# Thread: blackjack maniac: % of Shoes that reach each TC?

1. ## blackjack maniac: % of Shoes that reach each TC?

What % of shoes reach each TC

4.5/6 cut
6/8 cut

thanx

2. ## Dog Hand: Hmm... interesting question! A few queries, though, and one answer

blackjack maniac,

First, the queries:

1. I assume we're talking HiLo here, right?

2. How closely do you want to estimate the remaining decks: to the nearest deck, half-deck, quarter-deck, or exact card?

3. For positive TC's, do you want the percentage of shoes that reach AT LEAST the specified value, or the percentage that hit EXACTLY the specified value?

4. Similar question for negative TC's: EXACTLY the value, or the value OR LOWER?

5. Are you asking only about the TC at the start of each round (i.e., the betting TC), or at ANY POINT in the shoe?

6. How many players? What are the rules? These will have a slight effect on the results.

Now, one answer: the percentage of shoes that reach a TC of zero is... 100% ;-)

Post your answers, and I'll see if I can figure out a way to find the results.

Dog Hand

3. ## Dog Hand: Preliminary Results

blackjack maniac,

I ran a series of 400-million-round CVData simulations for a 6D, S17, DA2, DAS, 75% pen game. The table has one "average" player who plays all, and one wonger who wongs in when the HiLo TC reaches or exceeds the indicated value, plays a single hand (no splitting for the wonger), then wongs out, after which the deck is shuffled. (By "exceeds", I mean for positive TC's, that the TC is that high OR HIGHER, while for negative TC's, the TC is that low OR LOWER.) In this way, the number of hands played by the wonger is precisely equal to the number of shoes into which he wongs, and thus the number of shoes that reach or exceed the indicated TC. Since CVData also counts the total number of shoes played, the ratio of hands played by the wonger to the total shoes gives the fraction of shoes that reach or exceed the indicated TC.

Here are the results:
```
TC>=	Number		Shoes		Percent
1	13,112,754	17,263,266	75.96%
2	7,411,186	12,553,647	59.04%
3	4,552,167	10,767,006	42.28%
4	3,220,690	10,087,478	31.93%
5	1,998,546	9,683,165	20.64%
6	1,336,409	9,503,407	14.06%
7	775,213		9,402,326	8.24%
8	534,539		9,359,837	5.71%
9	278,483		9,331,384	2.98%
10	169,350		9,319,756	1.82%

TC<=	Number		Shoes		Percent
-1	13,603,322	17,582,980	77.37%
-2	7,646,761	12,617,509	60.60%
-3	4,721,386	10,780,628	43.80%
-4	3,364,885	10,090,098	33.35%
-5	2,104,006	9,681,338	21.73%
-6	1,418,738	9,501,243	14.93%
-7	830,599		9,400,436	8.84%
-8	575,832		9,358,406	6.15%
-9	300,226		9,330,555	3.22%
-10	183,326		9,319,100	1.97%
```
.

Is this the type of information you want?

Note that the number of shoes played is higher for TC's closer to zero: this is because, once the wonger enters the shoe and plays a round, then the shoe is broken and shuffled. Since the wonger enters a lot more often at TC's close to zero as opposed to those far from zero, the poor dealer has to shuffle a lot more... and her hands are REALLY TIRED ;-)

Dog Hand

P.S. For future reference, the way to get CVData to do this sim is first to create a new counting strategy based on complete B.S. but using the HiLo count tags, then modify the strategy to prevent any splitting. This is necessary, since if the wonger splits, then CVData would count that as TWO hands played, so it would appear that the wonger had entered TWO shoes. Second, create a new betting strategy in which the wonger "sits out" and then Starts Play when the TC>= the positive TC value (or TC<= the negative TC value), and then Stops Play at any TC<=99. Since the TC never reaches or exceeds +99, the wonger always leaves right after playing only one hand. The wonger simply flat-bets when he plays. Finally, be sure to check the "Force shuffle on exit" box, as otherwise he might enter the same shoe more than once, and we only want to count ONE entry per shoe.

