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1 1 Optimal Betting Spreads The tables of Optimal Betting Spreads, in Chapters 6-10 of The Brh Systems Book, contain all the information which a player requires to design Betting Schemes which fit their style of play and bankroll. In order to the tables, it is necessary to understand how optimal spreads work, and what the various terms mean. Definitions Betting Unit: A betting unit is the basic unit of a betting spread. Betting Spread: A 1-M betting spread is a series of values for each value of the (running or true) betting count, such that the minimum value is either zero or one unit, and the maximum value is M units. Unit Expectation (ev): The lower case ev denotes the unit gain per round, for the counting system with a given betting spread. Unit Standard Deviation (sd): The lowercase sd denotes the unit standard deviation per round for a given betting spread. Long Run Index (N0): The Long Run Index N0, is equal to sd N 0 =, (1) ev which is the number of rounds which need to be played such that the total expectation is equal to the total standard deviation. It has a wider significance however, in that it is proportional to the bankroll doubling time for either a fixed or proportional bettor. The label N0 comes from the fact that if the player is losing by one standard deviation below the expected win, the after N0 rounds they will be even. For a spread that incorporates Wonging or backcounting, N0 also includes rounds watched but not played. However, the method used to generate the data in the tables incorporates all remaining unplayed rounds until the end of the shoe. This does not affect the accuracy of the betting spreads, but this extra factor may need to be taken into account if calculating, win rate per hour, in conjunction with the percentage (%pl) of rounds actually played.

2 Unit Equivalent Kelly Bankroll (ekb): The Unit Equivalent Kelly Bankroll ekb is equal to ekb sd ev =. () This quantity plays a crucial role in proportional (Kelly) betting schemes, and Risk of Ruin calculations for fixed betting schemes. Optimal Betting Spread: The Optimal 1-M betting spread for a given Wonging or backcounting strategy, is the spread that minimizes N0. The time to get into the long run is minimized, so that fewer rounds need to be played to overcome an initial downswing of standard deviation or 'bad luck'. However, since it is proportional to the doubling time, minimizing N0 ensures the fastest rate of bankroll growth. Betting Scheme: A betting scheme is different from a betting spread. A betting scheme B is obtained when a betting spread is multiplied by a monetary unit bet \$B. For example a 1-10 betting spread, with a \$5 unit bet, becomes a \$5 to \$50 betting scheme. The unit may change, and so the scheme will change, but the spread remains the same. Expectation (EV): The uppercase expectation EV for the betting scheme is equal to EV = B ev, (3) and is the monetary expectation per round for the betting scheme B. Standard Deviation (SD): The uppercase standard deviation SD for the betting scheme is equal to SD = B sd, (4) and is the monetary standard deviation per round for the betting scheme B. Note the standard deviation for N rounds is SD N, so that the SD for 100 rounds is only 10 times that for one round. Optimal Betting Scheme: An Optimal Betting Scheme is a betting scheme that incorporates an optimal spread. Note that the ratio of EV/SD is equal to the ratio of ev/sd, so that N0 is always the same provided the same betting spread is used, regardless of the unit \$B.

4 4 Use of Optimal Betting Tables The first consideration is to find the spread with the lowest possible value of N0 you can get away with. This entails as much backcounting and Wonging (leaving the table if count falls below some value) as possible, combined with spreading to two hands at the appropriate count value. One immediately sees that the play all shoe games are to be avoided at all costs, since the N0 values are extremely high. That means that even with perfect counting play, one could go for years without winning. Also for these spreads, the value of ekb is also quite high, which means a large bankroll is required, for any significant gain. The second is the ability to spread to two hands in positive expectation. The values in these tables assume that there are three other players at the table. When the running or true count is greater than zero, the player spreads to two hands, each with a bet equal to the value in the table. Note that for equivalently sized spreads, the fractional bet value is less than for the single hand case. This is due to something known as covariance, where both hands are subject to the outcome of the dealer s hand. The reason for spreading to two hands in this way, is that it is a good method for lowering N0, although in this case, N0 must now be interpreted as a number of rounds, rather than number of hands. You may not necessarily win quicker this way, but you will lower the swings in bankroll, provided you size the bets correctly. Fixed Bettors This kind of player has to be concerned with risk of ruin. Using the Unit Equivalent Kelly Bankroll (ekb), it is possible to either determine the bankroll required for a given unit bet \$B, or alternatively the value of \$B for a given bankroll and risk of ruin. Example: Consider the 1-8 spread, play two hands UTC 0, play only UTC(Brh-I) greater than -6 (roughly equivalent to Hi-Lo TC >-1), example game given in the table below. TC Spread Scheme \$ \$ \$ \$ \$ \$ \$ \$ \$ \$ \$ \$ \$ \$40 ekb 633 \$3165 N (Hi-Lo) %Pl 7.66

