# Method to reliably determine abnormal statistical values

I'm searching for a statistical method to determine if a player is cheating in an online game.

Given a number of positive points and a number of negative points per player (score) and given $n$ players ($n <= 64$). Each player can cheat independent of each other. I used standard deviation, which works great on a single player but fails miserably as soon as several players are cheating at the same time.

Is there any useful algorithm or formula for this problem?

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I've posted it to stats.stackexchange.com/questions/4904/…, with further explanations. –  Quandary Nov 25 '10 at 11:25

How is their score generated (what kind of game is it)? What should your non-cheating data look like? How do people cheat? How will their score be different (in a statistical sense) when they are not cheating? Do you know roughly the proportion that are cheating? Or is that something you also want to find out?

I would also look at outlier detection algorithms: wikipedia looks useful on this topic (link). Using a Q-Q plot on your data may also be useful if your non-cheating data should be approximately Normally distributed; points that are significantly above the line might be cheaters.

You may also try posting this on the stats.stackexchange.com since this is really more of a statistics question.

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