4 ms·

I know of people who have written things like online casino games (in unregulated jurisdictions) where the shuffle was deliberately skewed in order to achieve c

I know of people who have written things like online casino games (in unregulated jurisdictions) where the shuffle was deliberately skewed in order to achieve certain configurable winning percentages from the games. ie it's not done by accident but design. That said people do sometimes unintentionally write something like this (terrible and also buggy) algo for idx in size(deck): new_spot = int(random() * size(deck)) swap(deck[idx], deck[new_spot]) ...which won't give an even distribution of all possible outcomes. If shuffling, look up a real algo (like Fisher-Yates for instance) and implement that. Or better yet, use a library implementation.

gambiting 4y ago
Of course, the question is why would this be the case in Arena. You play against other players, not the casino.
- jna_sh 4y ago
  The theory I’ve always heard about why the shuffler might be biased is that they’re trying to reduce land flood/screw. Drawing too few or too many lands is a commonly cited cause of frustration with players and if you’re reasonably assuming Arena wants to do all the usual monetised-game things of increasing playtime and MAU whatnot, this conclusion seems one of the first people come to.
- seanhunter 4y ago
  They make money by selling the cards right? I would think that might change their incentives somewhat. I don’t really know the game.
  - dagi3d 4y ago
    The better "experience" they transmit to the players, the more engaged they will be and the more cards/packs they will sell
  - nkrisc 4y ago
    Players who aren’t having fun won’t buy cards or will stop buying cards when they quit.
- slackfan 4y ago
  Yes, but a frustrated player is more likely to buy event entries, aka gems, to draft more, and blame the poor randomization on bad luck, rather than intentional screw, because that is what you do at real life events. It's an insidious dopamine loop strategy, but it absolutely works.
manimino 4y ago
The correct Fisher-Yates shuffle is this (from Wikipedia): -- To shuffle an array a of n elements (indices 0..n-1): for i from 0 to n−2 do j ← random integer such that i ≤ j < n exchange a[i] and a[j]
- seanhunter 4y ago
  Right. The subtle difference being that because you only sample from position i to n you only ever exchange each card exactly once. In my algo you sample from 0 to n-1 so a card exchanged in a previous round can be exchanged again. This generalises into cards early in the shuffle being exchanged more than later cards, which changes the distribution of possible outcomes. Nerd sidenote: Because generating random numbers tends to be expensive, I had an idea once where you generate the full permutation with only a single random sample. Basically you could use something which fully enumerates a space like Gray codes[1] (you want one with a closed form solution which can arbitrarily you the nth code) then you generate one random number, multiply by the number of combinations, look up that code and decode that into the sequence of cards. I never actually got around to implementing it, but I suspect if your code lookup was fast it would be much faster than Fisher-Yates. The use case was if you wanted to make a Monte Carlo algorithm to evaluate strategies in a card game for instance. [1] https://en.wikipedia.org/wiki/Gray_code https://en.wikipedia.org/wiki/Gray_code
  - 6keZbCECT2uB 4y ago
    I've wondered about the same thing of generating a permutation with a minimum number of samples. I'm not sure how Gray codes helps you here, and the multiplication sounds wrong since many outputs aren't reachable from any input.
    - seanhunter 4y ago
      The idea is just a closed form solution that gets you from a number in 1...nPermutations to a single specific permutation. I was using Gray codes as an example of a sequence that exhausts all permutations with a closed form that gets you to a specific point in the sequence. Might not work - as I say I never actually got around to implementing it.
toast0 4y ago
> If shuffling, look up a real algo (like Fisher-Yates for instance) and implement that. Or better yet, use a library implementation. If using a library implementation, you do still need to validate that it's using a proper algorithm. And that it doesn't change to something else during an update. Which probably requires you to understand the algorithm, and looking at wikipedia, it's a handful of lines of code to do it right and know that it doesn't change because it's your code. Maybe not worth the time to inspect and reinspect from a library.

gambiting 4y ago

Of course, the question is why would this be the case in Arena. You play against other players, not the casino.

jna_sh 4y ago
The theory I’ve always heard about why the shuffler might be biased is that they’re trying to reduce land flood/screw. Drawing too few or too many lands is a commonly cited cause of frustration with players and if you’re reasonably assuming Arena wants to do all the usual monetised-game things of increasing playtime and MAU whatnot, this conclusion seems one of the first people come to.
seanhunter 4y ago
They make money by selling the cards right? I would think that might change their incentives somewhat. I don’t really know the game.
- dagi3d 4y ago
  The better "experience" they transmit to the players, the more engaged they will be and the more cards/packs they will sell
- nkrisc 4y ago
  Players who aren’t having fun won’t buy cards or will stop buying cards when they quit.
slackfan 4y ago
Yes, but a frustrated player is more likely to buy event entries, aka gems, to draft more, and blame the poor randomization on bad luck, rather than intentional screw, because that is what you do at real life events. It's an insidious dopamine loop strategy, but it absolutely works.

manimino 4y ago

The correct Fisher-Yates shuffle is this (from Wikipedia): -- To shuffle an array a of n elements (indices 0..n-1): for i from 0 to n−2 do j ← random integer such that i ≤ j < n exchange a[i] and a[j]

seanhunter 4y ago
Right. The subtle difference being that because you only sample from position i to n you only ever exchange each card exactly once. In my algo you sample from 0 to n-1 so a card exchanged in a previous round can be exchanged again. This generalises into cards early in the shuffle being exchanged more than later cards, which changes the distribution of possible outcomes. Nerd sidenote: Because generating random numbers tends to be expensive, I had an idea once where you generate the full permutation with only a single random sample. Basically you could use something which fully enumerates a space like Gray codes[1] (you want one with a closed form solution which can arbitrarily you the nth code) then you generate one random number, multiply by the number of combinations, look up that code and decode that into the sequence of cards. I never actually got around to implementing it, but I suspect if your code lookup was fast it would be much faster than Fisher-Yates. The use case was if you wanted to make a Monte Carlo algorithm to evaluate strategies in a card game for instance. [1] https://en.wikipedia.org/wiki/Gray_code https://en.wikipedia.org/wiki/Gray_code
- 6keZbCECT2uB 4y ago
  I've wondered about the same thing of generating a permutation with a minimum number of samples. I'm not sure how Gray codes helps you here, and the multiplication sounds wrong since many outputs aren't reachable from any input.
  - seanhunter 4y ago
    The idea is just a closed form solution that gets you from a number in 1...nPermutations to a single specific permutation. I was using Gray codes as an example of a sequence that exhausts all permutations with a closed form that gets you to a specific point in the sequence. Might not work - as I say I never actually got around to implementing it.

toast0 4y ago

> If shuffling, look up a real algo (like Fisher-Yates for instance) and implement that. Or better yet, use a library implementation. If using a library implementation, you do still need to validate that it's using a proper algorithm. And that it doesn't change to something else during an update. Which probably requires you to understand the algorithm, and looking at wikipedia, it's a handful of lines of code to do it right and know that it doesn't change because it's your code. Maybe not worth the time to inspect and reinspect from a library.