Game Balance is a fundamental part of Game Design. It describes how values and game mechanics relate to each other. Game balance has the power to elevate and uniquely shape the player’s experience – likewise you can have game systems of world-class design, but if the game isn’t balanced it can completely ruin the whole experience.
While some games come pretty close, there is no such thing as a “perfectly balanced” game – given enough variables there will always be dominant strategies, OP characters and combos. Even worse, carefully crafted game mechanics that are completely underutilized because they’re not viable due to poor game balancing.
It helps to think of the goal of a “balanced game” a bit differently: Ensure that a certain player experience is achieved that is in line with the objectives that you as the game designer have defined for your game.
In this article we’re going to explore five different ways on how you can approach game balancing for your own game, at any stage of development.
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Game Balancing Methodologies
There are many different methodologies you can use to approach game balancing. People often tend to think about game balance as only the mathematical aspect of it, namely “figuring out the numbers” – the reality is that game balance is much more than that. It’s as much science as it is art (in the most cases).
On a very high level, there’s three major aspects to consider when it comes to game balancing:
- ⚙️ Systems: Understanding the ways in which the game works and how features are connected is essential before even thinking about game balance.
- 🎲 Numbers: Figuring out which values you have and how numbers relate to each other is at the core of this discipline.
- 🧠 Psychology: Player perception and the numerical truth aren’t aligned most of time.
Game balancing is almost per definition an iterative process, meaning that you will make changes to the game, test it, and make further adjustments as needed. You will need to consider all of the three aspects above when doing so. This cycle is then ideally repeated until you are either satisfied with the resulting player experience or until some or all project/business goals have been hit.
Various methodologies that can and should be used for balancing games include:
- 💡 Intuition & Experience: You’re an expert in a certain field and want to make a system behave in a certain way – that’s where the designer’s experience comes in.
- 🌍 Genre & Competitor Expectations: Your game will have competitors which will bear some resemblance to your game’s systems and features. Use their knowledge.
- 📈 Mathematical Modeling: Use math to establish and understand how numbers behave in relation to each other in your game.
- 🎮 Playtesting & Focus Groups: Have people such as yourself, the team, loyal players or even total strangers play your game and observe them.
- 📊 Game Analytics: A form of behavioral analytics used to extract metrics and data such as KPIs from your game and use them to understand how players are playing your game.
These methods are not exclusive to each other – ideally all are used in some capacity, if applicable. Some are more important at various stages of a project’s lifetime or iteration cycle. These methodologies all have their own set of pros, cons and pitfalls that you should consider.
Intuition & Experience
When you’re designing a game, chances are you have at least some ideas on how you want the player experience to be (and you should). Early on in a game’s development cycle intuition and experience can play important roles in game balancing, as it can provide you as the designer with a sense of what feels right and what doesn’t.
Contrary to popular belief you can start early with game balancing – at this stage you want to establish the broad strokes and not get lost in fine-tuning and details, as you will likely make adjustments to your game design as the project develops. Knowing when to move on is ironically one of the most time-consuming skills to acquire when it comes to game development – as only having played, designed and developed many, many different games will give you the confidence to rely on intuition and experience at this stage.
Consider the three creatures above – what roles would you envision for them? How would you make sure they stand out from each other? These aren’t easy questions to answer and depend heavily on the game you’re developing the context in which players would encounter them. The important part is to define what you want them to be and then use this as a guideline to inform your numerical modeling.
Another angle to consider is if your game mechanics are based on real-world concepts or phenomena – research and use models and values that already exist. If they are too complicated, abstract them – this grounds your game balance in reality, will give you a frame of reference and may make it easier for your players to grok your game mechanics.
However, it’s important to note again that intuition should not be the only method used in game balancing – apply it to figure out the broad strokes, ideally early on in the development cycle. Harness your intuition to inform other more data-based methodologies, such as mathematical modeling to provide a more complete picture of how the game is supposed to work and what parameters and values are needed.
Genre & Competitor Expectations
Understanding the market and your competitors is beneficial for a lot of reasons, but a major one is game balance. Maybe you’re reluctant to categorize or label your game, but unless you’re creating a highly experimental avant-garde game it will most certainly fall into some genre and it’s very likely that the game you’re developing shares at least some systems and mechanics with other games out there.
Play your competitor’s games and consciously think about how they are working – not only will you learn a lot and likely get some inspiration for your own game, you can get an understanding on how other designers have solved certain balancing or design problems you might encounter in your own game too. If you can’t find direct genre competitors, pick systems and game mechanics and compare those.
Consider the balancing of the game and it’s systems – Where are the imbalances if you believe there to be any? If you wanted to correct those imbalances, what are their underlying causes and how would you go about fixing them? Putting your ideas in writing is always a good exercise too.
Other players (or even yourself!) might indeed expect certain aspects from your game based on their own experience with similar games – this is called “genre expectation“. Lets take a first-person shooter for example – it’s reasonable to assume that a shotgun in a FPS game will be less effective than a sniper rifle at distance – assumptions and expectations like these already give lots of clues on how to balance a game and can then directly influence your mathematical modeling.
Expectations should be guidelines that inform your approach to balancing, they are not hard rules to follow. Should you want to break these expectations – both in systems or balancing – you should have a good reason to do so.
