UNLV professor’s research challenges longtime ideas about slot machines

November 23, 2021 2:38 PM
  • Rege Behe, CDC Gaming Reports
November 23, 2021 2:38 PM
  • Rege Behe, CDC Gaming Reports

Every time Anthony Lucas, Ph.D., and his colleagues at the University of Nevada, Las Vegas, produce a study about slot machines, he gets feedback from the gaming industry.

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The latest release, The House Edge and Play Time: Do Industry Heuristics Fairly Describe This Relationship?, is the eighth time Lucas has examined the way casinos set up slots. And it’s also the eighth time there’s been pushback from industry experts.

“It’s very unsettling to them to have their understanding of something challenged,” says Lucas, a professor in UNLV’s William F. Harrah College of Hospitality. “Which I totally get. It happens to me all the time. But every time we do a study, they’ll try to reframe the results into their original scheme or understanding of how slot machines work.”

“I did the study because the industry needs to understand how slot machines work,” he adds, “and clearly a lot of them do not.”

Published recently in the UNLV Gaming Research & Review Journal and co-authored with A.K. Singh, Ph.D., a colleague in the  Harrah College of Hospitality, the study’s findings are based on how casino’s view par, a slot machine’s programmed house advantage. Most operators look at these results over long-term periods. But that view is flawed, according to Lucas, because players don’t ever have that perspective – they play over much shorter periods.

As an example, Lucas cites the difference between slot machines with 10% and 5% par. It would be expected that with buy-ins of $100 on both machines, the 5% game would yield 2,000 in coin in, and the 10% game, 1,000 in coin in. Thus, there would be more time spent by a player on the 5% game.

Lucas says that while in the long run, those figures might be right, there are two inherent flaws: First, that scenario assumes that nobody wins a “megabucks” jackpot which has to be cycled back into the game to result in a zero balance.

But even more problematic, according to Lucas, is that the long-run scenario “doesn’t apply to the individual gambler in any way shape or form.”

“The player never has that long-run experience,” he says. “Even over the entire life a player, they don’t amass enough spins to make that distinction. It’s just a bad way to understand how slot machines work.”

Also problematic is that most coin out results from players hitting jackpots or top awards. But on the majority of their visits to a casino, players don’t hit those significant payouts. And while players can see the awards schedule on  5% and 10% games, they can’t figure out the probabilities of the payouts and can’t discern the difference between 5% and 10% machines, even if the industry thinks they can.

“That’s a question that human beings just cannot answer,” Lucas says.  “We are just patently bad at that. Our brains just do not work that way. I don’t think it’s not that they’re not savvy enough, it’s just that they’re not equipped with the right sort of intelligence — none of us are — and there’s no difference to detect. It just a grave misunderstanding in the industry.”

Nor is it true that for Lucas’ theories to work, bettors must increase their gaming budgets. The way for operators to make more money is by paying out less monies.

Lucas compares this to the movie Office Space, where three workers write a program that shaves fractions of pennies from a company account.

“It’s the same thing,” Lucas says with a laugh. “We’re just not paying out these big jackpots quite as much. No one’s going to notice because for the individual sample, they don’t have a big enough sample size to detect a difference in the population. No individual player will ever notice, but we will notice because we –management – we’re in the long-term aggregate, so we will see that we’re not paying out as much and we will put that money in our pockets. And that’s the game right there.”

But why, if Lucas’ research can be used to increase a casino’s profits, are his efforts rebuffed? He makes an analogy between his work and the rise of analytics in baseball, which was often discredited by old-school managers.

“It’s challenging their existing beliefs and their credibility, and they hate me for it,” Lucas says. “… It literally is cognitive dissonance, that’s exactly what it is.  It’s unsettling. They’ve been in the industry for so long and they thought they knew something, and now there’s new information, new evidence, that challenges those beliefs.”