This is how I feel:
BoardGameGeek was kind enough to let me do a designer diary for it, which you can and should read here.
While the game has buzz among those who know about it, the app store is so crowded, an app needs to be both good AND broadcast widely to have a chance. I badly want mine to have a hearing because if it succeeds, it’ll pave the way to more work in the game industry. What I’m saying is: if you spread this around to anyone who might be interested you’ll more or less make my life.
(also note: anyone who does help spread this around will be entered into a contest to receive an artist-commissioned table-top version of the game, among other things. See here for more.)
I’m just a TEENSY bit excited about it. If it sells well (oh please oh god please god please), we’ll develop the app further.
Which begs the question (if I may jump the gun): what kind of improvements shall we make?
Some won’t be related to the game itself, but we’ll also add options which change gameplay. That’s my purview, and I’m writing about it today because, as usual, I want a pretense to talk about game design.
If there’s one thing I’ve come to believe about game design, it’s that every game, no matter how good, can be improved. There is always some way to make a game better.
The difficulty is, as a game improves, the fraction of potential modifications which will further improve it plummets. It gets to be like looking for water in the Sahara. One characteristic of great game designers, which I try to emulate, is they keep looking longer than everyone else.
It’s even harder to do for games which can be played at many skill levels. Some weaknesses only appear at high skill levels, which means the designer may not find those weaknesses without either achieving that skill level himself or finding someone who has.
Having worked on Catchup for years, it’s become hard indeed to improve it. Nonetheless, I’ve got three possibilities to share. None have been tested enough, so they could all be wrong, but here they are.
You’ll need to know something about the game’s rules to understand what I have to say. The following paragraph should suffice:
Players take turns claiming hexes on a grid, and the player with the largest contiguous group of hexes when the board is full wins. The trick is every time you increase the size of the largest group on the board, your opponent gets to claim an extra hex on her turn, which makes her more powerful.
#1 – An adjustment to the catchup mechanism
This one I’m least sure about, as it’s the most fundamental. Catchup mechanisms (mechanisms which make the leading player weaker or trailing players stronger) are hard to implement. They have to be just the right strength. Catchup (the game) is built around a catchup mechanism, and it’s critical I get it right.
There’s an additional difficulty: the “right” strength for the catchup mechanism may be different for experienced and inexperienced players. As they improve, players often learn to better exploit a catchup mechanism, making it effectively stronger. If it gets too much stronger, both players will each try to avoid triggering the catchup mechanism for as long as they can, which leads to a boring sort of waiting game.
Now, I don’t know whether Catchup has that problem. I’ve played the game more than 1000 times, I’m the best player in the world, and it’s not a problem at my skill level. But I can see it might become an issue for players who become even more skilled. Here’s why:
As the game is now, the catchup mechanism is triggered when a player increases the size of the largest group on the board.
This makes it possible to take the lead without triggering the catchup mechanism, thanks to the tiebreak mechanism: if players’ largest groups at the end of the game are the same size, they compare their second-largest groups to see who wins.
If your largest group is smaller than your opponent’s, you can sometimes enlarge your largest group to match the size of your opponent’s. This doesn’t trigger the catchup mechanism, but if your second-largest group is larger than your opponent’s at that time, you effectively take the lead!
A good player can use this effect to “draft” – to stay neck-and-neck without triggering the catchup mechanism. If his opponent then triggers the catchup mechanism, he can take much stronger advantage of it: it becomes less of a catchup mechanism and more of a “leap out in front” mechanism.
As I say, this doesn’t make the catchup mechanism too strong at my skill level or any level below it, but it could make it too strong at higher levels.
My fix, if one turns out to be needed, is to trigger the catchup mechanism when a player increases or matches the size of the largest group. This would keep a trailing player from “drafting” as closely, and would thereby reduce the incentive to trail.
Of course, this change might also make the catchup mechanism too weak for lower skill-levels, which means maybe we should present it as an advanced option.
#2 – Different opening setup for larger boards
Catchup is played only on a hex board with 61 spaces. On larger boards, the game’s opening turns are harder to understand, too hard. Can this be fixed?
My proposed solution: when playing on a larger board, before each game, place a small number of “neutral” stones on randomly chosen spaces. These stones will not belong to either players’ groups, but will instead act as barricades. This would:
1. shorten the opening.
2. give players a strategic focus (how do you exploit those barricades to limit your opponent’s group size, and prevent your opponent from doing the same to you?)
3. add variety. Each game would play out differently depending on the random setup.
Because this would only apply to larger boards, we should present it as an advanced option as well.
#3 – A handicapping system
This is simplest modification and the one I’m most sure will improve the game.
