On 10/14/2025 2:09 PM, Francesco Ariis wrote: > tl;dr: running Luck analysis at 2-ply reduces the discrepancy between > Luck and Implied Luck, but not by that much.
So, what does that tell you..? > I asked why the difference between Error total% and Luck total% > sometimes did not follow this formula: Keyword = "sometimes" Your sentence implies that it "follows the formula *most of the time*". In other words, the times when it does not follow the formula are rare exceptions compared to the times when it follows the formula. In other words, you are making a misleading, false statement! > ..... Moreover he explained that gnubg is not a perfect engine, so > there will always be discrepancies between the two calculations. Keyword = "perfect" Keyword = "discrepancies" For decades, I objected to the usage of phrases "bots are imperfect", "bots are not perfect", etc. because those imply bots being "almost perfect" when in reality bots are way too far away from being perfect to justify using such expressions. Every time people make such statements, I ask them to quantify the magnitude of imperfectness (or "discrepancies" as you put it also). "Not perfect" by how much do you mean? By 2%? 5%? 10%? 25%? 50%? 75%? At what point do you think you should stop using the word "perfect" and start using a more appropriate word to describe the bots..? Unless and until you all answer this question, all you are doing is again making misleading, false statements! > Squaring the difference `(L−IL)²` over each of those games, > averaging it and calculating the square root of the average `σ` > leads to the money shot. > > games ply σ > ----- --- ------- > 471 0 8.4 > 471 2 7.3 I could but I don't even need to say your calculations are useless, meaningless because you can't face up to the implications of the results of your own calculations. Frankly, I even get a mildly sadistic pleasure from just watching you all torture yourselves... > So running Luck analysis at 2-ply reduces the discrepancy between > Luck and Implied Luck, but not by that much. Back to the question: so, what does that tell you..?? MK
