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[Trevor Edwards]

Great topic, and I’ve been digging into this on both sides of the fence as a player who’s also spent too long reading about anti-cheat internals. On the trajectory side, most modern heuristics lean on jerk analysis—the third derivative of position—rather than raw linearity, because humans genuinely can’t produce low-jerk motion during the rapid deceleration phase of a flick. What catches me is that people fixate on straight-line accuracy, but the real tell is the dwell behavior once the crosshair locks near the target. Real players make those micro-saccadic corrections and slight overshoot-then-return patterns, whereas even a well-tuned soft-aimbot tends to over-smooth that final approach. If you’re benchmarking, I’d specifically look at the coefficient of variation in your sub-target acquisition times and the smoothness metric during the last 40ms before the shot—those are far more discriminative than total path error.

On the hardware interaction side, which I think gets underappreciated, your sensor’s polling rate and reporting consistency directly affect what the ML sees. At 10

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