Sun. Oct 2nd, 2022
Think you can tell if one slot machine has a bigger house edge than another?  Think again.
enlarge Think you can tell if one slot machine has a bigger house edge than another? Think again.

Arterra/Universal Images Group/Getty Images

It’s a common mantra that when it comes to casinos, the house always wins, at least in the long run. That’s because casinos have a small “house edge” – not enough to deter gamblers, but enough to ensure that the house eventually comes to the fore. Some gamblers think they can get around this by, for example, jumping from slot machine to slot machine, hoping to hit one at the right time to win a big payout.

There is a corresponding long-held belief among casino operators that experienced players can actually feel shifts in how much and how often a particular machine pays out, i.e. they can detect subtle differences in the house edge between machines. But the math says otherwise, according to a recent article in the International Journal of Contemporary Hospitality Management.

Slot machines are the source of most of a casino’s revenue. It’s all about manipulating the payback percentage: the percentage of the “coin in” that a player gets back when he is done with the game. “When slot machines are made, the manufacturer will license multiple paytables (usually around five),” said study co-author Anthony Lucas, a professor at the University of Nevada, Las Vegas. “After a casino operator decides to buy the game, they have to decide which of the five licensed pars (also called paytables) they want to install. This is where our work becomes useful, as most operators don’t know which par is the revenue will optimize.”

Lucas spent some 34 years in Lake Tahoe as an operational and financial analyst in gaming, just after college, so he’s long been interested in the types of challenges the industry faces. He has been doing research at UNLV for 20 years. “Most of the research questions I asked arose from the problems we faced in the industry,” he said. “We’ve never had time to sort them out because the decision horizon is so short in business, and you don’t have the chance to do that academic thinking in the longer term.”

The price is correct

The house edge for slot machines is typically between 5% and 10% with most machines offering a payback percentage of 90% to 97%. (If it’s 90%, the casino’s profit — and the player’s loss — is, say, 10% of the coin.) But how can casino operators determine the best house edge for their winnings within that range? “It’s really a price issue because it’s a unique product,” says Lucas. “With real slots, the price is not stated anywhere.”

Conventional wisdom among casino operators is that while there is no expressly marked price, the law of demand kicks in. They think that regular players can intuitively sense when a game they are playing has a higher “price” – that is, has too much of a big house edge – and so, if that house edge is too big, the players will move their business to another casino. with a more generous approach.

“It’s basically how you react to a price shock,” Lucas says. For example, if Whole Foods doubles the price of your favorite brand of almond milk, you can switch to a cheaper brand. That is the law of demand, which means that if you increase the price of a product, you can expect demand to decrease. The big question for slot machines is, “how much will that demand decrease?”

“Maybe we’ll see a drop in the coin, but if it’s less than the product of the coin in the higher par game times the par, we don’t care,” Lucas said.

Casino operators think that regular players can sense when a game they are playing has a higher “price”.

Working with Katherine Spilde of San Diego State University, Lucas sought to test this long-held belief by observing the behavior of slot machine players at local casinos in the suburbs of Sydney, Australia, where all gaming is done electronically. Many previous studies have been based on simulations or have taken subjects into the lab to play slot machines. Lucas thinks that field research is a much better indicator, and mentions two important advantages. “First, you mute the games differently because you have the capacity to really lose your own money,” he said. “In addition, when people go into a casino and gamble, they don’t play the games like they do in a lab. The advantage of the field research is that you observe behavior as it occurs in the setting you are trying to understand.”

For example, virtual players in a simulation will not react the way a human would react if they lose, say, six or seven times in a row. And a typical lab setup will ask subjects to play a game for 500 spins at a constant stake. In a realistic scenario, that just doesn’t happen. Players are not going to play on one slot machine for exactly 500 spins, without varying their bet. They tend to mix up the bets and switch machines if they don’t get the desired result.

According to Lucas, this causes considerable variation in the outcome distribution. “You’re jumping, so that makes identifying the real population parameter, which is par, even more difficult,” he said. “You have unequal sample sizes. You have non-constant bets.” For example, if a study includes a 3% game and a 9% game, there is a wide range of outcome variance in both, with a lot of overlap between the two. “As an engineer would say, the signal-to-noise ratio is not good,” says Lucas. “You hear this little weak signal beeping in a sea of ​​variance.” That’s before taking into account cognitive biases like the gambler’s fallacy and the hot hand fallacy.

Myth: broken

For their own study, Lucas and Spilde tracked the daily performance of two identical slot machines (pairs of “Tokyo Rose” or “Dragon’s Fortune X”) in similar positions on the casino floor for nine months. Each machine in a clutch was set to a different par (the percentage of total coin entry that the machines retain over time), ranging from 7.98% to 14.93%. They measured the daily coin-in and theoretical win (“T-win”), determined by multiplying coin-in and par to get the expected value of a machine. According to Lucas, such a comparison would show whether players really migrated from higher parity games to lower pairs over time.

Unfortunately, mathematics does not support conventional wisdom. The differences between the high and low par games were stable throughout the nine-month period, and the high-par games posted significantly higher revenues. But that conventional wisdom is so strong and enduring that Lucas has struggled to get operators to listen when his research challenges their favored operational paradigms.

“We get so much criticism from the industry because no one likes to put that mental model to the test,” he said. “I get it. But the pie is growing and everyone is getting a smaller piece, so they’re going to have to get a little more technical. Ultimately, I think the power of the research will catch up with the resistance because there’s so much pressure on it to optimize revenue.”

Lucas recently completed a similar study in Mexico with two slot machines placed side by side. “One was a 15% game and one was a 4% game, eleven percentage points apart — almost a 300% price increase,” he said. Still, he found that the same amount was played in both games and the same amount won over a 180-day period. Players did not move to the machine with the smaller house edge. “This place doesn’t even have a hotel, so all the players are frequent players, which is said to be the population that would have the best chance of detecting the prize,” he said.

The message to casino operators is clear: they need to stop worrying so much about losing customers by opting for higher parity machines, which are better for a casino’s profits in the long run. “Many believe that lower pars will generate more revenue by appealing to customer appreciation of game value (ie, lower ‘prizes’), but our work suggests otherwise,” says Lucas. “Our results are, of course, likely due to players’ inability to detect par. Still, it’s helpful to know that the higher pars perform better in the revenue optimization game.”

DOI: International Journal of Contemporary Hospitality Management2019. 10.1108/IJCHM-07-2018-0577 (About DOIs).

By akfire1

Leave a Reply

Your email address will not be published.