The quality of your game is directly related to the number of iterations you have time to make.

The adage is that game development is an iterative process. We know we should be tweaking and tuning our game until it feels and runs great. To make it the best it can be; greater than the sum of its parts. Early on, to make sure that the features we work on are worth pursuing.

An iteration can be as small as an incremented variable or as big as a complete reset of your entire game project. What iterations have in common is that the only way to get more of them is to teach yourselves the right mindset and to continuously remove anything that costs time.

For the past few years, this has been at the top of my mind: how to maximise iteration. At the very highest level, you need to remove obstacles, clicks, and tools. The fewer things a developer needs to know and do per iteration, the better.

• Remove obstacles. Make the process of iteration as fast as possible, by removing gatekeepers and bottlenecks. Maybe you shouldn’t go through the full approval process for a quality of life improvement, maybe your playtesters should get three separate sets of things to test instead of just one, and maybe a developer can prioritise their own tasks rather than sitting in hours-long meetings or being micromanaged.
• Remove clicks. I once heard the suggestion that you lose 50% of viewers with every required interaction on a website. More clicks will invite more pain points, more potential human errors, and will also lead to fewer iterations. Just imagine (or remember) not having box selection in a node tool vs having it.
• Remove tools. You need special skills, licenses, installation time, and more, the more tools you require. Everything in your pipeline that can be either bundled into something else or removed entirely via devops automation should be considered. Not least of all because tools development is itself a deep rabbit hole.

Those three are what this is all about. I’ve come up with five areas where you need to optimise iteration, that I’ve obsessively built into my own pipelines. These five are what the rest of this post elaborates on:

• Authoring objects and data.
• Transitioning objects between states.
• Tweaking and rebalancing data.
• Testing and comparing iterations.
• Updating the game for testing and distribution.

Authoring

Iterating on object and state authoring means creating new objects and states and connecting them to data. A character that can roam, shoot, and take cover, and has MoveSpeed, TurnSpeed, and Morale, perhaps.

This is one of those things where many developers will get used to how their first engine does things and forever see it as the norm. But most tools for object authoring are actually quite terrible (in my opinion), and are also highly unlikely to match your specific needs. They are far more likely to present you with hoops to jump through and prevent you from achieving fast iteration.

It’s not unusual for getting a new object into a game to take hours and involve multiple people. Particularly if the game’s pipeline has grown organically over several years of production. Where you only had to add a single collision capsule at first, maybe you must now add a full ragdoll, two different sets of hit capsules, IK targets, and a bunch of other things before the new asset works as intended. Some of which has to be created manually. Forget one step, and your game may crash or exhibit weird results.

This is a big threat to iteration. Maybe the biggest. So if you can, you should make your own tools for object authoring that are perfectly suited to your needs, require as few steps as possible, and waste as little time as possible. Or use a tool that’s specifically made for exactly the thing you need, if you can find it.

Objects

I tend to think of objects in systemic design as Characters, Props, and Devices. This is not in any way strict, it’s only what my favorite designs tend to need. If you are working on a grand strategy game, a puzzle game, or something else, the nature of your objects may vary.

The key to object authoring is variation. A lamp is not the same thing as a crate or a human, but they should be able to interact in interesting ways. To make them interact, you need to be able to vary them easily and then hand off responsibility to the game’s systems in a predictable way.

Something that can’t be stressed enough is to always set working defaults for all of your objects. Make sure that objects work out of the box so iteration can begin immediately. Few things waste more time than “oops, forgot the flag that did the thing.”

Object-oriented

The most intuitive way to represent objects is to use objects, unsurprisingly. A Character can be expected to do certain things and a Door will do other things. Enemy and Player can now inherit from Character and they may make use of a Gun or a Broom depending on the kind of game you’re making.

With this setup, authoring objects is no harder than inheriting from the right class and then tweaking the numbers. This is how Unreal Engine is used by many teams.

But this gets cumbersome if you want a character that can fly or to utilise the dialogue system in a character but for something that cannot move. Or maybe the spline following that characters have, but now for a train car.

Authoring with object-oriented systems seems intuitive but doesn’t handle exceptions well. Everything now needs to be a character if it wants to access certain things, and designers will have to learn the intricacies of all the objects in the game before they can truly begin iterating.

• For object-oriented authoring: clearly visualise what an object can (and can’t) do based on its inheritance; don’t hide logic deep into a dropdown hierarchy.

Component-based

If you want your object to collide with things in a physics simulation, you add a Collider. If you want it to move on a flow field, you add FlowFieldMove. The sum of an object’s components dictates its behavior.

This may use many different types of component setups, but the two most common are GameObject/Component (GO/C) and Entity Component System (ECS). Both Unreal and Unity uses the first, but in very different ways. Both Unreal and Unity also provide ways to use the second, but in ways that are mostly incompatible with the first.

Conceptually, component-based object authoring is great. In practice, it tends to be a deep rabbit hole of exceptions and flawed component combinations that have grown organically through an engine’s lifetime.

• For component-based authoring: make non-destructive tools with opt-in as the default rather than opt-out. Provide good error messaging for when requirements are not met.

Data-driven

Most game engines today are data-driven at some level. You plug data in, it gets compiled into an engine-friendly format, and voila: the engine knows what to do. The data is picked up by a renderer, physics engine, or something else, and things simply happen just the way they are supposed to because the data is clear enough to just chug along. Like feeding coal into a steam engine.

With a data-driven approach, you will usually be collecting all that data and bundling it up using authoring tools. Bring in the mesh asset, animate it using animation assets, play some sound assets on cue, etc. The data itself will drive the process. For example in a “target-based” setup, where one piece of data activates another which activates a third, etc., until the game level or other logic has run its course.

• For data-driven authoring: provide clear debug information and visual representations for where data is coming from, when, and what it allows. Make it clear what data is expected where, so no steps are missed.

Transitioning

You need ways to define how something goes from Alive to Dead, or when something should be Idle instead of Moving.

This layer of authoring and iteration is very rarely straightforward, and parts of it are almost always deep down in the code for your game. This is bad. So let’s discuss how to make it not bad, and how to open up your game for more direct rules authoring through state transitions.

The State in your State-Space

If my use of the word “state” in this post gets confusing, you can look into the state-space prototyping post to see what I mean. This is not standard jargon used by all game developers, but it is a key part in my own framework.

A good state authoring tool allows you to list which states an object can be in, where it can collect changes from, and how it behaves in relation to other objects and their state. Just to be clear: this doesn’t have to be complex at all. It can be enough to list the actions an entity can use and then leave it to other systems to actually select actions.

• Make it easy to list states and transitions per object.

Permissions and Restrictions

Take a look at the An Object-Rich World post if you are curious about other models for working with permissions and restrictions.

The most important element of permissions and restrictions is predictability. There are many cases where our games become interconnected in ways that are not immediately visible. For example, when you say that a character’s ability to Move has been restricted due to a state, you may have to manually add this to multiple places. Perhaps the sound, animation, and head-bobbing system also need to be paused separately. This is extremely bad, because it means both that you will get unpredictable results and that you will often have to revisit the same changes.

• Provide state transition information with data reporting, so that you can keep track of all the whens and whys.
• Make states have meaning; if a state says that an object cannot move, this should be definitive.

Specific or Generic

A specific state is only relevant for a particular object. A generic state can be used by any object sharing the same characteristics. Think of the idea of spotting something, for example. A sensor picking up that an object can be seen.

If a player is going to spot something, this needs to be specific, since the player’s avatar, unlike a NPC avatar, will generally have a camera attached to it. So to check if the player spots something, we can use the camera’s viewport to determine if the thing is on-screen or not.

A generic version of the same thing could instead use the avatar’s forward vector, an arbitrary angle, and perhaps a linecast, to determine if the object can be seen. This could be used by any avatar, player or otherwise, and would probably be accurate enough if your game doesn’t need more granularity.

• Differentiate between Specific and Generic states, so that you will never accidentally add state to an object that won’t work.

Exclusive, Inclusive, or Parallell

An exclusive state is the only state that can be run at a given time, whereas an inclusive state also allows other state to run alongside it. Parallell states are made to run at the same time as each other and may therefore not poke at the same data, or you could get unpredictable results.

• Set clear guardrails between Exclusive, Inclusive, and Parallell states. Plan what you need each state to be able to do and where to get its data.

Conditions

A state is conditional if it only activates based on preset conditions. It’s your if-then-else setup. Conditionals will often need considerable tweaking, and if you’re not careful in how you build such systems, they can turn into a tangled mess. Just like nested ifs.

Common ways to handle conditional states are predicate functions, tags, flags, and many of the other things brought up in the A State-Rich Simulation post. Preferably, setting or changing conditionals should be just a click or two, and it should respect the type of data separation mentioned earlier.

When a game has multiple dynamic sources for conditions, it quickly gets complicated. For this reason, your tools should provide debug settings for visualising where conditions are coming from, and you can also log everything that gets triggered by certain conditions during a session.

• Visualise which conditions apply at a given moment and why.
• Show when conditions are unavailable and why.
• Log transition changes and which conditions made them change.

Injected

A state is injected when it’s pushed into an object. This can follow any number of systemic effects, from straightup addition to slightly more granular propagation.

Common points in a game simulation for state to get injected are collision events, spawning or destruction, proximity, spotting, and various forms of scripted messaging. This means that having a solid system for defining such injections is a great starting point for how transitions will work in your game.

If you have the concept of a Room, for example, this Room may keep track of what’s inside of it and then propagate that knowledge to anyone visiting the room. Objects would then inject their presence into the room, while the room would inject relevant state into the objects in turn.

• Show when, how, and from where a state injection occurs.

Explicit or Dynamic

An explicit conditional state is something like the Idle state pushing a Move state onto an internal stack because move vector magnitude is higher than zero. These are the only circumstances where Move will ever happen, making it an explicit transition.

A dynamic state would be something like a gunshot killing you by injecting the Dead state. This is a dynamic transition because it can happen at any time, and beyond any restrictions on the injection itself (ammo, aiming, etc.), you won’t be defining anything in advance, and you’re not really waiting for it to happen. It happens when it happens, or it may not happen at all.

• Make it clear which explicit states are running at any given time.
• When dynamic state is triggered, make all of its relevant overrides predictable and singular: it should always be enough to turn something on or off once.

Timed

A state is timed if it remains active for a limited time. It can also loop over a given duration and either bounce back (i.e., from 0 to 1 back to 0) or it can reset and repeat. The current value of the timed state is often referred to simply as T and should be a normalized (0-1) floating point number.

This type of state is extremely handy, and you will want to tweak how the T value output gets handled in as many varied ways as possible. You want to be able to use curves, easing functions, and all thinkable different kinds of interpolation.

Timed state can be used to achieve anything from a Thief-style AI sense of “smell,” to a menu blend, to an animation system, to reward pizzazz. It’s the perfect type of state for an interstitial and is where you will be able to do much of your polish.

• Provide visualisations of start and end positions for timed states.
• Allow developers to scroll timed states manually to preview them.

Interstitial

A state is interstitial when it’s added between other states without affecting them beyond the delay this may cause. Screenfades, stop frames, and sound triggers, are some examples of this.

• Allow states to resume after interruption, so that you can use interstitials in a non-destructive way.

Tweaking

Objects and states will be defining the game at its highest level. But you will also want to change the rat catcher’s catching range from 2.3 to 2.5 and maybe add an additional key to a curve to make a fade-in smoother.

It’s been mentioned before, but may be worth repeating: you should separate data from objects from the very beginning of your project. Every second you can avoid having to navigate the jungle of files in your project is a second gained towards additional iteration. Remember: remove clicks and remove tools.

Many games will expect either a database approach (“spreadsheet specific,” in Michael Sellers’ terms), or they will have a hard connection between an object and its data. But a good data authoring tool is either integrated with the game engine or is an established external tool, such as a spreadsheet or database, that has a single-click or dynamic export/import process into the game.

Data in the Client

Many games still to this day keep data hard-coded into their compiled executables. This can be done for security or obfuscation reasons, out of habit, or because the engine used for a certain game is structured that way.

For a small game with simple data, this is rarely an issue. You can make your changes, recompile, and then test, within seconds. But for bigger or more complex projects, it can have a cascading effect on iteration complexity. It also forces you to rely on programmers even for changes that have nothing to do with game logic or code.

If you can avoid this, do so. It doesn’t matter if a compile takes five minutes, it’ll be stealing those five minutes over and over again. It will also decrease the number of iterations you can make.

Data in Scripts

Issues with compiled data are not new. One common way to avoid some of them is to use lightweight text files that can be loaded and interpreted at runtime. This can be done in one of two ways.

You can construct data this way. The below is a small example of this, where Lua was used to package information about different sectors in a space game. In this case, a sector has details about which other sectors the player can travel to, which pilots are present in the sector, and which stations and colonies can be visited.

This is information that could’ve been hardcoded into the client, but this way it’s made available at runtime and much easier to iterate on.

Sector201 = {
        Name = "CETACEA",
        X = 0.0,
        Y = 0.0,       
		Objects = {}, 
        Colonies = { 201 },
        Stations = {},
        Pilots = { 201 },
        Sectors = { 202 , 203 , 207 , 103 , 1001 }
    },

You can build logic this way. The next example is also Lua, but is a narrative sequence from the same space game. By exposing gameplay features to Lua, it becomes possible to script these sequences that can be loaded and parsed by the engine on demand. One benefit of this is that you can rewrite the script, make the engine reload the data, and then test within moments of making the change.

-- Intro: TURN ON THE LIGHTS!

Lights1 = "You flip the switch. A raspy mechanical sound spreads through the room before a row of floodlights illuminates the scene."
Lights2 = "The room is a small tubular compartment with a single bunk. Everything is made of shining black metal, lined with other metals and a dark faux-leather finish in some places."

function intro_5 ()
    SendMessageS( "narr" , Lights1 )
    SendMessage( "wait" )    
    SendMessageS( "narr" , Lights2 )
    SendMessage( "wait" )    
    SendMessageS( "Examine this room" , "LifeSupport" )    
 end

Data in a Database

If there’s such a thing as a standard today, it’s to store your data in a database. This database may live on a proprietary server owned by the developer or publisher, or it can utilise something in the cloud, like Microsoft Azure or Amazon Web Services (AWS). It can also be an offline database that you store with your game client much like a script.

A database forces you to decouple data from objects and allows live editing of data (if in the cloud). Most modern live service games do this for some of its data, if not all, as it makes it a lot easier to respond to community feedback and fix data-related issues.

Baseline-Attribute-Modifier

Planning how you structure your data before a project begins can save you many headaches. If you want to do MoveSpeed, you could have a MoveSpeed baseline multiplier at 1.0, each object could have a MoveSpeed attribute of maybe 10-20, and gear or other props could then add their own MoveSpeed modifiers on top as additions, multipliers, cumulative multipliers, or some other thing. You’d get something like MoveSpeed = Baseline * (Attribute + Modifier(s)).

If you manage to separate these from their objects you can mix things up for any reason you want without ever touching or even looking for the objects ever again. The amount of time this saves for more iteration can’t be overstated. (Again: remove clicks, remove tools.)

Maybe you want to modify Baseline based on difficulty, so that MoveSpeed is 1.5x on Easy, but only 0.75 on Hard. Or go in there and double the MoveSpeed attribute for all enemies that have the Small trait. With this type of separation, all of those things can suddenly be done in seconds.

This makes everything from bulk operations to conditional exceptions a lot easier to make and therefore to iterate on.

• Separate your data into logical containers, such as Baseline, Attribute, and Modifier.

Change Sets

A change set is a collection of changes made to your existing data. You can look at it as a changelist or commit in version control. Bundling variables into change sets is a handy way to keep track of what you are doing and makes it easier to compare one change to another.

Change sets really come into their own if you can combine them, turn them on/off, and provide more than one at a time. Over time, these sets can become like a log for your earlier tweaks, creating a kind of tweak history for your game’s design.

• Bundle collections of changes into change sets. E.g., “double move speed.”
• Identify change sets modularly, so you can test more than one thing at a time.

Testing

To know how any iteration works out you need to play it. But it’s not enough to merely play as you usually do. You need to compare changes and report when something doesn’t work out. Even as a solo developer, a solid reporting tool can be the difference between fixing problems and shipping with them.

This is where your change sets from before will work their magic. Let’s say you made a “goblin damage debuff” change set where you decreased how much damage the goblin dealt by half, and you now go into your change set tool to activate that change set. Or you tell external playtesters to play once with and once without the change set.

You can suddenly talk about balancing the same way you’d talk about feature implementations.

Versioned

I encounted Semantic Versioning during my first mobile game studio experience, at Stardoll Mobile Games. I’ve stuck to it ever since. The summary for Semantic Versioning is so simple, yet so powerful:

“Given a version number MAJOR.MINOR.PATCH, increment the:

1. MAJOR version when you make incompatible API changes
2. MINOR version when you add functionality in a backward compatible manner
3. PATCH version when you make backward compatible bug fixes”

This is a convenient way to plan your assets. The Patch version can be automatically incremented whenever you build your game to identify each change and you can regulate when the Minor and Major version must be incremented.

For example, you can plan that you only release a new Major when you are releasing new content and a Minor when features are added or changed.

• Maintain clear versioning, even if just for yourself.

Always Playable

At Calm Island, we used to maintain one Dev and one Stable branch. The latter meant we could always show the game to any external stakeholders, even if it may have been an older build. The stable version was also the one deployed to stores after final validation.

The idea to always keep your game playable may sound self-explanatory, but good processes for this are uncommon. Many studios still use a single main branch for everything and when a deadline looms the only way to safeguard its health is to enact some kind of commit/submit stop where no one is allowed to push anything that risks the playability of the build.

This often results in a rush of new code and content right after the stop is lifted, that almost always breaks something and may take days or weeks to resolve.

• Make sure that you can always play a recent version of your game.

Targeted

A common issue with playtesting is that you need to jump through hoops before you can test the thing you’re actually working on. This can be because you need to launch the game, go through the splash screen, load the right level, noclip or teleport to the right place, etc., before you actually play. If your game is unstable (see Always Playable above), this can be further exacerbated by crashes or bugs that are not yours to fix.

To avoid this it’s important to be able to do targeted testing. Using isolated environments, such as a “gym” level for movement testing, and testing exactly the thing you just tweaked or implemented without any distractions.

• Provide shortcuts and settings that let you avoid time sinks.
• Make it easy to choose what to test.
• Make it clear what is being tested.

Modular

You need to be able to mix and match both systems and change sets in your game, to iterate as much as possible. Play without the enemy AI running, no props spawning, or with that goblin damage debuff or double move speed turned on or off.

You can look at this like the layers in Photoshop, where you can turn things on or off so they don’t impact your testing when you need to test something specific.

