FIGURE 13.1 A designer’s view: Aesthetics result from dynamics caused by mechanics.
This suspense is terrible. I hope it will last.
—OSCAR WILDE
Games have an interesting problem. If you ask someone what a book is about, generally the answer comes in one of two forms: plot and theme. The plot in the Harry Potter series is about a wizard confronting an evil power from his past. Lots of events happen: He gets his invitation to Hogwarts, he makes friends, he fights a giant snake, and so on. The theme of Harry Potter is about learning your place in the world and dealing with death. Both of these (plot and theme) are accepted ways to talk about the essence of what a book is. This works with other storytelling media: You can reflect on what a movie is about by talking about its plot and theme. You can describe a play in the same way. But what about games?
Games are fundamentally different. Games that use traditional storytelling forms can be shoehorned into the “plot and theme” method of answering what the game is about, but that is only because those games are primarily linear stories before they are games. For instance, Heavy Rain uses a game veneer to deliver traditional storytelling devices, so it’s easy to reduce the game to plot and theme. So does Mass Effect. But what about Space Invaders? What is it about? What is World of Warcraft about?
For example, everyone experiences World of Warcraft differently. For some, the game is highly focused on meeting and interacting with new people. Some may use it to set up an item-trading business. Some may explore a vast new world. Others may never interact with other people on a meaningful level and may just treat it as a virtual rat-slaying simulator. How can you answer what this game is about if everyone can have such a different exposure to it? In this case, the plot is meaningless—while one player went on tours of exotic vistas, another repeated the same dungeon over and over again for hundreds of hours looking for rare items. Not only are the events different, but any thematic interpretation of those events is also meaningless since it differs so vastly from player to player.
Writers have it easy. They use the elements available to them (words) to create structures of meaning (sentences, paragraphs, allusions, similes, and so on) that allow them to easily answer the “what the story is about” question. What game designers need is a framework that uses the elements available to game designers to evaluate meaning.
This may seem academic and pedantic, but game designers largely design systems. Systems need to be understood holistically in order to be designed intelligently. When you understand what a game is about holistically, it helps inform you about how to go about making the chosen experience happen.
Resident Evil and Go are both games. This is unarguable. But it’s easier to answer “What is Resident Evil about?” than it is to answer “What is Go about?” This is because we fall back to more familiar definitions of meaning based on theme and story. For an abstract game like Go, that does not apply.
Designers and researchers have a difficult time reconciling competing philosophies into a coherent vocabulary of games. What some call “mechanics” can mean something completely different within the context of another theory. This makes discussing design theory often a war of defending definitions, which is unfortunate, because it prevents more interesting discussions of depth and importance from happening. You should attempt to avoid arguments on what the “real” definition of a term is—instead, focus on how the underlying theory can be instrumental to your development.
One of the answers to the question of what a game is about is based on the work of designers Robert Zubek, Robin Hunicke, and Marc LeBlanc.1 They posit that games have three specific elements:
1 Hunicke, R., LeBlanc, M., & Zubek, R. (2004, July). “MDA: A Formal Approach to Game Design and Game Research.” In Proceedings of the AAAI Workshop on Challenges in Game AI (pp. 04-04).
• Mechanics are the elements of the game themselves. These are generally defined as the “rules of the game.” These may be formal rules, such as “A player cannot move his king into check,” or rules about the features of the game, such as “The properties in Monopoly have the names of places in Atlantic City.” From the mechanics alone, someone should be able to reconstruct the game.
• Dynamics are the “runtime behavior(s)” of the game. When the players interact with the rules, what happens? In Chess, you know to sacrifice relatively worthless pawns to capture the powerful opponent’s queen, yet nowhere in the rules does it say that a player should do that. This behavior emerges from the rules.
