HIDDEN DEPTHS (part 1)
In my last post, I discussed various solutions to the two main problems that cooperative games suffer from: quarterbacking and inconsistent challenge. One of my solutions to the quarterbacking problem was to maximise and distribute what I referred to as strategic complexity (or depth).
However, there are other kinds of complexity, and not all of them are good for your game. In this two-part post, I’ll dive into what I mean by this, how this impacts the design process, and how these lessons were applied during the creation of Sub Terra.
Onwards and downwards!
Mark Rosewater is the head designer of the long-lived trading card game Magic: The Gathering. Magic’s coming up to it’s 24th year on release and is still thriving with over 20 million active players worldwide. The design technology underpinning its frequent content updates has been honed to a razor-sharp edge, and it is a massive success worth paying a lot of attention to. Rosewater has been working on the game for over twenty years, and produces excessive amounts of fantastic game design content (not all of it Magic focused) through his weekly articles, Q&A blog, biweekly podcasts and occasional lecture.
Back in 2011, Rosewater wrote an article introducing a design philosophy known, somewhat sinisterly, as New World Order. A few years earlier, Magic had just released three nostalgia-heavy sets as part of the Time Spiral block, bringing back numerous cards and mechanics from Magic’s past. This set was a hit with longtime players, who loved the callbacks and revelled in the new gameplay interactions that were now possible. Despite this, the sets were not a commercial success, as newer and more casual players were being put off. With such a long-running game, acquiring new players was essential to Magic’s survival. Finding and fixing the flaw was critical.
The design team quickly realised that the main culprit was complexity. For experienced players, the block was taking mechanical elements that they had already learned over the preceding years and mixing them together in new ways – the amount of extra information they had to absorb was relatively low. For less experienced players, all these mechanical elements were new – not only did they have to learn how they worked, they also had to figure out how they interacted with each other and how to best use them while playing the game. The barrier to entry was simply far too high, so new players weren’t sticking around long enough to find the fun.
For the next block, Lorwyn, the team dialled things back and made the individual cards much cleaner and easier to understand.
This didn’t work.
It turns out that even though each card was less complex, the game itself still wasn’t. This particular block revolved around ‘creature types’ – usually irrelevant bits of rules text on cards that told you whether a creature card was a Goblin or a Wizard (or a Goblin Wizard). A lot of effects either required or scaled up with a certain type of creature in play. This added a lot of hidden dependencies between card abilities, which meant that busy gameplay states and deck construction problems were suddenly a lot harder to figure out.
The Magic team realised that instead of one single thing called ‘complexity’, it came in multiple flavours:
- Comprehension complexity
How hard is it to understand how a certain rule or component works?
This is the obvious kind of complexity, and it’s the most straightforward to ramp up or down depending on the target audience for your game.
- Firstly, complex mechanics can be streamlined into versions that are almost functionally identical but are much more elegant and easy to grasp.
- Secondly, by piggybacking off intuitive concepts known to your intended audience, you can make arcane rules much easier to remember and reason with. (For example, compare a rule that says “when you move onto a red square, return one red cube to the supply” with “when you fall into a spiked pit, take one damage”.)
- Finally, if this is still too high, you can just cut mechanics directly.
- Board complexity
How hard is it to look at a game in progress and understand (a) what state everything is in, and (b) what actions are available at this point or in the near future?
This form of complexity involves the interaction between separate components – you may comprehend what each component does on its own, but put them all together and suddenly figuring out what’s going on might be a nightmare.
In my opinion, a game that illustrates this complexity well is Steampunk Rally. Here, you’re a famous scientist building a Rube Goldberg machine of interlocking inventions in order to win a race. Each invention isn’t that difficult to understand – you’re generating a resource, or you’re repairing your vehicle, or you’re spending energy to move along the track. But when you have a machine comprised of a large number of simple inventions, figuring out the best way to spend your resources among them and in what order becomes a vastly harder task. (The game is still fun, but I wish there was some sort of limitation on machine size to stop this effect getting out of hand)
- Strategic complexity
How hard is it to look at a game in progress and fully understand the future consequences of your immediate actions?
This form of complexity involves the full decision tree of future actions/interactions for all the players in the game. Certain future actions and states may be predictable, but some events and the behaviour of your opponents may not be. Figuring out optimal lines of play can be difficult, even for computers.
Much like how not all types of fat is bad for you, not all types of complexity are bad for your game. Strategic complexity has the magical property of only being visible to experienced players. It doesn’t make the game harder to initially learn, which allows newer players to start playing and enjoying the game much sooner. It also allows the game to remain interesting and challenging to experienced players for a much longer period of time.
Because of its contrasting status as ‘good complexity’, I prefer to call this concept ‘depth’. Deep games are easy to learn, and hard to master. I don’t believe it’s possible to have too much of this.
Creating strategic complexity can be fairly easy – you just turn up the other two forms of complexity, add long decision chains, and stand back. Creating strategic complexity without making the game completely inaccessible is much harder, and will be the subject of the second half of this post.
For all their faults, it’s abstract strategy games like Chess that illustrate this division the best. Understanding how each piece moves is easy (low comprehension complexity). Looking at a game in progress and seeing which pieces are under threat is also fairly straightforward once you’ve got a few games under your belt (low board complexity). But knowing when to sacrifice a piece to capture another, or setting up complex traps for your opponent multiple turns in advance takes a lot of effort and skill to master (high strategic complexity). The combination of these ensures Chess is a game for all ages and skill levels, and goes a long way towards explaining its enduring global dominance.
To keep Magic appealing to both new and veteran players, the design team figured out that they needed to do the same: keep comprehension complexity and board complexity low, while ensuring the game had enough interesting decisions to push strategic complexity as high as possible. They called this philosophy ‘New World Order’
My initial reaction to this concept was: “Design to minimise comprehension and board complexity while maximising strategic complexity. Got it!”. When iterating on my designs, I’d make decisions to make the game system as easy to understand as possible, while letting the underlying interactions hide numerous complex strategies.
It turned out this was a mistake.
I now believe complexity is like nutrition – you don’t want too much of the bad stuff, but you still need some. Because true depth is invisible to new players, new players won’t take it into account when deciding whether your game is worth playing. The lower forms of complexity are visible, and their absence can be jarring. With most games, depth usually increases as the other kinds of complexity increase, so players can justifiably use these forms of ‘bad complexity’ as a heuristic for depth.
Instead, I’ve found it helpful to think in terms of a complexity budget, with size depending on your target audience: smaller for kids, families and casual gamers, and larger for the more serious hobbyists. Instead of minimising ‘bad complexity’ at all costs, you want to maximize depth while using as much of your ‘bad complexity’ complexity budget as possible. (However, you still have to be careful about board complexity – adding one more component or tweaking a simple rule can have huge consequences!).
I think it’s effects like these that cause brilliant games like Hey, That’s My Fish! to be overlooked by ‘serious’ gamers – it doesn’t resemble the abstract strategy game it actually is, and the theme and simple ruleset imply (incorrectly) that the gameplay is very shallow. Go released today could easily sink without trace.
So how can we safely generate as much depth as possible? And how does Sub Terra put all this theory to good use? It turns out that there are a number of common differences in how new players and experienced players perceive game systems. With some tricky engineering, it’s possible to exploit these to create deep but accessible gameplay experiences.
In the second part of this post, I’ll describe these techniques in more detail, and then show how I tried to use these in the design of Sub Terra. See you then!
Game Designer, Sub TerraIndie gamedev robot. All opinions, fatalities and apocalypses are the responsibility of my creators, who should have worked harder on the control problem