• Make your systems modular.
• Make modules easy to toggle.

Interchangeable

Once you have a modular setup, make sure that you can switch quickly and easily between different modules as well. Make them incerchangeable. If you need to test playing against only a single goblin, but that goblin can’t move, and you have only torches and stale bread; then it should be as few clicks and tools involved as possible to do so.

• Allow testers to easily switch out and modify what they are testing: anything with the same output should be able to tie into the correct input.

Simulated

Once the data is separated, you can take it one step further: you can remove entire segments of your game and isolate iteration and testing to retention loops or other longterm systems.

Think of a standard game loop. You have some inputs into each session, such as matchmaking settings or difficulty selection. This input affects how the session plays. Once the session completes, you get outputs, such as XP or treasure, that you can then reinvest into progression. This is the template for many standard game loops.

Simulated state allows you to pretend that one of these steps happened without actually having to take the time to play them. You can randomise the inputs and then play, or skip the session entirely to only work on the output and investment cycle. Once you reach the modular and interchangeable iteration dream, this is quite possible.

The value of this type of testing is high, since longterm systems often don’t get the testing they need simply because you must finish a real session of gameplay to get the “proper” outputs.

• Make it possible to simulate the systems without running them.

Comparable

Being able to compare different iterations to each other and choose which comparisons to make is more of a meta tool than it’s directly testing related. It’s more about comparing the results you gain from testing than the testing itself.

Look at the Game Balancing Guide for some inspiration on what kinds of things you could potentially compare.

• Show the data; show comparisons.

Reportable

If you find something that’s not great or that you want to revisit, make it easy to take notes or report to a central system; you may even go so far as to generate planning tickets from an in-engine event. Have your testers press some easy to access key combination (on controllers, maybe to hold both triggers and both stick buttons down for one second).

• Make it easy to file bug reports and provide feedback without leaving your game.
• Integrate screenshot tools and video recording.

Updating

Sometimes in a big team, the more technical tasks involved with the build and distribution process are invisible to you. You may hear about porting or signing or compliance, but you never have to deal with any of it. You happily playtest on whatever is easy and available, usually your development computer. Sometimes even inside of your development environment.

The reason this happens is because your updating process is not built with iteration in mind. Builds take too long, frequently don’t work, and distributing to local devices is a hassle. Many teams “forget,” or rather downprioritise, testing on their proper target devices.

Test on Target

One of the stranger things I’ve run into is developers who not only dislike testing on their current target platform but basically refuse. It’s so much easier to stay in your comfortable development environment indefinitely. Some studios may even resent some of their own target platforms, for example mobile platforms or consoles, because they are allowing personal opinion to affect their professionalism.

But there’s really no excuse: you should always test on your target devices.

• Test on target devices.
• Test your lowest spec targets.

Visible Versioning

Something that’s easy to overlook is to keep visible and easily copy/pasteable version information on-screen in your game. This is good for a product after launch too, so that players can provide you with more detailed information if they experience bugs or crashes.

• Make version numbers visible in all game builds, including release.

Test Automation

One of the first things I did in gamedev was to drive cars along a race track’s edges to make sure that the collisions worked like they should. A kind of testing that you can automate relatively easily. In test-driven development, testing and automation is already part of the thinking, and there’s really no need for game development to be different.

Automate the right things, however. An automated test can’t tell you about quality. It can’t suggest design changes or warn that a player may not understand the phrasing of a dialogue line. Automate regression testing, compliance testing, integration testing, and the driving along the tracks to test collision. But don’t automate quality testing.

• Automate functionality testing, but not quality testing.

Build Automation

Building for all of your platforms without having to do so manually is an essential element of game development. No amount of testing in a development environment compares to testing real builds.

Automated builds are often triggered by new commits or version increments. It’s also common to have nightly builds, hourly builds, and build cadences based on testing needs and build duration. What’s important for such a pipeline is that it can clearly say what’s going wrong by posting logs and details to the relevant people. A Slack channel, for example.

What you absolutely don’t want is to put developers on fulltime duty to get builds out.

• Building the game automatically and get new builds continuously without requiring manual intervention.

Distribution Automation

Once you have a build, you need to get that build onto the right device for testing. Most devkits and software platforms allow remote connection. You can usually set up jobs to trigger automatically when a build completes and publish your game to your testing platform (or even live) without requiring any work at all.

• Remove all obstacles for build distribution: make it a single click (or less) to get a functional build to play on the right device.

Endnotes

Hopefully, this post provides some food for thought on iteration and what it really means. If not, tell me every way I’m wrong in an e-mail to annander@gmail.com or in a comment.

Here’s the list:

• For object-oriented authoring: clearly visualise what an object can (and can’t) do based on its inheritance; don’t hide logic deep into a dropdown hierarchy.
• For component-based authoring: make non-destructive tools with opt-in as the default rather than opt-out. Provide good error messaging for when requirements are not met.
• For data-driven authoring: provide clear debug information and visual representations for where data is coming from, when, and what it allows. Make it clear what data is expected where, so no steps are missed.
• Make it easy to list states and transitions per object.
• Provide state transition information with data reporting, so that you can keep track of all the whens and whys.
• Make states have meaning; if a state says that an object cannot move, this should be definitive.
• Differentiate between Specific and Generic states, so that you will never accidentally add state to an object that won’t work.
• Set clear guardrails between Exclusive, Inclusive, and Parallell states. Plan what you need each state to be able to do and where to get its data.
• Visualise which conditions apply at a given moment and why.
• Show when conditions are unavailable and why.
• Log transition changes and which conditions made them change.
• Show when, how, and from where a state injection occurs.
• Make it clear which explicit states are running at any given time.
• When dynamic state is triggered, make all of its relevant overrides predictable and singular: it should always be enough to turn something on or off once.
• Provide visualisations of start and end positions for timed states.
• Allow developers to scroll timed states manually to preview them.
• Allow states to resume after interruption, so that you can use interstitials in a non-destructive way.
• Separate your data into logical containers, such as Baseline, Attribute, and Modifier.
• Bundle collections of changes into change sets. E.g., “double move speed.”
• Identify change sets modularly, so you can test more than one thing at a time.
• Maintain clear versioning, even if just for yourself.
• Make sure that you can always play a recent version of your game.
• Provide shortcuts and settings that let you avoid time sinks.
• Make it easy to choose what to test.
• Make it clear what is being tested.
• Make your systems modular.
• Make modules easy to toggle.
• Allow testers to easily switch out and modify what they are testing: anything with the same output should be able to tie into the correct input.
• Make it possible to simulate systems without running them.
• Show the data; show comparisons.
• Make it easy to file bug reports and provide feedback without leaving your game.
• Integrate screenshot tools and video recording.
• Always test on target devices: no amount of emulation will ever compensate for real qualitative testing.
• Have as many diverse target devices available as financially and physically possible.
• Test on target devices.
• Test your lowest spec targets.
• Make version numbers visible in all game builds, including release.
• Automate functionality testing, but not quality testing.
• Building the game automatically and get new builds continuously without requiring manual intervention.
• Remove all obstacles for build distribution: make it a single click (or less) to get a functional build to play on the right device.

This post is all about what game balancing is and how to do it. Just remember that every game has its own unique needs and challenges, so cherry-pick whatever sounds reasonable for your game. This post will become a “living” post of sorts, added to over time.

Tell me about your own balancing tools and tricks at annander@gmail.com or in a comment.

Sections in this post:

• Targeting: who you are balancing for.
• Points of Reference: what you are balancing against.
• Points of Differentiation: the exceptions you are making to your points of reference.
• Tools: various methods and techniques that you can use when balancing your game.

Targeting

Before we get into the balancing itself, we need to know who we are balancing for. Paradoxically, this doesn’t have to be your target audience per se. A player who bought your game but never installed it is still part of your target audience; but they are not part of your balance targeting.

Player Attrition

Some players simply don’t care for your game at all for one reason or another, or lose interest after a while. These matter to game balancing because they are inevitable. One element of your balancing is who you are not balancing for.

There are two very broad types of player attrition: the burn and the churn.

Burn

Players who touch your game and get burned, like on a hot stove, never to touch it again. Knowing who you are willing to burn means that you can plan for it and exclude any balancing fixes that cater to that group. Pleasing the burned only wastes time.

Burned players will never come back. It can be because the genre or gameplay doesn’t appeal to them, because it didn’t match expectations, or for many other reasons. What’s important to understand is that this is fine. You’re not making a game for everyone. Your multiplayer action game is not going to appeal to a fan of turnbased singleplayer games and no amount of balancing will change this.

Churn

Churn rate is the rate at which players stop playing your game. In the best of worlds, you are able to collect data that tracks when players are churned. In a puzzle game with linear progress, for example, if many players stop playing halfway through the fifth puzzle, that could be an indication that they don’t understand how to proceed. Or if many players stop playing after dying four times against the second boss, it may mean that it’s not clear enough or too hard.

Players churn after giving your game a chance. You can win churned players back or delay the churn by understanding your audience. One goal of good balancing is to keep these players playing.

Profile

In his book, Introduction to Game System Design, Dax Gazaway employs measurements that are very practical and useful for when you want to figure out your design target. The book has more measurements. For this post, I’ve stuck to those that can be quantified.

Tolerance for Learning Rules

Understanding how a new game works is an acquired taste. Many a gaming console has been purchased to play Grand Theft Auto and EA Sports FC exclusively. A gamer today can be someone whose hobby is to play Fortnite or League of Legends, and who hasn’t spent more than a handful of hours in total even trying other games.

• Refusing: players that don’t want to learn anything new at all, regardless of how you package it. They want things to behave a certain way. Gazaway’s example is how Wii Bowling managed to attract people who didn’t really play games, because it was close enough to real bowling for the rules to transfer readily between the different media. They don’t want new rules, but they can transfer what they already know.
• Resistant: players that are willing to learn some new things to be able to engage with games in a genre they like or a series they follow, but tend to not leave their comfort zone. The aforementioned Grand Theft Auto and EA Sports FC players.
• Neutral: where you’d categorise most “casual” players. Willing to learn new rules to play a specific game, but more as something that goes with the territory than something to be actively sought.
• Accepting: players that don’t just reluctantly embrace new rules but dig deeper and even learn more than they may need to. This is the space for many “hardcore” players, that stick to a genre and explore it deeply with character builds and clever solutions. More likely to try something new that they still recognise.
• Enthusiast: people that read game rulebooks for fun. They will probably move on to the next game once they have understood this one.

Tolerance for Failure

Gazaway expresses interest in challenge as a ratio of failures against successes. A game that can be measured as 20 failures against 1 success (20/1) is clearly a lot harder than one that is measured as 1 failure against 100 successes (1/100).

A player that starts getting frustrated after failing twice against each success will be burned by the 20/1 game. But so would a player that thrives at 10/1 while playing a 1/100 game. Not to mention that a game that suddenly goes from 5/1 to 20/1 is likely to churn some of its players.

Desired Time Investment

Free-to-play advocate Nicholas Lovell talks about the Starbucks Test, which he paraphrases from then Natural Motion CEO Torsten Reil as, “Can you play your game and have a meaningful experience in the time it takes for a barista to make your macchiato?”

This is the very bottom of the time investment rung, where you can fit a play session within your other daily phone activities. On the opposite end, you have games that take many hours, even several days, to finish.

According to Midia Research, “[c]onsole gamers spend – on average – 10 hours gaming per week, while PC players spend a little less (9.7 hours).”

Gazaway talks about session time vs total time. A single-player roleplaying game may take 80 hours to complete, but you can play sessions of variable length. It may even pass the Starbucks test, letting you jump in and defeat a monster before they call out your name.

Payment Ceiling

If you are making your game for middle-aged gamers in the west with stable income, you can expect them to pay more than a kid with no personal bank account, or to a young student in a third-world country. Income inequality is sadly universal.

Deciding to charge €69.99 for your game will exclude everyone whose ceiling is €5, for example. Simple mathematics. They’re burned before they even start the game. They don’t get to the stove. Even if they’d give the demo a chance, they could still never afford your game.

This needs to be mentioned here, because we tend to forget that the money and the balancing are actually strictly related, even if all it affects is the point of entry.

Points of Reference

The first step to balancing is setting points of reference. This is the foundation for everything you will do, and can live in a bullet point list, a spreadsheet, a design spec, or some other form.

The Three Dials

In the excellent book Game Balance, by Ian Schreiber and Brenda Romero, game balancing is divided into three “metaphorical dials that are coming together” to create the sense that a game is balanced.

Difficulty

Think of difficulty as how much pushback the game has against your success. This can be expressed as a ratio of success. For example, if you want the average player to win 75% (or 1/3 in Gazaway’s failure to success ratio) of the fights they start on the first try, but only 25% of bossfights (3/1), you can see if those numbers check out by collecting data from play tests.

Quantity

The number of things in your game. Enemies, ammo, loot, levels, coins, dialogue lines, health points, and so on. Quantities are often adjusted for practical reasons more than balancing and must then be balanced accordingly, for example how many enemies that can be rendered at any given time, or how many weapons you have budgeted time for delivering.

Timing

When to press the key. How fast you need to move and when you should stop moving. For how long an interstitial “hurt” animation plays before returning controls to the player. The duration of the progress bar on that new building you are constructing. Timing is about duration as much as the moment.

Using References

As has been discussed before, the lack of common language around game design means that we often resort to references to other games. This makes it really hard to talk about balancing with any consensus.

Therefore, the first thing we need is everyone’s buy-in. Everyone working on the game, that is.

Balance References

We may want our game to be as difficult as Dark Souls, feel as good to play as Super Mario Odyssey, and take about as long per match as PUBG. These are fairly concrete and measurable comparisons where we can apply a more scientific approach. If it takes us about 10 attempts to kill a boss in Dark Souls, that gives us a number to balance against.

Just don’t make the mistake of copying. If you have those 10 attempts against a boss with you, take that number and consider it. Test lower, test higher. Look at it from quantity and timing angles as well. These are inspirational and communicative references, not your rulebook. They say something about how the referenced game works, not how your game should work.

Antithetical References

It’s also common to set up antithetical references. We don’t want a match to take as long as a full Battlefield 3 Conquest match, or we don’t want timing to feel as punishing as in Ninja Gaiden, or the UI to be as confusing as in Crusader Kings II. Whatever it is, it needs to tap into this same common pool of references.

References shouldn’t be limited to games. It’s common to refer to movies, comics, TV shows, books, documentaries, historical events — anything that can act as an antithetical to what you have in mind. Same goes for balance references, of course. The key to references is that everyone on the team can understand them.

Designed References

A designed reference is something you come up with in the team that becomes true for you. It can be a pillar, such as “Character-based play,” that lets you tap into your own project to figure things out. Someone changes something, and you can then go back to check if the thing actually is character-based play. If it’s not, it’s failing, and you may have to rebalance or redesign it.

Setting Limitations

Just like the spend ceiling mentioned before, there are limitations you must contend with. When you print a deck, it has a certain number of cards. A Switch console can only push a certain number of textures per frame at 60 frames per second.

The worst part with limitations is that they are extremely inflexible. If you break the card count on a print plate you need a whole second plate, even if all you are after is a single card. Similarly, rendering just a few more textures per frame will make your game run slower. Technical, practical, and financial limitations are important to know before you set your other references.

Experiential Goals

Measurable goals for what you want the experience of play to be. This can be session lengths, more or less pushback, or specialised metrics like how many seconds should be the maximum allowed to pass between game launch and the first kill (“seconds to kill”).

Set these goals very broadly. This will make it easier to make exceptions to them the same way a bossfight against an enemy that has a lot of hit points immediately changes the “seconds to kill” dynamic.

Content Goals

Many action games have an average lifetime for enemies around five seconds. Maybe you want your enemies to be tougher or smarter, so you state that you want average enemy lifetime to be 15 seconds. This is a type of content goal, where you state how much screen or even CPU time something is intended to get.

With many games content-driven or even content-locked by design, this should be more of a consideration than it is.

Balancing Anchors

It’s helpful to use an object or variable as an anchor for the central mathematics of your game.

Health points is an effective anchor. If you set a player character’s health to 10 and you let this serve as your anchor, you set the damage weapons deal and armor prevents, what ratios you want between gold and health, and how effective the conversion of mana to health points should be. This would turn health points into the main dial for almost all balancing in your game. You can also speak of multiples of health points as measures of difficulty. An easy enemy may have half of the player character’s health, while a tough enemy has ten times the same.

When you do this for an object, it can be the game’s default pistol and the experience of playing with it. Which is how John Romero writes about testing new Doom levels: all of them needed to be playable from a pistol start. The pistol is then the anchor for Doom‘s balancing and all the various numbers that affect the pistol, such as ammo pickups placed in the level, damage, fire rate, etc., will affect the play experience of every single level in the game.

Numeric Ranges

A range is a floor and a ceiling and all the numbers between. If you have a numeric anchor, like 10 health points, it should probably represent the bottom of the range in a progression-driven game. However, an object anchor like the pistol could represent an average for multiple ranges.

You may have ranges representing distance, damage, armor, gold value, durability, ammo, and so forth. Ranges are a good way to incorporate limitations. If you know that your frame rate will limit the rate of fire for your firearms, for example, you can set the ranges accordingly.

A handy thing with ranges is that you can use them in random generation. For example, if you determine the extremes (see Set Extremes, later) you can test with random values within that range when you run your tests.

Semantic Ranges

One way to set references that I’m personally very fond of is to use words instead of numbers. To fuzzify the numbers. If you have the concept of range in your game, you can talk about it as Close, Far, Long, and Distant, for example. When something needs to be changed, you bump it on this ladder rather than changing the numbers directly.

This makes it easier to talk about the balancing in relative terms. It also lets you determine which ranges you want to have without having to get stuck discussing the numbers. If you need more nuance, you can add more rungs on the ladder.

MI/MO

Game economy design is basically a science in itself. But a good way to start building a virtual economy is to tally all of your sinks first. These will show you how much virtual currency even has the potential to flow through your system. If this number is capped or particularly low, you should limit how many sources you have based on player time investment, difficulty, and other targeting goals from the previous stage.

Make sure that the player can always afford something, but also make sure that they can never afford everything until your reference goals are reached.

1-3-5-10

When you set out to create a system of balancing that has numbers at its foundation, you always need to start from somewhere. One way to start is to simplify everything down to one of four value systems: 1s, 3s, 5s, or 10s.

Start from just 1s or 10s, then introduce some 5s, and finally some 3s. This way, you will quickly have the gut-level foundation for your balancing. To refer back to health, one mana could be worth five health points, while one gold is worth three in the form of a health potion that heals three points.

Fibonacci sequence

Another way to create base numbers is to use a Fibonacci sequence. A Fibonacci sequence is “a sequence in which each element is the sum of the two elements that precede it.” If you start from 1, this gives you 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, etc.

