Welcome back to my 2-part article series about various methods to disguise the variance in your game to give your players an illusion of control. You can read part 1 here.
There’s a very understandable revulsion to “being manipulated” that makes this subject a little strange to write about. After all, we can’t pop open the news without finding another grim headline about how our personalities and behaviors are largely the product of market forces that have been influencing us since we were children. The idea that a game, which we often play to reclaim a sense of control, is also “cheating” in a sense, can feel slimy and disheartening.
The key is that a well-designed game engages in manipulative behavior purely for the player’s benefit. A “fair” experience that doesn’t lie to or manipulate the player can often feel stark or brutally economical. This is especially true in video games, where nearly every game cheats, usually in the player’s favor, in order to better fit the model provided by human cognitive bias. The random number generator used by the Fire Emblem franchise is a nice, simple example: By using the mean of two RNG numbers to determine hit chances, it makes a 75% chance to hit “feel” more like how we think a 75% chance to hit should feel.
Just like how media is a safe way for audiences to experience emotions like fear and distrust that would be dangerous in the real world, it’s also a good space for creators to try psychological tricks that would be unethical outside of the game context. Of course, this applies only to techniques used within the “magic circle” of the game environment; manipulating your players into, for example, constantly paying for microtransactions in a mobile game falls back under the umbrella of questionable ethics.
Anyway, let’s look at some more techniques that I didn’t cover last time.
Chess: Disguise Variance Through Many Non-Variant Moves
Despite being a big-brain game for smart people and bad guys in action movies, chess and games like it have a fair amount of variance. They must have, because otherwise every single chess game between the same two high-skill players would turn out the same. However, chess has no “luck” per se beyond determining which player goes first; players are in total control of every piece at all time.
The trick is that players create variance through minute decisions that eventually compound into unknown game states. The average game of chess between high-level players is about 40 moves long; if you consider, for example, how moving a bishop two squares or three squares completely changes what pieces it threatens, you can see how each small move eventually creates a relatively novel gamespace. “Perfect information” Hobby games like Terra Mystica that use this form of variance go even further, with hundreds of individual decisions adding up to a game state that’s different even with identical setups, character selections, and players.
In a way, this method of creating variance isn’t an “illusion” of control – it is control. But it falls under the banner of this article series because it sneakily adds variance into a state where everyone involved is being perfectly rational. Instead of dice or a deck of cards, these games use the human mind as the ultimate random number generator.
Ra: Trick Players Into Logical Fallacies Through Weak Evidence
Humans are subject to several common cognitive biases. Many, many articles have been written about them, partially because they’re fun to write and partially because trying to rid yourself of them is a good step on the road to self-improvement.
But as game designers, we’re not out to force our players to change how they think; it’s better to go along with human nature, which includes human cognitive biases, and provide a game environment that works the way it “should.”
As an example, let’s look at the classic Reiner Knizia auction game Ra. In Ra, players draw tiles out of a bag and place them up for auction. Any tile taken out of the bag never goes back in; it’s either discarded at the end of the round or kept in a player’s tableau for end-game scoring.
This allows players to predict the outcome of future rounds based on previous rounds; for example, if you haven’t seen a lot of flood tiles, you might be more bullish on Nile tiles (which need flood tiles to score). If a lot of Ra tiles, which immediately start the auction, are drawn, you can be greedier and draw more tiles in hopes that you can bid on a better lot. These tiny edges might add up to an eventual win at the end of the game!
There is one problem, however: Everything in the last paragraph is a lie! There are so many tiles in the bag that the distribution isn’t substantially affected even if weird draws occur. To use the flood tile as an example: The bag has 180 tiles in total and 12 flood tiles. Let’s say you draw half (6) of them in the first round. If you drew 40 tiles total that round, in the first draw of the next round you’ll have a 6 in 140 chance to get a flood. That’s about 4 percent. The odds of drawing a flood tile as the first tile in the first round is 12 in 180, about 6 percent. So even though you drew half the flood tiles, the odds of getting more is changed only by an imperceptible amount that doesn’t really affect your strategy.
(Yes, I know I basically threw out a number of total tiles drawn at random, but 40 is my rough estimate for the number of tiles drawn in an average round. I’m more trying to illustrate my larger example.)
However, the odds have changed to a small degree, and enough of a degree to trick players into the gambler’s fallacy – even players who would normally know better. If you bid low on Nile tiles in a later round because you saw so many floods, you feel like you won because you knew there weren’t many left (ie. you weren’t due for one), even though the real reason was that the bag pulls worked the way you thought they’d work. Even better, if you do end up pulling more flood tiles, you can just blame the whims of fate for creating such a freak accident.
And you know what? This rules, because it works the way your mind wants it to work. Instead of fighting our brains’ incorrect perceptions all the time, we get to send them to Cognitive Bias Fantasy Camp, where we really were due for that flood tile. By using this method, games can have their cake and eat it too: We get variance, but we also get enough reason to believe that we can predict what happens next that we don’t feel like we lost because of luck.
Conclusion
As a designer, your responsibility is to make a game environment that’s fun for the player without being exploitative. Your responsibility isn’t to make a game environment where everything is as it seems. Just like how audiences accept that a stage magician is tricking them somehow, they’ll accept the same from your game, as long as you entertain them. I hope these tricks to disguising variance help you do so.