• Aesthetics are the emotional results generated by the game. When a player says that a game is “fun,” that is a generic, emotional response. Players can often be more specific, using terms such as exhilarating, challenging, frightening, tiring, or eye-opening. These are more specific, emotional responses. LeBlanc lists eight kinds of fun that he sees most often but claims it’s an incomplete taxonomy: sensation, fantasy, narrative, challenge, fellowship, discovery, expression, and submission. For instance, a game such as Farmville may be fun to some because it’s an act of submission to a set of systems. League of Legends might be fun to some because it’s like solving a particularly intense real-time math problem that provides a feeling of accomplishment. To others, it may be fun because it involves playing with friends and the fellowship that comes with team sports. Different features of games generate different aesthetic responses.
Many people have difficulty with the use of the term “aesthetics” in the context of games because it has differing definitions elsewhere. When I say aesthetics in relation to MDA, I mean “play aesthetics,” or the emotional values generated by the game states. What I don’t mean is the art or sound used in the game. Although those can be aesthetically pleasing, that’s a different use of the word: the philosophical study of beauty. Aesthetic is also used sometimes as a noun as a signifier of the look and feel of a game. This is also not the definition I use here. Again, aesthetics here refers to the emotional state generated by the game or, in many cases, the category of fun that the game generates.
Using these three elements and putting them into a series shows their relationship (FIGURE 13.1).
What is interesting about this relationship is that designers experience their games from left to right, whereas players experience them from right to left. Designers create mechanics, which generate dynamics when players interact with them, which then hopefully generate desired emotional responses. Players, however, experience emotional responses from playing the game, and only through further analysis are they able to determine the source in their own behaviors and the rules that cause them to act.
This leads us to one unfortunate end: The only “knob” that designers get to turn is the mechanics knob. All other elements regarding the dynamics and aesthetics are generated from the designer’s choice of mechanics. Designers define what the rules and setup of the game are, but the dynamics and aesthetics are generated by the players in their interactions with those rules. Designers cannot add more “scary” to a horror game. All they can do is add rules that tell the system to place a monster at location X,Y,Z. If X,Y,Z is a corner where the player is particularly vulnerable and this creates a dynamic in which the player can feel particularly frightened, then the designer has met her goal and done her job.
Note
This particular mechanic has been used in so many games that board game designers and enthusiasts often simply call counting only what resource you have the least of Knizia scoring.
In many of Reiner Knizia’s board games, the player must collect all kinds of resources. Knizia wanted this to be an effect that the players pursue, so he wrote the rules of Ingenious (and other games) so that the player only counts—for scoring purposes—the resources of which he has the least. If a player has three orange tiles, one red tile, and one green tile, then the player is incentivized to no longer go after orange tiles because they don’t increase his score. Instead, the player is constantly switching desired tiles to match whatever he has the least of. Once he gets a second green, then he no longer wants green because red is now the least in quantity. This behavior is not written in the rules. Only the rule about the least populous tile being counted is written there. But that rule births a behavior that meets what the designer desires.
Because designers can turn only the mechanics knob, game design cannot be simply coming up with “good ideas” if those ideas are limited to settings, characters, or genre. In order to create those ideas, the designer is required to come up with a complete system of rules that generate desired dynamics that lead to targeted emotional responses. It’s not as easy as saying, “My idea is a zombie stealth game!” The designer needs to come up with a full topology of rules and conditions that explain every input of the system with its output (this is generally what the game design document explains). Any secondarily generated effects need to be elicited from those rules.
It’s important to understand the purpose of a system like MDA. Often, confused students struggle to place their analysis into the three elements. They frequently give me an analysis like, “The game had bugs (mechanics), which caused me to stop playing (dynamics) because it was boring (aesthetic).” Boredom is not an aesthetic just because you do not like the game. That is a bland value judgment. The aesthetics bullet in the previous list contains some of the primary aesthetics that you see in games. “Fun” and “Not Fun” are just far too broad to be useful in analysis. Often “Fun” and “Not Fun” are just synonyms for “I Like” and “I Do Not Like.” That kind of analysis could certainly be true, but it misses the point of using MDA. MDA is a descriptive system, not a normative system. A descriptive system is one that describes an element or process. A normative system assigns value judgments. It advises what a person should do. Comparing the two, descriptive systems tell us what is and normative systems tell us what should be.