This sequence can often come in handy, and you can play with the principle of the sequence as much as the sequence itself, for example to set item prices with a good initial spread. Perhaps if your health potion costs 25, then you could price the following item tiers 50, 75, 125, 200, etc., using the same rule of summing up the two preceding numbers to get the next price.

Points of Differentiation

If points of reference are there to give us something to anchor our balancing to, points of differentiation are where we design the game. A focus on diversity. Ways to mess with your points of reference and give players something to strategise around.

Greg Costikyan wrote about this on Linkedin, in the context of combat systems, saying that “The key is multiple points of differentiation, to create interesting strategic choices for players. If it’s all about DPS, it’s boring.” His examples include things like reload times, costs, damage, damage type, combined effects, and more.

Ways to add more ranges and more points of differentiation between one gun and the next.

Removal

Destroy them, disable them, put them on timers, require resources for their use. Take things away. Once the player is used to something, try removing it and seeing what happens. It can be the worst thing you did, or it can give room for you to create a needed change of pace. Like when the enemies in Batman: Arkham Asylum start mining the gargoyles Batman is using to hide.

Dominance

In game theory, a dominant strategy is one that always trumps other strategies, while a dominated strategy is one that is always trumped by everything else. Players will naturally gravitate towards dominant strategies as their understanding of a game evolves (at least if they are accepting of learning new rules), and will bounce away from dominated strategies.

This is not necessarily a bad thing. You may want the starting pistol to be a dominated strategy, same as the BFG 9,000 is a dominant one, but other restrictions of usage means that you will never stop using the first and can’t rely entirely on the latter throughout the game.

Transference Systems

Many games restrict features by requiring transference. You are highly unlikely to find the best mod in Warframe, if it’s even possible, so instead you engage in the act of combining mods to convert them into better ones in multiple tiers. A process that costs resources at every step along the way.

Going back to the Game Balance book and its three dials, most of these systems use time as the essential anchor. You need to play to collect more of the resources you need for the crafting, and there are rarely any guarantees, which means you need to put even more time into it.

Discovery

Controlling when a difference is introduced is a key element of time balancing. If you find the best weapon in the game right out the gate, players are unlikely to ever switch, and if you provide access to it too late, many players will never see it at all and many who do see it may be less inclined to change their winning strategy.

You can also control how easily a difference is accessed. Players may have to complete a special quest or spend an expensive amount of resources or time.

Content Modifiers

Perhaps most commonly for Massively Multiplayer Online Role-Playing Games (MMORPGs) and similar genres, where you will have the squeeze the best possible mileage out of every piece of content, changing a color and making something deal a different type of damage (red for fire, blue for lightning) modifies things enough to keep the player playing.

Diminishing Returns

Patterns you don’t want the player to fall too deeply into can be altered by diminishing returns. Enemies may start wearing more body armor if you kill many of them, forcing you to switch things up.

Tools

The following list will serve as a living document, with tools added over time. (Sporadically, I must add.)

One Change at a Time

Make sure to only change one thing at a time, and to document what you changed. This makes it easier both to know what you did, what made the ultimate difference, and to write changelists once you publish it to your players.

Do it Again

Sometimes, you have a solution or feature that just works. In a first-person shooters, you’re shooting, aiming, and reloading and shooting again, constantly. Same with card games; you’re drawing and playing and drawing. If a segment of your game isn’t working as well as another, repeat a solution that worked before. Keep a record of go-to solutions for future use.

Do the Opposite

If you get stuck on something you decided on, try doing the exact opposite in your design and see if that takes you anywhere. Maybe you added more health to the enemies because the combat was too short, and it made them feel like bullet sponges. Trying to decrease their health instead and then increase the spawn rate could be the solution you seek.

Offer a Bite

Touch, but don’t taste, is when you have a really cool feature that’s so restricted that players never use it, or they save it for a “later” that never happens before the end of the game. If you see this pattern in your game, you can give the players a bite instead. Let them play with the feature without any risk of losing anything, to teach them that the feature is worth using. First one’s free.

Rock, Paper, and Scissors

If you feel that something lacks depth or isn’t interesting enough, you can try to add an additional dimension. Maybe your dialogue system with the Yes and No response options is making for bland conversations. Add a third option that plays against both Yes and No. Rock, paper, and scissors, is a metaphor for the related variation.

Say It

Sometimes when an action feels like it doesn’t have enough “oomph,” you can add more feedback to it. Tell the player that the thing is in fact happening. Particle effects, cheer sounds, camera shake, stop frames, easing functions leading into or out of the action. Think of the sounds the Halo energy shield makes as it starts and finishes recharging.

Divide It

If your game has many moving parts that are active at the same time, it can be helpful to divide them into separate stages of interaction. Games that are maths-heavy, such as some styles of role-playing games, will often divide their “buffs” into stages. Something that lasts for 30 minutes is a “prebuff” that you can activate when you are expecting something to turn tough, while the one that lasts for just 30 seconds is something you use in the midst of combat. This division serves as a subtle way to structure the player’s buff cycle.

Make it Viable

If you see players doing something over and over again, even though it’s the wrong thing to do, you can try to make it viable to play the way they are playing. This is the territory of Coyote time, auto-aim, and other mechanics that try to predict game effects from player intent.

Double or Halve

This balancing tool is almost cliché at this point. Double or halve. You want the thing you are doing to make a tangible difference, so you double it or you halve it depending on whether it needs an increase or a decrease.

By Ten

When you feel that something needs a bigger impact than doubling or halving it yields, you can try multiplying or dividing it by ten instead. This is a much more drastic move and will rarely be used except as a method to find your extremes.

Put the Door Before the Key

If players are unaware of interesting features in your game, you can make them excited for it before they get to play with it by putting the door before the key. Dangle the treasure, the lever, or the new enemy in front of them, so that they will actively seek out how to get to it. Whether by finding an actual key or by understanding that they need to go up to get inside the locked room somehow. Metroidvanias are fantastic at this.

Set Extremes

An exercise you can use when numbers feel off is to decrease or increase by a lot (doubling/halving or by ten) until you find the lowest low and highest high. Then you construct a range out of those two values, and you start testing with different values within that range to try and find a sweetspot. It’s a good way to get away from pure feel and narrow it down.

Lift it Up

Probably the most common trap in balancing is to create a cool new thing and immediately feel a need to make it worse. To “nerf” it. This is a reminder to not do that, but to try to capture why the thing feels cool and to extend the same coolness to as much of the game as possible.

“We’re making an ARPG with survival and roguelike elements,” begins the pitch. “It also has some light platforming, is made with Godot, and intented for release on Steam in Early Access.”

For the business-minded person in the crowd who just played Path of Exile 2, they may focus on the ARPG bits or conjure up mental images of lucrative microtransactions.

One who recently finished Subnautica may catch on to the survival bits, for good or bad.

One who bounced off Hades 2 for some reason could be negative about the roguelike element.

Another may latch on to the idea of platforming and think that there’s no point to go up against some other popular platforming game that’s about to hit stores around the same time.

Someone may dismiss it simply because they said “early access,” or because they have opinions on the choice of engine.

This pitch has managed to confuse everyone in the room, using seemingly standard terms. The genres and abbreviations we take for granted seem just as watertight and solid as any formal academic definition, but they really are not.

In fact, I want to argue that attempts at general definition harms game design. Definitions can and should change from one game to the next. Asking someone to define something in general terms derails the creative conversation we could be having instead.

Let’s look at definitions of game design, to hash out what I’m trying to say. And as usual, if you disagree, please do so in comments or to annander@gmail.com.

We Have No Words

Why is there no definition of game design? In fact, the definitions are legion. We simply can’t agree which one to use. Not even at the university level. Faculties across the world use different ways to talk about game design. One university may talk about game design as level design, while another involves scripting, and a third uses boardgame design as the springboard.

So let’s look at some ways that great game designers have tried to concretise the language around our work.

The Art of Computer Game Design

“Creativity is concerned with the invention of something new and different,” said Chris Crawford in 1989, in his famous ‘whip speech’ at the Computer Game Developers Conference. I was seven years old at the time, so can’t say that the prospect of developing games had had a chance to form yet at the time, but it’s an incredibly inspiring talk to watch today.

But before wielding a bullwhip on stage, Crawford also wrote one of the earliest and most lucid texbooks on game design, The Art of Computer Game Design, published in 1984. A book that thinks a game needs three things: representation, interaction, and conflict.

Representation

“[A] game is a closed, formal system that subjectively represents a subset of reality,” writes Crawford.

Closed: “By closed I mean that the game is complete and self-sufficient in its structure. The model world created by the game is internally complete; no reference need to be made to agents outside the game.”

Formal: “By formal I mean only that the game has explicit rules. There are informal games in which the rules are loosely stated or deliberately left vague, but such games are not typical.”

System: “The term system is often misused, but in this case its application is quite appropriate: a game is a collection of parts that interact with each other, often in complex ways. It is a system.”

Subjectively represented: “Representation is a coin with two faces: an objective face and a subjective face. […] The distinction between objective representation and subjective representation is made clear by considering the differences between simulations and games. A simulation is a serious attempt to represent accurately a real phenomenon in another, more malleable form. A game is an artistically simplified representation of a phenomenon. The simulations designer simplifies reluctantly and only as a concession to material and intellectual limitations. The game designer simplifies deliberately in order to focus the player’s attention on those factors the designer considers important.”

Subset of reality: “[N]o game could include all of reality without being reality itself; a game must be, at most, a subset of reality. The choice of concerns within the subset provides focus to the game.”

Interaction

Game design concerns itself with all of these elements. But Chris Crawford also define games by what they’re not. “Games provide [an] interactive experience, and it is a crucial factor of their appeal.”

Games Versus Puzzles: “Games can include puzzles as subsets and many do. Most of the time such puzzles are a minor component of the overall game, because a game that emphasizes puzzles will rapidly lose its challenge once the puzzles have been solved.”

Games Versus Stories: “A story represents a series of events in a time-sequence that suggests cause-and-effect relationships. […] One important difference between games and stories is that a story presents its facts in an immutable sequence, while a game offers a branching tree of possible sequences and allows the player to make choices at each branch point and thus to create his own narrative.”

Games Versus Toys: “Games lie between stories and toys in manipulability. Stories do not permit the audience to control the sequence of fictional events. Games allow the player to manipulate some of the facts of the fantasy, but the rules governing the fantasy remain fixed. A toy is much less constrained; the toy-user is free to manipulate it in any manner that strikes his fancy.”

Conflict

“Conflict arises naturally from the interaction in a game. […] If the obstacles are passive or static, the challenge is a puzzle or an athletic challenge. If the obstacles are active or dynamic, if they purposefully respond to the player, the challenge is a game.”

If an “intelligent agent” is trying its best to stop you from succeeding, reacting to your interactions, it’s a game. “A game, then, is an artifice for providing experiences of conflict and danger while excluding their physical realizations. In short, a game is a safe way to experience reality.”

Crawford’s book is well worth reading still to this day. Though its examples may feel dated, what was true for Star Raiders is still true today. Unfortunately, like an example of how much game design knowledge has been lost through the years, few game designers use these terms today.

Formal Abstract Design Tools

One game designer who discussed the lack of a shared game design vocabulary early on is venerable Looking Glass alum Doug Church in his essay, Formal Abstract Design Tools, from 1999. This essay takes an example game — Super Mario 64 — and extracts “tools” from its design that can then be used more generally.

The first tool is Intention: “Making an implementable plan of one’s own creation in response to the current situation in the game world and one’s understanding of the game play options.” This is a seemingly clear device that defines how Super Mario 64 plays.

The second is Perceivable Consequences: “a clear reaction from the game world to the action of the player.” Another strong staple of Nintendo games in general.

What’s important to note here is that these tools are examples of what you can take with you from another game. In the essay, they are then applied to other games theoretically. You can certainly use them if you want to share some of the design sensibilities from Super Mario 64 with other games, but the point is to show you how Formal Abstract Design Tools can be devised and used across game design to generalise concepts that games can share.

This is further illustrated by the tool Story: “The narrative thread, whether designer-driven or player-driven, that binds events together and drives the player forward toward completion of the game.” A tool that can easily be generalised, and also serves as a reminder that stories drive the player’s motivation.

What’s fascinating with this essay is that it’s a framework and conceptual starting point. It even states directly that “this article was not intended to be exhaustive or complete,” and that “[i]t’s a justification for us to begin to put together a vocabulary.”

Still an insightful essay, and could’ve been a starting point for real work in this area, but now instead serves as a reminder that we’re several decades further along and still haven’t figured out how to talk about game design. The quest for abstraction was never completed.

MDA Framework

The next design treatise is often referenced by game educations, and it’s the MDA Framework, where MDA stands for Mechanics, Dynamics, and Aesthetics. The paper itself was written by three game design heavyweights, in Robin Hunicke, Marc LeBlanc, and Robert Zubek, and was developed between 2001 and 2004.

It begins with a lofty ambition:

“We believe this methodology will clarify and strengthen the iterative processes of developers, scholars and researchers alike, making it easier for all parties to decompose, study and design a broad class of game designs and game artifacts.”

There are a few key concepts in the MDA framework that are not too dissimilar to Doug Church’s sample tools. One is that “the content of a game is its behavior — not the media that streams out of it towards the player.” In other words, games are “systems that build behavior via interaction.”

This is a foundational assumption. Many types of games are bought, played, and then shelved as completed (or not) by their players. Those types of experiences are not what the MDA framework is primarily addressing.

With this grounding in mind, mechanics “describes the particular components of the game, at the level of data representation and algorithms.” It’s the conclusion of the paper that “all desired user experience must bottom out, somewhere, in code.”

Dynamics “describes the run-time behavior of the mechanics acting on player inputs and each others’ outputs over time.” A layer that is greatly affected by the sum of both mechanics and aesthetics. “Seemingly inconsequential decisions about data, representation, algorithms, tools, vocabulary and methodology will trickle upward, shaping the final gameplay.”

Aesthetics “describes the desirable emotional responses evoked in the player, when she interacts with the game system.” The sum total of everything, in a way, but also how we choose to represent it.

These three components can be considered “separate, but casually linked,” and should be used as lenses through which you can look at your game design. An important aspect of this is that players will generally see the aesthetics first, while developers often obsess over the mechanics. This difference in view is important, and the framework urges you to bridge it by switching your game design perspective to one focused more on aesthetics.

One way to do this is by employing Marc LeBlanc’s “8 kinds of fun,” sometimes referred to as LeBlanc’s Taxonomy. A setup that looks at what combination of eight key emotions you are trying to emphasise.

Critical Vocabulary for Games

Greg Costikyan, another veteran game designer, suggested in 2002 that “[t]o understand games, to talk about them intelligently, and to design better ones, we need to understand what a game is, and to break ‘gameplay’ down into identifiable chunks. We need […] a critical vocabulary for games.”

This piece hits off with “if it isn’t interactive, it’s a puzzle, not a game,” based on Chris Crawford’s musings in his early book on game design, The Art of Computer Game Design, from 1980. So interaction is what separates a game from a puzzle. But interaction in itself isn’t good enough. There also needs to be decision making; “interaction with a purpose.”

To make decisions relevant, you need goals. Ways to succeed or fail and choices to make along the way. But those goals cannot be trivial to achieve, or you may get bored instead. To make the goals non-trivial, we need struggle.

“We want games to challenge us,” writes Costikyan. “We want to work at them. They aren’t any fun if they’re too simple, too easy, if we zip through them and get to the endscreen without being challenged. […] That isn’t to say that we want them too tough, either. We feel frusrated if, despite our best efforts, we wind up being slogged again and again.”

The last concept Costikyan identifies is endogenous meaning. To describe what it is, he uses Monopoly money as an example. “Suppose you’re walking down the street, and someone gives you $100 in Monopoly money. This means nothing to you; Monopoly money has no meaning in the real world. […] Yet when you’re playing Monopoly, Monopoly money has value; Monopoly is played until all players are bankrupt but one, who is the winner. […] Monopoly money has meaning endogenous to the game of Monopoly.”

To summarise Costikyan’s essay, a game is “[a]n interactive structure of endogenous meaning that requires players to struggle toward a goal.” The game designer’s job is then to complete that whole.

Why We Play Games

Next up is Nicole Lazzaro’s excellent Why We Play Games: Four Keys to More Emotion in Player Experiences. Lazzaro further elaborates on the MDA Framework’s type of thinking, particularly in what the framework refers to as Aesthetics.

“Games are structured activities that create enjoyable experiences,” starts the paper. “They are easy-to-start mechanisms for fun. People play games not so much for the game itself as for the experience that game creates: an exciting adrenaline rush, a vicarious adventure, a mental challenge; and the structure games provide for time, such as a moment of solitude or the company of friends.”

To write Lazzaro’s paper, her game design consultancy XEODesign “went off in search of emotion and found Four Keys to releasing emotions during play.” Each such key is “a mechanism for emotion in a different aspect of the Player Experience.”

The first key is The Player: The Internal Experience Key. “Generate Emotion with Perception, Thought, Behavior, and Other People.” In the text, it’s also called “games as therapy.” A player that plays because of this key is playing to clear their mind, feel better, avoid boredom, or being better. “Games with this Key stimulate the player’s senses and smarts with compelling interaction.”

The second key is Hard Fun: The Challenge and Strategy Key. “Emotions from Meaningful Challenges, Strategies, and Puzzles.” It achieves this through emotions such as Frustration and Fiero (“an Italian word for personal triumph”). “Games with this Key offer compelling challenges with a choice of strategies.”

The third key is Easy Fun: The Immersion Key. “Grab Attention with Ambiguity, Incompleteness, and Detail.” Also referred to as “sheer enjoyment of experiencing the game,” dipping into senses of wonder, awe, mystery, and so on. “Games with this Key entice the player to linger, not necessarily in a 3D world but to become immersed in the experience.”

The fourth and final key is Other Players: The Social Experience Key. “Create Opportunities for Player Competition, Cooperation, Performance, and Spectacle.” Crucially, both inside and outside the game itself — community can meet the emotional goals of this key just as much as in-game features. Teamwork and camaraderie. Rivalry and competition. Schadenfreude and amusement. “Multiplayer games are the best at using this Key, although many games support some social interactions through chat and online boards.”

The paper provides a more clear description of each key, but what’s incredibly useful with these keys overall is that many games can benefit from supplementing a focus on one of them with additions of another. For example, if your game is highly competitive (“Other Players”, “Hard Fun”), it can still be nice to have a change of pace organising inventory or fiddling with other menu bits between sessions (“Easy Fun”).

The Art of Game Design

Jesse Schell’s The Art of Game Design: A Book of Lenses is one of the most commonly mentioned books on game design. If there was any such thing as a standard volume on game design, this would probably be it. It’s an excellent book and has two major elements that makes it useful (in my opinion).

