I was reading more about the Fisher-Yates shuffle that seems to be widely accepted and used for RNG shuffling on poker and card game sites. It seems to be the gold standard of computer "shuffling" and the best that programming, at this time, can provide. So "good" enough.

I'm not a math expert but seems like there are some flaws in this mode of shuffle that can change the frequency and/or distribution of certain "next item" (i.e. in case of poker the next card dealt) per the information listed about it:

Fisher-Yates Shuffle: https://en.wikipedia.org/wiki/Fisher...3Yates_shuffle

For example that some "permeation" of an outcome can occur more or less often than should be occurring or not at all. There's things such as rounding errors and potential for some "next" drawn instances to occur up to 17% more than others (from the link above).

So it seems it's "good enough" but not truly random.

Questions:

If this is happening with the shuffle, does this possibly explain why cards that fall (i.e. a 4.5% chance) may appear more or less often than they should statistically?

Should players be concerned about this and should it factor into one's consideration of the odds and betting?


To be clear I am NOT implying or saying it's rigged or site's are causing this.

I'm just curious if the noted problems with Fisher-Yates shuffles actually do make online shuffles have statistical blips due to limitations with the RNG that a physical deck will never have.

The best online players been knowing this for years.

Don't fear it, embrace it!

'Im not a math expert' but I'm trying to find a leak with stuff actual experts have been looking at for decades. Seems promising...

Lol , both humor and wisdom in one shot. I like it.

Just to clarify , my apologies , I’m not asking about a player leak (mine or others), I’m asking about the flaws of the Fisher-Yates shuffle referenced by your “actual experts” per the sources of the link I provided.

Appreciate the reply but this isn’t a leak question, it’s a question about frequencies and distributions based on the problems with computer shuffles.

More curiosity and looking to see if myself and others are misunderstanding the data presented, if there are different ways the companies maintaining these RNG systems are reducing impact of flaws , and how these impact the runouts of a computer deck vs a physical deck.

If I was a math expert on the matter I would have drawn my own conclusions and answered my own questions 😂.

If anyone is interested I did ask a friend, after my OP, with a PHD in mathematics specialized in computer programming about this Wikipedia data. They’re understanding is there are ways to reduce the impact of these flaws, which seems like a reassuring fact.

Why are you being so superficial? Flaws make us who we are <3

You're absolutely right, OP. - You're not a maths expert.