Something you mentioned briefly struck me as significant - biases in playtesting are just as important as playtesting itself.
That "experienced players" bias is one I'm sure has impacted others, and likewise there's definitely other biases skewing your data.
In data science, or science in general, we have a good grasp of data biases and what to look out for. I feel game design lacks this. Instead, we rely on intuition and guesswork.
Even a crowdsourced collection of "playtesting biases" compiled to a list could be a start. Wondering if anything like that exists? Super interesting if not.
I’ve had a really interesting view of perceived balance with the game Unmatched lately, and how different groups can see balance differently.
Unmatched is an interesting subject on its own - a game with wildly different fighters who need to have a fairly even chance of winning, but competitive play has thrown up some different views on balance and how fighters are ranked.
I play Unmatched competitively online, and fighters’ win/loss statistics are all recorded, so there’s a pretty well known meta - for that audience.
However, I also run face to face tournaments in the UK where the game is not as well established, and the view of who the ‘best’ fighter is in that environment is sometimes quite different. I have even seen a meta emerge within a tournament as players convinced themselves that Sinbad, not a top ranked fighter by most people, was undoubtedly better than the others.
Individual groups sometimes ban random fighters because they’re all convinced that they’re ’too good.’
It’s all interesting, and sometimes quite amusing, but it totally reinforces that it’s perceived balance, not mathematical balance, that is important to players.
Interesting perspective! "Meta" as a game concept is really interesting and complex, and I should really do a GameTek about that. Thanks for the input!
Something you mentioned briefly struck me as significant - biases in playtesting are just as important as playtesting itself.
That "experienced players" bias is one I'm sure has impacted others, and likewise there's definitely other biases skewing your data.
In data science, or science in general, we have a good grasp of data biases and what to look out for. I feel game design lacks this. Instead, we rely on intuition and guesswork.
Even a crowdsourced collection of "playtesting biases" compiled to a list could be a start. Wondering if anything like that exists? Super interesting if not.
A great article, as usual!
I’ve had a really interesting view of perceived balance with the game Unmatched lately, and how different groups can see balance differently.
Unmatched is an interesting subject on its own - a game with wildly different fighters who need to have a fairly even chance of winning, but competitive play has thrown up some different views on balance and how fighters are ranked.
I play Unmatched competitively online, and fighters’ win/loss statistics are all recorded, so there’s a pretty well known meta - for that audience.
However, I also run face to face tournaments in the UK where the game is not as well established, and the view of who the ‘best’ fighter is in that environment is sometimes quite different. I have even seen a meta emerge within a tournament as players convinced themselves that Sinbad, not a top ranked fighter by most people, was undoubtedly better than the others.
Individual groups sometimes ban random fighters because they’re all convinced that they’re ’too good.’
It’s all interesting, and sometimes quite amusing, but it totally reinforces that it’s perceived balance, not mathematical balance, that is important to players.
Interesting perspective! "Meta" as a game concept is really interesting and complex, and I should really do a GameTek about that. Thanks for the input!
Another great Gametek!