Balancing novices and experts

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Feb 062014
 

ninjasquirrelOnce again, another question that came in via Quora. The issue at hand is, what do you do to balance experts and novices in a game? Especially if there are persistent elements like leaderboards in the design, which tend to cement experts towards the top?

This is a big issue as games become more persistent and emphasize multiplayer aspects more heavily. Single-player games now swim in a soup of constantly connected profiles with all sorts of achievement and expertise data, effectively rendering them all multiplayer via the addition of a metagame. And we should not forget: the average player is below average; or to be more precise, the median player will have a win-loss record that is lower than the mean or average win-loss record, because the high-skill players win a disproportionate percentage of the match-ups. This results in the mode for the win-loss record curve being “loss.” (For more on how Pareto curves manifest in this sort of persistent environment, I refer you to my 2003 talk on “Small Worlds” [PDF]).

This sort of accumulated record of expertise can serve as a huge disincentive to participate. Novices will look at high ratings and consider the game hopeless. Nobody likes feeling inadequate. And of course, once in an actual game session in any sort of competitive scenario, it is rare for the match to actually be between perfectly matched opponents. It doesn’t even take a significant skill gap for an accumulated win-loss record between a novice and a ninja squirrel to begin to look pretty dismal. And of course, in skill-based systems that lack infrastructure, people can try to hide their ratings — that’s the basis behind being a pool shark.

There is no way known to solve this issue. In fact, balancing arbitrary teams, for example, is an NP-Hard problem. Fortunately, there’s a pretty standard grab-bag of tricks to ameliorate the issue: Continue reading »

Feb 052014
 

Slide14My GDCNext talk “Playing with ‘Game'” has been posted up here as video with slides:

Gamasutra – Video: Playing with ‘game’ – What games can be, and what they can mean.

I described the talk thus a while back:

The talk starts out with some basic semiotic theory — basically, the difference between a thing, the name we give a thing, and what the thing actually means. This serves as an entry point into talking about not only the way the word “game” is incredibly overloaded with different people’s interpretations, but also as a way to start discussing the way games themselves can mean things.

This leads to exploring the notion of “play” as space — free movement within a system, which is not a new idea at all, ranging from Derrida to Salen & Zimmerman. And then to looking at the two big sorts of play I see: the play of the possibility space of a set of rules, and the possibility space of a set of symbols or signs, which we might be more used to calling the thematic depth of a literary work. Along the way I break down writing techniques, game design techniques, and more, trying to find the ways in which these tools can be applied to games of different intents — which tools work best for a given craftsperson’s purpose?

For me, a lot of the reason I did the talk was to try to bring together the parties separated by contention over “what is a game” and similar debates. I wanted to show that there’s a lot more commonalities there than not, but also that different creators have different goals for their work, and therefore pick up different tools from the workbench. And that, actually, sometimes this means that games we’d never link together actually have structural commonalities just because the techniques that the creators choose to use.

I actually think I ended up spending too much time on the first half, which is effectively “game critic inside baseball” for quite a lot of people (though might be interesting nonetheless). The result was that I kind of rushed the second half, the part with the tools and techniques. Ah well. I am told it was an interesting talk anyway, just not one of my best.

Enjoy!