Like many luckless games exhibiting emergent complexity, skill matters a lot in Catchup.
You don’t want to feel like the outcome of a game is a foregone conclusion because your opponent is a little more or less experienced than you. My favorite fix (when adding luck isn’t an option) is to add a handicap system.
Thankfully, unlike for many games of its kind, Catchup allows for a simple, clean, and adjustable handicap: before the game begins, the players agree to add a certain number of points to the weaker player’s score (i.e. her largest group size, but not the size of any of her other groups) at game’s end. Scores are then compared as normal.
That’s it. If you like this stuff and want us to include it, by Jove look for Catchup in the app store on August 7, and please help us promote it by telling people you know about it. We’ll be grateful and will probably write Sonnets about you.
(also, if you help us spread the word, you’ll be entered to win an artist-created tabletop version of the game, which I will fly to you and present in person.)
Sometimes the best way to learn about game design is to examine one little issue like it’s a diamond under a jeweler’s lense. That’s what I’ll do with this post.
Here I discuss a problem that came up during the design of my game Catchup (coming out on August 7 for iPhones and iPads), which, as I’ve emphasized many times on this site, is one of the best games I’ve designed.
You can read the rules of Catchup here, but the idea is players take turns placing stones of different colors on the spaces of a hex grid, each trying to create the largest contiguous group of stones in her color by the time the board fills.
The trick is that if you take or advance the lead on your turn by creating a bigger group than has come before, your opponent gets to place an extra stone on her next turn. This keeps each player from making one big clump of stones in the middle and forces careful thought about how to time group growth – if you grow your groups too quickly, you give your opponent too many extra hexes, but if you grow your groups too slowly, your opponent can cut your groups off from one another so they can never connect together.
That’s all you need to know to understand the dilemma I’m about to describe.
Early versions of the game had the following rule:
You may not take your turn such that at the end of it, the players’ largest groups are the same size.
I’d included this rule to prevent ties, which would be too frequent otherwise.
But fixing problems by banning actions players feel like they should naturally be allowed to do is a bad idea. I knew this at the time, but I was in a bit of denial, probably because I didn’t know how to fix it. That was my dilemma.
The Solution: A Fractal Tiebreak
A fractal tiebreak is a series of nested, tiebreaking win conditions, all with exactly the same form, and all replicating the form of the game’s overall goal.
In Ingenious’ case, each player has a bunch of different point categories, and the goal is to have a higher score in your lowest-scoring category than your opponent does in hers’. If there’s a tie, players compare their second-lowest scoring categories, and so on, until they come to a pair with different scores, and whoever scores higher wins.
I realized I could add something similar (but conceptually simpler) to Catchup: if the players’ largest groups end up the same size, players compare their second-largest groups, and so on, until they came to a pair which weren’t the same size. Whoever owns the larger wins.
By adding this fractal tiebreak I could dump the rule against placing stones such that the two players’ groups were the same size. This fix was straightforward and intuitive and had the added bonus that, if the board you play on has an odd number of spaces, ties are impossible.
I was proud of that rule to begin with, but in retrospect, I’ve come to think of it as my niftiest Catchup design maneuver. The reason, which I didn’t appreciate until after I became skilled at the game, is that it made Catchup deeper, but that extra depth is hidden out of view such that new players won’t be troubled by it or even realize it’s there – a critical feature given I wanted the game to be inviting and unintimidating. This was a complete and completely pleasant accident.
Why the fractal tiebreak makes Catchup deeper
As I’ve mentioned, it’s common for the players’ largest groups to end up the same size. It becomes even more common as players become more skilled. This fact, combined with the fractal tiebreak, forces players to maximize not just their largest groups, but their second-largest groups, and so on.
As a result, more stones on the board matter, and players must focus on more areas of the board. There’s more pressure to develop a “whole-board” strategy.
This whole-board strategy entails choices about how to deploy your stones which are equal parts complicated and agonizing. Here’s why:
Imagine you’re playing a game of Catchup and you can see the players’ largest groups will likely end up the same size, so the game will be decided on a tie-break. So you start trying to ensure your second-largest group ends up bigger than your opponent’s second-largest group.
But when you do, you realize something more confounding: you don’t know how to ensure your second-largest group is larger than your opponent’s without simultaneously making your largest group smaller than your opponent’s – because a stone added to your second-largest group is a stone not added to your largest.
Each stone you place must somehow bring you closer to achieving both goals simultaneously, but they conflict. Whether you can solve this riddle (there are a couple of different general kinds of solutions) depends on patterns established back in the beginning of the game which seemed inconsequential at the time.
