In this chapter, we will examine what makes a good rule as opposed to a bad one. We will also examine the different kinds of rules that form a game designer’s palette and that we can look for in analyzing games. Finally, we will examine the relationship between the game rules and the player experience.
One of the few academic papers that achieved wide exposure within the game industry is MDA Framework by LeBlanc (no relationship to me!), Hunicke and Zabek. It probably helps that the authors are experienced game designers. There are two parts of this paper that made it really influential. The first is the Mechanics/Dynamics/Aesthetics (MDA) conceptualization, which offers a way to think about the relationship of rules to player experience, and also the relationship between player and designer. The second part is the “8 kinds of fun” which we will discuss in a later chapter.
LeBlanc et al. define a game in terms of its Mechanics, Dynamics, and Aesthetics:
- Mechanics are a synonym for the “rules” of the game. These are the constraints under which the game operates. How is the game set up? What actions can players take, and what effects do those actions have on the game state? When does the game end, and how is a resolution determined? These are defined by the mechanics.
- Dynamics describe the play of the game when the rules are set in motion. What strategies emerge from the rules? How do players interact with one another?
- Aesthetics (in the MDA sense) do not refer to the visual elements of the game, but rather the player experience of the game: the effect that the dynamics have on the players themselves. Is the game “fun”? Is play frustrating, or boring, or interesting? Is the play emotionally or intellectually engaging?
Before the MDA Framework was written, the terms “mechanics” and “dynamics” were already in common use among designers. The term “aesthetics” in this sense had not, but has gained more use in recent years.
The Process of Design
With the definitions out of the way, why is this important? This is one of the key points of the MDA paper. The game designer only creates the Mechanics directly. The Dynamics emerge from the Mechanics, and the Aesthetics arise out of the Dynamics. The game designer may want to design the player experience, or at least that may be the ultimate goal the designer has in mind… but as designers, we are stuck building the rules of the game and hoping that the desired experience emerges from our rules.
This is why game design is sometimes referred to as a second-order design problem: because we do not define the solution, we define something that creates something else that creates the solution. This is why game design is hard. Or at least, it is one reason. Design is not just a matter of coming up with a “Great Idea” for a game; it is about coming up with a set of rules that will implement that idea, when two-thirds of the final product (the Dynamics and Aesthetics) are not under our direct control.
The Process of Play
Designers start with the Mechanics and follow them as they grow outward into the Aesthetics. You can think of a game as a sphere, with the Mechanics at the core, the Dynamics surrounding them, and the Aesthetics on the surface, each layer growing out of the one inside it. One thing the authors of MDA point out is that this is not how games are experienced from the player’s point of view.
A player sees the surface first – the Aesthetics. They may be aware of the Mechanics and Dynamics, but the thing that really makes an immediate impression and that is most easily understood is the Aesthetics. This is why, even with absolutely no knowledge or training in game design, anyone can play a game and tell you whether or not they are having a good time. They may not be able to articulate why they are having a good time or what makes the game “good” or “bad”… but anyone can tell you right away how a game makes them feel.
If a player spends enough time with a game, they may learn to appreciate the Dynamics of the game and now their experience arises from them. They may realize that they do or don’t like a game because of the specific kinds of interactions they are having with the game and/or the other players. And if a player spends even more time with that game, they may eventually have a strong enough grasp of the Mechanics to see how the Dynamics are emerging from them.
If a game is a sphere that is designed from the inside out, it is played from the outside in. This is one of the key points of MDA. The designer creates the Mechanics and everything flows outward from that. The player experiences the Aesthetics and then their experience flows inward. As designers, we must be aware of both of these ways of interacting with a game. Otherwise, we are liable to create games that are fun for designers but not players.
One Example of MDA in action
In a First-Person Shooter video game, a common mechanic is for players to have “spawn points” – dedicated places on the map where they re-appear after getting killed. Spawn points are a mechanic. This leads to the dynamic where a player may sit next to a spawn point and immediately kill anyone as soon as they respawn. And lastly, the aesthetics would likely be frustration at the prospect of coming back into play only to be killed again immediately.
Suppose you are designing a new FPS and you notice this frustration aesthetic in your game, and you want to fix this so that the game is not as frustrating. You cannot simply change the aesthetics of the game to “make it more fun” – this may be your goal, but it is not something under your direct control. You cannot even change the dynamics of spawn camping directly; you cannot tell the players how to interact with your game, except through the mechanics. So instead, you must change the mechanics of the game – maybe you try making players respawn in random locations rather than designated areas – and then you hope that the desired aesthetics emerge from your mechanics change.
