Let's talk MATHS

[SparkyElf-2852]

@Smeet-1144

Quite a few.

@Derkan-2593

The general idea for statistics is that you can start extracting probabilities only when you reach a really large sample size.
Large generaly starts after several thousands.

Bla, bla, bla. Not a single formula! Or even a slightest notion of what ‘large’ etc is, as noted above.

For starters, check something like this out:
https://en.wikipedia.org/wiki/Binomial_distribution
In particular:
https://en.wikipedia.org/wiki/Binomial_distribution#Confidence_intervals
and also
https://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval

(WikiDumpster might not be the best or most accurate source, but it’s just a pointer at the proper subject and how these things work in general)

In the posts linked above, I’ve already noted that approximating the (binomial) distribution with the normal one probably isn’t a very good idea here.

It’d be an okay little project for a maths student to implement those formulae in a small program or something like that, otherwise it’d be a bit annoying, that’s why I asked. If you don’t wanna bother, well, for rather large sample sizes (although you’ve likely got no notion what that actually means) you could go with a crude approximation by the Gaussian distribution and use the ‘three-sigma’ recipe I hinted at earlier.

When you grasp at least the basics, we could talk — and the topic-starter has explicitly proposed to talk about MATHS… But, of course, those VERY VOCAL forum participants are eager as ever to contribute their oh-so-valuable clueless ‘opinion’ instead.

@Derkan-2593

The general idea for statistics is that you can start extracting probabilities only when you reach a really large sample size.

@Derkan-2593

And the smaller your probabilities are, the harder it will be to find them back in your statistics.

By the way, you’ve apparetnly got no notion of what ‘statistics’ even means.

For starters:

https://en.wikipedia.org/wiki/Statistic

(Yes, the definition there in the beginning is more or less correct.)

@Schyla-1490

Think of it like a subjective win rate (your personal deck’s win rate) and the objective win rate (the actual real win rate combined of all people using that deck)

Ugh… That’s a… creative way to put it. You might as well go on and tell us there’s no such thing, that a ‘win rate’ is a ‘social construct’ or whatnot. It’s fine and all, everyone is entitled to one’s own opinion, but this isn’t a mathematical approach, if you ask me.

@Schyla-1490

Your subjective win rate will need to be played enough times

The question is: how many?

Sorry for being curt, but you’ve literally said nothing about it, despite being verbose in your post.

@Schyla-1490

to substantiate the deck’s true win rate is X where X = the objective win rate.

That’s the only way.

Thus, you can never use your own deck’s win rate to calculate what the overall win rate of the deck is unless you are the ONLY one playing the deck.

Nope, that’s not how it works.

As said many times, a ‘proper’ way (well, at least one of — there are probably alternative approaches) would be to estimate the confidence interval, for which the player’s own data is as good as any, really, and the amount of data is related to its width — nothing more, nothing less. The ‘objective’ figure still remains one to be estimated.