Refer to the https://casinoenterprisemanagement.com/blog/theoretical-win-taking-cl... for some more discussion theoretical win (expected value). This blog is the expaned in an upcoming indepth series in CEM describing how to calculate the player rebate and expected value.
Player Rebates
The history of rebates or discounts on a player’s actual losses goes back to late 1970s when the high-rollers of the time would gamble for 30 to 40 hours on one trip, taking breaks for eating and sleeping, and generating gambling debts exceeding a million dollars, which was a large amount back then. These gambling debts remained unpaid for large periods of time, and the idea of Rebates on Player Losses was born. This program has now become an expensive marketing tool, and is offered by a majority of large U.S. and international casinos, sometimes without doing a proper mathematical and statistical analysis. Lucas et al. (2002) considered the problem of assessing the profitability of premium players and have shown that high-rollers don’t necessarily translate to high profits. A formula to calculate a rebate on actual loss that is equivalent to a specified percent of player theoretical loss is given in Kilby et al (2005). This formula is based on the well-known normal distribution approximation for total casino win in a sequence of N trials, the challenge of how large N must be before this formula can be used has been ignored in gaming literature or statistical literature. Sadly this means that, if not properly used, this marketing tool may actually be generating huge losses for the casinos; in other words, some of the casinos may be paying their high-rollers to fly in on a chartered plane, stay in luxury suites, and take home gambling winnings as well.
The expected value of game play goes by other names such as theoretical win. Expected win forms the basis for many compensations such as rebate programs or point programs, as we move forward in our series on game analysis we will show more examples of the danger of applying over simplified models to characterize player return. As supply of gaming product continues to grow it is critical that an understanding of the actual game play is part of the calculation of the player profitability. The operators who apply these deep techniques gain a mathematical edge over their competitors, an edge that has a direct impact on profitability.
In the past, the casino business was highly profitable and tactical decisions were normally sufficient for the maximization of profit. In today’s world it seems reasonable to question if these practices can continue and reasonable to ask if a casino should operate without mathematical optimization.
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