First of all, the chapters themselves frame many key elements of game design. First comes the chapter The Designer Creates an Experience, which clearly emphasizes that the game “enables the experience, but it is not the experience.” This is an important thing to understand if you want to grasph Schell’s perspective on game design.

From there, the book goes both broad and deep. The Venue where you play the game plays a role. The Game itself, the Elements, Theme, and Idea it’s composed of. That it’s improved through Iteration and made for a Player and made to create an experience in the Player’s Mind based on the Player’s Motivation. To achieve this, there are Mechanics that must be in Balance. There can be Puzzles, Interface, Interest Curves, you can tell a Story, allow Indirect Control, and build a World.

As you can tell, it’s a very complete view. This also doesn’t list the many more practical pieces of advice that the book goes into, such as how to make a Profit, the value of Technology and Playtesting, and what Documents you may need to write and how.

The second thing the book provides is just over a hundred “lenses.” Each lens is something you can look through when you analyse your game. They’re available in a deck of cards that you can get fairly cheaply and that has great utility whenever you need inspiration in your game design work. An example lens is the Lens of Balance, which tells you to ask the questions “Does my game feel right? Why or why not?”

A Game Design Vocabulary

The struggle to find a good game design language is the subject of Anna Anthropy and Naomi Clark’s book A Game Design Vocabulary as well. It takes a more high level approach than Schell’s book, perhaps most similar to Greg Costikyan’s article mentioned earlier.

“You’d think 50 years would give game creators a solid foundation to draw from,” writes Anna Anthropy in the introduction to the first chapter. “You’d think in 50 years there’d be a significant body of writing on not just games, but the craft of design. You’d think so, but you’d be disappointed. […] I see evidence that what both creators and critics desperately need is a basic vocabulary of game design.”

First are Verbs and Objects, and the relationship between them. Such relationships determine the Rules of the game you are making. Verbs are actions. Objects are things that can perform or be affected by actions. Perhaps a Hero, controlled by the player, can Shoot and an Enemy can Die. Suddenly, you have also added choices. If there are two enemies on your screen and you must pick which one to shoot.

Given that the game is made up of Rules divided into Verbs and Objects, then Scenes are the “units of gameplay experience that unfold during and create the pacing of a game as it’s played.” Many tabletop role-playing enthusiasts swear by scenes in this way, where scenes have beginnings, things at stake, and ends. Both like and unlike directing a movie. More specifically in Anthropy’s vocabulary, “[t]he purpose of scenes is to introduce or develop rules, to give a chance for the game’s cast — its verbs and objects — to shine, and a chance for the player to understand something new about them.”

Finally, Context “is what helps a player to internalize those otherwise-abstract rules that make up our game.” Spiky things are dangerous, red barrels explode, and nazis are (in fact) the baddies. Context affects many things, and is where much of a game’s content comes in. But it’s also what determines how we compose the scenes for our game.

However. This is only half of the book. The second half, written by Naomi Clark, looks at a game as a conversation between the game and the player. It dives more into the difference between authored and emergent stories, and how games can both be a vehicle for the former and provide unique room for the latter.

Building Blocks of Tabletop Game Design

Another way to look at and talk about games is by breaking them down into their mechanical components. In the book Building Blocks of Tabletop Game Design, Geoffrey Engelstein and Isaac Shalev have compiled a selection of tabletop game mechanics in encyclopedic form.

This book starts from Game Structure, calling out games that are cooperative, competitive, team-based, solo, and more. It goes from there into Turn Order and Structure, talking about claim turns, roles, random turn order and many more. Then Actions (meaning player actions), in some of its many forms. Resolution, for handling outcomes when the outcomes are contested. Game End and Victory collects some favorites (and criticised but common ones, like Player Elimination). Uncertainty then deals with topics like short-term memory limits and push-your-luck mechanics.

In its broader sections, the book then compiles details on Economics, Auctions, Worker Placement, Movement, Area Control, Set Collection, and general Card Mechanics.

Many tabletop designers swear by these terms. They may say they’re designing a “worker placement set collection game,” for example. Most of the time, these mechanics are known quantities and designers can talk about them in terms of how well they fit with a game’s themes or other mechanics. It’s also a handy way to make experiments. For example, “worker placement with a common pool of workers” makes sense as a mechanical idea, and gives you something to build on top of.

These are not quite definitions per se but descriptions of game elements that are common enough to be generalised.

Find Your Own Words

You should read and explore the craft of game design as much as you can. But you shouldn’t strive to define it in general terms. As you can see in the previous examples, even when there is overlap, there is never any real consensus. Games and game design are nebulous things and we all find different things important.

Once you design your own games you should make up your own terms too. Don’t put effort into complying with definitions you didn’t make and don’t discuss what definitions mean or which definition is right. All of that time will be wasted compared to the time you put into figuring out what your game is about.

Make up your own words that can inform how you want to design games. But by all means, do so by taking inspiration from the wealth that is out there, and use the work of great designers to inform your own designs.

The What and The How

Hey there, I’m Keelan.

For the better part of my career in the games industry I’ve worked as what’s known as a Game Economy Designer. Game Economy Design predominantly concerns itself with the relationship that the resources within your game have with the mechanics of your game. If this sounds like a very nebulous definition, it’s because game economy design (and really, economics) is perhaps better thought of as a lens through which to understand your game than anything else.

Still, I want to do more than wax philosophical about the nature of high-minded economic principles like utility and feedback loops. Yes, there will be some of that in this blog post, if only because I think it’s important to understand the abstract concepts before getting our hands dirty, but rest assured that I’ll be demonstrating some of the tools and methods I use to perform Game Economy Design. These tools and methods help us to measure and balance the distribution of resources within our game by taking a number of key economic concepts into account:

• Transference of Resources – The function of one or more units becoming another. Quantifying Damage per Second and other factors helps us understand Time-to-Kill which alongside XP-per-Kill and XP-per-Level tells us Time-to-Level.
• Utility – Involves attempting to find a universal measurement of value within our game that we can attribute to all resources. Perhaps, like me, you’re a fan of League of Legends (a fascinating game for studying feedback loops, an awful game for hair retention). If so, you may have come across the term “gold efficiency” when observing high level players comparing one item to another. In essence, these players are normalizing the stat-per-gold across each item in the game to determine which items give them the most stats for the gold invested; which items provide the best utility. 
• Relative Strength of Feedback Loops – Involves understanding how and why transference may change over time. For instance, different aspects of our design may decrease Time-to-Kill during our mid-game. Perhaps Enemy health and player stats increase linearly within our game, but we introduce combat synergies over time that increase the influence of player stats on damage output. How might this impact Time-to-Level? What about the transference of other resources within our game, such as the gold income per hour?  

If it’s true what Frank Lantz, Director of NYU Game Center wrote, that “Games are basically operas made out of bridges”, then Game Economy Design concerns itself with the tempo of the music and the points of slack and tension among the bridges.

So, what do Game Economy Designers measure and how do they measure it? Let’s discuss.

The What

System Flows and Points of Interaction

Systems flows describe the directionality of resource exchange such as from gold to weapons when you buy an item in a merchant system, whereas points of interactions describe the act of buying and selling.

System flows and points of interaction can range from simple to complex depending on the scale of the system (consider that a collection of systems is also a system) and on the kind of player experience we want to create.

On the one hand, we may want to tie player progress to a number of interdependent systems with varying complexity such as items, upgrades, player stats, level ups and skill trees. On the other hand, we may prefer taking a more straightforward approach to system interactivity in a purchase flow – a player doesn’t want to jump through hoops to enjoy something they’ve spent money on (or do they? See: Battle Passes).

Common components of system flows in games include the following*:

• Conditional Constraints – requirements that gate access to systems or content until specific conditions are met such as player levels, crafting requirements, or story milestones.
• Variance (RNG) – ways in which we generate different outcomes from the same input– think randomly rolled loot tables in treasure chests, random encounters, or randomly assigned modifiers on a crafted item.
• Efficiency Modifiers – Things that impact the strength of the system flow, on which the system is dependent. The impact of player level, inventory, and skill tree allocation on damage output, for instance.

*but are limited by my desire to voluntarily express them in a spreadsheet.

Progression Curves

Progression curves are the mathematical models governing how our gameplay experience changes over time. How many experience points should a player need for each level up? How much damage should a player do over time? How should enemy HP grow over time? 

This is where some level of algebra is helpful as we’ll be defining these curves as pen-meets-paper (or data-meets-spreadsheet). Some of my favorites include:

• Linear Progression – Perhaps the most trustworthy of all progression curves. The same input always yields the same output. This is useful for systems that you want to build your experience around– perhaps you want players to start your game struggling to defeat a single enemy and but eventually be mowing down hordes of enemies- assign a linear progression curve to enemy HP and then get wild with the progression curves on your various damage-generating systems. 
• Exponential and Logarithmic Progression – USE THESE WITH CAUTION. Exponential Progression Curves have a tendency to invalidate designs and wreck ecosystems over time. Exponential Curves do this by rapidly increasing the output for each unit of input and Logarithmic Curves do this by rapidly reducing the output for each unit of input. These become a lot easier to manage when we apply fractional modifiers to the curve or when our systems have definitive endpoints, such as a maximum Player Level.
• Sigmoid Curve – Also known as the “S-curve”. I’ve got to be honest, I haven’t found a great application for a Sigmoid Curve in a single system, but I think it’s a great curve for demonstrating a player journey. For instance, a player’s power progression journey in an ARPG might look like several Sigmoid Curves in a trench coat. 

Utility Functions

Utility describes how much we value something, ideally in a way that we can compare against other things. While the economic concept of utility is fascinating to discuss in the abstract (consider the myriad of factors that determines how much value we place on a bottle of water – time, place, and presentation to name a few), mathematically representing utility in economics is quite the headache. Luckily for us, we’re measuring the economy of a game and not that of say… the consumer car market. 

When it comes to measuring utility within our game, we might be happy enough to look at transference rate within a system. From a game balance perspective, we may look at the amount of stats provided relative to the gold cost of our weapons. However, in the interest of better understanding the player perspective we might alternatively be interested in knowing the number of enemies a player must defeat to afford the weapon.

Even better, we could try to understand the time-investment (“farm”) required for the player to defeat those enemies and acquire that weapon. Once we’ve arrived at a metric of time, we’re truly thinking about our game from a game economy perspective because ‘time’ is a universal resource that governs much of the player experience.

Another common ‘universal resource’ that governs the player experience is money. While it doesn’t necessarily explain why one store bundle performs better than another, it does at least partially explain why more players buy Battle Passes than store bundles. Battle Passes typically contain the equivalent of multiple store bundles in terms of content for a fraction of the price.

Feedback Loops

This is where things get fun. By manipulating the way our various progression curves interact with one another, we can change the nature of feedback loops in our game. We can speed up the income rate of one or more resources or slow them down. This allows us to manage the frequency and intensity of challenge, reward and relief within our game over time.

Feedback Loops are most easily identified in Player Data when we can observe cause and effect in a (hopefully) large sample size. However, the job of identifying them in Player Data is made substantially easier when we’ve first set about attempting to identify them in simulations and before that, in models. By dictating our expectations about the nature of the interconnections between our systems in models, and attempting to observe them in our simulations, we build the muscle memory necessary to observe them in player data.

The How

TL;DR: Spreadsheets containing system inputs, models that represent the behavior of those systems over time, and simulations that inform the behavior of the system.

Diagrams (or visual models)

Diagrams are important not only for refining our own understanding of a system, but also for communicating that understanding to others. The most common uses for diagrams in Game Economy Design are economic flow diagrams, where we map out system flow and points of interaction.

Here’s what that might look like in a simple merchant system:

But you could describe a more complex system as well:

Mathematical Models

Models are our way of representing how we intend for our gameplay experience to change over time. These are foundational to Game Economy Design. Not only are they used to concretely balance progression curves within systems, but they are also used to balance larger abstract design intents within the player experience.

For instance, we may use a model to define specifically how many experience points are required at each player level but we may also use a model to define our design intent for the transference of time-to-levels, or how much time our player should spend accruing those experience points in order to reach some level. The latter example is abstract because every player will play our game differently, but we can temper our game balance using simulations that dictate the conditions under which we achieve our design intent.

Simulations

Simulations are where we make assumptions about how our players will behave within our game and then use those assumptions along with our defined system parameters to determine whether or not the balance of our systems, when experienced by our assumed player behaviors, achieve the intent of our systems.

We may have a model that indicates a time-to-level based on enemy health data and player damage estimates. However, for the sake of testing our system, we might assume that we have a ‘more skilled player’ which achieves player damage 20% higher than our estimates and a ‘less skilled player’ which achieves player damage 20% lower than our estimates. We could then “simulate”* the difference in the time it takes for these two player types to complete our game or other relevant aspects of our design goals.

Additionally, as more players play our game, we’re able to get a better understanding of how different players will experience our game and use that knowledge to refine our assumptions. We may discover that players can be significantly more skilled than simply achieving 20% higher damage, or significantly less skilled than simply 20% less. These observations will yield more accurate simulations, which in turn will result in a more informed game balance. This is where player data comes in.

*Note: I’m using simulate in quotations here because this example is a fairly obscene over-simplification. If there’s enough interest, I’ll write up something more in-depth about this fairly under-utilized design practice.

Player Data

Player Data allows us to observe how our game is experienced in the wild, as opposed to how we believe the game will be experienced in our models and simulations or how we experience it as the developers. This is where we can finally see how close our design intent is to the real player experience.

Using this information, we can rebalance our systems to better achieve their intent – both individual systems and the game as a whole. Our more abstract models, those that combine multiple systems, are especially likely to benefit from Player Data as the interconnections between the systems will become more apparent.

For example, we may discover that our model for time-to-level presumed that a player would have acquired a weapon at level 2 only to realize that a poorly balanced gold economy prevented players from acquiring one until much later than we intended, significantly impacting early progression within our game.

Concluding Remarks

So there you have it, Game Economy Design in a nutshell. I genuinely hope that if you’re reading this, you’ve found it more than informative; I hope you’ve found it useful. If not, please reach out and voice your (hopefully well-worded) criticism. After all, much like Game Economy Design – really much like everything – this only gets better through critique and iteration. The diagrams, models, and simulations we make are always only our current best understanding of our designs, and we designers are typically in a constant struggle of improving our understanding of our designs as they change and evolve (roadmap and documentation be damned). These might represent the toolbox for game economy design, but the real “How” is communication and iteration.

Do the work, show it to your team, be open to criticism, then do it again and again until it’s polished – that’s the real how.

Until next time,
Keelan

The goal is to allow the player and their avatar to occupy the same emotional space.

Harrison Pink, Snap to Character: Building Strong Player Attachment Through Narrative

At Graewolv, while exploring the concept of the demon-powered first-person shooter, one question that kept nagging at my brain was who I was actually playing and why it led me to shooting people and interacting with demons in the first place. It bothered me that this didn’t have a straightup answer, or at least an answer that could make it comfortable to “occupy the same emotional space” as the character I played.

Shooting people can be fine in a military shooter. “You’re a soldier following orders” usually works, even if it carries significant historical baggage. But when put in another pair of boots it feels weird. Shooting people becomes murder.

Joel in The Last of Us murders some of the few remaining medical experts in the world in cold blood. He is written well enough — and we get enough time to sympathise with him — that we can still see Joel as the good guy. In any attempt at an objective analysis, he’s a selfish psychopath, but we can understand his motivation and pick his side over that of the nameless doctors in the game. In fact, I’m somewhat bothered by how easily some players can say “I would’ve done the same.” But in the end, we feel like we know Joel, which makes us side with Joel.

I wanted this to be resolved for VEIL too. You commit despicable acts of violence and this needs to be motivated so that the player doesn’t get uncomfortable occupying this emotional space and so that the violence doesn’t become too gratuituous.

These lines of thought made me look at role-playing as a design tool for exploring game concepts further. In this post, I’ll cover how I worked with it. Hopefully it can be interesting to other game designers out there. It’s a tool I still use whenever there’s a chance to do so.

If you’ve done similar experiments, I’d love to hear about it. Write a comment or e-mail me at annander@gmail.com.

Note that some of the stuff I’m about to share in this post is the property of Graewolv and is shared with their kind permission. Special shoutout to the incredible David Brochard, who drew all the concept art.

Wishlist VEIL on Steam: https://store.steampowered.com/app/2436490/VEIL/
Join the VEIL Discord server here: https://discord.com/invite/7JxqcDZ9Pq

Background

I started playing roleplaying games around the age of 10. It’s been my favorite hobby ever since, with a few breaks at times when life got in the way.

My approach has always been somewhat experimental, trying to find new ways of playing or just variations on existing ways, and rarely playing the same thing through more than one campaign. Experiments like building a scenario where all of the information is within the group, putting all conflicts between players, playing with multiple game masters, no game master at all, or playing court intrigues based on the assassination of Gustav III.

This has led me to focus on a number of things that I think make role-playing games unique and that makes them excellent as game design tools beyond being games in their own right.

Roleplay can be empathetic, where you try to imagine how another person thinks or feels and you act it out. You can roleplay an asshole, like playing Cyberpunk 2077 as a Corpo, because there’s a detachment between you personally and the avatar you are playing. It’s engaging to make decisions based not on your own morality, but on your interpretation of this other person’s morality. Real or imagined. This is equally true whether you are a player or a games master. Every participant can engage in empathetic role-play. It also stays true with one character on several players, one character per player, or multiple characters per player — we can still engage in empathetic role-play.

It can be exploratory, where you act out different things and find out what happens. Basically the FAFO (F*ck Around and Find Out) of role-play. Insult your friends. Kill the princess and rescue the dragon. Sail off on a ship instead of going down into the dungeon. Since the only limitation you have in role-playing is your own imagination, this element is one of the most unique that the hobby has to offer. It can also be used for more than just entertainment, such as exploring what may happen in a second Trump presidency. Exploration is related to empathy, but doesn’t have to be. It can also be purely for fun or as a method for pseudoformalised conjecture.

It can be mechanical, where you play through situations using a platform of rules to see where the rules lead. Maybe you want to have rules for detailed mech customization, for realistic firefights or fencing, for exploring the unknown, or for leveling up and unlocking new tools to play with. This is very similar to hex-and-counter wargaming, which incidentally is also where the roots of role-playing games are firmly planted. It’s an effective way to see where the game may need more or fewer choices, or if you may have forgotten something that needs to be designed in more detail.

