As a counterpoint to some of Gavin's, perhaps the best approach would be a data collection task. Write the intercept plugin, but for a month simply harvest data on players. Use that to construct a few "ideal" or "average" models that encapsulate what real players actually do.
The AI guy in me says to use these models and train a decision machine / "deep neural network" or SVM to discern player vs. bot or newbie.
The practical guy in me says we could use those models to make pretty good decisions concerning how to weigh player actions in determining if a player is legit or not without resorting to fancy AI.
Basically, if the only way to get full damage is to approximate a real player's actions based on several legit models discerned from actual players, and you go to all the trouble of actually approximating that behavior over time, aren't you effectively just a legit player?
We could tie ourselves in circles on this, or just get some hard data to see if its feasible. If after collecting data for a month you've got activity soup and no clear stochastic or average models emerge, call this idea dead and move on.