Question for Don: Tracking EV and Variance

[MJ1]

I've been meaning to ask this question for a while but have procrastinated for various reasons. In any event, I'll do my best to articulate what I am trying to ask.

I use two methods of attacking the shoe-- play-all and wong out. Which method I employ will depend on conditions. For play-all, I play through the entire shoe. For wong out, I play right from the first round and then leave once the count becomes negative.

I use CVData to determine the EV and variance per shoe based upon # players at table, location of cut card, and # hands I play per round. Now suppose I play through an entire shoe where the count is either neutral or positive (never becomes negative). For EV and variance purposes, should that shoe be considered play-all or wong out? I believe an argument can be made for either case. A play-all simulation certainly accounts for those instances where the count is either neutral or positive throughout the shoe. On the flip side, it also accounts for shoes where the count is either neutral or negative. At the same time, a simulation that is run with a wong out methodology ONLY takes into consideration shoes that are either neutral or positive because once the count becomes negative you wong out. The play-all simulation is kind of a one size fits all approach, whereas the wong out simulation exclusively pertains to neutral and positive counts.

In short, for EV and variance tracking purposes, which simulation should I use to get the most accurate estimate of my EV and variance per shoe for the situation I have just described?

Thanks,
MJ

[Gramazeka]

CVShuffle + CVData/ST

[theblackjackplayer]

bear in mind that the actual variance per hand is huge while the average ev per hand (at a positive true count) is tiny in relation. Hence, practically speaking from experience it shouldn't make a difference.

[Norm]

Not sure I understand what you are attempting. I don't see how EV and variance in one shoe has a useful meaning. Your theoretic EV and variance are what a sim says it is for a very large number of shoes, which will include shoes where you never wong out. That's part of the variance.

[MJ1]

Not sure I understand what you are attempting. I don't see how EV and variance in one shoe has a useful meaning. Your theoretic EV and variance are what a sim says it is for a very large number of shoes, which will include shoes where you never wong out. That's part of the variance.

I am going to play through hundreds of shoes so I want to get a sense of how much each shoe is worth, on average, in terms of EV and variance. I can then take this information and use it to calculate total EV and variance after playing through several hundred shoes. Then I can determine where my actual play falls on the bell curve.

Using CVData, I can determine EV and variance for a shoe. If I play through all rounds of a shoe, I suppose I could just run a play-all simulation to estimate EV and variance. But what if the count were either neutral and/or positive for a shoe. Instead of using a play-all simulation, would it not be more accurate to run a Wong out simulation to determine EV and variance for the shoe? After all, a Wong out simulation only factors in those cases where you either play through a shoe (count is either neutral or positive) or you exit the shoe. A play all simulation factors in negative, neutral, and positive counts. In short, the play all sim is generic whereas the Wong out sim is more specific to this particular situation.

With that being said, which sim is more accurate for neutral and positive counts-- play all or Wong out?

MJ1

[DSchles]

Clearly, you're overthinking this, and Norm is, of course, correct. Why would you need the EV and variance of 100 individual shoes to calculate the overall EV and variance of 100 shoes? Just let the sim run, and the final result is all you care about.

If you play-all in a shoe that never gets negative, that's part of the overall process. You do NOT designate that as a Wong-out shoe; it's just a shoe in which you played all and it remained positive throughout. So, again, don't overthink this. The game is one long, never-ending process. Breaking down results by shoe makes little sense to me. It has no value.

Don

[Norm]

I am going to play through hundreds of shoes so I want to get a sense of how much each shoe is worth, on average, in terms of EV and variance. I can then take this information and use it to calculate total EV and variance after playing through several hundred shoes. Then I can determine where my actual play falls on the bell curve.

Not sure the value. But CVReview can do all of this including plotting the bell curve.

[Gramazeka]

As I understand it, he is interested in the mathematics of the game specifically in the better half of the shoe. And this applies to ST issues. I have given you a list of tools to get results.

[Gramazeka]

For example, we know for sure that by cutting the shoe, we placed 10 more big cards in a certain part of the shoe. Let it be 3 out of 6 decks.

[Gramazeka]

Now the question arises: what method should we use to evaluate and play this play zone? NRS, Snyder or basic strategy? What kind of mathematics will this be?

[Gramazeka]

https://www.blackjackinfo.com/commun...tuition.24392/

[MJ1]

Clearly, you're overthinking this, and Norm is, of course, correct. Why would you need the EV and variance of 100 individual shoes to calculate the overall EV and variance of 100 shoes? Just let the sim run, and the final result is all you care about.

If you play-all in a shoe that never gets negative, that's part of the overall process. You do NOT designate that as a Wong-out shoe; it's just a shoe in which you played all and it remained positive throughout. So, again, don't overthink this. The game is one long, never-ending process. Breaking down results by shoe makes little sense to me. It has no value.
Don

Thanks for weighing in. The reason I try and track EV and variance on a per shoe basis is because every shoe is unique. By that, I mean, one shoe might be heads up, 1.5 decks cut off, with 2 hands per round. Another shoe might have 1.75 decks cut off, 4 players, with 1 hand per round. Wouldn't the EV and variance for each of these shoes differ? Isn't it important to properly track EV and variance to locate AV on the bell curve? This is why I'm considering recording these variables for every shoe that I play. Does that make sense?

Okay, so the bottom line is if I play through a shoe, then I should consider it play-all and use the corresponding sim. Only in those instances when I actually Wong out of a shoe do I regard it as a Wong out shoe. Makes sense to me! :-)

MJ

[Gramazeka]

I thought your question was much more complicated...Sorry...