Anyway, when you realize this, that’s when the real thinking about Catchup starts. You realize every little thing matters, all the way back to the very first turns of the game, and so you start thinking about every little thing.
So far, in nearly all games of Catchup I’ve played in or watched, only the largest and second-largest groups are in play, which is complicated enough.
But I’ve also played in 4 games decided by the third-largest groups, and I’ve even played in one game (out of more than 1000) decided by the fourth-largest groups (I lost). I suspect such endings will become more common as players get more skilled. The thinking required to win such battles will be ferociously complex (assuming no one figures out how to break the game before then).
But, thankfully, inexperienced players should and will remain blissfully unaware of this complexity. Most players need only worry about making the largest group, and the other stuff will slowly dawn on those who play enough to start losing frequently on tie-break.
fractal chess image via fdecomite
Well, it is for me anyway, because Catchup, one of the best things I’ve done with my time here on Earth, is coming out for iPhones and iPads on August 7.
I’ll be talking it up in the next few weeks (please subscribe over there on the right if you want to follow along), and I want to start not with the game, but a person connected to it: Martin Grider, because this little dream is only happening because of him.
Martin’s a skilled app developer you may know from such game apps as For the Win. I had no idea who he was until about two years ago, when contacted me and asked if he could develop Catchup for iOS.
He wasn’t pitching me a project I would pay for. He would do it at no cost to me, even though, as a successful developer, he’s not exactly in the habit of making such offers. Of course I jumped at it.
And then it became a passion project for Martin. Consequently he spent way, way more time implementing Catchup than he normally would have – time he could’ve spent doing paid work as he normally does. He’s been working on Catchup for almost two years now.
He also enlisted outside help to make everything perfect, for example hiring AI specialist Tysen Streib to create the computer opponent. So now the app has an incredible AI whose strength automatically adjusts to match your own, but it also increased the size of the already-big effective pay cut Martin took to make Catchup a reality.
He’s told me that for this effort to make anything like financial sense, the app has to get well north of 10,000 downloads (at $3 a pop). That’s a whole, whole lot.
Now, Martin doesn’t expect to get that many downloads. This is his passion project and he seems pretty intent on just making a good thing.
I, on the other hand, am utterly flabbergasted someone I didn’t even know before this project began decided to see it to completion and such great cost to himself and zero cost to me.
So, I want to help him, and to show my gratitude, and the best way to do both is to get him downloads.
I can’t do it by myself. I can’t repay him without a lot of help. If you want to help me give a great, great guy a gift he richly deserves, I’d be grateful for help publicizing this game.
I’m offering a “stretch” reward
(…even though this isn’t crowdfunding)
I’ll keep a list of people who help spread the word about the game between now and August 21 (e.g. social mentions, links to this article, reviews, app reviews when the app is out, and anything else you can think of). If the app gets 10,000 downloads between August 7 and August 21, I’ll pick one person from the list at random and award him/her with the following:
1. I’ll commission an artist to make a high-quality, artfully-designed Custom catchup set.
2. I’ll fly to the lucky winner, at my own expense, to give that custom set to him/her in person.
3. I’ll bring a few other print-and-play sets with me, and using them, will run a one-night Catchup tournament for the winner and up to 7 of their friends, at which I will be the Master of Ceremonies and Cooker-of-Dinner (contingent on Kitchen availability).
Please spread this around like it’s rich loamy manure.
Two final things:
1. Martin has told me that if by a miracle the app gets that many downloads, ever, he’ll give himself permission to work more on the project, which means, among other things, updating the app with an advanced version of the game I’ve cooked up.
2. Both Martin and I will be at GenCon, probably wearing Catchup T-shirts, iPads in hand and ready to play. Stop us and throwdown with us. We’ll try to cook up something interesting for occasion.
The question under debate: does randomness in games limit skill?
Kory, who voted nay, cited a talk by Magic: The Gathering designer Richard Garfield in which he uses a toy game called Rando-Chess to argue randomness doesn’t limit skill (relevant part starts at 2:39):
Rando-Chess is the same as normal Chess, except after the game is over, the players roll a die and if it comes up “1”, the winner becomes the loser and vice-versa. Though Rando-Chess has more randomness than Regular Chess, it has equal skill, since you can apply all your Chess knowledge to improve your chances of winning Rando-Chess. This seems to demonstrate randomness doesn’t limit skill.
I told Kory wasn’t so sure. He asked where my doubts lay but I couldn’t explain them without writing scores of tweets, so I told him I’d reply via blog. And Lo! I’m actually following through.