5 5 The '(Hi-Lo)' row represents the value of N0 a player could expect if the player were using the well known Hi-Lo count, details of which may be found in 'Professional Blackjack' by Stanford Wong. Hi-Lo is considered to be a standard of sorts, as it is the simplest balanced ace-reckoned count. Using any of the Brh Systems, including the running count versions, will outperform Hi-Lo. It is only since we have been able to compute optimal betting spreads, that a truly fair method of system comparison has been possible. For a given 1-M optimal betting spread, the system that delivers the lowest value of N0, can truly be said to be the more powerful system. The use of the optimal betting spread, or equivalently the same bankroll for betting scheme construction, ensures that each system has the same risk of ruin, and so EKB/N0 becomes the net rate of return on investment for a fixed bettor. Another problem when comparing systems relates to the backcounting Wonging method and the percentage of rounds played (%pl). There is a question of fairness regarding the ability of a system to predict betting advantage. Some say that all systems must use the same Wong point in terms of (dis)advantage, for example leave when each system predicts an advantage of -1%. I personally have used the method where the percentage of rounds played for each has been matched. For true count systems there is usually little difference between the two, but there are differences between the two methods when comparing running count systems due to the non-linear advantage curve. In the tables in the Systems Book, I have attempted to match the percentages, when comparing with Hi-Lo, but in some cases it was either not possible or required an awkward number as a running count Wong point. The percentage reported in the table is for the particular Brh system, not Hi-Lo. This explains some discrepancies, particularly with running Brh-0 in shoe games, where Brh-0 outperforms Hi-Lo for play all, but not for some of the Wonging cases. Using the table above, if the player wishes to bet \$5 to \$40, the unit bet is \$5. The optimal scheme is obtained by multiplying each value in the column by \$5, and rounding to the nearest bettable unit. This results in a maximum bet of \$40 at TC=+6. Now, ekb is equal to 633 units here, so that the EKB for the \$5- \$40 betting scheme is \$3165. For a fixed bettor, this is the amount for which there is a 13.6% risk of ruin, generally felt to be unacceptably high. The risk of ruin can be lowered to whatever is desired by having a larger bankroll. How much larger can be seen in the following table: ROR x EKB 13.6% % 1.5.0%.0 1.0%.3 0.1% 3.5 Therefore, to have a ROR of 5%, the player would require a bankroll of 1.5 x \$3165, which is \$4747. This would be rounded in practice to \$4750. The ROR is equal to ROR ( Bankroll / EKB) = e, (6) where e=.718 is the Natural number. The derivation of this result is given in Appendix B pf the Book, and was originally derived by Patrick Sileo. Alternatively, if a player has a \$10000 bankroll, and desires a % ROR, then the EKB must be \$10000/.0=\$5000. But if the EKB is \$5000, then the betting unit \$B must be EKB/ekb=\$5000/633=\$7.90. Now while it is impossible to actually bet \$7.90, the minimum bet will be \$5 or maybe occasionally \$10 for cover purposes, and each intermediate bet will be \$7.90 times each unit value up to a maximum bet of \$60. Unfortunately, there are table minimums, so that for a given game there will always be a minimum value of \$B. This means that while choosing an optimal spread, there will either be a minimum bankroll

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