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.
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