The point of MDA is not to explain whether a given game or rule set is “good” or not. That is the job of a normative system. What MDA helps you and other designers do is evaluate how the elements of the game work together to create targeted emotional ends.
Realm of the Mad God (FIGURE 13.2) is a persistent-world, online, shoot-’em-up game. Like many persistent-world games, it has a ton of different mechanics at play. The game is somewhat social, but the burgeoning of the community only happened when the designers added what they considered a fairly benign feature: dropping items. Once players could drop items, they could effectively trade items by bartering: “OK, you drop that sword, and I’ll drop my shield, and we can trade them.” Not only did this create the simple behavior of trading, but other behaviors emerged: A currency was created and even complex trading consortiums were established. All this because of a drop feature. The creators never intended for it to be used for anything besides sloughing off excess inventory.
Note
Habbo Hotel discovered this lesson earlier. In it, there was no trading currency, so players used a particular in-game chair as the standard currency.2
2 Haro. S., (2010). “The Evolution of Habbo Hotel’s Virtual Economy.” Game Developer’s Conference. San Francisco, CA.
Examine this behavior of the players using MDA. A rule was created: You can drop items, and other people can pick them up (FIGURE 13.3). This created a runtime player behavior: You have something I want, and I have something you want; let’s use the drop feature to trade! This led to an aesthetic response of fellowship and challenge among many players, so much so that they started their own trading groups.
Imagine now that you are designing a persistent-world, online game. Your game is lacking in the kinds of community behaviors you want it to have. You want people to feel as if they are part of a larger whole. In short, you want a play aesthetic of fellowship. You just examined one example of a dynamic that would create that aesthetic, but there can be many others. Say you want players to be able to trade. This leads you as the designer to come up with the rules that support that: Players must have items that they value; these items have to be transferrable, and players need to be able to see what items others have available. These mechanics support the desired dynamics that then would support the desired aesthetic. It’s not enough for a designer to say that there should be trading. She must come up with all the supporting mechanics that enable that dynamic.
You probably play Monopoly incorrectly. That’s OK, most people do. Answer these two questions about the game: What do you get when you land on Free Parking? What happens if the player who lands on an unpurchased property doesn’t buy it?
Most people would answer that you get some amount of money for landing on Free Parking, sometimes $500, sometimes a collection of fees paid into the game from various penalties like the Luxury Tax. But that is incorrect. Players actually are not supposed to do anything when landing on Free Parking. Players do not get bonus money; you just get to park there for free. Hence the name.
Additionally, say I land on St. Charles’ Place. It’s unpurchased, so I do not have to pay rent to anyone, but my two opponents own the other two maroon properties (one each), so I have no desire to buy it. Most players would just pass the dice at this point, but that is not how the rules are actually written. What you are supposed to do is then auction the property between all players until it is purchased.
People do not play with these rules for a number of reasons, but I bring it up here to show you the impact of rule changes on dynamics. What is the number one complaint about Monopoly? It just takes too long to finish! What happens when you inject free money into the system? People are happy in the short-term because, hey, free money. But since every player has an equal chance to hit Free Parking, it takes much longer for players to bankrupt because they have this major cushion of money that can be replenished every trip around the board. The game loses any strategic merit it had and becomes more luck-driven.
The same goes for the auctioning rule. People eschew it because it is complicated and seems “unfair” that someone who did not land on the property can claim it. But this rule makes the portion of the game where people are collecting properties much shorter. You get only one chance! It also serves to decrease the amount of time the game takes before players start going bankrupt because it allows for monopolies to be more easily collected on less than three lucky turns around the board.
Here you see the impact of mechanical changes. Just two rules that seem to be innocuous can lead to huge dynamic and aesthetic changes. Who would not take free money? And that auctioning rule seems complicated, right? However, get rid of them and the game loses any strategic tension. The play aesthetic goes right out the window, and the game becomes only marginally more interesting than Candy Land.
