And Now…A Post About Starcraft (Sort Of)

A while ago, I discovered the blog Illiteracy Has Downsides via a link tweeted by pro Magic player Matt Sperling. Despite being about a type of game  I never play and possess only passing familiarity with (real-time strategy games, primarily Starcraft II), I found a lot of their work to be clearly written and extraordinarily insightful. If you’re a game designer of any type or genre, you’ll find some of IHD’s writing useful.

One article in particular I wanted to focus on is entitled “Why Starcraft II Feels Difficult To Play”. The article primarily discusses the real and perceived skill floor to Starcraft II, but in a tangent, brings up a term called “power mechanics” that shone a light on a key difference between video games and tabletop games: Their learning curves. This article goes into how “power mechanics” smooth out the curve to video games in a way that tabletop games often have difficulty with.

Protoss: Too Smart For Their Own Good

The IHD article defines power mechanics like this:

Let’s compare Zerg and Protoss. Zerg has lots of simple, high priority tasks – injects, spreading creep, moving overlords around, and maintaining constant production. I call the most important of these “power mechanics” – basic tasks that need to be exercised constantly and deliver a measurable, substantial boost to the player each time they’re employed. Injects and spreading creep are examples of what I’d consider “power mechanics”.

Protoss doesn’t have very many power mechanics – things players can do constantly to put themselves in a better position. The game’s design instead calls for the average Protoss player to focus on more complex tasks, such as careful placement of structures, appropriate game sense and scouting of the opponent’s composition, ensuring a unit is on hold position within their simcity, etc.

Note that “mechanics” in real-time strategy games refer to game components that rely on the player’s dexterity and execution.

To broaden this definition, a power mechanic could be any system in a competitive game that relies on mechanical execution, can be improved through practice, but that doesn’t rely on high-level strategic thinking. In fighting games, a power mechanic might be executing a combo; in MOBAs, it might be managing the flow of creeps into your lane.

The main benefit of power mechanics in video games is it gives the player something to improve that produces consistent, visible results. If I practice combos in a fighting game for a week, at the end of that week I will most likely be able to execute that combo better and feel happy about my improvement. Improving my overall strategy and ability to read my opponent is something that is much more difficult and subtler to improve, so a game with no power mechanics is one with a very steep learning curve.

As opposed to video games, where almost all have at least some kind of power mechanic as part of their gameplay, board games essentially have none. This has a lot to do with the real-time nature of most competitive video games; it’s easier to make mechanical execution challenging when you can control the necessary timing of the motion using a computer mediator. Board games are also more accessibility-concerned in that a player not being able to properly manipulate components is seen as unacceptable on the part of the game rather than a sign of the player needing to get good.

While many people, myself included, enjoy not having to repeatedly practice mechanical execution to get better at a game, it does have the downside of making improvement more difficult and less rewarding. This is a bit abstract, so let’s compare a board game and a video game to demonstrate the difference.

Doing Reps in the Lab With Reiner Knizia

The board game is Modern Art, which I chose because it’s relatively freeform, and the actual strategy has to be puzzled out over repeated plays. For those who haven’t played, it’s about buying and selling art whose value changes depending on how many cards from a particular artist have been played in the round.

The video game is Street Fighter V, both because I’ve been watching a lot of Street Fighter tournaments lately and because I used to try to be good at fighting games, so I feel more qualified to discuss the genre than MOBAs or shooter games.

The improvement process in Modern Art primarily consists of learning lessons and applying them to new situations. You’re trying to get as much money as possible and deny your opponents as much money as possible, so many of these lessons have to do with predicting profit margins on different paintings. “Paintings max out at $30 each in the first round, so bidding $31 is guaranteed to lose me money” is a lesson most players learn halfway through their first game; “Try not to end the round” and “there’s 13 paintings on average for each artist in the whole game, so if 10 have shown up in the first three rounds, they can’t come in first in the fourth” might take longer. Regardless, you advance in your level of Modern Art success by learning these big lessons.

Street Fighter V has lessons as well. The broad strategy for most characters is to force your opponent into a corner and hit them with combos until you win. You learn a “neutral” game, a corner game, and ways to escape a bad situation for whichever character you like. However, half of the challenge of Street Fighter is successfully executing these strategies. It’s not just enough to have a theory of how to pressure Urien with Cammy, once you’re put into that situation you have to actually hit buttons with the right timing, complete your combo, and maximize the damage you can get out of it. 

Training your execution is fundamentally different from learning strategy. You can go into training mode and execute your combos over and over again until you start getting them right consistently, then harvest the fruits of your labor as you get these higher-damage combos against other players. While it requires more rote practice than learning strategy, you’re also rewarded quickly and frequently as your combos become more consistently reliable.

To summarize, if you look at a theoretical graph of player improvement for Modern Art, there’s a lot of sharp increases followed by plateaus where your skill remains functionally the same, while Street Fighter‘s graph is a lot smoother of an incline.

Who Cares?

So what can we, as tabletop game designers, learn from looking at power mechanics?

The first lesson is that learning is best digested a little bit at a time. Much of what I’ve written about was achieving mastery, not competence, but even learning the basics of a complex game can be better handled by rewarding the players continually and quickly. For example, Magic Maze is in the unenviable position of having a lot of content and not allowing communication between players, and it handles this by doling out the rules one at a time throughout 15 or so short tutorial games. Most importantly, all of the tutorial games feel fun to play and satisfying to complete, meaning that even as you’re not playing with everything in the game, you’re still having a good time.

The second is to balance rewarding players for discovering new tactical alleys in your game with not punishing people too much for not getting it yet. Of course the person who understands the game better should win, theoretically, but there’s a difference between “I lost but I think I did alright” with “I got absolutely clobbered and I don’t even know what happened.” Variance can help here in a way that’s inappropriate in video games, both to make people at a higher level of strategy have to improvise and to give the less skilled player a chance at victory. Since the learning curve is more punishing for tabletop games in general, make the gameplay less so.

The third is to regularly create satisfying moments in your game that makes your players feel rewarded. Although we can’t replicate the feeling of perfectly executing a power mechanic fully, we can help reach some kind of game journey that doesn’t make the player feel like every decision is fraught with stress. With the exception of extremely tight games like Agricola, it can be helpful to have moments to “breathe” where players collect resources, rally their troops, and so on, so people don’t feel like the game is too oppressive.

Conclusion

The more I critically examine the designs of games that aren’t in a box on my shelf, the more I learn about their differences. Reality TV shows have to make the audience have fun, but not the players. Subjectively judged contests like ice skating need to reward variety and creativity in addition to mechanical execution. And video games can reward players for well-practiced rote behavior in a way that’s impossible in most tabletop games. These contrasts help illustrate the strengths and weaknesses of my chosen medium and allow me to understand how to make the best of both.

The Illusion of Control, Part 2: Chrom Fireemblem Is A Dirty Cheater

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.

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.