Complete statistical divergence from the mean of the population? no, that's just simply not supposed to happen. That last one should be impossible.
Well, I have a theory that would explain this. Lets assume that duels decks starts of sorted the way they are in the deckbuilder, meaning that we have all the land in the bottom of the deck. Then we shuffle using a random comparator. This introduces a bias for cards originally in the bottom of the deck to end up closer to the top. Now, because most magic games only look at the top ~20 cards of the deck, that bias will add up to some statistical significance. There is a nice visualization of different distributions caused by bad shufflers here:
https://bost.ocks.org/mike/shuffle/compare.htmlThings that would make or break this theory are:
Does the amount of bias decrease with number of cards drawn, if it does, it supports my theory.Are the particular lands in the back of a deck more likely to show up in the deck then other cards? If they do, that supports this theory.
In the larger data set provided by VT2WA we have evidence of the bold (we don't have data for the second part - we did not for example count how often rare lands showed up). There is a statistically relevant downward trend as card count increases. ~ -.0063874% per card drawn, and it's statistically different from 0.
GoboRab's data does not agree with this finding. If anything in GoboRab's data the trend is positive instead of negative, but we can't reject 0 (95% CI -.0084004 to .0193979) - 0 is what we'd expect the trend to be if the shuffler was built correctly, and his data's confidence interval includes 0.
So basically, no we don't have conclusive evidence to support this theory, and we have found yet another way the two data sets contradict each other. Need more data.