One of the great documented examples of a use for looking at things through the lens of MDA comes from the development of a total commercial failure: A game that would support a “multiplayer online virtual environment.” Nowadays, we don’t find that feature particularly interesting, but this game was made in 1985 for a system that only had 64 kilobytes of memory. The game was named Habitat (FIGURE 13.4) and was being developed by LucasArts. Here’s a quote from the developers:
The first goal-directed event planned for Habitat was a rather involved treasure hunt called the “D’nalsi Island Adventure.” It took us hours to design, weeks to build (including a 100-region island), and days to coordinate the actors involved. It was designed much like the puzzles in an adventure game. We thought it would occupy our players for days. In fact, the puzzle was solved in about 8 hours by a person who had figured out the critical clue in the first 15 minutes. Many of the players hadn’t even had a chance to get into the game. The result was that one person had a wonderful experience, dozens of others were left bewildered, and a huge investment in design and set-up time had been consumed in an eyeblink. We expected that there would be a wide range of “adventuring” skills in the Habitat audience. What wasn’t so obvious until afterward was that this meant that most people didn’t have a very good time, if for no other reason than that they never really got to participate. It would clearly be foolish and impractical for us to do things like this on a regular basis.
Note
The development lessons were given in the form of a paper at a conference known as “The First International Conference on Cyberspace.” Is there a more 1990s conference name than that?
Massive multiplayer online (MMO) designers continued to make the mistake of ignoring multiplayer dynamics for the next 20+ years. Since designers can only set up mechanics and watch how the dynamics play out, they must understand all the mechanics and dynamics that lead to their particular aesthetic choice. In Habitat’s case, they were looking for the same kind of aesthetic as in a modern (at the time) adventure game—the satisfaction and challenge in solving a puzzle. But Habitat did not have the same mechanics or dynamics of a single-player adventure game. It had a rich community that shared everything! How could it possibly have the same dynamics? When a player played Zork, it did not matter if someone else had solved the puzzle before. In Habitat, it did. That was revolutionary at the time. Habitat’s designers made a great discovery in making these mistakes that is sound advice even today:
Again and again we found that activities based on often unconscious assumptions about player behavior had completely unexpected outcomes (when they were not simply outright failures). It was clear that we were not in control. The more people we involved in something, the less in control we were. We could influence things, we could set up interesting situations, we could provide opportunities for things to happen, but we could not predict nor dictate the outcome. Social engineering is, at best, an inexact science, even in proto-cyberspaces. Or, as some wag once said, “in the most carefully constructed experiment under the most carefully controlled conditions, the organism will do whatever it damn well pleases.”
Designers can affect the mechanics, but after that, everything is up to the individual player. The impact of game dynamics is unearthed, especially vividly, in the context of making multiuser communities, but it’s just as true for a self-contained single-player adventure.
Now, how do we use that today? You must look at your mechanics and try to think one step ahead of the player. Given all the tools available to the player, how do you predict what the player dynamics will be? That is the essential question at the heart of designing game mechanics. One of the modern ways that you determine this is by playtesting and observing the results. I discuss this in Chapter 7. What’s important is that you take the time when designing to determine the boundaries of what kinds of behaviors your game will allow and what play aesthetics those dynamics will generate.
Its main actions don’t involve acting at all, but waiting. Yet that waiting contains information essential to play the game well.
—IAN BOGOST, A SLOW YEAR
Dynamics are myriad. However, a few dynamics tend to come up with regularity that are worth mentioning.
If a player can gain more by doing nothing than by doing something, then the player is incentivized to do nothing at all. This is sometimes known as turtling. This can be a dangerous dynamic for a game because it incentivizes players to not interact with the game’s elements and to not move the game forward to its conclusion.
Turtling often occurs in game scenarios where there is a cost or risk to attack but not to defend. For instance, in a real-time strategy game, each player has a base with some amount of attack and health that can repel small attacks. Players can either send their units over to attack or make more units. The first person to break the detente and attack either defeats the base and wins the game or loses units with respect to the defensive player. The defensive player now has a unit advantage and can thus repel any attack from the weaker opponent. He can just sit back and build units until he has enough to overwhelm the opposition.