How do you know if your change worked? Playtest, of course!
How do you know what change to make, if the effects of mechanics changes are so unpredictable? We will get into some basic tips and tricks later. For now, the most obvious way is designer intuition. The more you practice, the more you design games, the more you make rules changes and then playtest and see the effects of your changes, the better you will get at making the right changes when you notice problems… and occasionally, even creating the right mechanics in the first place. There are few substitutes for experience… which, incidentally, is why so much of this course involves getting you off your butt and making games :).
Mechanics, Dynamics and Complexity
Generally, adding additional mechanics, new systems, additional game objects, and new ways for objects to interact with one another (or for players to interact with the game) will lead to a greater complexity in the dynamics of the game. For example, compare Chess and Checkers. Chess has six kinds of pieces (instead of two) and a greater number of actions that each piece can take, so it ends up having more strategic depth.
Is more complexity good, or bad? It depends. Tetris is a very simple but still very successful game. Some games are so simple that they are not fun beyond a certain age, like Tic-Tac-Toe. Other games are too complex for their own good, and would be better if their systems were a bit more simplified and streamlined.
Do more complex mechanics always lead to more complex dynamics? No – there are some cases where very simple mechanics create extreme complexity (as is the case with Chess). And there are other cases where the mechanics are extremely complicated, but the dynamics are simple (imagine a modified version of the children’s card game War that did not just involve comparison of numbers, but lookups on complex “combat resolution” charts). The best way to gauge complexity, as you may have guessed, is to play the game.
One kind of dynamic that is often seen in games and deserves special attention is known as the feedback loop. There are two types, positive feedback loops and negative feedback loops. These terms are borrowed from other fields such as control systems and biology, and they mean the same thing in games that they mean elsewhere.
A positive feedback loop can be thought of as a reinforcing relationship. Something happens that causes the same thing to happen again, which causes it to happen yet again, getting stronger in each iteration – like a snowball that starts out small at the top of the hill and gets larger and faster as it rolls and collects more snow.
As an example, there is a relatively obscure shooting game for the NES called The Guardian Legend. Once you beat the game, you got access to a special extra gameplay mode. In this mode, you got rewarded with power-ups at the end of each level based on your score: the higher your score, the more power-ups you got for the next level. This is a positive feedback loop: if you get a high score, it gives you more power-ups, which make it easier to get an even higher score in the next level, which gives you even more power-ups, and so on.
Note that in this case, the reverse is also true. Suppose you get a low score. Then you get fewer power-ups at the end of that level, which makes it harder for you to do well on the next level, which means you will probably get an even lower score, and so on until you are so far behind that it is nearly impossible for you to proceed at all.
The thing that is often confusing to people is that both of these scenarios are positive feedback loops. This seems counterintuitive; the second example seems very “negative,” as the player is doing poorly and getting fewer rewards. It is “positive” in the sense that the effects get stronger in magnitude on each iteration.
There are three properties of positive feedback loops that game designers should be aware of:
- They tend to destabilize the game, as one player gets further and further ahead (or behind).
- They cause the game to end faster.
- The put emphasis on the early game, since the effects of early-game decisions are magnified over time.
Feedback loops usually have two steps (as in my The Guardian Legend example) but they can have more. For example, some Real-Time Strategy games have a positive feedback loop with four steps: players explore the map, which gives them access to more resources, which let them buy better technology, which let them build better units, which let them explore more effectively (which gives them access to more resources… and the cycle repeats). As such, detecting a positive feedback loop is not always easy.
Here are some other examples of positive feedback loops that you might be familiar with:
- Most “4X” games, such as the Civilization and Master of Orion series, are usually built around positive feedback loops. As you grow your civilization, it lets you generate resources faster, which let you grow faster. By the time you begin conflict in earnest with your opponents, one player is usually so far ahead that it is not much of a contest, because the core positive feedback loop driving the game means that someone who got ahead of the curve early on is going to be much farther ahead in the late game.
- Board games that feature building up as their primary mechanic, such as Settlers of Catan. In these games, players use resources to improve their resource production, which gets them more resources.
- The physical sport Rugby has a minor positive feedback loop: when a team scores points, they start with the ball again, which makes it slightly more likely that they will score again. The advantage is thus given to the team who just gained an advantage. This is in contrast to most sports, which give the ball to the opposing team after a successful score.