Before I get to my argument, two caveats:
1. I’m not sure what camp I’m in and my argument below could be bunk. I just want to explore the possibility that Garfield’s argument papers over some complexity.
2. For soon-to-be apparent reasons, my argument only applies to strategy games, by which I mean games whose first aim is to get players grappling with interesting strategy/tactics stuff in an attempt to win. It’s not a universal argument about the role of randomness in games, or even in orthogames (the games about which Garfield made his claims).
Randomness Limits Skill…Sometimes
Let’s start with the following claim: Rando-Chess is bad. Including randomness in the way Rando-Chess does makes the game worse than normal Chess (a claim Garfield himself makes in his talk).
If I played Rando-Chess, and won the Chess game but lost on the die-roll, I’d be frustrated I outplayed my opponent but lost anyway on a single random event which negated in one instant all my prior decisions.
If that’s not frustrating enough for you, let’s replace Rando-Chess with Super-Rando-Chess. In Super-Rando-Chess, we use a 100-sided die. If the die lands on any number from 1 to 49, the winner becomes the loser and vice-versa. All arguments that apply to Rando-Chess also apply to Super-Rando-Chess, and the two games are bad in the same way. One is just more bad in that way than the other.
But why should it matter if these games are bad? The Rando-Chess’ quality should have no bearing on the logic of Garfield’s argument regarding skill, right? Alas, I think it might!
What if, to make a good strategy game that includes randomness, it must be incorporated in such a way that it does limit skill? Below I explain why I think it could be true. My case consists of two contentions:
Contention #1: for randomness to make a strategy game better rather than worse, it must be difficult for a player to determine the respective extents to which random events and her own choices determine the outcome of each game.
Why? Imagine losing a game which conforms to this requirement. When you lose, since you’re unsure what led your loss, instead of getting frustrated, you think about what you could have done differently, and to tease apart the factors involved. The game gets you thinking about strategy, which is the the point of a strategy game.
On the other hand, if you know why you lost, you have the same problem as in Rando-Chess: when you lose due to some random event(s), you’ll know it, and it’ll be frustrating for the same reason Rando-Chess is frustrating: it negated your choices and you know it.
This is why my argument only applies to strategy games: if strategy isn’t the main focus of a game, the quality isn’t necessarily hurt if randomness diminishes the importance of strategy. Many games focus more on the “thrill of finding out what happens”, to create a vivid story or a gambling atmosphere, etc, where that’s the case. Contention #1 therefore doesn’t apply there.
Contention #2: the harder it is to distinguish the effects of your own choices from those of random events on a game’s outcome, the harder it is to accrue skill.
The harder it is to know how your choices affected a game’s outcome, the harder it is to know how to change them in the future, and thus the harder it is to improve. If I’m examining the choices I made in a game I lost, how do I know if I made bad choices or if I got unlucky? If I can’t distinguish the effects of randomness from my own choices on the outcome, I’m stuck.
As a result, the rate at which I can accrue skill is limited and that limits the ceiling on the skill I can reach for a game with the time I have to play and study it. The difference in skill between the best players and average players will not be as large as it is for games where it’s easier to distinguish the effects of random events and choice, or for games without randomness.
Put contentions #1 and #2 together, and you get this:
Good strategy games incorporate randomness such that it’s hard to distinguish the effects of player choice vs. randomness, which limits the rate at which players can accrue skill, which limits skill. Ergo, randomness limits skill in good strategy games.
I wonder if Garfield would agree. There’s another essay on the same topic where he says “The reward for skill depends on how much luck there is in a game…“, which suggests he might be open to my feedback-centric argument.
Anyway I sense I haven’t fully thought this through and may be problematic assumptions lurking. For example:
Maybe knowing you got screwed by randomness isn’t the problematic as I’ve claimed. Maybe I’m overgeneralizing from my own preferences. In fact, in Garfield says randomness should make you feel that, when you lose, you’re unlucky, but when you win, it’s due to skill. On the other hand, while that may be true for many sorts of players, I doubt it’s true for strategy lovers. After all, it’s this “knowing you got screwed” quality that makes Rando-Chess a bad game.
Another assumption is, when I say skill, I’m referring to skill real humans can acquire in practice, not skill “in the game” but out of human reach. For example the best Chess engines now play more than 500 ELO points better than the best humans, and some of that extra skill may be impossible for humans to acquire. My contention #2 above doesn’t apply to this sort of theoretical skill. Which kind of skill should we be talking about?
If you can bring other such assumptions to light in the comments I’d be grateful.
Side note: Everyone knows Reiner Knizia is one of the great game designers. What makes his games so good? One feature of many is they make it very hard to know where skill ends and luck begins. In fact Knizia’s games inspired my idea that games should exhibit this quality. Tip o’ the old hat to the master.