4. ## blackjack maniac: Re: Hmm... interesting question! A few queries, though, and one answer

> blackjack maniac,

> First, the queries:

> 1. I assume we're talking HiLo here, right?

Can we use halves? TC florred

> 2. How closely do you want to estimate the remaining
> decks: to the nearest deck, half-deck, quarter-deck,
> or exact card?

full deck

> 3. For positive TC's, do you want the percentage of
> shoes that reach AT LEAST the specified value, or the
> percentage that hit EXACTLY the specified value?

at least, we also want to play if the TC goes higher.

> 4. Similar question for negative TC's: EXACTLY the
> value, or the value OR LOWER?

can drop negatives if more work, but if not more work perhaps leaving for new shoe at TC-1 wether playing or watching

> 5. Are you asking only about the TC at the start of
> each round ( i.e. , the betting TC), or at ANY POINT
> in the shoe?

betting tc to show wonging in?

> 6. How many players? What are the rules? These will
> have a slight effect on the results.

6h17dasrsa
4.5/6 cut
2 or 3 players while adding a wonger

> Now, one answer: the percentage of shoes that reach a
> TC of zero is... 100% ;-)

I agree

> Post your answers, and I'll see if I can figure out a
> way to find the results.

> Dog Hand

Perhaps the real question is this:
If you were in a casino and were only going to play or wong into one shoe, what is the TC you should wait for? I belive the orginal question is related to the correct answer.

5. ## Don Schlesinger: Nice work!!

For what it's worth, it isn't every day that we get research that, to my knowledge, has never been done before, anywhere!

I printed out your charts, for future reference, and, believe me when I tell you, I don't do that very often. :-)

Lovely work.

Don

6. ## Dog Hand: Halves 6D Results

blackjack maniac,

I ran the sims described in the "Preliminary Results" post (see that one for details), but this time I used Halves for the wonger. I'm afraid I didn't follow all of your requests, though: I still had only 1 player play all, and still used half-deck resolution for the first half of the shoe, and quarter-deck for the remainder.

Here are the results for no "quitting strategy":
```TC>=	Number		Shoes		Percent
1	13,669,617	17,772,500	76.91%
2	7,612,600	12,682,224	60.03%
3	4,883,190	10,921,851	44.71%
4	3,333,524	10,147,374	32.85%
5	2,207,204	9,741,716	22.66%
6	1,491,372	9,540,979	15.63%
7	937,929		9,425,069	9.95%
8	602,514		9,370,232	6.43%
9	354,471		9,338,209	3.80%
10	212,294		9,324,153	2.28%

TC<=	Number		Shoes		Percent
-1	14,196,363	18,139,262	78.26%
-2	7,836,108	12,745,172	61.48%
-3	5,050,921	10,935,855	46.19%
-4	3,472,044	10,149,431	34.21%
-5	2,319,561	9,740,767	23.81%
-6	1,581,159	9,539,766	16.57%
-7	1,006,622	9,424,419	10.68%
-8	650,371		9,369,231	6.94%
-9	388,177		9,337,883	4.16%
-10	235,129		9,323,814	2.52%
```
.

These results show that nearly one-quarter of the shoes seen never go positive... I seem to get a lot of those :-(

On the other hand, over 20% of the shoes never go negative.

Finally, here are the +TC results when the wonger "gives up" on any shoe where the TC falls to -1 or below. These were found by setting the "Stop Observation" value to -1:

```TC>=	Number		Shoes		Percent
1	21,229,469	43,440,629	48.87%
2	9,979,102	29,079,480	34.32%
3	6,199,852	23,878,381	25.96%
4	4,270,677	21,477,520	19.88%
5	2,923,730	20,211,372	14.47%
6	2,036,943	19,559,458	10.41%
7	1,331,279	19,188,910	6.94%
8	877,461		19,004,169	4.62%
9	533,618		18,902,463	2.82%
10	326,153		18,845,286	1.73%
```
.

Note that while the "quitting" percentages are smaller than the corresponding "no quitting" percentages, the absolute number of hands played (out of a constant 400-million rounds seen) is quite a bit higher.

Let me know if these are what you want... if so, I'll try to run the 8-deck results.

Hope this helps!

Dog Hand

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