It can also be narrative, testing or fleshing out the story or world-building. Role-playing games are extremely dynamic and pretty much all of the previously mentioned reasons to role-play clash fundamentally with the idea of a prewritten plot, but as a tool, narrative role-play is great. You can try out different villains to see how they work and see what kinds of interactions players expect, and you can work with language in interesting ways. In one test session a few years ago, the first question that came up in play was, “how do people in this world communicate?” Something the world-builder at the time (me…) had completely overlooked that became obvious through play when the characters needed to talk to each other.

Note that these four forms of role-play are not an attempt to classify or define anything, and they definitely don’t cover the full breadth of the role-playing game hobby. They are often mixed together in different ways and sometimes hard to separate from each other.

These four ways of approaching role-playing are consciously structured to answer relevant questions, and you should hopefully see the interesting space that starts to emerge between them.

Role-Play as a Tool

What the four forms help you do is push the game experience around the table towards empty spaces in your design. It helps you ask interesting questions and provide compelling answers. All of those answers won’t be what you actually use, but as a design process, role-play can be one of the fastest ways to explore your designs. All you really need is imagination.

You will be playing the characters and having the experiences you want your game to offer, without having to finish your game.

We can use empathetic role-play to sample our characters, factions, and conflicts. To figure out ways to make the world we are building or the villains we are introducing more compelling. It can also show us where our world-building may be missing something. If the hero may need a foil, for example, or if the conflicts sound a bit undercooked when put in motion, or become repetitive faster than we had anticipated.

Exploratory role-play allows us to push the boundaries and see what happens. It’s a great opportunity to let developers improvise solutions to the problems or missing designs that may come up, and essentially design the game through participation. When someone decides to kill the main quest giver, for example, that may be something the game needs to solve for. Or when a certain spell or weapon is used in an unconventional way. What’s important here is that you never say no. See where the exploration leads and make decisions after you have talked it through. Take notes, but avoid turning the play session into a meeting. The beauty of the process is that you can just throw stuff out that doesn’t work.

Mechanical role-play is a bit more tricky to make use of as a design tool, since it easily becomes a deep rabbit hole of mechanics design that are then only written for the tool and will never translate into its digital incarnation. Some of this can be worth a lot, since it can explain your intentions at a high level. But avoiding time waste is often a careful balancing act. If you focus on outcomes more than specifics, for example how many options you may choose from in customization, how much gold you make, or how much damage is dealt and taken, it’s still a valuable tool since it can hide large complex systems behind the improvised decisions of your players. You want the mechanics to be similar enough to your intended game to feel like it hits the same structural beats as your digital game would without only becoming a clunky version of it.

Finally, narrative role-play is quite useful as a tool, since it allows you to take a trip through your broad story beats and see how they connect. If something needs a higher pace, clearer clues, or other changes. In some ways, it’s like a script reading session with some additional improv. It can also make use of random generators like tables and cards to help you create a fitting story for your game or even to decide where you want the narrative to connect to procedural elements. It’s particularly useful for filling in gaps between the story beats you already have in mind. Together with empathetic role-play, you may even get to see how the factions and characters in the game interact over time, and you can surmise empathetically how the story should play out in ways that are hard to do with just a word processor.

ROLE-play

Let’s look at how to do this, in practice, by first looking at the roles involved. The avatars whose emotional space we are about to share. The role part.

If you’ve ever studied journalism, interrogation, questioning, or something along those lines, you should be familiar with the 5Ws (or 5W+H). They’re intended as a shorthand for getting to the meat of a story: Who, What, Where, Why, When, and How?

These one-word questions are extremely useful for any form of characterization, regardless of context, since they help you tell a whole story. You don’t need to answer all five at the character level. Some can be answered by the setting or through collaborative improvisation.

You can also consciously leave some of the answers blank in order to figure them out through play.

Who, of course, asks who was involved. Who did the thing, who was affected by it, and what a third party thinks about it. In journalism, three sources is a kind of golden rule: two people representing the opposite sides, and a third neutral party. Even better if you can have more than just one neutral party. This is a great way to think of scenarios for games too, since the player is often a third party engaging with an external conflict.

This was the trickiest one for VEIL, but the decision was to look at you as an occultist for hire. Someone who solves other people’s demonic woes in exchange for money and power. These “someone” were set as four specific factions in the game world, representing tradition, law, crime, and change. With those pieces in place, there was enough friction to create interesting missions.

What tells you about the thing that happened. Murder? Injury? Theft? Job opportunity? There’s another journalistic axiom that says, “does it bleed?” Because suffering and bleeding traditionally sells stories, so the more violence or trauma — or risk of violence or trauma — you can push into this, the better. Games rarely shy away from violence in the first place so simply making someone bleed won’t catch anyone’s attention. Instead, this goes into the high level activities that you’re going to engage in. Not the verbs of the moment, but the motivations behind them.

You exorcize demons and you take missions connected to that, but you also work for the power players of The City, running their (usually violent) errands. To explore this, a system for generating objectives was created. More on this later.

Where lays out the geography of the matter, so you know if you need to care or not. Closer to home tends to mean higher relevance, which is why local news papers fill a role in journalism: you care because you live there. But fantastic cities and other pure escapism works too, just not on the same instinctual level. Even with fantastical environments, it’s usually good to anchor the where in something recognisable.

The game takes place in The City. It has districts, it has class struggles, it has all the things you’d expect from a modern city but with a slightly gothic overtone. It’s Gotham City, in a way, but if Gotham City had demons from Hell instead of tragic villains with mental issues.

Why is trickier, since motives are not always clear and because opinions may differ. This kid did the crime because they play Dungeons & Dragons says one side, while the other says they were bullied in school. A consulted psychologist chimes in with something about sexual frustration. (Three sources, remember?) What we like the least is when there’s no explanation whatsoever, even if it can also make us run wild with speculation. Cliffhangers exist, after all. But we tend to more easily reach for the obvious explanation. Figuring out why is trickier in real life than for game design, because in game design we already tend to obsess over motivation. The trick is to connect this motivation to the motivation of the characters in the game world.

You’re a selfish sort of person that happens to do good by coincidence. An antihero. The reasoning behind this is that a player in an action video game of the VEIL kind, is inherently selfish. They want to get the next reward, collect the loot, finish the level, etc., and going back to Harrison Pink’s point on the avatar and player occupying the same emotional space this fits well with the goal. You pick your employers. You solve your problems. You get your rewards. The rest are a means to an end.

When isn’t fifth in relevance, it’s just how I’ve taught myself to remember these words (Who, What, Where, Why, When). It’s the time and the place, in history or the present. When can be very broad, such as “19th century Paris” or “Middle-earth in the Second Age.” It can be extremely specific; “At 03:45 last night.” If a major plot beat in your game is the assassination of a king, then when can also inform you whether something is happening before, during, or after this assassination. You can also leave when blank and figure it out through play, in case it’s one of the issues you want to resolve.

It’s not a flashback. It’s not the future. It’s the fictional world’s present, in a noirish gloomy perpetual fall season where it seems to never stop raining. (Because modern game engines obsess over real-time ray tracing, which makes reflections a thing.)

How will be the verbs. Your players’ inputs and intentions as supplied to the systems of the game, and what kinds of outputs they generate. What’s important if you want to make something interesting is to examine this at multiple levels. Your video game will more effectively demonstrate the second-to-second or micro loop of your game; shooting, jumping, taking cover, etc. But what the role-play tool can do is explore the minute-to-minute or macro loop, and potentially even the hour-to-hour or meta loop.

Shooting, summoning demons, completing objectives, failing objectives, working for the factions, introducing factions, revealing secrets, collecting ritual materials, getting tricked, etc.

role-PLAY

Now that we know the roles we will take on, we need to know how to play the actual game intended to explore them. At their core, role-playing games are formalized conversations. You talk, respond to what others are saying, and you may use some rules to generate outcomes that steer the conversation in unexpected directions.

The key differences between role-playing systems isn’t which polyhedral dice you roll or whether they take place in Narnia or Night City. It’s how truth is established and which parts of the conversation that we influence with mechanics.

Truth

Some variants of role-play use a referee, often called a game or dungeon master, that acts as a rules moderator and comes up with parts of or even the entire plot or story of the game you are playing. Others eschew this in favor of collaborative storytelling.

The key difference this makes is how truth is established.

• Authoritative truth. The game’s referee has the final say on what is true. Usually combined with one or more of the other forms of truth. In some games, the authoritative role can rotate between players or players can have authority over specific parts of the truth. Truth is established by the person(s) with authority.
• Pre-established truth. Lore. Whole geographies, histories, anthropologies, astrologies, and otheries. Can be your favorite IP, something you’ve written yourself, or what your favorite author came up with and published. Truth is established by what is written before play.
• Procedural truth. Often in the form of tables, charts, or dice rolls used to generate random outcomes, but it can also be the direct consequence of other forms of mechanics. Any entry or combination of entries could become true by rolling them at the point of generation, but you can’t know what the truth is until it’s put into motion. Truth is established by combining components in a given moment.
• Relational truth. Using relationships between people, places, or events, to establish what’s true. A hates B loves C trades with D; there’s the basis for our truth. The mechanics will typically push things, challenge things, and cause or handle conflicts of interest, but the relationships are still what are most important. If the king has an agenda, this agenda will affect what the king decides to do, for example. The agenda is true, but what the agenda makes the king do can only be decided in the moment. This is the primary vehicle for empathetic role-play. Truth is established in the moment, based on how things are related to each other.
• Situational truth. Where we don’t know what’s true in a certain situation until the situation plays out. A combat system won’t tell you who was injured until the dust (and dice) settle, just like we won’t know how casting a certain spell plays out until we’ve cast it and described its effects. We go through the motions, then we know what actually happened. Truth is established after the fact.
• Unreliable truth. Any variant of truth where the outcome can change after the fact. Maybe you roll to change it, or you collaborate, or you spend some kind of currency, or you rewind time because nah, that’s not what happened. Truth is established only after all unreliable steps have played out.

Mechanics

As mentioned previously, mechanical role-play is always at risk of wasting time if you write complex throwaway rules. Writing a deep combat system for a game that’ll ultimately be a first-person shooter is probably a waste, for example, because you are not actually solving any problems by doing so that you are not already tackling in your game engine.

For most role-playing games as tools, you need to touch on some or all of the following elements in your mechanics:

• Situations means rules for the kinds of scenarios you expect (or want) to happen in play. This can be very broad and may include genre expectations for your game, such as survival, firefights, construction projects, and so on. What’s important is to leave the potential outcomes open. A situation is the cause, it’s not the effect. It can represent the food shortage, but it won’t present for where to find food.
• Abilities describe characters. What they can or can’t do, but also as description. This doesn’t have to be detailed, but it can be. One project may need detailed lists or decks of cards that describe different capabilities, while others can use abstractions. This is the toolbox you are providing your characters with.
• Conflict doesn’t have to be armed and dangerous. It can be anything where there is a clear stake involved. Conversation, bartering, seeking aid, etc. One side wants to gain something and the other side stands in their way or needs convincing, cajoling, seducing, or other methods for changing their outlook. Role-playing games benefit from clear statements or triggers to tell you when a conflict has occured. When the first shot is fired, when the intent is stated; something to tell everyone playing that this is in fact a conflict. The clearer you can make this trigger, the better. But you can also skip this entirely, the way some screenwrights will just say “fight happens,” and then it’s up to the choreographers on the film to make it compelling.
• Scene is the moment of play, and may change key dynamics. This is where you can apply permissions, restrictions, and conditions in systemic terms. If the situation is a firefight, this is where you can add pouring rain, a particularly tough enemy, or other changes. If the situation presents the shortage, this is where you can collect the resources to solve it and where some other party may stand in your way. The scene is where it all comes together.

There are some practical ways you can approach making your test rules faster:

• Generic Mechanics. You can always start from a set of generic rules, such as Chaosium’s percentage-based Basic Role-Playing, Steve Jackson Games’ Generic Universal Role-Playing System (GURPS), Evil Hat’s Fate Core system, or Fantasy Flight Games’ Genesys. The simpler and more accessible the choice of rule system is, the better. Just like you don’t want to waste time building complex systems, you don’t want to waste time teaching them either.
• Proxy Mechanics. A lightweight version of using a generic system is to use proxy mechanics. This is when you take something like the combat system from Risk to represent battles, and perhaps use the cards from the board game Root to add some flavor. Using a proxy mechanic works best if it’s one that all participants already know.
• Focused Mechanics. You can also make extremely specific rules intended to model things that are unique about your game. Perhaps character customization is important to your game, and you decide to represent all the different parts with cards that let players have fun with the main ideas of this concept. Or you want to have a suppression system that allows you to force enemy AI to keep their heads down, so you model a simple rule system for only that rather than combat as a full simulation. Picking one or two things to turn into mechanics can be very effective, and lets you zoom in on exactly the things you want to explore while skipping everything else.
• Generators. Whether using decks of cards, random tables, or online generators, making use of random generators is a very powerful tool since you can construct them in such a way that they leave interesting blanks for you to fill during play.

Oathbreaker

The following example of a role-playing game as a design tool is from work I did for Graewolv on the upcoming first-person shooter VEIL. I served as Design Director for the project for about a year, in 2020-’21, and during that time it fell on me to explore the design in whatever ways I could while working on the early prototypes for the game.

It was an incredibly useful tool for me, that helped flesh out the different factions and missions in the game, and it was the key inspiration for this post even if it’s a tool I’ve used several times since.

Goals

Oathbreaker was written specifically to figure a few things out. As a foray into systemic design (of course), many of its more interactive elements worked better in digital form and were never included. But the playful ideas around changing reality and affecting things through the use of demonic powers were definitely included.

My design goals were:

• Figuring out who the player’s avatar is, what motivates them, and how they are connected to the world they live in. Empathetic role-play, considering what motivations the world provides based on the key “demon-powered” elements of the setting and making it plausible enough not to cause dissonance.
• What kinds of factions and different interests could exist in this world based on the player and how to generate conflict from the player’s goals. More narrative than empathetic, but one of the most effective parts of the tests when I look back at it today.
• Experimenting with missions, objectives, success, and failure. Mechanical role-play, as a way to figure out which kinds of missions felt more compelling than others, but also narrative role-play since it implied what kinds of story beats we’d be interested in pursuing if we took a more narrative direction with the game.

Some things were also actively avoided, since they didn’t really help the game’s design:

• Combat was largely ignored, because it would be designed in the first-person shooter in some detail and Oathbreaker couldn’t really solve any issues.
• Enemy design was also ignored, except as exploratory role-play to find inspiration on what kinds of opposition could be encountered in The City based on the factions involved.

Truth

Most of Oathbreaker is a conversation engine. We can set up some scenes and talk through how they play out. Because of this, it doesn’t use any authoritative truth but relies instead on procedural truth via random tables combined with situational truth and table consensus.

Cooperative Play

The digital game itself is cooperative, so it made sense to make Oathbreaker mostly cooperative too. We randomise things together, we create and discuss our characters together, and we generate and complete missions together. Each player does play a single selfish character, so sometimes they may not have enough reasons to cooperate, but then we can explain it using the goals and objectives. Discover more reasons for them to cooperate.

Sketch Maps

With an objectives-based game, it can help to think of a map as the sketch for a movie set. We don’t care so much about how it’s related to other sets, as long as it’s believable enough to work and has some measure of internal consistency. We should also have a good concept of how it looks like, as descriptive adjectives.

Role-playing games may refer to the areas on maps like this as “zones,” and the trick to making it interesting is to have enough of them.

In the below example, there’s just Mansion, Parking Lot, and Guard House. The mansion itself could just as easily have been subdivided into Kitchen, Atrium, Gym, Entrance Hall, and so on. How detailed we make it is up to us.

Mission Generator

The beating heart of Oathbreaker is a set of random tables that creates missions. It generates this in a number of steps.

First, a Goal is set, which gives you the reward you will be given if you complete the mission. You also figure out which Faction you are working for, and which faction you are working against.

Second, a very broad Location is determined. A Faction Claim, since it has to have ties to one of the power groups of the setting. It’s one of six districts of The City and provides some ideas on what you could find there.

Third, and illustrated in the screen grab below, you find out what the Mission Structure is, and then generate the objectives this requires.

Once all three steps have been completed, you have a mission to play.

Mechanics

For Oathbreaker, the focused mechanics approach fit quite well. It has mechanics for creating characters, playing objectives, changing reality, and making demonic pacts. No other mechanics are necessary.

Character Creation

Each character is a selfish individual that managed to gain access to the Veiled Path but chose to break their oath and leave as an oathbreaker. When characters are created, each player rolls to find out first who recruited them, what they did for the Veiled Path, who made them leave, and who they tried to find after leaving.

Each of these tables only has six entries, so that it’s fairly likely that some characters will share one or more of these. The idea is then that they also know each other and that these connections can be good or bad. This is good grounding for empathetic role-play. Maybe the recruiter was my brother, but also your lover. Or we had the same employer inside the Veiled Path, but left for different reasons. This creates situations where we may not trust each other and where we will automatically start to dig deeper into the game’s world.

It’s also great grounds for quickly generating a number of faces that can represent characters we’d encounter in our world. If we missed something at this stage, it will usually be obvious.

Soul

Soul is measured in dice placed on your character sheet or on the notes representing specific threats at a location. There was never a hard rule for how many of these dice you would start with, or if you should start with any at all. If someone opposed you when you tried to use magick, you’d roll dice from your Soul.

Sometimes, only creatures or characters with ties to demons have Soul. At other times, everyone has Soul. It’s a simple dial to turn..

Path

There are two paths in magical tradition. The right- and left-hand paths. Simplified, the saying is that “the right hand giveth, and the left hand taketh away.” What you would see as black magic follows the left-hand path.

For this system, which was just a paragraph or two long, the taketh and giveth was used literally. With the right-hand path, you could give someone dice from your Soul; with the left-hand path you could take dice from someone else’s Soul.

This way, dice can also be rolled to oppose such an attempt, or to transform into resources, damage, or something else, either for yourself or someone else. It’s an extremely high level abstraction since it made it possible to not commit to anything in particular.

Pact

Pacts are measured in debts that must be paid off with Soul. If you look at the character sheet above, each of Annie’s two pacts (the one with Tchort and the one with Naamah) has three diamond boxes where none are checked. Each time the demon’s quite considerable power is activated, the player needs to either spend one Soul by discarding a die or check a single box that must then be paid off with Soul later. (The observant reader will also see that you can use the left-hand path to take Soul from someone else to pay this cost.)

There was never a hard rule for when a demon’s drawback would trigger, since that was part of what was being explored.

Using This Tool

As a final note, let’s go over how you can use this tool yourself. This is by no means a checklist of things you must do. In fact, you should only do exactly what’s needed for your specific project and nothing more.

Goals

If your game has empathetic, mechanical, situational, or narrative components, you may benefit from playing a role-playing game that explores it. But before you do, consider what you want to get out of it. Set up some concrete goals, like what was done for Oathbreaker.