I’ve lately turned my attention from designing games for myself to designing with commercial intent, and I’ve been developing new methods to that end. Here I mumble about two and the philosophy behind them.
But before I strafe you in a hail of wisdom, a warning: though I’ve designed table games for 15 years, I’ve just started designing games to sell, and licensed only one in this new effort (out in November if it stays on schedule). These aren’t the words of experience. They might offer fresh perspective or they might be hooey. I might disavow everything. Constructive criticism is welcome.
An introduction by way of the soda industry
There’s a famous story in the annals of marketing about brand power in the soda industry. You’ve probably heard of the Pepsi Challenge: a promotion from the 70’s-80’s showing most folks prefer Pepsi to Coke in blind sip tests.
The ads weren’t lying. Studies by third parties at the time showed Pepsi indeed beat Coke in such tests.
However, the same studies found another effect: while Pepsi beat Coke in blind sip tests, Coke beat Pepsi in unblind sip tests, where the sippers knew what they were sipping. Coke’s brand was so powerful it overrode the chemistry.
Branding doesn’t have equal power for all product-types. For some, brands are weak relative to other factors, such as price (commercial airlines are an example – most of us go for the cheapest flight no matter who’s offering it, despite airlines’ endless efforts to change that)
But I contend that for board games, traditionally, branding is powerful, perhaps even more powerful than for sodas. Mass market/casual game players especially are loyal to the games they know and ignore everything else. Evidence:
Monopoly has been the best selling board game in the world since the 1930’s – How many products have been the best-selling products in their category for that long? Coke maybe? Maybe Arm & Hammer baking soda? Very, very few. This sustained dominance is probably due to powerful brand associations.
No doubt many games would beat Monopoly in “blind taste tests”, where players learn both Monopoly and another game for the first time and decide which to buy. Yet Monopoly dominates, because it’s a familiar name casual players trust and it’s synonymous with the idea of the board game.
And consider: most Monopoly sets sit unplayed on closet shelves. We buy it more for what it symbolizes than because we want to play it. Another way to put this: we buy Monopoly more for its brand than for its functional purpose.
Bananagrams – I’ve used this example elsewhere but I’ll repeat it because it illustrates the power of game branding. Bananagrams is a huge best seller now, but the same game was also marketed before under a different brand, with nowhere near the success. The branding, not the game, was the difference (it doesn’t seem to have been due to more aggressive marketing). A canvas banana and a funny name can work miracles.
Two complications to this story:
1. Games hobbyists aren’t like casual players. Hobbyists aren’t as loyal to individual games and they prefer novelty. If hobbyists have any brand loyalty, it’s not to individual games, but to publishers or designers. To take myself as an example, I’m more loyal to the Reiner Knizia brand than to the brand of any one of Reiner Knizia’s games.
Historically, the hobby market has been much smaller than the mass market, so where profit was a priority, it paid to design games with the mass market in mind and to think about branding in that context. That brings us to the second complication:
2. The hobby market is growing, and its values may be spreading. What I mean is, more casual players are becoming more like hobbyists in the way they think about games. Likewise, their loyalty to individual games may be weakening a bit. Secondarily, crowdfunding may be making it easier to make a living publishing hobbyist games (Example: Stonemaier Games).
I don’t want to overstate these effects though: the mass market remains bigger, casual players still exhibit more loyalty to individual games, and bottom-line, the biggest hits still usually rely on mass-market adoption to become hits, whether hobbyists adopt them or not.
In addition, though crowdfunding has created a new source of revenue for hobby designers, it’s also creating a lot more competition among them. In fact, the internet generally has created such a focus on hobbyist game design, I suspect the mass market may now be comparatively underserved.
For these reasons, if making money is a priority, I believe designing games with potential for mass market adoption is still the way to go*. If you create a game which is popular among casual players, there’s a good chance it’ll stay popular (and generate revenue) for a long time. Contrast this with hobbyist games, where even revered games go out of print as hobbyists move on to the next new thing (Example: El Grande).
To sum up so far: I’ve argued designing games for mass market adoption is still the way to go if commercial success is a priority, and in that case a game’s brand is as important as the game itself.
That brings us to my central point: if you’re designing for the mass market, put as much effort into designing the game’s brand as you do gameplay. How? Here are two techniques I’m experimenting with:
How to integrate brand design and game design
Technique #1: brand-first design – There’s a rule in journalism which holds you should always write the headline first. Why? The headline is the promise you make to readers. By writing it first, you can better assess its value, and it focuses you on fulfulling it once you’ve committed to the writing.