In games with three or more players, turtling can be a dangerous dynamic. Say that each of the three players has 100 units. If Player 1 attacks Player 2 and both risk losing resources, Player 3 can sit back, watch the carnage, and preserve his power. Player 1 wins the battle, but sustains losses. Now Player 1 has 50 units, Player 2 has 20 units, but Player 3 still has his 100 units. When the battle is over, if both participating players are weaker as a result, then the correct strategy would have been to do nothing. Player 3 has an advantage over Players 1 and 2 because he did nothing.
If players realize that the best strategy is to do nothing, then they will sit in stalemate forever. This is actually a game theoretic reason why countries in the real world do not go to war, especially in cases where they have multiple enemies. However, in many non-real-world games, war is preferable because it is exciting and generates desired aesthetic responses.
A design fix for turtling is to make it advantageous to act. In this battle game example, perhaps implementing an upkeep cost per unit and a glory bonus for winning battles could fix the stalemate. Players would then want to go to war to avoid paying high costs to have units sit around for no potential gain, instead risking the units for the glory bonus.
Camping is another form of turtling where a player’s position causes a positive feedback loop. For instance, some first-person shooters have tactically superior spots on the map where a player with a long-range weapon can sit and wait for opponents to come out. Since the position is tactically superior, the player has an advantage where staying still provides benefits over moving. If opponents cannot force the player to move, that player will engage in a positive feedback loop where her superior position will become permanent.
If players want to win the game, then the players’ decisions should have a determining factor on who wins the game; otherwise, the game is blind luck. One dynamic that works against the player’s decisions is the determining factor in victory known as kingmaking. Kingmaking happens when a player who has no chance to win uses his actions to determine which of the other players will win. This is problematic because the game is not decided by the winning player’s decisions or fortune, but by another player’s whims.
Methods of fixing this are to build into the game’s mechanics ways of isolating potential kingmakers:
• Ensure that actions do not have enough power to determine the winner on a single (or on a few) move(s).
• Ensure that players do not know who is in a position to win, thereby eliminating the possibility of colluding to choose a winner. Games with hidden victory points and hidden roles do this well.
• Isolate the players enough so that their actions cannot affect each other. Some European-style tabletop games take this to an extreme and are derided for being “multiplayer solitaire.”
• Add a random aspect to the game, such as dice rolls or card draws, to determine game events that can disrupt kingmaking plans. As always, be careful when adding randomness to ensure it does not disrupt meaningful decision-making.
Button mashing is seen as a derogatory term in fighting game circles. A button-mashing player plays almost randomly, smashing buttons in frenzied attack. If the game is not designed well, a button-mashing player can have success over a skilled and thoughtful player. If someone randomly pressing buttons can win, then there is no actual decision-making in the game. It’s reduced to a game of War, and whoever wins the random number generator wins the game.
The key to avoiding button mashing is to give every move a reasonable risk so that playing randomly is discouraged. I’ll discuss the game theory behind this more thoroughly in Chapter 19.
Consider two versions of Rock, Paper, Scissors. In the first version (TABLE 13.1), the equilibrium is for each player to play perfectly randomly with each strategy being chosen one-third of the time. This strategy gives the player the maximum expected value of 0. This encourages button mashing since every button is as good as any other.
However, if you change the risks involved to make the game more interesting, the strategy changes. Let’s make scissors a risky move. If you throw scissors and hit, you get a big reward. If you throw scissors and miss, you get a huge penalty. If you look at rock and paper in isolation, you are tempted toward paper, which tempts your opponent toward scissors, as shown in TABLE 13.2.
One of the optimal strategies is to play rock with a probability of around 0.59, paper with a probability of around 0.35, and scissors with a probability of 0.06. If that player played against a player who was button mashing by playing all three with equal probability, the player with the more thoughtful strategy would have an expected lead of 0.52 points per game.
This makes sense. If you know a player is going to overplay the risky scissors strategy, then you can sit back and enjoy collecting easy bonuses with more throws of rock. This kind of balance upends the likelihood of button mashing succeeding and directs players to more nuanced strategies. Note also that it employs the risk-reward techniques discussed in Chapter 10.