Characters

Use the 5W+H questions, as many of them as needed, and look at them through the lens of the following.

1. Theme. Start with a central theme stated as cleanly as possible. There are demons beyond the veil that are powerful enough to control reality.
2. Agendas. Move on to the different agendas that the theme provides. Wanting to control the demons. Wanting to serve the demons. Wanting to hide the demons.
3. Groups. Connect groups to the agendas, whether they are for, against, or neutral towards them. Law enforcement; those who want to hide the demons and maintain the status quo.
4. Individuals. Populate the groups with individual characters. Emmet the Corrupt Cop, working for those who want to keep everyone in the dark.

Rules

You can skip this step entirely, or you can put extra effort into it at any level of detail that you want. One of my current spare time projects uses a fairly in-depth board game element to test full-scale combat, even though it won’t translate into its digital form. This has been written because I enjoyed it, an element that is certainly more important for hobby projects.

1. Authority. Decide what kind of authority you want. The default tends to be a referee, but it’s not necessary, and for a more collaborative team of designers you shouldn’t have authority that is too centralised or bottlenecked to a single person.
2. Mechanics. Use proxies, think about situations and abilities, and dig into what characters can and can’t do, as well as the role of luck in the mechanics. Randomisation can be important to a game in order to generate tension through uncertainty, but in role-play as a tool, it can actually distract you from the conversation. Only add randomisation, success, failure, and so on, if it’s important as a representation of what your game is about.
3. Modularity. Since systemic design is my jam, and in many cases this benefits from a modular approach. If you can take any system and decide whether it’s active or not in a playthrough, this can help you zoom in or out as you need to. Oathbreaker does this in several ways, not least of all by making some of the concept’s core elements entirely narrative, such as the magick.

Play!

With just a page or two, maybe some dice, bring your team together and get to it. There’s no point to any of this if you don’t make use of it. Building a role-playing tool like this can definitely be an interesting intellectual exercise in itself, but the real magic won’t happen until you gather some other people around a table, friends or coworkers, and start exploring your game.

Systemic design comes down to making objects and rules and inviting the player to interact with them. This sometimes clashes with game design at large or the expectations of external stakeholders. This post is dedicated to some challenges that are facing systemic game design right now.

It won’t go into broader problems like financing or marketing — not in this post. This one is focused on design.

I would also love to hear about the challenges you are facing, as a comment or to annander@gmail.com.

Overcoming Recency Bias

Indie game developer Mike Bithell once tweeted that game design tends to favor the past five years’ most prominent hits. I’ve tried to put this in context in the past, writing about different broad “eras” of game design, but this is a considerable challenge for game design overall. Maybe the biggest one. Recency bias is one of the root causes for many of the other challenges described in this post.

The only way to overcome recency bias and broaden your personal references for games is to play games from different eras. To push yourself out of the five-year recency bias. Playing games from genres you don’t normally play and engaging with games and gaming positively rather than through hearsay or preferences.

Play lots of games and you will find both gems and turds along the way. Over time, this will make you a better game designer. Allegedly, Quentin Tarantino used to watch around 200 movies per year. Maybe as a designer you should take 30 minutes every morning to just try a game you wouldn’t normally play. Like a concept artist doing warmup sketches. Eventually, you’ll at least try as many games as Tarantino watched movies, and this will broaden your frame of reference.

Avoiding Reductionism

Call of Duty, which is a first-person shooter, has a sprint button that boosts your movement speed; therefore a game cannot be a first-person shooter without a sprint button.

This line of reasoning is design reductionism. Portraying a thing as represented by a specific part, thereby reducing the thing to this part. You can extend the same kind of argument to almost any genre or game, and sadly this is very common.

Many discussions on definitions in game design become reductionism. Not always intentionally, but whenever we say “X is not a Y because it doesn’t Z,” we’re falling into this particular trap.

Two ways where reductionism become game design obstacles are as denial and as obligation. X doesn’t have the feature, so we shouldn’t have it either; or, X has the feature, so we must have it too.

One way to avoid reductionism is to remember the Mechanics, Dynamics, Aesthetics (MDA) framework and its conceptual division and to categorize what you may be reducing accordingly.

If you look at sprint in Call of Duty (CoD) as a mechanic, for example, the running for cover to regenerate your health is the dynamic it leads to in combination with other mechanics. This means that a game that doesn’t have the regenerating health or even any cover to run for doesn’t benefit as much from a CoD-style sprint mechanic. If you borrowed only the mechanic, expecting the dynamic, you’d be disappointed.

Playing Less Reference Tennis

Since we don’t really have an established language around game design, and genre definitions lack unanimity, references to other games easily becomes the only common ground we have. But this easily leads to “reference tennis,” where you are bouncing different game references back and forth until someone mentions a game the other party isn’t familiar with, thereby dropping the ball and either ending the conversation or conceding it in some direction. This is not conducive of constructive design work. It’s often the worst possible kind of reductionism, or it’s simply a game developer form of might makes right.

Avoiding reference tennis and designing by reference requires that you move the conversation to your own game. This is where game design pillars, established facts, and a playable game with clear problems that require solving come in.

Actively avoiding references to other games during a game’s earliest design stages is the best way to try to build confidence in your design. Describe the experience, the emotions, the themes and mechanics; just don’t use other games to describe them.

There’s little use in trying to boil something as complex as a video game down into a single hook or elevator pitch line, because this often forces you to say something like “the mechanics of X plus the art style of Y,” and that will have as many interpretations as it will have listeners.

Disbanding the Design Committee

Designing by committee is where no one dares to have a vision and everyone defers to everyone else. It either leads to no decision-making at all or to decisions that are as vanilla as they can be so that no one in the committee risks feeling sidelined.

As a colleague liked saying, it’s the heat and the pressure that makes the diamonds. Creative discussions, constructive disagreements, making things someone feels strongly about, and scrapping things that didn’t work out even when someone did feel strongly about it. Game development can’t afford fragile egos and also requires a diversity of skills that makes it a poor fit for auteur directors. Put a bunch of experts in a room and let them be experts.

In reality, the only way to disband the design committee is to find people you can talk to and work with in an open and constructive manner. People you trust and who trust you. It also helps to have a clear vision, with the already mentioned pillars, facts, etc.

Stop Chasing Trends

Making a game that is in one way or another extremely close to something already on the market can be an efficient way to make a buck or two. Not always, of course, but the number of games that carry a World of Warcraft painted aesthetic, make use of extraction shooter mechanics, or strives to be another roguelike, Minecraft, or deckbuilder speaks for itself.

Like reductionism, this often comes from risk aversion. If you see someone else demonstrating the success of a thing, you imagine that you can skip directly to the profits by making a similar thing. This is sometimes called the packaged goods model, where marketing is functionally more important than the product being marketed. Coca Cola vs Pepsi marketing often tries to sell an identity more than a beverage, for example.

But games are not packaged goods. Games are creative products where gamers can express themselves through play or experience something outside of themselves. Gamers are also highly likely to vote with their wallets if you only give them something that is a repackaged version of something else. Some trends die faster than they appear, and it’s hard to know this before you get started.

Considering how much business in game development that is handled by people from packaged goods industries, this issue is probably not going anywhere anytime soon. But please, as a designer, try not to chase trends. You don’t have to make the next extraction shooter survival game.

Don’t be an IP Tourist

When Kane returned in a coma with that thing clinging to his face, you had no clue what it was. It frightened you nonetheless. Its strangeness, its alienness, frightened you.

But that terror can’t be replicated anymore. We’ve labeled the creature a “facehugger” and made it available as plushies, on mugs, and adorning the jewel cases of the special collector’s edition DVDs we hold on to but haven’t watched for fifteen years.

Yet, more Alien-branded games are made. More scenes with facehuggers are featured, often predictably. It’s no longer a creative choice, it’s a must-have. Something to check off a list when we’re on Alien safari. Android, check. Distress call, check. Facehugger, check. It’s the same when characters in The Mandalorian keep joking about how bad Storm Troopers are at shooting. That was never a joke: it’s something the fans made fun of. To the Storm Troopers, what they are doing is real and most definitely not a joke.

All of this is IP tourism. It adds nothing new, it doesn’t contribute anything. It only repeats the key selling points of a franchise either as fan service or as a lazy attempt to retain an existing audience by using self-referential in-jokes that only the “real fans” will get.

In my opinion, the best games in the Halo franchise were Halo: Reach and Halo 3: O.D.S.T, simply because they did things that weren’t just IP tourism but took the IP to new places and painted the war against the Covenant in a different light. We didn’t need more Master Chief, even if the original games set the stage, and we got the Fall of Reach story and a noirish detective story with Halo framing instead.

If you ever have a chance to work on a cool IP, don’t be an IP tourist. Build a real experience that explores that IP in some way.

Make Decisions Matter

The key to Sid Meier’s classic statement on decisions is the word interesting. A game is a series of interesting decisions. If you remove the emphasised word and the player is making decisions that were all created equal or from only partial information, then the player no longer has any meaningful decisions to make, they are just along for a ride.

I always felt that the style of choices you made in series like Mass Effect were this type of choice. You could choose to be altruistic or evil and you’d get an immediate often spectacular response, but the longterm effects were usually not that relevant. From your own intentions, you could end up making a right or wrong choice, but it would often be either completely obvious or entirely opaque and you’d be picking mostly as a gut reaction. Someone dying in a cutscene at the end of the game isn’t the consequence of an interesting decision, it’s just a shallow reminder that a decision was made.

If you are interested in a deeper take on choices and consequences, you can watch Bob Case’s excellent video on the subject. To me, this is where systemic design truly shines, as interacting systems will be restricted more by which inputs and outputs you allow than by content.

Focus on Art Direction over Fidelity

Remakes have always been a thing in video gaming, ever since the early days. But a trend that may have started with the Halo: Combat Evolved Anniversary Edition remake and that deeply affects game design is to take a game and increase its visual fidelity to a modern standard without considering the core art direction of the original game.

To contextualize this a bit, production pipelines for video game graphics were revolutionized in the early 2000s with the gradual but widespread introduction of Physically-Based Rendering (PBR). The techniques were described in the 1980s, but what set this off for games was partly a book by Matt Pharr, Wenzel Jakob, and Greg Humphreys (link is to the table of contents for the 2023 edition).

Before PBR, much work with textures had to be manually tweaked until it looked right. With PBR, artists could start relying on real world measurements and assign material properties that always provide realistic results.

What many 3D remakes then do is that they take a pre-PBR 3D video game and they remake the visuals for PBR. A realistic look from a purely practical perspective, but also one that doesn’t respect the original often carefully crafted art direction.

In a pre-PBR game, the environment and interactive objects could be designed to read more easily. In remakes with full PBR and high resolution textures, everything looks the same. More often than not, you need to compensate for the loss of art direction, for example by using dabs of contrasting paint to highlight what the player can interact with.

Two things to note is that this in no way means PBR is bad or that it shouldn’t be used, or that this is limited to remakes. All it does is that it shows you how tricky it is to match game design and art direction when all you are doing is making something look “more realistic” by increasing fidelity. Movies, which are filmed in the actual real world, very rarely focus on looking realistic, but will instead use lighting, composition, and other techniques to make sure that the right information comes across.

Allow art direction and game design to inform each other, and please stop letting whoever paints all the yellow paint have all the fun before the hero even gets there.

Stop Commodifying Player Imagination

We can look at old school gaming — as far back as hex and counter wargames — as fantasy systems. Our imagination takes the output of dice rolls and table results and conjures up fantastic chains of events. Like how you can imagine the anti-tank crew in a game of Advanced Squad Leader sit there and whisper hoooold to each other in Mel Gibson fashion while you, the player, are hoping that the tank will move one more hex so your chances of hitting are increased before you tell your opponent “I shoot!” All of that tension is a natural and emergent effect of the game’s systems. The actual physical experience of playing the game is just a bunch of cardboard counters and dice.

Player imagination is the most powerful tool in a game designer’s toolbox. Yet, in many types of games, the design doesn’t really allow it. Instead, we sell you the permission to imagine things and actively restrict you to only imagine things we can charge money for. The official experience.

You won’t find freeform customization as often as for-purchase skins of popular characters. The workings of our fantasy systems are paywalled, and there will always be a next purchase for you to make if you want to satisfy that fantasy you had in mind. Be it the all-black gothic armor set or the bladed boomerang or something else that you didn’t actually want or need.

Players are creative anyway, of course. They will always draw penises if you give them half a chance, and some can spend hours in your character creator to imitate their favorite celebrity. But the reason this is a challenge for systemic design is that the official allowed content that we sell is never going to be half as cool as what players can discover on their own if you let them.

Facilitate player imagination, don’t commodify it.

Use Technology to Solve Problems

Generative AI has been saved for last, because I’m not personally that worried. If people can find inspiration from a ChatGPT chatbot or get past programming obstacles that are hindering them in their work in some way thanks to some flavor of Copilot, then that’s great. Use the tools that make you more effective.

But one thing is problematic: people’s faith in Large Language Models (LLMs) and other black box technologies. How people from outside the industry can come in and tell us that hey, you can use AI to make your enemies smarter or to write dialogue for you. Because yes we can, and we’ve been able to for decades, but we shouldn’t and we won’t. The amount of text that we put into our games has never been the problem, and having to expensively teach our enemies how to do actions we could much more easily build systems for is a bottleneck more than a solution.

To make more dynamic and responsive games, we don’t need a new black box, we need to develop the paradigms around how we think and design. We need to design games in more systemic ways. Complex systems start from simple systems that work — they are not made out of black boxes. LLM technology, Machine Learning, Reinforcement Learning, and much more, are useful algorithms that we should put to good use when they solve problems for us. But only then.

The best stuff we can get out of the LLMs probably hasn’t appeared yet, and it won’t do so until we get past the stage of overhyped excitement that seems to dominate the tech space today.

Solve problems, don’t buy into hype.

There, but certainly not back again.

It’s sometime around the late 1980s/early 1990s that some developers start talking about a “game engine” as a thing. Maybe not even using the term “engine” yet, but in the form of C/C++ libraries that can be linked or compiled into your project to provide you with ready-made solutions for problems. Color rendering for a particular screen, perhaps, or handling the input from a third-party joystick you want to support. The two Worlds of Ultima games are built on the Ultima VI: The False Prophet engine, as a decently early example.

When you put a bundle of these ready-made solutions together, it becomes an engine. In those days, the beating heart would usually be a bespoke renderer. Software that transforms data into moving pictures and handles the instruction set of whichever hardware it’s expected to run on.

What id Software perhaps revolutionised, if you are to believe John Romero in his autobiography Doom Guy: Life in First Person (an amazing book), was to make developer tools part of this process. To push for a more data-driven approach where the engine was simply the black box that you’d feed your levels and weapons and graphics into.

This is how we usually look at engines today: as an editor that you put data into and that makes a game happen. To give some context for this, I thought I’d summarise my personal software journey. One stumbling step at a time, and not all of it strictly engines.

QBASIC

When I grew up in the 80s/90s, I was often told that programming was simply too hard for Average Joe poor kids like myself. You had to be a maths genius and you had to have an IQ bordering on Einstein’s. At a minimum, you needed academic parents. If you had none of those, programming wasn’t for you. Sorry.

This is the mindset I adopted and it affected my early days of dabbling profoundly. Where I lived, in rural Sweden, there were no programmer role models to look up to, and there was no Internet brimming with tutorials and motivation either. Not yet. We didn’t have a local store with game-stocked shelves or even ready access to computers at school. Again, not yet.

But eventually, maybe around the age of 10 or so, I ran into QBASIC on the first home PC that was left over from my dad when he upgraded. Changing some values in the game Gorillas to see what happened was my introduction to programming in its most primitive form.

Ultimately, I made some very simple goto-based text adventures and even an attempt at an action game or two, but I didn’t have enough context and no learning resources to speak of, so in many ways this first attempt at dabbling was a deadend.

It’s clear to me today, looking back, that I always wanted to make games, and that I would probably have discovered programming earlier if I had been introduced to it properly.

Hex Editing

Even if I felt programming was too complicated, I did pull some games apart and attempt to change things under the hood. One way you could do this was by using a hex editor (hex for hexadecimal) to manipulate local files. This is something you can still use for many fun things, but back then hexadecimal was part of how games were packaged on disk. (Maybe it still is and I’m letting my ignorance show.)

The image below is from Ultima VII: The Black Gate seen through a modern (free) hex editor called HxD. As you can see, it shows how content is mapped in the game’s files.

Back then, my friends and I would do things like replace “ghoul” in Ultima VIII with “zombi” (because it has to be the same number of letters), or even attempt to translate some things to Swedish for some reason. (To be fair, the Swedish translation of Dungeon Keeper 2 is in every way superior to the English simply because of how hilariously cheesy it is.)

To grab this screenshot I could still find the file from memory, demonstrating just how spongy and powerful a kid’s brain really is…

Build Engine

With Duke Nukem 3D, and to a lesser extent DOOM, I discovered level editors. The Build Engine, powering the former, was a place where I spent countless hours. Some of the levels I made, I played with friends. I particularly remember a church level I built that had sneaky pig cops around corners, and how satisfying it was to see my friends get killed when they turned those corners.

How this engine mapped script messages to an unsigned byte, and memorising those tiny message codes and what they meant, were things I studied quite deeply at the time. I fondly remember a big level I downloaded at some point (via 28.8 modem I think) that was some kind of tribute level built to resemble Pompeii at the eruption of Vesuvius. It’s a powerful memory, and I’m quite actively not looking to find that level to get to keep the memory of it instead.

The fact that walls couldn’t overlap because it wasn’t actually a 3D engine were some of the first stumbling steps I took towards seeing how the sausage gets made.

Half-Life

Several years after playing around with the Build Editor, I discovered WorldCraft. I built a church here too for some reason, despite being a filthy secular Swede, and tried to work it into a level for the brilliant Wasteland Half-Life mod. This was much harder to do, since it was fully 3D, and you ran into the limitations of the day. The engine could only render about 30,000 polygons at a time, meaning that sightline optimisations and various types of load portals were necessary. Things I learned, but struggled with anyway. Mostly because Internet was still not that great as a resource. Had I been smarter, I would’ve started hanging around in level design forums. But level design never stuck with me the way programming eventually would.

During this time, I also learned a little about tools like 3D Studio Max, but as with programming in the past I thought you had to be much better than I was to actually work on anything. My tip to anyone who is starting out in game development: don’t bring yourself down before you even get started. It can deal lasting damage to your confidence.

DarkBASIC and DarkBASIC Pro

During the late 90s and early 2000s, something came along that finally “allowed me” to make games, at least in my head. At first it was DarkBASIC, which is a BASIC version with added 3D rendering capabilities produced at the time by the British company The Game Creators.

