[emgeee]

I've always wondered about this too. It should be pretty easy to recognize statistical outliers. I'm sure cheaters would start to adapt but that adaptation might start to look more in-line with normal skill levels so at least the game wouldn't be utterly ruined

[babypuncher]

The problem is that most cheaters don't just go full aimbot and track people through walls. That is a surefire way to make sure your account gets reported, reviewed, and banned regardless of what anti-cheat is in place.

Serial cheaters cheat just enough to give themselves an edge without making it obvious to the people watching them. By just looking at their stats, it can become very difficult (though not impossible) to differentiate a cheater from a pro player. This difficulty increases the odds of getting a false positive, necessitating a higher detection threshhold to avoid banning innocent players.

[nicce]

Valve has adapted this kind of thing in Counter Strike for almost a decade.

They try to make own matchmaking for possible statistical outliers so cheaters end up playing against each other. Of course, real good players can still get there and there are (at least used to) real humans on reviewing on those games to see if someone is actually a cheater. It is not a simple task, since you can cheat to be just slightly better than others and that is enough to be good.

[alex_lav]

This post is so interesting because it highlights the people that don't know anything about the requirements or state of cheats/anticheat. What you're describing is 10 years out of date. Every modern cheat has a toggle, and (almost) every modern cheater masks augmented behavior with misses/native behavior.

[lifeformed]

This thread is full of armchair developers who see a problem and immediately think, "Oh, it's easy, just do this simple thing I just thought of," as is there haven't been billions of dollars and decades of research spent on this problem.

[lifeformed]

Good players are statistical outliers. False positives are hard to avoid with this kind of approach.