable from the GUI. 0-ply luck analysis is quite inaccurate. With a command "set analysis
luckanalysis plies 2" (or even higher, although that might be slow) you can improve the quality of
the luck analysis significantly. You'll probably find that doing luck analysis at higher settings
reduces (but does not remove) the discrepancies between error analysis and luck analysis.
Kind regards,
Robert-Jan Veldhuizen
On Tue, Sep 23, 2025 at 1:04 PM Francesco Ariis <[email protected]> wrote:
Hello gnubg users,
I have a question about the relationship between “Error total (MWC)”
(Err%) and “Luck total (MWC)” (Lck%).
Before I continue, some definitions to make sure I got this correctly:
- Err%(A) is the equity (in Match Winning Changes) that player A dropped
in the match, both chequer play and cube actions. This is expressed in
Match Winning Chances (MWC) and has always a negative sign.
- Lck%(A) is the equity player A gained/lost each time he rolled the dice.
This too is expressed in MWC, can have positive or negative sign.
- AR is the actual result in MWC, 50% if I win, -50% if I lose.
- Each of those variables above are non normalised.
Example from a recent match I have played:
PlayerA PlayerB
-------- --------
Err% −39.614% −64.202%
Lck% +37.250% −2.534%
AR 50% −50%
Now, the question.
I would think AR to be:
R = Lck%(A) − Lck%(B) + Err%(A) − Err%(B)
or in longhand, I expect “Result − Luck” to be equal to “Skill”; and vice
versa “Result − Skill” to be equal to “Luck”.
But this seems not to be case:
# From the perspective of PlayerA
Result = 50%
Luck = 37.250% + 2.534% = 39.784%
Skill = −39.614% + 64.202% = 24.588%
Implied skill (Result − Luck) = 50% − 39.784% = 10.216%
# ↑ This is “Luck adjusted result” − 50%.
Implied luck (Result − Skill) = 50% − 20.588% = 29.412%
I expected some minor discrepancies between the two numbers, because (if
I understood the calculation correctly), luck evaluations would have to be
done 1-ply deeper than error evaluations to perfectly match.
But there has to be something else that eludes me, right? What other factors
make one method of estimating skill so different from the other?
Thanks in advance, happy rolls
—F