This discovery was amazing. Suddenly I was building little games and learning how to do things I had only dreamed of in the past. None of it was ever finished, and I always felt like I wasn’t as good as people from the online communities. It’s pretty cool, however, that Rami Ismail hung out in these forums and that I may even have competed against him in a text adventure competition once.

Along the way, I did learn to finish projects however. I made two or three text adventures using the DarkBASIC sequel, DarkBASIC Professional, and even won a text adventure competition all the way back in 2006 with a little game I called The Melody Machine.

RenderWare Studio

In 2005 I enrolled in a game development education in the town of Falun, Sweden, called Playground Squad. It was the first year that they held their expanded two-year vocational education for aspiring game designers, programmers, and artists. My choice was game design, since I didn’t feel comfortable with art or code.

This was a great learning experience, particularly meeting likeminded individuals, some who are still good friends today. It’s also when I started learning properly how the sausage gets made, and got to use things like RenderWare Studio. An early variant of an editor-focused game engine, where designers, programmers, and artists could cooperate more directly to build out and test games.

It was never a hit the way Unity or the UDK would become, but I remember it as being quite intuitive and fun to play around with. We made one project in it, that was a horde shooter thing. I made the 3D models for it in Maya, which isn’t something I’ve done much since.

SimBin Engine

I don’t remember what SimBin called their engine, but I got to work in two different iterations of it in my first real work at a game studio, as an intern starting in 2006. One engine was made for the older games, like RACE: The WTCC Game that became my first published credit. The other was deployed on consoles and was intended to be the next-generation version of SimBin technology. There I got to work on particle effects and other things, that were all scripted through Lua or XML if I recall correctly. Writing bugs in bug tools while performing light QA duties. To be honest, I’m not sure SimBin knew what they needed any designers for. But I was happy to get my foot in the door.

My best lesson from SimBin was how focused it was on the types of experiences they wanted. They could track the heat on individual brakes, the effects of the slipstream behind a car in front of you, and much more. They also focused their polygon budget on the rear of cars, since that’s the part that you see the most. You typically only see the front of a game model car in the mirror, rendered much smaller than you see the rear of the car in front of you.

This is an example I still use when talking about where to put your focus: consider what the player actually sees the most.

Unreal Development Kit (UDK)

I did work with the visual scripting tool Kismet (precursor to Blueprint) and Unreal’s then-intermediary scripting language UnrealScript in my spare time in 2006, for a year or so. It had so many strange quirks to it that I just never got into it properly.

First of all, Unreal at the time used a subtractive approach to level editing unlike the additive approach that everyone else was using, which meant that level design took some getting used to. With BSP-based rendering engines, the additive norm meant that you had an infinite void where you added brushes (like cubes, stairs, cones, etc.) and that was your level. In the UDK, the subtractive approach meant that you instead had a filled space (like being underground) where you subtracted brushes to make your level. The results could be the same, and maybe hardcore level designers can tell me why one is better than the other, but for me it just felt inconvenient.

Never got into UDK properly, because I always felt like you had to jump through hoops to get Unreal to do what you wanted it to. With Kismet strictly tied to levels (like a Level Blueprint today), making anything interesting was also quite messy, and you had to strictly adhere to Unreal’s structure.

Starbreeze Engine

My longest stint at a single company, still to this day, was with Starbreeze. This is the pre-Payday 2 Starbreeze that made The Chronicles of Riddick: Escape from Butcher Bay and The Darkness. The reason I wanted to go there was the first game, the best movie tie-in I had ever played. A game that really blew my mind when I played it with its clever hybridisation of action, adventure, and story.

Starbreeze was very good at making a particular kind of game. Highly cinematic elements mixed with first-person shooter. If this makes you think of the more recent Indiana Jones and The Great Circle, that’s because Machinegames was founded by some of the same people.

Starbreeze Engine was interesting to work with, with one foot firmly in the brushy BSP shenanigans of the 90s (additive, thankfully), and the other trying to push forward into the future. Its philosophies, including how to render a fully animated character for the player in a first-person game, and how scripting was primarily “target-based” in the words of the original Ogier programmer, Jens Andersson, are things I still carry with me.

But as far as the work goes, I’m happy that we don’t have to recompile our games for 20 minutes after moving a spawnpoint in a level anymore. (Or for 10-24 hours to bake production lighting…)

Nuclear Fusion

During my time at Starbreeze, I finally discovered programming and C++ and learned how to start debugging the Starbreeze Engine. Something that made my job (gameplay scripting) a lot easier and finally introduced me to programming in a more concrete way at the ripe age of 26.

At first, I tried to use the DarkBASIC-derived DarkGDK to build games in my spare time, since I understood the terminology and conventions, but soon enough I found another engine to use that felt more full-featured. It was called Nuclear Fusion. It was made by the American one-man company Nuclear Glory Entertainment Arts, and I spent some money supporting them during that time. Now they seem to be gone off the face of the Earth unfortunately, but I did recently discover some of the older versions of the software on a private laptop from those years.

As far as projects go, I never finished anything in this engine, but I ended up writing the official XInput plugin for some reason. Probably the only thing I ever wrote in plain C++ to be published in any form.

Unity

Having built many throwaway prototypes by this time, but never quite finished anything, I was still looking for that piece of technology that could bridge the gap between my lower understanding of programming and that coveted finished game project I wanted to make. At this point, I’m almost six years into my career as a game developer and my title is Gameplay Designer.

It’s in 2011-2012 that I discover Unity. On my lunch break and on weekends, I played around with it, and it’s probably the fastest results I’ve ever had in any game engine. The GameObject/Component relationship was the most intuitive thing I had ever seen, and my limited programming experience was an almost perfect match for what Unity required me to know.

Unity became my first introduction to teaching, as well, with some opportunities at game schools in Stockholm that came about because a school founder happened to be at the Starbreeze office on the lunch break one day and saw Unity over my shoulder. “Hey, could you teach that to students?” All of two weeks into using it, my gut response was “yes,” before my rational brain could catch up. But it turned out I just needed to know more than the students, and I had a few more weekends to prepare before course start. Teaching is something I’ve done off and on ever since—not just Unity—and something I love doing. Some of my students have gone on to have brilliant careers all across the globe, despite having the misfortune of getting me as their teacher at some point.

Since 2011, I’ve worked at four different companies using Unity professionally, and I have been both designer and programmer at different points in time, sometimes simultaneously. It’s probably the engine I’m most comfortable using, still to this day, after having been part of everything from gameplay through cross-platform deployment to hardware integration and tools development in it.

You can refer to Unity as a “frontier engine,” meaning that it’s early to adopt new technologies and its structure lends itself very well to adaptation. You set it up to build a “player” for the new target platform, and you’re set.

Today it’s more fragmented than it used to be, with multiple different solutions to the same problems, some of which are mutually exclusive. If you ask me if I think it’s the best engine, my answer would be no, but I’ll be revisiting its strengths and weaknesses in a different post.

Unreal Engine 4

The same person who pulled me in to teach Unity also introduced me to Unreal Engine 4 in the runup to its launch. I was offered an opportunity to help out on some projects, and though I accepted, I didn’t end up doing much work. It coincided with the birth of my first child (in 2013) and therefore didn’t work out as intended. I’ve still used Unreal Engine 4 quite a bit, including working on prototypes at a startup and teaching it to students.

It’s a huge leap forward compared to the UDK, maybe primarily in the form of Blueprint. Blueprint is the UE4 generation of Kismet and introduced the object form of Blueprints that you’d be used to today. Rather than locking the visual scripting to a level, Blueprints can be objects with inheritance. They are C++ behind the scenes and the engine can handle them easily and efficiently using all the performance tricks Unreal is known for.

Funnily enough, if you came from UDK, you can still find many of the Kismet helper classes and various UnrealScript template shenanigans are still there in Blueprint and Unreal C++ but wrapped into helper libraries. It’s clearly an engine with a lot of legacy, and the more of it you know before starting the better.

Toadman Stingray

Autodesk Stingray is an engine that was developed from the Swedish BitSquid engine after Autodesk purchased it and repurposed it for their own grand game engine schemes. BitSquid was a company founded by some of the developers that once made the Diesel engine, that was used at the long-since defunct Grin and later Starbreeze-merged Overkill game studios.

When I worked with it, Autodesk had discontinued the engine, but three studios were still using it and supporting it with internal engine teams. Those three were Arrowhead, Fatshark, and Toadman. I worked at Toadman, as Design Director.

As far as engines go, Stingray has some really interesting ideas. Two things struck me, specifically. The first is that everything in the engine is treated essentially as a plugin, making it incredibly modular. Animation tool? Plugin. Scripting VM? Plugin. The idea of a lightweight engine with high extensibility is solid. Not sure it was ever used that much in practice, but the intention is good.

Another thing I bring with me from those days isn’t strictly about Stingray, but about a fantastic data management tool called Hercules that Toadman used. It allowed you to make bulk changes to data, say doubling the damage of all weapons with a single command, and was an amazing tool for a system designer. It decoupled the data from the game client in ways that are still inspiring me to this day. Sadly, since earlier this year (2025), Toadman is no longer around.

Unreal Engine 5

The jump between Unreal Engine 4 and Unreal Engine 5 is not huge in terms of what the engine is capable of, even if Epic certainly wants you to think so (Lumen and Nanite come to mind). But there is one big difference and that’s the editor itself. The UE5 editor is much more extensible and powerful than its older sibling, and is both visually and functionally a complete overhaul.

There’s also a distribution of Unreal Engine 5 called Unreal Editor for Fortnite that uses its own custom scripting language called Verse, that is said to eventually be merged into the bigger engine. But I simply have no experience with that side of things. My amateur level designing days are long-since over.

Probably the biggest change between UDK and UE5 is that the latter wants to be a more generic engine. Something that can power any game you want to make. But in reality, the engine’s high end nature means that it’s tricky to use it for more lightweight projects on weaker hardware, and the legacy of Unreal Tournament still lives on in the engine’s core architecture and workflows.

As with Unity, I don’t think it’s the best engine. But I’ll get into what I consider its strengths and weaknesses in a future post. I’ve spent years working with UDK, UE4, and UE5, in large teams and small, but haven’t released any games with them thus far. Projects have been defunded, cancelled, or otherwise simply didn’t release for whatever reason.

Star Stable Engine

Imagine that you release a new update for your game every week, and you’ve been doing so consistently since 2013. This is Star Stable Online—a technical marvel simply for the absolutely insane amounts of data it handles. Not to mention the constant strain on pipelines when they’re always in motion.

My biggest takeaway from working alongside this engine last year (2024) is its brilliant snapshot feature that allows you to to save the game’s state at any moment and replay from that moment whenever you like. Even shared with other developers. This approach saves a ton of time and provides good grounds for testing the tens of thousands of quests that the game has in store for you after its 14 years (and counting) life span.

You may look at its graphics and think, “why don’t they build this in Unreal?”, but let’s just say that Unreal isn’t an engine built to handle such amounts of data. The visuals may improve, but porting it over would be a much larger undertaking than merely switching out the rendering.

Arrowhead Stingray

Can’t really talk about it. It’s Stingray, but at Arrowhead, and it powers Helldivers 2. Like the engine’s Fatshark and Toadman variants, it has some features and pipelines that are unique to Arrowhead.

Summary

• QBASIC (around ’89 or ’90?)
• Hex Editing (early 90s)
• Build Engine (early-mid 90s)
• WorldCraft/Hammer (late 90s, early 00s)
• DarkBASIC/DarkBASIC Pro (late 90s, early 00s)
• RenderWare Studio (’05 or ’06)
• SimBin Engine (’06) First professional work.
• UDK (’05-’07)
• Starbreeze Engine (’07-’12)
• DarkGDK/Nuclear Fusion (’09-’12)
• Unity (’12-today)
• Toadman Stingray (’17-’20)
• UE4 (’14-’21, sporadically)
• UE5 (’21-today)
• Star Stable Engine (2024)
• Arrowhead Stingray (2025-?)

Today

I hope I get to play around with even more engines than I already have. They all teach you something and expand your mind around how game development can be done.

At the end of the day, it doesn’t matter which engine you use, and it’s not often that you can make that decision yourself anyway if you’re not footing the bill.

Like an old colleague phrased it, “there’s no engine worse than the one you’re using right now.”

Fortunately, there’s also no better engine for getting the work done.

The object-rich world is crucial for making systemic games. Similarly, the state-space of your game can be used to describe the entirety of your design and to facilitate more holistic game development.

But it’s about time that we talked about data, since it keeps coming up. How to describe the smallest pieces of your simulation and the effects of this choice on your game.

This nicely rounds out the design space for systemic games.

State and Context

One of the key things I have long wanted to solve is how to handle data as an external element to a project to facilitate both modularity and extensibility. The engine will have to interface with the data, but you shouldn’t have to chase down specific objects in a level to modify them.

To better understand why this matters, let’s establish some terminology.

Data

We’ve defined data as almost everything a computer is operating on, and something we tend to bundle up and package as content using various tools. At this level, all data is more or less the same.

• Everything in a game is data.
• Data is often bundled up as content.

State

A person’s state of being or state of mind define data in the moment: how you are right now and what you are thinking about or feeling. In computer science, state is remembered data; things that are stored and can be referenced.

• State is data that is stored and can be referenced.
• Something’s ‘state’ is its value when checked in the moment.

Context

Context, in computing, is the minimum amount of state that needs to be saved to be able to restore the same state at a later point (where “context-switching” comes from). But for this post’s purposes, it’s more literal.

The local context is an object’s local state at a given moment in the simulation.

• Local context is an object’s local state at a given moment.

Once we start introducing more objects to the simulation, their relationships will result in relative context: object-relative state in a given moment. Comparisons expressed as state. For example, whether one object is moving faster or slower than another.

• Relative context is an object’s state in comparison to other objects.

State Properties

When you plan out your state, it’s also relevant to consider how and by who it will be used. If you change a value that only exists for a single-player game it’s probably fine to treat it more carelessly. If players decide to go in and change it, this will not amount to cheating since it’ll only change their local gameplay experience. It’ll functionally be modding.

But if you are building a multiplayer game with server-side authority and a network backend, you need to make different considerations and plan your data much more carefully.

• Hard-coded. Data is “hard-coded” when it’s written directly into program code and compiled, making it impossible to iterate on the data while the game is running and complicating knowledge sharing and tweaking. Initial test data, like move speeds or jump heights, can sometimes be hard-coded to make sure something works.
• Constant. A named variable that is available throughout a given scope. Pi and the gravitational constant, or your game’s easy mode damage baseline (see later) can be constants.
• Variable. A variable is a name for data that changes at runtime, or at least can change at runtime. Move speeds, jump heights, and other classics are examples of variables that may be manipulated during play.
• Tweakable. A number that developers can access readily and that may need several rounds of tweaking. This type of number benefits from templating (see later) and from being externalized from the object(s) it is affecting. Individual values for long lists of items, like the Damage value for all of your 250 guns, or the gold costs for your 1,000 items.
• Metric. A metric is something that gets sent to a backend and can be used to analyze how players engage with your game. It’s rarely a variable or even a tweakable that gets sent this way. May be something as simple as telling the backend which level is started or the duration of a challenge the player played.
• Optional. This is data, typically a variable, that is accessed directly by the player. The font scale, color of the UI, music volume, etc.; but it can also go deeper, as with the many customization options you have in a game like Civilization.
• Persistent. Data is ‘persistent’ when it needs to live across multiple game sessions. You don’t need to make constants persistent, for example, or really anything that is represented by content, but anything that should stay the same between play sessions will have to be persistent. Current health, current level, location of character in the game world, optional settings (like volume), etc., will usually be expected to be persistent.
• Visible. Whether a number or other point of data is player-facing is a crucial consideration. Anything that is player-facing will usually require filtering (e.g., Imperial vs Metric, or other localization), and needs to be more carefully designed than data that only exists in the simulation. Damage and health numbers, character names, dialogue subtitles, etc.
• Content. Usually when a game is referred to as data-driven, it’s because files on disk are defining how things get set up. Tweaking this data is about changing it, sometimes through an external tool or suite of tools. A premade level, an enemy with all its key data assigned through a registry file, or a 3D asset.
• Global. Data that is accessible everywhere in the game is global. This is generally the only scope consideration you need to do when you are designing your state space, since individual scopes are not as relevant or even automatic to the context you are working in. Quest facts, like if you have met Character Y before can be global, and optional and player-facing data is often global.
• Input. Data that comes from hardware input is a bit different, since you rarely want your game to access it directly. Rather, it’s good practice to use some kind of abstraction between the input and the gameplay action triggered by it. Analogue X/Y stick movement axes, touch gesture events, button presses and releases, etc.
• Replicated. Data that gets sent to clients across a network to simulate the same game state is said to be replicated. Which data a game replicates is an extremely important design consideration for multiplayer games and is therefore an important property to consider. Input sent to a server, timed events sent across peers in peer-to-peer networking, etc.
• Fuzzified. Data sets that has variable degrees of membership are referred to as “fuzzified” data, and we get into that later in this post. It’s a technique that can be used to turn tricky numbers into human-readable form and to allow computers to communicate in a way that somewhat resembles human conversation. How ‘warm’ a temperature is, how ‘damaged’ a character is, etc.
• Partial. If merely to track connections between pieces of data, it can be relevant to flag something as only part of a larger whole. If you separate data into base, attribute, and modifier, for example, noting that the data is partial and how can be very relevant. Any data that needs other data to be functional; maybe Strength is added to Damage and then multiplied by HitLocation; these three are then all partial pieces of data from the damage function.
• Temporary. Data that has a start and end time during the simulation and that isn’t technically variables. They can still be parts of key functions, but are not something that the developer is actively tweaking. Match points that are tossed out after tallying, score multipliers that are accumulated for just a single second, etc.

State Representation

All games represent state in some way, even if we may not think of it or plan it as such. There will be health numbers, speeds, and all manner of things to represent, and sometimes this grows organically from implementing the features we want.

“Eh,” the designer says to the programmer, “we need to add a Headshot Damage Multiplier to each enemy now that we have the helmeted one.” Additional state gets added, and often to every single object in the game, and not just to the ones that need it.

How we represent this state in our logic is what this section is about. It can be just a flat number in a spreadsheet somewhere; what Michael Sellers would call the “spreadsheet specific” layer of your data. But it can also use one of many existing ways for easy or efficient data representation.

Conceptual Separation

When you work with numbers in games the only thing that is certain is uncertainty. You will change the numbers down the line. But the great risk of any numeric system that changes it that you get cascading effects if you don’t plan for which levers you need beforehand.

To do this, you can separate the numbers up front into Baseline, Attributes, Modifiers, and Functions. You can read more about this in a previous post on gamification.