Negative feedback loops are, predictably, the opposite of positive feedback loops in just about every way. A negative feedback loop is a balancing relationship. When something happens in the game (such as one player gaining an advantage over the others), a negative feedback loop makes it harder for that same thing to happen again. If one player gets in the lead, a negative feedback loop makes it easier for the opponents to catch up (and harder for a winning player to extend their lead).
As an example, consider a “Kart-style” racing game like Mario Kart. In racing games, play is more interesting if the player is in the middle of a pack of cars rather than if they are way out in front or lagging way behind on their own (after all, there is more interaction if your opponents are close by). As a result, the de facto standard in that genre of play is to add a negative feedback loop: as the player gets ahead of the pack, the opponents start cheating, finding better power-ups and getting impossible bursts of speed to help them catch up. This makes it more difficult for the player to maintain or extend a lead. This particular feedback loop is sometimes referred to as “rubber-banding” because the cars behave as if they are connected by rubber bands, pulling the leaders and losers back to the center of the pack.
Likewise, the reverse is true. If the player falls behind, they will find better power-ups and the opponents will slow down to allow the player to catch up. This makes it more difficult for a player who is behind to fall further behind. Again, both of these are examples of negative feedback loops; “negative” refers to the fact that a dynamic becomes weaker with iteration, and has nothing to do with whether it has a positive or negative effect on the player’s standing in the game.
Negative feedback loops also have three important properties:
- They tend to stabilize the game, causing players to tend towards the center of the pack.
- They cause the game to take longer.
- They put emphasis on the late game, since early-game decisions are reduced in their impact over time.
Some examples of negative feedback loops:
- Most physical sports like Football and Basketball, where after your team scores, the ball is given to the opposing team and they are then given a chance to score. This makes it less likely that a single team will keep scoring over and over.
- The board game Starfarers of Catan has a negative feedback loop where every player with less than a certain number of victory points gets a free resource at the start of their turn. Early on, this affects all players and speeds up the early game. Later in the game, as some players get ahead and cross the victory point threshold, the players lagging behind continue to get bonus resources. This makes it easier for the trailing players to catch up.
Use of Feedback Loops
Are feedback loops good or bad? Should we strive to include them, or are they to be avoided? As with most aspects of game design, it depends on the situation. Sometimes, a designer will deliberately add mechanics that cause a feedback loop. Other times, a feedback loop is discovered during play and the designer must decide what (if anything) to do about it.
Positive feedback loops can be quite useful. They end the game quickly when a player starts to emerge as the winner, without having the end game be a long, drawn-out affair. On the other hand, positive feedback loops can be frustrating for players who are trying to catch up to the leader and start feeling like they no longer have a chance.
Negative feedback loops can also be useful, for example to prevent a dominant early strategy and to keep players feeling like they always have a chance to win. On the other hand, they can also be frustrating, as players who do well early on can feel like they are being punished for succeeding, while also feeling like the players who lag behind are seemingly rewarded for doing poorly.
What makes a particular feedback loop “good” or “bad” from a player perspective? This is debatable, but it seems to be largely a matter of player perception of fairness. If it feels like the game is artificially intervening to help a player win when they don’t deserve it, it can be perceived negatively by players. How do you know how players will perceive the game? Playtest, of course.
Eliminating Feedback Loops
Suppose you identify a feedback loop in your game and you want to remove it. How do you do this? There are two ways.
The first is to shut off the feedback loop itself. All feedback loops (positive and negative) have three components:
- A “sensor” that monitors the game state;
- A “comparator” that decides whether to take action based on the value monitored by the sensor;
- An “activator” that modifies the game state when the comparator decides to do so.
For example, in the earlier kart-racing negative feedback loop example, the “sensor” is how far ahead or behind the player is, relative to the rest of the pack; the “comparator” checks to see if the player is farther ahead or behind than a certain threshold value; and the “activator” causes the opposing cars to either speed up or slow down accordingly, if the player is too far ahead or behind. All of these may form a single mechanic (“If the player is more than 300 meters ahead of all opponents, multiply everyone else’s speed by 150%”). In other cases there may be three or more separate mechanics that cause the feedback loop, and changing any one of them will modify the nature of the loop.
This chapter was adapted from Level 5 of Ian Schreiber’s Game Design Concepts course.