When people spend enough time in a casino, they settle on a small number of favorite games. Even table players eventually choose a game they head for first. People who visit frequently visit several casinos may even favor different games depending on each casino.
It feels as though the games pay differently in different locations. My mother complained that her favorite Double Diamond slots didn’t work at a new casino the way they did in her local casino. She went back to playing the machines she enjoyed.
Many gamblers are superstitious. If not superstitious, then they practice rituals to help them relax and “get in the groove.” People form habits, and one habit is how a player chooses the next game to play.
A new report from the University of Nevada-Las Vegas explores gamblers’ beliefs about their abilities to pick “winning” games. Players may not be happy with the findings.
Anthony Lucas is a former gaming industry operations analyst. He now teaches at the UNLV College of Hospitality. He knows gaming from both sides of the equation.
Casinos have long believed that some players (not all) can find slot machines that pay better. Some vendors publish the theoretical RTF in their game info screens.
Casinos make business decisions on the belief that players know how to gamble. Their decisions include where to put the games and how to adjust their payouts (or pars). Game pars – the percentage of wagers games are expected to retain over time – represent the house edge.
Theoretical payouts are usually higher than actual payouts. Casino financial reports on file with state governments reveal players lose more playing table games than RTP predicts. Because slot games are deemed more profitable, it follows players are losing more there too.
By determining how accurate player instincts are, casino operators can adjust their payouts. The ratio of wins to losses may be higher than the market is willing to bear. If so, casinos stand to improve their per-player profits.
Professor Lucas and a colleague, Katherine Spide of San Diego State University, set out to see what effect – if any – player migrations from game to game had. Tradition says that players test games and find the ones that pay best.
The study involved casinos in several states, Mexico, and Australia. Operators provided data to the researchers about how players interacted with designated games. The research has spanned several years.
The latest report follows player activity on “two pairs of reel slot games at a ‘locals’ casino in Sydney, Australia.”
The study lasted for nine months. Game pars varied from just under 8% to nearly 15%. These variations are normal and don’t suggest the casinos reset the games. In short periods of normal play, casino games may vary from expected ratios.
Lucas and Spide calculated the daily T-win for two sets of games by multiplying their “coin in” (wagers made) by the games’ par percentages. Their hypothesis was that if players noticed a higher par on one game, they would spend more time on the other game.
They tracked use data for “regular” players on the assumption that people familiar with the machines would be more likely to favor a game that paid better.
Had players detected better chances of winning on one machine over another they should – Lucas’ hypothesized – spend more time playing the better-paying game.
In other words, the regular players were not spending more time than average on the games with the lower pars. They also found this to be true in similar casinos in Mexico in a concurrent study.
These findings remain consistent with the team’s previous research extending back several years.
In the full abstract for the first paper on the university’s Website, Impacts of Increased House Advantages on Reel Slots, the team analyzes 274 daily observations. The abstract does not say how many total players sat down at either game.
Nor does the abstract mention crowd conditions at the casino. They only used time-series regression to determine if players were migrating from the high par game to the low par game.
Anyone who has spent time in a busy “local” casino knows the crowd is smaller. The regulars often have favorite machines. Those machines may be unavailable, or the regular players may grow bored with them.
With gaming operations experience, Professor Lucas must be aware of player habits.
How did the team address these concerns?
I’d also like to know how the games they used for research were chosen. The press release says they analyzed activity for “Tokyo Rose” and “Dragon’s Fortune X.”
Is this the original “Tokyo Rose?”
That’s an old game.
It’s easy to generalize about who plays the slots in a casino catering to local customers. Setting aside personal assumptions about regular customers at local venues, these crowds are different from the big casino crowds.
The researchers may have decided to look at data for the same players. Their hypothesis assumes that – given enough time – an aware player should see which machine pays better.
On a personal level, I know if they had tracked my mother, they would have a lot of data for one small set of games. She is set in her choices. She tries new games each year but always returns to her favorites.
Contrast with that how my wife and I move around the floor when we visit Vegas. We want to experience all the games if we can. Some games have lines during peak crowd periods.
It seems the researchers were not interested in the Vegas-style crowd.
In the age of growing public awareness of how much data businesses collect on us, the gambling world is surprisingly calm. Major venues now deploy facial recognition technology and compile profiles of players.
They know who we are and which games we like to play.
But the crowd plays on.
Local casinos feature fewer games and cater to fewer clients. They have access to many of the same gaming applications the big casinos do. They may not yet have facial recognition systems, but they will get there.
The casino could provide them with club member numbers and no other personally-identifying information. If that is all the team needs, then any of us could be counted in future studies anywhere.
Professor Lucas lays out the benefit of his work for the casino industry. Operators shouldn’t hold back on setting pars for fear the players will avoid the worst games. It’s a sellers’ market.
On some level, gamblers have always known this.
What casino specializes in slot games that pay more to players on average than they bet?
You can’t run a business like that.
On the other hand, casinos know that players share their experiences online. Tourists use sites like TripAdvisor to ask which the best casinos are to play at.
And other travelers answer them.
On the Internet, it’s a reviewers’ world. To stay competitive, the casinos must find a sweet par range and stay there. Local casinos have an advantage over the larger casinos.
The only players who should care about this research are also the ones least likely to. They are the regular local gamblers who keep the small casinos in business.
Where else are they going to play?
Unless a town has a good selection of gaming venues for locals, the players are trapped.
It’s easy to see how this research compares to similar studies about cinema ticket prices. If your town only has two cinemas, what prices are you willing to pay to watch movies and eat popcorn? Local health laws restrict what you can take into the venue.
Cinema operators experiment with lowering ticket prices. They make their money on concessions.
When I was in college, my friends and I hung out at a local cinema. One of our girlfriends worked there. The manager allowed us to watch any movie for free as long as we bought a snack and drink.
Gaming club memberships provide a similar discount experience to players. They redeem their points at the sandwich shop for “free” food. And then they go back to playing slot games.
Sounds like a “win/win” scenario for the local casinos already.
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