A game’s title/tagline work the same way: they make a promise about the game’s experience. For that reason, I’ve started creating titles/taglines for games that don’t exist yet, and then designing games to fulfill their promise.
This is how I do it in practice: I wrote recently about my game design workflow, called the 100:10:1 method. In the first step, I write 100 concepts for games, each in a sentence or two. In the past, those have usually described mechanics, themes, components etc, which interest me.
But now, I’m composing game titles+taglines, or sometimes even packaging concepts. After I have 100, I select the 10 which most excite me, and carry out the rest of the process as usual.
I’ve designed one game this way so far:
It is, by far, the most visited game description on this site. And this is a game almost no one has played, I haven’t promoted it much or tried to license it, and the gameplay itself may be unsuitable for a broad audience. All this suggests that the method has value.
Technique #2: online branding split-tests – I didn’t invent this method. The author Tim Ferris famously used it to design the branding for his best-selling book The 4-Hour Work Week. But I’ve not seen it used on a table game. The basic version is a method for testing the attractiveness of game titles and taglines, and it goes like this:
You create several different Google Adwords ads featuring different game titles and taglines, for the same keyword, set them to be displayed at the same frequency (“rotate evenly”), and see which one has the highest Click-Through-Rate (CRT), which is a measure of how intriguing the ad is to the audience.
It’ll cost money – a couple hundred dollars to identify a statistically significant winner – which means you should only use it on a game you’re committed to publishing. If you do it right (e.g. you use appropriate keywords, etc.), it can make a tremendous difference to your marketing.
Similar techniques can be used to test packaging concepts or graphic design elements, using services like Optimizely. There are many ways to do this and too many details for me to cover here. But you get the idea.
I’m only just starting to use this technique for games, but I’ve used it for a variety of purposes in my professional life, with good results. I expect it to work for games.
1. None of this works if your publisher doesn’t want your branding help. Find publishers who welcome your involvement (It shouldn’t be hard – several publishers have told me they wish designers cared more about commercial considerations). Likewise, earn their trust by explaining your philosophy well, presenting amazing, thoughtful ideas, and being sensitive to the publisher’s needs (a publisher has to worry not only about each game’s brand, but also the company’s brand, which adds constraints – your game about orcs beheading each other with piano wire does no good for that family-friendly publisher you’re working with).
2. A brand only really becomes a brand when potential customers are familiar with it and they have positive associations with it (the whole point of branding). That means consistent, long-term outreach after publication is as important as design before publication. Designers with commercial ambitions would do well to consider that a part of their jobs as well. Some might argue that’s a job for marketing folks, but I disagree. Most marketers can’t be as authentic and honest as you can be about what you’re offering, and authenticity and honesty are critical to good branding.
That’s all I have to say. I hope it isn’t stupid. It’s always a struggle to see light through the obsidian storm of one’s own perceptions.
* This is where some hobbyist readers accuse me of arguing for “dumbed down” game design. I disagree and here’s why:
Casual players want and get different things from games than hobbyists do. Hobbyists tend to assume the desires of casual players are inferior to the desires of hobbyists. I think this sentiment is an expression of our ego-protecting tendency to believe those who are different are inferior (a tendency which, incidentally, causes unthinkable amounts of misunderstanding, heartbreak and injustice in other contexts). This isn’t to say there are no such things as unhealthy desires, but rather hobbyists are misguided in thinking the desires of casual players are unhealthy (or anyway less healthy than those of hobbyists).
Anyway I believe a great game for casual players can be every bit as artful and profound as a great game for hobbyists. It just serves needs to which we hobbyists have trouble relating, so the art is lost on us. It certainly was lost on me, for a long time (a subject for another day). Back to essay
This is the second post of a series on practical game-design techniques. Here’s the first.
In my years designing games, my methods have evolved from Games-Randomly-Emerging-from-the-Inchoate-Chaos-of-my-Brain-Area to something resembling an honest-to-goodness, write-downable process. I’ve decided to share this process here, for four reasons:
2. I haven’t seen anything exactly like it.
3. Writing about it will give me ideas for improving it.
4. Pondering game design is one of the two great pleasures of my life (the other is spending time with my ladylove, who’s just sort of discombobulatingly great to be around)
I call it the 100:10:1 method. I’ll start by describing it, then discuss why it helps me.
The 100:10:1 Method
It has three steps:
Step 1 – I quickly write 100 short game concepts in a notebook. In less than a week. Even in one day. I don’t give much thought to quality; I include whatever comes to mind, even if it’s dumb, incomplete or violates physical law (I do include good ideas as well). I keep spitting out ideas especially after I feel “spent”.
