Analysis of System Dynamics in Patchwork

Patchwork is a 2-player analog game designed by Uwe Rosenberg and published by Lookout Games (official page). The box rates it ages 8+ with about 30-minute games, so its target audience is families and casual players, even though the quilting theme suggests elderly seniors who like knitting. I played a total of around an hour and 2 games. The game’s about getting the most buttons, and the way you get buttons is by filling up your quilt with tiles with buttons and passing the income squares which are denoted as buttons on the center board.

Game Setup:

Patchwork is a tile-placement strategy game, where most of your thinking goes into selecting which tiles you should put in your quilt. Because of this, it is less adversarially focused. Sometimes, you consciously look at your opponent’s quilt and possible moves to try to prevent them from playing their desired move.

Taking tiles uses up your time, and tiles with extra bonus buttons as well as larger ones generally take more of your time away. The game presents the dynamics of balancing your time and current buttons, so that you are able to fill your quilt as well as the amount of buttons you ultimately collect at the end. In Fullerton’s terms, there is a reinforcing loop: patches with buttons printed on them pay out every time you pass an income marker on the time track, and that income buys patches with more buttons, which increases your income the next time you mass the income square. A balancing loop prevents one person from leading too much by having it so that whoever is furthest back on the time track takes the next turn. Taking a very time heavy patch can give your opponent many turns to catch up.

I am inspired by the simplicity of the game. It was very easy to understand. It only took me around 5 minutes to understand the game, and I felt like it was a great example of easy to learn, takes a lifetime to master. The game is very difficult to understand the dynamics because there are many pros and cons with each move you make. Should I spend and get a good deal on buttons, but use up a lot of time? This complexity helps with replayability. Even if you had to set the tiles in a very specific order, there are still opening moves. For example, in chess, the starting position is the same, but people can make different moves. Even if the pieces in Patchwork were not randomized, you could still play the game over and over again. This differs from tic-tac-toe, which is Fullerton’s example of a game players solve quickly and don’t play too much afterwards. The gimmick I want to borrow for my own system games is time as a currency that also sets turn order. In an AI race game, for example, a lab that spends extra time on safety would fall behind and hand its rivals extra moves, which builds race pressure directly into the rules.

I felt like the addition of the 7×7 reward felt like a little arbitrary milestone because right after you form the 7 by 7 grid, you can still place tiles that break up the symmetry of the quilt.

The values that are present in the game are trade-offs between time and “success” in life. Perhaps, you want to do something that is very cheap for you monetary-wise but will take a lot more time because you are not spending as much money, or vice versa where you spend a lot of money but it is quicker. Both buttons and time are currency in the game, which adds complexity of using these resources effectively. Fullerton’s four economy dials are shown: the amount of patches doesn’t change, the money supply grows as players collect button income, prices are printed on each patch, and there is no trading between players.

In Cook’s terms, the core loop is the turn, where you either buy a patch or advance your token to the space just in front of your opponent, earning one button per space moved. Tradeoffs are difficult to analyze; for example, you are interested in buying a big patch because it will pay off later; you decide to buy it; you pay buttons and place it (action); the time track moves your token forward, possibly past your opponent (rules); you watch them take the next turns (feedback); and you learn that time spent is turns handed away (updated model). Filling the quilt is a slower loop on top of that: it repeats every turn, and you get better at it across games, though sometimes you have to make the best of the pieces you got. The arc, in Cook’s sense, is the quilting theme and fabric art. They make you feel something but don’t change the rules, so the game would mechanically play the same with blank tiles. The game’s about planning ahead and trying to form patterns in your quilt so that it is as easy as possible for you to fill it up later on in the game.

Patchwork has quilts, patches, the time board, and buttons. Every square on the quilt you leave empty subtracts two buttons from your final score, and each patch costs buttons and time to add to your quilt. As you pass the squares with the income marker on it, you get the amount of buttons you have on the quilt. In Fullerton’s terms, no information is hidden, and players have direct control over their actions instead of chance dictating their actions. That makes Patchwork close to a pure formal system; once the patches are shuffled at setup, every outcome comes from the rules and the players’ choices.

I used AI to help provide feedback and suggestions on my writeup.

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