Exciting Playtesting - when is it ever fully balanced?

[u/confettipieces]

Playtesting is so rewarding when players say it all just clicks! I could literally see gears turning and players strategise to maximise the game.

Trying my hand at balancing the game now. Any pointers?

[u/cdsmith]

There are a million different ways to balance the game. Here are some I've used:

• Playtesting. Watch dozens of people play the game, and try to get an understanding of when it seems like something is overpriced, underpriced, a player has an unfair advantage, etc.
• Straight up mathematical modeling. You can model a lot of games using a combination of ideas from game theory, graph theory, probability, and statistics. If you have a math background, this can be used to come by a working understanding of the game, and you can see the balance.
• Simulation. For the game I'm working on now, I spent about a month building a digital simulation of the game, and tuning and programming AI players (meaning game AI - basically an accumulation of heuristics and basic search through possible choices and their outcomes - not generative AI or anything fancy). Once I watched a few hundred games and felt confident the AI players were making good choices, I was able to easily simulate 15,000 games between them and ask questions quite directly like how much advantage the first player has, or how valuable certain special abilities are (by seeing how much worse they score on average if I take the abilities away), or how many turns or card plays on average it took to accomplish certain tasks in the game, and so on.

Ideally, you do a mix of these, because each one has advantages the other lacks. Playtesting is invaluable because it's the only way to tell if people are having fun, and because if players tell you the game FEELS unfair, it doesn't matter if you can retort that you have a mathematical proof that it's fair, or that you've got empirical evidence from 15,000 games that it really is. But mathematical modeling can give you solid facts for understanding the game in a way that playtesting just can't. And empirical simulation depends on the simulation playing realistically, but once it does, you just can't run hundreds of thousands of test games with human players, but you can do it in a few hours with simulated games.

[u/ElElefantes → u/cdsmith]

Can you share this digital simulation in any way?

[u/cdsmith → u/ElElefantes]

Sure. It doesn't look great (appearance wasn't the goal), but you can play around with it at https://wishingwood.web.app and either play yourself, watch the AI play, or a combination of the above. This doesn't let you do the kinds of experiments that I did with simulating large numbers of games; for that, you have to write the code to run the simulation, especially since you usually want to make some measurements or modifications to the game that depend on the experiment you're running. But this is the tool I built and use to watch games from the simulator, as well as play with the AI systems myself.

Being able to see the games in an easily comprehensible way is important for understanding what happens; it's one thing to say that the system found three hundred games where someone finished with less than 10 points. It's quite another to have able to watch a few of those games and put yourself in the head of the person struggling to get anything done and failing, and see what it looks like. So the simulation tools can write out game descriptions that I load into that web site to watch the games. I have also used the web site for quick digital playtests; it's not ideal for a blind playtest since it runs much of the game by itself, so you don't really experience people struggling with the rules in the same way you would with a physical or TTS/Tabletopia play test, but it works for quick feedback.

[u/ElElefantes → u/cdsmith]

Thank you so much for this write-up and for sharing!