The Risky Business of Loss Rebates By Eliot Jacobson, Ph.D. April 7, 2014 at 8:56 pm In early 2011, Don Johnson won more than $15 million playing blackjack at Atlantic City. Before he began, he negotiated a number of perks that moved the edge squarely to his side. The most valuable was a 20% rebate on his losses whenever he lost more than $500,000 in a day. These loss rebates had no minimum play requirement and reset after each day’s play. Johnson’s optimal winning strategy is not obvious. Using computer models, I determined that Johnson could maximize his earnings by stopping for the day after either winning 2.4M or losing 2.6M. On average, this strategy netted him a theoretical win of about $137k per day. With other cash incentives and other techniques, his actual expected win per day was in the range of $350k to $400k. Johnson recently confessed to using “Ph.D. mathematicians” to help develop his strategy. He planned, he played and he conquered. The advantage Johnson achieved was possible because the incentives he received were not correlated to his theoretical win (T-Win). The correlation principle is well-understood internationally, where high-rolling baccarat players are given rolling chip incentives that rebate a fixed percentage of their T-Win. With this structure, players know exactly what they are getting and casinos know exactly what they are giving. Rolling chip programs are similar to earning points for playing slots. These players are rewarded based on simple formulas that link their T-Win to the number of points they earn. Slot players know what they earned in comps, free play, and cash back for their play. They do not expect to get more when they lose more. Likewise, they expect to get their rewards even if they win. By contrast, a loss rebate program is an uneven and unfair cash incentive program. Players will win and lose – that’s part of the natural volatility of casino games. But when a casino uses loss rebates, the player who wins is not eligible for that rebate, no matter his/her value to the casino. By contrast, a player who loses may get a rebate that is far in excess of the T-Win s/he generated. This lack of correlation is the basis for the risk, to casinos, which is inherent in loss rebate programs. The logical flaw behind loss rebates is a casino’s belief that when a player loses money, that is the same as the casino earning money. The reality is that a casino does not earn its income by beating individual players. Casinos make their money by offering wagers which have a house edge. Each gaming event imposes a sort of “tax” on the player. The gaming income for a casino is simply the sum of the taxes it collects. Winning and losing players contribute equally to the casino’s bottom line. Most marketing departments understand the equivalence between gaming events and income when it comes to slots and video poker. Internationally, this equivalence is well-understood for baccarat. Somehow, this wisdom has been lost when marketing to premium table games players in the domestic market. When casinos believe that their goal is to beat each player, they may conclude there is room to reward a losing player and still be profitable against him/her. The belief that casino profit is tied to beating each player ignores the mathematics on which the industry is built. Loss rebate incentive programs are a flawed marketing instrument. Don Johnson’s results are just the tip of the iceberg for the losses the industry continues to incur by offering loss rebates to their premium players. Three years later, the lessons that Johnson taught the industry about cash incentives appear to have been forgotten. Eliot Jacobson is a gaming mathematician and advantage play expert. His blog apheat.net is widely recognized as the premier resource for legal methods to beat casino games. Information on his “Advanced Advantage Play” seminar on May 16, 2014 is available on his blog.