Here’s an example I just pulled randomly from a notebook: “Mortals: pieces age as they move – they’re dice and when a die moves, the pip count of its top face is reduced by one. When the top face is reduced to one pip, it dies.” This isn’t even a whole game concept; just a mechanic around which a game could be built. Other examples describe themes, or problems I want to fix with other games, or ideas for combining my favorite aspects of multiple games into one, or just hallucinatory nonsense. I have no rules about what each concept should contain except it should tickle my fancy.
Note: the exact number doesn’t matter as long as it’s a metric crap ton.
Step 2 – Based on some selection criteria (which depend on my design goals and which I discuss below), I pick 10 of the 100 concepts and try to turn them into actual games. Just crude working versions. I work on all in parallel. This usually take six months to a year.
Step 3 – I pick the most promising game of the 10 I’ve developed and playtest+polish it till I’m sure I can’t improve it. Then I make a list of its weaknesses and improve it more. Then I’m done. The time required depends on how much patience I have in pursuit of perfection, the type of games involved, and how close I got to the mark in step 2. Here’s the time I spent in step 3 for each of the three games mentioned above:
Cat Herders : 1 year
Stinker: 3 years
Catchup: 4 years
Why does the 100:10:1 method work?
First I’ll describe benefits of the individual steps and then some emergent benefits of the whole process.
Benefits of the individual steps
If you know about creative thinking theories, you’ll see similarities pre-existing techniques – the 100:10:1 method works in part because it exploits their known benefits.
This is particularly true of step 1, which embodies the classic brainstorming principle: to find a good idea, have a lot of ideas, and go past obvious ones by forcing ideas after you feel “all out”. It takes practice because we’re used to stopping when we feel our ideas are exhausted. But it’s a time-honored and well-tested way to break free from habitual thought patterns. When I do it right I get into an almost-stoned state where my thoughts scramble and bend in odd and original ways. I goose this effect by combining the technique with other formal techniques for disrupting normal thought-patterns, some of which I’ll write about in the future.
Step 1 offers another benefit: it’s easier to get a feel for the promise of an idea when I have other ideas with which to compare it. Comparisons open otherwise unreachable avenues of critical thinking. By starting with 100 concepts, I start with a lot of fodder for comparison, which helps me better assess which to pursue.
The benefits of step 2 can be understood by answering the question: “Why not just pick 1 idea instead of 10 from the initial 100 to develop?” i.e. “Why not just go from step 1 to step 3?” Three reasons:
1. When I focus on one game, I can get attached to it, which makes it easy to delude myself about how good it is. When working on 10 games, I have no darlings.
2. It keeps me from getting stuck. When I get stuck on a problem in one design (I always do), I work on another. Later, I return to the problem with new perspective and can often solve it. Going back and forth between 10 games, I always have at least one on which I can make progress. Also, I use ideas from one game to solve problems in another.
3. Many of my initial ideas don’t work like I thought they would once I develop them, so I have to develop them to judge them. Sometimes a single key rule change can change a bad game into a great one. Developing a bunch of games into rough form at once allows me to more quickly and accurately know where the real promise lies.
Step 3 is just the latter phase of most designers’ normal process: the polishing/refinement phase, where I scrutinize every detail for improvements. I’ll write about the techniques I use in this step in future posts, but for now I’ll remain silent about this step.
Emergent benefits of the whole process
There are benefits of this process beyond the benefits of the individual steps. By working through an end-to-end system like this, I can:
1. stay focused, because I know exactly what I’m doing at any given moment. It’s the difference between going to the gym with a specific plan vs. going to the gym with the vague notion of working out.
2. focus on process rather than outcome. When I stop worrying about whether what I’m doing is good enough or worth the time, and concentrate instead on executing each step well, it frees me emotionally and allows for heightened creativity.
3. practice, and capture the benefits of, what are often cast as exclusive modes of invention. Here’s what I mean:
People often describe invention as coming from two sources. I’ll call one “problem solving” invention, and the other “imaginative” invention. The first means fixing problems in pre-existing things (in this case, games, game-types, or game-mechanics), and the second means making flights of fancy real.
For game design, I don’t think one is better than the other. Rather I think both work and work best when combined, because they have different strengths and weaknesses.
“Problem solving” invention helps ensure a design is understandable (because it has precedent), and ensures a level of quality, but it can feel derivative. Imaginative invention is the source of more original/exciting stuff, but can produce weird, non-optimized things no one understands.
The 100:10:1 method encourages the practice of both imaginative invention (particularly in step 1, because it’s hard to write down 100 ideas quickly without following flights of fancy), and careful problem-solving invention (in steps 2 and 3).