Mathematical modeling can be a very powerful tool. In contrast to the two earlier methods, this approach uses mathematical equations and simulations to model a game’s mechanics in order to predict how they will behave under different conditions. You’re essentially creating a numerical model of your game (e.g. in a tool like Excel or Google Sheets) and will be simulating how values will behave in relation to each other.
This approach can provide a more objective view of the game, as it can quantify your intuition and provide data-driven insights into the game’s performance. This can be especially useful for designers who may struggle with making subjective decisions about a game’s balance.
Take the units and their roles we’ve defined earlier – we can first define some attributes such as health, damage and defense and then assign relative values to each of the units based on the roles we envision for them. Our stalwart tank for example might have tons of health points compared to the meager health pool of the glass cannon. This approach can then be taken a step further and be refined into concrete numbers, such as the actual health values that appear in-game and are used for combat calculations and so on.
The important part here is that you create a theoretical model that helps you and your team achieve the player experience you envision. You can compare this numerical model to your mental model and act accordingly: Are roles among your units not pronounced enough? Further set apart their relative values. The tanky unit dies too fast? Increase it’s concrete numbers, such as health or defense points.
Such a model will also help in identifying major issues early on, ideally before you actually release your game. It will also help with playtesting – proving (or disproving!) hypotheses you might have based on your intuition and expectations, compared to your mathematical (and mental) models.
For this method to be most effective it’s important that your game systems and features – such as your feedback loops and compulsion loops – are as mature as possible. This is especially true when it comes to fine-tuning and ideally you have the broad strokes of your game design in a final state, as hard as that may be. Otherwise it’s like changing the engine of your car while you’re driving it.
Playtesting & Focus Groups
Playtesting is honestly one of the most underestimated and at the same time most important methods to balance a game. It involves having a group of players play the game and provide feedback on various aspects of your game (such as the difficulty, progression, etc). The players could be people such as yourself, the development team, loyal players or even total strangers.
Playing what you’ve designed is the equivalent of dogfooding, meaning that you play what you have balanced – as obvious as it sounds, you’d be surprised on what you can learn about your own game if you just play it. You can actually learn to take off the developer’s hat and view your game through the lens of a player – one ugly truth about the games industry in general is that too many developers don’t play their own games, unfortunately.
Keep in mind that feedback from testing will be inherently biased and you should ideally conduct your playtests by observation – meaning you watch players play instead of asking them outright what they think – that’s because what players say they want isn’t what they actually want or need. Of course you want to hear what what they have to say but you shouldn’t just blindly trust it. Confirm it with your models and hypotheses.
Observe behavior and separate words from actions as much as possible – but keep in mind that if the overwhelming majority is vocal about some issue in your game, they likely have a point. Take it seriously, but determine the root cause of the problem before you act on it.
Based on this feedback you can formulate an action plan and make adjustments to your game balancing and mathematical models – or in egregious cases even go back to the drawing board and iterate on the game’s systems and features.
The purpose of game analytics is to produce data that can help developers make decisions about player behavior and business operations. Ideally your game is hooked to some form of analytics tool that tracks all sorts of metrics, so that you can examine the game’s performance. Depending on your project, team and company these tools can range from basic measurements to whole analytics platforms which track a plethora metrics requiring a whole team of data scientists, designers and product managers to analyze, parse and evaluate said data.
A straightforward example of game analytics would be to have a video game track how many times and at which points in a level players die and then have that data sent back to you in some form of analytics interface – this way you would know which segments of a level are too difficult in comparison to others.
The diagram above illustrates another very common game analytics readout: The first time user experience (FTUE) funnel. This metric seeks to answer how many players who have started or installed your game are still around at various stages of play. The way this works is that you would define important progression points (such as starting the tutorial) and then send an event every time a player completes said step to your analytics tool.
You can then use this data to get an idea for where players churn (stop playing your game) and identify potential issues. In the example above 14% of all players stop playing in stage 1, a good indicator that there’s a problem. Maybe the game is too easy, or too hard, maybe players are confused or certain mechanics aren’t explained well – whatever the issue is, it helps pinpointing problems in your models.
A third example is to track how often a certain item is bought or how often abilities are used in relation to each other – this data can then be used to in conjunction with playtesting to get a more accurate understanding of your game’s current balance and help you make informed adjustments to the numerical models of your game.
There are many ways through which game balancing can be approached.
Early in development start with the broad strokes and rely on your intuition and take cues from your competitors – then as the project matures, shift towards more data-based methodologies such as mathematical modeling. Confirm your hypotheses by playtesting and cross-reference your findings with metrics from game analytics. Following this general approach will put you on a good path towards are balanced game!
In any case this should give you some ideas on how to approach game balance at a high level. The specifics of course are highly dependent on the game that you’re developing: it’s systems, mechanics, genre and the player experience that you want to build.
I’ve only glossed over the individual methods and there’s many more words to be written about game balancing. If that sounds interesting to you, please subscribe to the GameDevGems YouTube channel!
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About the Author
Written by Steve Haßenpflug, a seasoned game designer with a strong product & technical background. His focus is on creating engaging games for companies who want big results. GameDevGems is a passion-project of him.
Steve has developed top-grossing AAA games for IPs beloved by players around the world (Angry Birds, Trolls) with international companies (NBC Universal, DreamWorks, Rovio) and helped bootstrap gaming startups in the early stages of seeding. He’s an expert in mobile free-to-play mechanics.