Grinding is repeated play without meaningful decisions. When players grind, they trade time or effort for value such as in-game currency or experience points. Players are playing for those extrinsic motivators instead of for the intrinsic motivators of fun or satisfaction. With this dynamic, players are not directing themselves toward what provides them the most enjoyment.
Grinding happens often because of lack of content. It’s easy for a developer to spend most of a development cycle getting two battles to be fun. Knowing that they cannot release with only two battles and still charge a sustainable price, they then require the player to do those same two battles 20 times each. This makes the game the length of a game with 40 battles, but once the player has mastered the two battles, she must still complete the actions many additional times. In these additional battles, the players are just repeating meaningful decisions that they made in the past; they do nothing to formulate new meaningful decisions. Thus, they just follow a recipe.
It’s generally recommended to avoid grinding, if possible, in lieu of content that creates original, meaningful decision-making. This, of course, has development costs and is not always wholly possible. Understanding the extent to which players are not making meaningful decisions makes for an unbiased view of the efficacy of the decision-making in the game.
Grinding is not always bad. Sometimes the anticipation of a variable reward is enough to sustain meaningful play, but this is a dangerous element to bank upon. See Chapter 23 for more on this topic.
Press-your-luck is often cited as a mechanic, because the mechanisms that create it are explicitly called out in the rules of games that use it. However, the behaviors that are created from those rules are what make press-your-luck so interesting.
Can’t Stop is a classic game by Sid Sackson that is one of the best examples of the press-your-luck dynamic. In it, players attempt to get three of their pieces to the top of an octagonal board (FIGURE 13.5). Players do this by rolling four six-sided dice and grouping them into two pairs of two. For instance, a player who rolls a 1, 3, 4, and 6 could group this into 4 and 10, 5 and 9, or 7 and 7. Whichever grouping the player chooses is in which columns his pawns move up. For instance, if the aforementioned roll was grouped into a 4 and a 10, the player would move his pawns up in the 4 and 10 columns. Players can advance up to three columns per turn. However, if they roll and are unable to advance a column because they have already advanced up three columns or the column has already been completed, then they lose all their progress for the turn, and their turn is over.
IMAGE OF CAN’T STOP BY SID SACKSON. VERSION PICTURED IS © 2011 GRYPHON GAMES.
FIGURE 13.5 Can’t Stop.
This dynamic forces players to decide on safely moving only a step or two at a time or attempt to continue rolling to move farther and farther. The farther the player moves in a turn, the more he risks by continuing to roll. Press-your-luck dynamics often focus on regret. Players who push unsuccessfully regret their loss. Players who take the conservative route often regret the possibilities of untaken paths.
This kind of dynamic between pressing for a higher reward or sticking with a safe payoff plays out in many kinds of games. One of the most visible press-your-luck dynamics occurs in football. In it, teams get four downs to legally advance the ball 10 yards. If they do so, they get four new downs. On the last (fourth) down, teams are faced with a decision: They can punt the ball away, which gives away their chance to score but gives the opponent a disadvantage in field position, or they can try for that first down. If they make the distance, then they have successfully pressed their luck and are rewarded with a new set of downs. If they fail, their opponent is rewarded with great field position.
Press-your-luck is generally a positive dynamic to encounter because it means that the mechanics were crafted to allow for interesting trade-offs.
• To answer what a game is about, you must look beyond the surface details of theme and plot. Many games have no theme or plot at all, so those elements must not be sufficient to explain what a game is about.
• MDA is one theoretical toolset designers can use to understand a game. In it, a game’s mechanics lead to runtime player behaviors known as dynamics, which in turn result in player emotions known as aesthetics.
• Designers can directly affect only a game’s mechanics when examining a game through the MDA interpretation. To affect other elements, the designer must create mechanics that generate the desired dynamics or aesthetics.
• Examining case studies of dynamic situations can help designers understand both the aesthetics generated by said dynamics but also the mechanics from which those dynamics emerge.
• Dynamics live in support of aesthetics. Dynamics are generally neither good nor bad, except if they support a desired aesthetic response.