Moreover, my initial 100 ideas are usually a mix of “problem solving” ideas and “imaginative” ideas, and lining them all up together as I try to select 10 to develop allows me to better understand (again, through comparisons) which are worth pursuing.
Many game inventors gravitate to one mode of thought or the other. I think we miss out by doing so. By formalizing the use of both I force myself to practice and hone my skill with both and combine their advantages. I’m a better inventor for it. In fact the more I practice them, the less distinct they become. They’re being replaced by some chimeric mode I lack the language to describe.
I wonder if this last benefit is why the 100:10:1 method works better for game design for me than for other kinds of invention: game design is an unusual, balanced mix of art and engineering that favors both modes. Other disciplines maybe aren’t as much like that.
For most of my game-design life (~15 years), I’ve designed games for my own amusement, so my selection criterion following step 1 was just “what’s interesting to me”. I love designing that way but it often fails to produce games of broad interest, because I have idiosyncratic tastes.
That’s no problem when I’m designing for myself and the few others who share my taste. Lately, however, I’ve started designing with commercial intent, so I’ve adjusted my selection criteria.
First, “what’s interesting to me” remains a key criterion. I can’t design well unless I have enthusiasm/passion for the task.
But an additional set of criteria have to do with what buyers will want from my game (which requires I first develop a clear picture of who I’m designing for). For example, I want to design games for casual players, so when I’m using the 100:10:1 method to that end, I select concepts with qualities they tend to like: simple, straightforward, intuitive rules, not too competitive-feeling, components at a reasonable price point, etc.
An unanticipated side-benefit of including audience-related criteria is they help me to a) better appreciate game dynamics not in my wheelhouse; and as a result, b) make me a more sophisticated designer generally.
For example, I adore competitive, interactive games, and have spent most of my time designing them. In designing other kinds of games, I’ve come to see the artistry of a well-done, non-competitive design, and further, I now know better how, and have more tools at my disposal, to adjust competitive feel.
One more point about audience-related selection criteria: rules-of-thumb about what others want are of only limited use. When I’m selecting my 10 concepts to develop from the initial 100, I rely on such rules of thumb because they’re all I have.
But I don’t really know what others want until I play prototypes with folks in my target group and get good feedback. The magic of great games is an emergent property of all their aspects combined, and it’s not captured by descriptions of their separate parts. Therefore playtesting must be the ultimate arbiter, and I rely heavily on it starting at the end of step 2, and for all of step 3 of my process.
Most designers know this, but how to playtest well is a critical and under-discussed subject about which I’ll write at length in a future post (the way most designers do it leaves room for improvement, imo).
Beyond audience-related selection criteria, I also use a “how hard it will be to produce a finished, polished design” criterion. Just as a novelist can waste years reaching for The Great American Novel, a game designer can be too ambitious. That way lies the Cones of Dunshire:
But! It’s easy to be wrong about (and especially to underestimate) how hard it will be to produce a finished design. Even the simplest games can take years to polish. Nonetheless I still use this criterion because it helps me weed out concepts which portend obvious quagmires.
For example, lately, I often think of game concepts which would require computational design assistance to complete, and thus custom software. While designing with commercial ends in mind, I’ve avoided these (though when I’m designing for personal learning, I do the opposite – someday when I get good enough at writing this kind of software, that will change).
Finally, I don’t combine all my criteria into any kind of formal metric. There’s not enough predictive data after the first step to make formal metrics useful.
Instead I think hard about each game in relation to each criterion, and then after a whole lot of such thinking I go with whatever my gut says. Picking right is an art that takes practice.
More to come
While the 100:10:1 method is the overarching framework of my design process, I use other techniques within it, and it wouldn’t work as well as it does for me without them. So I’ve decided to write about those too. I have a bunch more posts planned to cover them.
As mentioned, I have lots to say in particular about playtesting, but it’ll be a while before I get to that one because it’s the most ambitious post I’ve planned, and some of the practices I’ll write about are still in development.
I want to learn about other methods, document them and try them as I refine my own. So if you’re a designer with your own tricks, or know of other designers’ processes, please share them in the comments. Here’s an example of what I mean – Rob Daviau’s talk on how he designed Risk: Legacy:
PostScript: two books played major roles in the development of the 100:10:1 method:
Both are among a tiny handful of books which have noticeably changed my life for the better – I recommend both for those interested in creative thinking.
Other-PostScript: As predicted, writing about my work flow has given me ideas for improving it. If they pan out, I’ll write about them too, but not here because this post is already longer than the day is long.