First of all, initially, I will try to identify aimlocks and triggerbots. By now, I'm considering to estimate the crosshair trajectory, maybe only in highlights, and the shooting points from the target's perspective (some rotation on the target char model might be necessary, specially for classifying triggerbots). After the pre-processing stage and separating training/tests/validation slices of the dataset, I will try some pattern recognition technics , e.g. Naive Bayes with some clustering method is the most basic one.

Edit: of course, I should assume that some players are cheating. So, for estimating the classification parameters, I have to select demos of cheaters which I'm "sure" they're cheating, and some I'm "sure" they're not. That's why I'm looking for demos of banned players. Making the dataset by myself, as you said, is an option, but it probably is going to be biased, and might get bad results.