Your primary concern is on my reluctance to field test MOST in casino play to “validate” it, and my reliance on two mathematical tests of its ability. In Chapter 5, my crucial replay test is applied to a running bankroll sequence of wins/losses/pushes from 1000 hands of actual game play. Then the exact same numerical sequence is reprocessed using my tactical exits. The replayed version exhibits an unmistakable up-tilt towards more winnings, in a way that is precisely predictable from the mathematics that isolates the positive advantage. It’s not much of an up-tilt, but it’s as much as the imbalance in the player/dealer rules-of-play will allow.

In my e-book, I also show the same predictable up-tilt on a random simulation of 3200 hands of play. There’s no need to keep repeating this effect, because Math tells us that what applies to any one such random sequence, applies to all of them from the same source. And that source is my Standard Play, the methodical playing style you must follow to exploit this advantage. One aspect of it is Basic Strategy. The other is a bet-boosting style that mimics the randomness and frequency that conventional card-counting offers, but, it does it much more easily.

Also, you might be interested to learn about the field testing of the classics in the BJ literature, Basic Strategy and card counting, before they were openly published. In Ed Thorp’s original work, published in 1962, his field test consisted of 30 man-hours of play (he and two others over a weekend in the Reno area). If you do a rough statistical analysis of that amount of play to assess a confidence that his winnings were due to his system, as opposed to plain luck, the result is not much better than a coin toss that his system was the driver. It takes a lot more than 30 hours of play to pluck a 3% win signal out of an ocean of random noise, with black-and-white confidence.

And what about Peter Griffin’s masterpiece-work on card counting? No field testing was conducted before publication in 1979; it’s validation was all mathematical. He didn’t call his book “The Theory of Blackjack” for nothing!

To non-mathematicians, math validation seems second-rate or a cop-out somehow, but it depends on the problem being addressed. In the field of cryptography (codes and cyphers), for example, no one would trust a coding algorithm UNTIL it is validated mathematically. Math can actually cross check itself. I truly regret that my system is validated mathematically in my e-book, which means that many folks will not be able to understand it, but my logical alternative is also flawed.

Would you prefer that I publish a field-test showing my system works well, that might just be perceived as a cherry-picked example of a run of good luck? You would trust my test data, but not my math approach? Wouldn’t I have to show you that it’s statistically significant, and wouldn’t that be more incomprehensible math to many readers. You have set me a hurdle that is impossible to clear, simply because most folk are not math-oriented. Or, would you prefer that I invent a bunch of glowing testimonials about my system, as other system promoters do?

Or would you like your science served straight up, explained in layman’s terms as much as possible, so you can make an informed judgment, and see for yourself that it all fits together. Plus it’s been peer-reviewed by experts in financial statistics. That’s how science gets done. At some point, you have to trust the established integrity of the researcher. I have over 30 years of experience in scientific research, and 28 peer-reviewed papers in the primary literature. I don’t demand that you buy it; the choice is yours, based on whether the perceived pay-off is justified by the supporting material.

My comparison with financial markets also concerns you. As I explain in my book, when a system, which is effectively one of statistical arbitrage in the casino-financial market, has isolated a trader’s advantage, it deserves to be compared with other conventional investments. I explicitly state that this is not a logical alternative to using MOST, which is of course, to continue playing BJ without it. But the comparison with financial markets is instructive in showing a couple of things. One is the accelerated time-scale the casino offers to MOST users, relative to the financial markets to hedge-fund traders, when these are compared on an annualized basis.

The second is that MOST’s Exit Range Strategy is based on an empirical, validated, Normal distribution in the player’s bankroll as one critical component. Normal distributions are mathematically very well-behaved. The distributions used in econometric models are unique to their particular market, and exhibit variable “fat tail kurtosis”. They lack any mathematical universality, and are only useful approximations to the prevailing markets conditions. As such, they are vulnerable to fundamental market changes, like sudden stampedes for liquidation. My point is this: the math behind MOST is much more reliable than that behind market models. As long as the basic rules of BJ stay the same, the distributions behind the MOST advantage are unchangeable. There can be no surprises. Also, I explicitly state that MOST must never be considered as an alternative to conventional nest-egg investing.

Anyway, all of these issues are elaborated in my e-book. The first two chapters are available free at MOSTStrategy.com, and can really orient your thinking to understand what my system is all about. Remember, you don’t have to understand its math to use it.

One last thought: If you had discovered a statistical advantage hidden in the game rules of BJ for all these years, what would you do? And as I say in my book, the price is somewhat arbitrary, without an established market to guide me. What should I be charging for it? I would really appreciate your help on that matter.

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