Long Term Index: NO

The Calculation of NO

NO Values


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The long term could be defined as the point where the delta of one standard deviation is equal to the average return:

average return = (er-1+cb) x hands
standard deviation = sqrt(variance x hands)
(er-1+cb) x hands = sqrt(variance x hands)
(er-1+cb)^2 x hands^2 = variance x hands
hands=variance/(er-1+cb)^2


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N0=variance/(er-1+cb)^2 hands

positive expectation:
FPDW + .25% cb N0 = 260,000 hands
10/7 DB + .5% cb N0 = 630,000 hands
10/7 DB N0 = 9.7 million hands

negative expectation:
Pick'Em N0 = 60 million hands
8/5 SAB N0 = 175 million hands
9/6 DDB N0 = 400,000 hands
8/5 JOB N0 = 26,000 hands


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Very early on, upon joining this board, iggy introduced a concept which he references in shorthand as 'N0'. It's a reference to a 'long term' concept that doesn't have ER/EV as it's primary focus, but instead examines the length of play required before you have strong confidence of positive (profitable) results.

This is a rather liberating perspective on play for, speaking for myself at least, I can deal with a certain degree of uncertainty with respect to closely achieving some given ER in my play -- but I have a critical concern when it comes to the risk of loss. In other words, if I play with a 1% positive return expectation, I'll deal just fine if I only manage an actual return of 0.5%. But, where I really look for some comfort is that I'm not exposed to undue loss risk.

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'NO' is the number of hands for a game after which you have a strong expectation of positive results - namely where a shortfall from ER in results of no more than one 'standard deviation' (SD) represents no worse than a break-even result.

Without dwelling on the calculation of SD, the significance is that for a given ER, the range of possible outcomes that are +/- 1 SD represent 68% of all likely results. For example, if a game has an ER of 100.5% and, after x hands played, the standard deviation is 1%, then 68% of likely outcomes will fall between 99.5% and 101.5%. As you play more hands, results are expected to more closely approximate the ER, and the standard deviation decreases.

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Ok, cutting to the chase, the significance of all this is that for a game such as FPDW, there is a given number of hands played for which the value of 1 SD equals the positive return of the game -- in other words, after that number of hands, the range of outcomes that lie within 1 SD of the game ER all lie in positive territory, i.e. you have a strong probability of coming away a winner. For FPDW, this would represent the point in play where 1 SD = .76% and 68% of results will fall between 100.76% +/- .76%.

With 68% of expected results falling within 1 SD of the ER, 32% of results outside of that range. Half of that 32% will represent results that are even stronger than that range -- at 1 SD, when you reach 'N0' hands of play, you only have a 16% expectation of suffering a loss in your play (and a considerably smaller expectation of a 'signfiicant' loss).

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What's really revealing here comes when you listen to the naysayers who speak of the millions and millions of hands before which you achieve long term results (i.e. expect to closely approach game ER). If you set your sights on being satisfied, at minimum, with positive results, the scope of that 'long term' shrinks tremendously -- particularly if you're talking about a game with a strong return and yet modest variance.

The most notable example for LV denizens is FPDW -- and it's why there are numerous locals who've enjoyed steady profitable play with only a moderate downside, provided that they're sufficiently bankrolled to survive the short-term swings.

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The last equation provided by iggy in the quote above defines how to determine just how many hands it takes to reach this point in play. What you'll find is that the number of hands for FPDW is quite tangible for most reasonably active players. Apply the equation to a thinly positive and more volatile game such as 10/7 DB, with modest cb, and the number of hands required is greater by magnitudes. It highlights the importance of game selection on 'survivability'.

Hope I didn't overly belabor this -- I find that iggy's introduced one of the most valuable concepts expressed here to date but figure that others, like myself, could use a little assist in filling in some details.


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