Spreadsheet Specific

King Arthur may have his Excalibur; as system designers we wield Excel! For many game designers it’s natural to gravitate towards spreadsheet tools for data management. To separate things into rows and columns and make any relevant changes as needed.

Because of this, you will find variations on spreadsheet support for most game engines. It’s quite common to use the comma-separated values (CSV) format to export them from spreadsheets and pull them directly into your game engine.

I use spreadsheets for a lot of things but very rarely for direct authoring of data. This is a preference, of course, but also comes from how spreadsheets represent data. Since it’s natural to simply add another column to represent a new feature for an object, even if it means that there’ll be an additional “0” in that column for every object that doesn’t use it. The risk for bloat is very high.

Some of the procedural implementations of features described in the post on building a systemic gun come from a spreadsheet specific line of thinking and is far more common than you’d expect.

XML

The Extensible Markup Language (XML) is sometimes used for registry files that can be compiled into game data, and sometimes in portable formats where the XML remains accessible for developers or players to change the values if they want. Variants of XML were extremely common in the past but is something I haven’t personally seen as much in recent years except in its XAML format for UI construction.

XML has a very readable and extensible format, with tags and closing tags that tell the parser what to expect. It can also be generated easily using custom tools.

<gameobject type="Character">
    <name>Goblin</name>
    <class>Fighter</class>
    <str>10</str>
    <hp>4</hp>
    <equipment>
        <item>Dagger</item>
        <item>Letter to home</item>
    </equipment>
</gameobject>

JSON

Probably more common today than XML, the JavaScript Object Notation (JSON) has pretty much the same benefits but is maybe slightly more readable. Which one you prefer, if any, is mostly down to preferences.

JSON is used extensively in web development and database formats, which is probably one of the reasons it’s become more and more common.

{
    "type": "Character",
    "name": "Goblin",
    "str": 10,
    "hp": 4,
    "equipment": [
        "Dagger",
        "Letter to home"
    ]
}

Lookup Tables

A lookup table is an array that contains all potential instances of some piece of data and allows it to be referenced by index. In any situation where you end up copying the same data over and over, potentially into hundreds or even thousands of instances of identical values, this can be a big way to save yourself from headaches (and memory waste).

Imagine a flow field, for example. A space that represents the vector force you’d apply to any unit walking a grid based on which grid cell it’s currently occupying. This could have each cell use its own Vector3D, with three separate floating point numbers per cell, or it could store a single byte with a lookup table index. The Vector3Ds would only be stored in a single place. This shrinks the amount of data you need to use by a lot and makes it easier to plan the data from a design perspective.

Since many types of state will repeat, lookup tables are a good way to represent them and can also provide a single location for developers to tweak values. For example, the damage modifier added from difficulty could live in a difficulty lookup table.

Array<Vector3D> FlowfieldVectors = 
{
    Vector3D::Zero,                                         // 0
    Vector3D::Up,                                           // 1
    Vector3D::Down,                                         // 2
    Vector3D::Left,                                         // 3
    Vector3D::Right,                                        // 4
    Vector3D::Normalize(Vector3D::Up + Vector3D::Right),    // 5
    Vector3D::Normalize(Vector3D::Up + Vector3D::Left),     // 6
    Vector3D::Normalize(Vector3D::Down + Vector3D::Right),  // 7
    Vector3D::Normalize(Vector3D::Down + Vector3D::Left),   // 8
};

Scripting Language

If you want more than just object representation in a serialised format, a good way to achieve it is by using an external scripting language. Where spreadsheets and object notation allow you to populate your game with data, a scripting language allows you to provide logic along with the data.

The below example is taken from the excellent book Programming Game AI by Example, by Mat Buckland, and shows a small Lua script defining a state (State_GoHome) for a state machine. A good example of what you can turn into data-driven parts of your game with a scripting language.

This is often within the realm of what a technical designer would be working with, since it allows behavior to be constructed outside the compiled game client and therefore makes iteration a lot faster.

State_GoHome = {}

State_GoHome["Enter"] = function(miner)
    print ("Walkin home in the hot n' thusty heat of the desert")
end

State_GoHome["Execute"] = function(miner)
    print ("Back at the shack. yer siree!")
    if miner:Fatigued() then
        miner:GetFSM():ChangeState(State_Sleep)
    else
        miner:GetFSM():ChangeState(State_GoToMine)
    end
end
  
State_GoHome["Exit"] = function(miner)
    print ("Puttin' mah boots on n' gettin' ready for a day at the mine")
end

If you push it even further, you can even make the scripting language a player-facing element, but then you’re obviously going into a different realm than data handling.

Key-Value Pairs

Context the way I refer to it in this post is inspired by Elan Ruskin’s approach to dialog on Left 4 Dead. In his own words (from the book Procedural Storytelling in Games), “A context is a single key-value pair such as PlayerHealth:72 or CurrentMap:Village5. For performance reasons it’s best to use numeric values as much as possible, so for string values such as names, consider internally replacing then with unique symbols or hashes.”

A key-value pair can be represented in many different ways in code and is often used in data structures like maps and dictionaries. You’ve probably already made use of them many times before.

template <typename KEY, typename VALUE>
struct KeyValuePair
{
    KEY key;
    VALUE value;
};

World Properties

Inspired by Jeff Orkin’s world state representation, one way you can represent state is by using a union in C++ or explicit memory layout in C#. Each piece of state will always take up the same amount of memory, you can pool it easily, and you can use it across your game to describe the state of individual objects.

In the case of Goal-Oriented Action Planning (GOAP), this state is used to represent the current setup of the world so that enemy AI can make up a plan to execute. The state is handled as nodes in a graph with the edges represent actions. A goal-first A* algorithm handles the planning.

This way of representing runtime state has other benefits too. One of them is that it can be decoupled from the objects that the data represents and can then be used for other intermediary operations as well.

How it looks in the paper:

struct SWorldProperty 
{    
    GAME_OBJECT_ID hSubjectID;    
    WORLD_PROP_KEY eKey;    

    union value    
    {       
        bool   bValue;       
        float  fValue;       
        int    nValue;       
        ...    
    }; 
};

And here is how the paper demonstrates the use of a world property:

SWorldProperty Prop; 
Prop.hSubjectID = hShooterID; 
Prop.eKey = kTargetIsDead; 
Prop.bValue = true; 

“If the planner is trying to satisfy the KillEnemy goal,” writes Jeff Orkin, “it does not need to know the shooter’s health, current location, or anything else. The planner does not even need to know whom the shooter is trying to kill! It just needs to find a sequence of actions that will lead to this shooter’s target getting killed, whomever that target may be.”

In other words, it’s enough to store exactly what you need right now as world properties, and not treat game state as a runtime database.

Tags

Tags have a lot in common with keywords in card and board game design. It’s the use of a single word or few-word sentence as shorthand for a game rule or exception. Some creatures in Magic: The Gathering deal their damage before other creatures get to deal theirs, for example. A rule effect referred to consistently as “First strike.”

This same principle can be applied to game state too. As a descriptor (“Elf”), for conditional reasons (“Immunity.Fire”), or as a modifier (“Burning”). Consider a concept such as damage types for example. Just a damage number is fine, but you may want to qualify certain types of damage. Maybe a Piercing weapon does less damage to skeletons, or is better protected against by a chainmail armor. Then Piercing can be a tag applied to all three: weapons, enemies, and armor.

Most game engines use tags in one way or another. They may be developer-facing strings that get hashed at compile-time or they can be sent as a stream. Some engines do none of this automatically, however, and may expect you as the developer to not do unnecessary string comparisons or other expensive things at runtime. (As a general rule you should always avoid comparing strings to each other: compare their hash, length, or other cheaper thing instead.)

struct Tag
{
    // A hash of the original string, used for fast comparisons.
    int32 Hash;

    // An index into a single array where all the strings can be found.
#ifdef _DEBUG
    int32 StringIndex;
#endif
};

With a tag specified, and the developer-facing strings present somewhere, you can then create a structure for comparing groups of tags against each other and to test if specific tags are present. Of course, you may want to make the strings player-facing too and expose it completely to the game, but that’s not a requirement.

struct TagCollection
{
    Array<Tag> Tags;

    void AddTags(Array<Tag>& NewTags);

    // Has this specific tag.
    bool HasTag(Tag& Tag);

    // Has any of the tags in the other collection.
    bool Any(TagCollection* Other);

    // Has all of the tags in the other collection.
    bool All(TagCollection* Other);

    // Has exactly the same tags as another collection.
    bool Exact(TagCollection* Other);
};

Maybe you want to do additive trait-matching, and check if an armor has Resistance.Piercing before you deal damage with a sword that has Damage.Piercing. Or you want to collect tags as context before you do fuzzy pattern-matching.

Simply put: tags are extremely useful.

Data Assets and Fuzzy Sets

Many struggle to remember the exact number 9.80665. But if we refer to it as Gravity we don’t have to use the number. We can also change it down the line in a single place if we suddenly want things to behave differently across our game. When we do this, we fuzzify the data. We use words to describe it, as with variables in code.

This can be done in a template (or C# generic), for example:

template <typename T>
class DataAsset
{
    T value;

public:
    DataAsset(T new_value) : value(new_value) {}
    T GetValue() const { return value; }
    void SetValue(T new_value) { value = new_value; }

    // Serialization and other fun stuff!
};

With a template like this, you can easily add saving and loading, comparison checks, and other handy ways of reusing the concept of data across your game. It’ll all just be added to the DataAsset class and you can make all of them live in a single place in memory, on disk, or whatever you want.

DataAsset<float> Gravity = DataAsset<float>(9.80665f);

It’s straightforward to use, even if this variant would still rely on hard-coded numbers, and it’s generally a better idea to use external JSON or other scripting methods that can be changed without having to recompile your code.

The real power of fuzzification is that you can start referring to numbers conceptually and not just as plain numbers. This doesn’t just simplify the conversation, it also means you don’t have to painstakingly change that price point for a gazillion individual items.

struct Prices
{
    DataAsset<int> cheap = DataAsset<int>(5);
    DataAsset<int> ok = DataAsset<int>(150);
    DataAsset<int> costly = DataAsset<int>(2200);
    DataAsset<int> expensive = DataAsset<int>(17000);
};

This same principle can be applied to sets with more than just one point of data. We will then want to define fuzzy sets where your input will have a degree of membership with each value in the set.

struct FuzzyKeyValue
{
    float key;
    float value;

    FuzzyKeyValue(float _key, float _value) 
    { key = _key; value = _value; }
};

template <typename T>
class FuzzySet
{
    T object;
    Array<FuzzyKeyValue> keys;
    
public:
    FuzzySet(T _object, Array<FuzzyKeyValue> _keys)
    {
        object = _object;
        keys = _keys;
    }

    T GetObject() { return object; }

    float Evaluate(float t)
    {
        // Assert that there are at least two keys; pointless if not

        for(auto i = 1; i < Keys.Num(); i++)
        {
            auto a = Keys[i-1];
           auto b = Keys[i];

            if(t >= a.Key && t <= b.Key)
            {
                // Return the 'degree of membership' of the supplied t
                return Lerp(a.Value, b.Value, (t-a.Key) / (b.Key-a.Key));
            }            
        }
    }
};

Let’s grab an example of something fuzzified from the Internet. In this case temperature:

To represent this in the simple code from before, it’d look something like this:

// Low
keys_low = {
    new FuzzyKeyValue(1f, 0),
    new FuzzyKeyValue(1f, 10),
    new FuzzyKeyValue(0f, 20)
};

FuzzySet<string>("Low", keys_low);

// Medium
keys_medium = {
    new FuzzyKeyValue(0f, 10),
    new FuzzyKeyValue(1f, 20),
    new FuzzyKeyValue(1f, 30),
    new FuzzyKeyValue(0f, 40),
};

FuzzySet<string>("Medium", keys_medium);

// High
keys_high = {
    new FuzzyKeyValue(0f, 30),
    new FuzzyKeyValue(1f, 35),
    new FuzzyKeyValue(1f, 60)
};

FuzzySet<string>("High", keys_high);

To finally make practical use of this data, we can wrap a number of sets together, like the example below, to find out how warm a certain temperature is.

struct FuzzyTemperature
{
    FuzzySet<string>[] Temperatures =
    {
        FuzzySet<string>("Low", keys_low),
        FuzzySet<string>("Medium", keys_medium),
        FuzzySet<string>("High", keys_high)
    };

    string Evaluate(float t)
    {
        string returnString = "";
        auto evaluation = 0.f;
        
        for(auto set : Temperatures)
        {
            auto eval = set.Evaluate(t);
            if(eval > evaluation)
            {
                evaluation = eval;
                returnString = set.GetObject();
            }
        }

        return returnString;
    }
};

Predicate functions

A predicate function is a function that returns a single boolean true or false from supplied parameters. It’s an excellent way to test the validity of different situations at runtime and graduates state into its relational equivalent, which we can call context.

Many world property unions will effectively do the same thing, such as the kTargetIsDead property example illustrating a desire for the target to be dead. A predicate function is where we learn what is true at runtime.

This can be simple and effectively reusable, for example if you have a resource object that can be reused for any number of resources:

bool ResourceCheck::ResourceBelowThreshold(const float Threshold) const
{
    return PlayerData.ResourcePercentage < Threshold;
}

Since predicates can be used for almost anything it can make a lot of sense to keep a bunch of them around in a gameplay-scope helper library. For the following examples, I was a bit lazy, but you can see how quickly this becomes useful. For example, if InFront and FacingSame are both true at the same time, it would be the contextual requirements for a classic video game stealth takedown.

static bool InFront(Transform* Self, Vector& TargetLocation)
{
    return Self->InverseTransformPosition(TargetLocation).Z > 0.f;
}

static bool Behind(Transform* Self, Vector& TargetLocation)
{
    return Self->InverseTransformPosition(TargetLocation).Z < 0.f;
}

static bool Left(Transform* Self, Vector& TargetLocation)
{
    return Self->InverseTransformPosition(TargetLocation).X < 0.f;
}

static bool Right(Transform* Self, Vector& TargetLocation)
{
    return Self->InverseTransformPosition(TargetLocation).X > 0.f;
}

static bool FacingSame(Transform* Self, Transform* Target)
{
    auto FacingDot = Vector::Dot(Self->Forward(), Target->Forward());
    return FacingDot > .9f;
}

Once you have these helper functions, you can use them in code to generate tags, populate bitmasks or lookup tables, or determine what happens when objects hit each other. You can use them to generate context queries for dialogue or to qualify gameplay interactions.

Bitmasks

A bitmask means using a variable’s individual memory bits as flags. With a byte, you can store 8 bits. With a 32-bit integer, you can surprisingly enough store 32 bits. Many tutorials you’ll find will become shock-full of boolean flags faster than you can blink. A “bool,” though it stores the equivalent of a bit, is still one byte of memory due to the smallest addressable thing in memory having that size. A bitmask is therefore a way to not fill your memory with unnecessary waste while only recording bits anyway.

For the purposes of data, it’s also a convenient way to bundle related information together. A good example is spawn points and spawning in general. If you have, say, five different game modes and you want to be able to support all five using different spawn points, you can use a bitmask to store this information for each spawn point.

enum GameMode
{
    assassinate = 1 << 1,
    infiltrate = 1 << 2,
    steal = 1 << 3,
    defend = 1 << 4,
    horde = 1 << 5
};

int32 CurrentState = assassinate | infiltrate | steal;

// Set a bit
CurrentState  |= 1 << defend;

// Clear a bit
CurrentState &= ~(1 << defend);

// Toggle a bit
CurrentState ^= 1 << defend;

if((CurrentState & GameMode.assassinate) == GameMode.assassinate)
{
    // 'assassinate' mode is supported.
}

Asset Data

Last, but certainly not least, there are many ingenious ways to use asset data to store information. I will mention just a few, to give you some pointers, but suffice it to say that one reason technical artists are in high demand is that clever solutions to pipeline problems can save considerable amounts of time and money even for small projects.

The same principles can be used in many different ways to store systemic data and state.

Keyframes

Animation keyframes are used to store the positions, rotations, and scales of bones that are weighted to skinned meshes. This doesn’t have to be an animated character but can just as easily be a piece of cloth or parchment, or even a whole level.

The latter was a way for Legacy of Kain: Soul Reaver to represent the two different worlds that the player could shift between. One keyframe per world (out of two).

Vertex Colors

Using vertex colors to paint objects is tried and true, but when you texture your objects you may no longer need it for this purpose. This opens up countless other opportunities to store data in your mesh objects. For example, Vagrant Story used vertex colors to store its baked lighting. A technique that worked quite well at the resolutions for that game.

Most game engines have support for one full RGB vertex color per vertex. It’s possible to store more than one vertex color per vertex too, such as is the case in The Last of Us Part 1, where the different vertex color channels are used as mask values for things like mould, dirt, and cracks.

Furthermore, vertex colors can be accessed at runtime as well, and can then be used for updated live information. Say, the heat or magnetism generated by an object. I don’t know that this is how Splinter Cell does its heat vision, but it could be.

U-Dimensions

Something that has been mentioned before is how Neon Giant used the “U-dimension” (UDim) workflow not as a means to map more textures to an object but as a way to create masks simply by the act of UV-mapping a mesh.

This technique is quite clever and relies on mesh UVs (which are simply coordinates; “XY” was taken) using normalised values as a standard. I.e., values between 0 and 1. So by storing coordinates at higher values, like 1-2 or 2-3, you can map more than one set of UVs to the same object.

You can use this for anything where you’d use a mask or map more than one texture to the same object. It could be the albedo and metallic of a PBR material, as for Neon Giant, or you could map it to other properties such as bounciness or Resistance.Piercing.

Which One?

When you pick which way to represent your data, you need to consider four factors:

• Which tools pipeline you are already familiar with. Using UDims and other mesh techniques only make sense if you feel at home in a 3D suite, working with meshes. Similarly, you should only use CSVs and spreadsheets if you’re already comfortable with them or want to learn.
• Which problems you are solving. If your game is tied to a backend, JSON makes a lot of practical sense since it’s already speaking the language of the web. But if you want players to customize your game, it may make more sense to use a scripting language.
• Which levers you will need for testing and balancing. This is the most important, and the one that requires most design and planning. If you need to go back to an external tool every time something must be changed, whether that’s Excel or Blender, some changes may become too cumbersome to test.
• How the data will be communicated. Both internally, between objects in your game, and towards the player. Some things will be developer-facing only, others will be player-facing. Making sure to have one source of truth is extremely important.

Hopefully those pointers can help you at least consider how to represent your data. There are many ways that these things are tied together ultimately. Objects, data, state-spaces, etc., and there are more ways than can ever be summarised in a post like this.

I will come back to this post to extend it when new things crop up. So if you have any suggestions for clever data representations, please send them to annander@gmail.com and I’ll consider adding them along with a thank you.