(Pictured Above: An illustration of what I imagine when I think of the delicate touches and fixes of a designer)
Unlocking the Secrets to Competitive Game Balance: Is Data Alone Enough?
In the intricate dance of game development, striking the perfect balance is akin to capturing lightning in a bottle—a quest for harmony that is as elusive as it is essential. For indie developers, the challenge of testing game mechanics, particularly those involving movement, often hinges on a critical, yet scarce resource: playtesters. But what happens when you're operating with a shoestring budget or a skeleton crew? Does the key to equilibrium lie in numbers, or is there more to the game than meets the eye?
(Pictured Above: Heatmap Data I created for T.I.M.E)
AAA titles may boast armies of testers, both paid and voluntary, amassing a wealth of data that can be meticulously sifted to fine-tune every aspect of gameplay. But for the indie developer, resources are often not as plentiful, even for the fortunate few who manage to gather a reliable testing troupe.
Historically, developers have turned to innovative methods pre-testing, like Unreal Tournament's foray into genetic algorithms for weapon balance. Today, the frontier has expanded to include neural networks, teaching AI to play—and balance—the game itself. Yet, this technological sorcery often fails to capture the human element—the 'feel' that is so integral to a player's experience.
(Pictured Above: An Excerpt of Unreal Tournaments Process for Genetic Algorithms)
Consider the metrics that often dominate balance discussions: Damage Per Second, Time-to-Kill, Kill-to-Death Ratio. These figures sketch an outline of balance, but they leave the canvas of movement largely unpainted. For shooters, movement is typically a fixed variable, and consistent across the board. But introduce dynamic movement—power-ups that tweak player speed or influence damage—and the equation becomes exponentially more complex.
In the realm of competitive shooters, the intuition and 'feel' of a designer remain invaluable, a testament to the artistry of game creation. Yet, as player demands for fairness and precision escalate, these subjective qualities must be complemented by a more rigorous approach to game balance.
Faced with a deficit of data and a surplus of variables, developers confront a pivotal choice: to employ Deep Mathematics and High-Dimensional Modelling or embrace an intransitive balance that is enhanced by the strategic depth of instant rematches. One approach requires the designer to arduously reconstruct the missing data. The other approach simplifies the problem to relationships and offers the player a dynamic environment ripe for trial and error, continuous strategy refinement, and psychological one-upmanship, cultivating a deeper metagame with every replay. Broadly speaking there are a multitude of other systemic approaches other than intransitive balance, but its elegance and simplicity make it ideal for our purposes here.
(Pictured Above: The Intransitive Relationship of an ancient game)
Intransitive balance is a concept as old as Scissors, Paper, Rock—a cyclical hierarchy where every option has a counter. It's a principle subtly woven into class-based shooters like Team Fortress 2, offering a rock-solid foundation for balance. Yet, how does one apply this to a classless movement shooter or any indie game swimming in the uncharted waters of dynamic gameplay?
(Pictured Above: Our game T.I.M.E and a shameless plug)
The answer, it seems, is to design not for balance but for options. To provide players not with a perfect system, but with the tools to navigate imperfection. This philosophy is the essence of systemic design, where, instead of numbers implicitly shaping relationships, it's the explicitly crafted relationships that dictate the numbers. In our project, T.I.M.E, this took shape through the ability to rewind time post-mortem, granting players the chance to alter their fate, to strategize anew within the chaos of play. All whilst relying on the relationships they knew between powers, weapons, and movement to define what synergies they might use against their opponent.
It's important not to forget this human factor. Even in the seemingly random Scissors, Paper, Rock, the psychological play—body language, patterns, tells—injects a layer of strategy that no algorithm can predict. It's a stark reminder that at the heart of game balance is not just data, but the unpredictable pulse of human interaction. When the logic of a game is clear beyond the numbers and can be understood via intuition and relationships. Then the natural human thing to do is to evolve that game into a meta-game.
In my journey through the data deserts, I've discovered a key insight that you, too, might employ when traditional data is scarce: streamline the issue and focus on holistic relationships. After all, the quest for game balance transcends mere statistical symmetry; it's about sculpting an experience that resonates with balance for the players immersed in it. Because, in the grand tapestry of game development, it’s the player's experience that tips the scales, isn't it?