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Basing this theory of effectiveness on a mathematical formula based on statistics and assumptions is all fantasy warrior-ship.
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The formula/calculations have no bearing on effectiveness in the sense of predicting a person's success in an actual gunfight.
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No, it isn't a fantasy warrior-ship and such exercises do not readily relate to any sort of predictive realities for any one given situation. Simply put, it is unreasonable to assume that based on historic data of autonomous events (which is basically what is being assumed by the summary hit rate considerations) that whatever pattern they show in the past will necessarily predict the outcome of a given autonomous incident occurring now or in the future, but can be accurate in predicting a pattern for such events in the future. Looked at another way using medical information, if a given type of cancer has a 50% mortality rate, just because you get it doesn't mean you have a 50% chance of dying from it, though people may continue to die from it at a rate of 50%. It very well may be that when discovered quickly, historically folks recover 99% of the time and when discovered late that they die 99% of the time from it. So while the average death rate for the particular cancer may be 50% for the entire population, the entire population trend indicated isn't really even a reasonable predictor of the rate at which an individual may die from it. We actually went through something like this with my dad and his doctors. In his case, the cancer kills folks in the first year after discovery 90% of the time. As it turned out, about 85% of the time when discovered, the patients were already terminal. Pop's was discovered very early, within a 3 month window and he got the correct treatment. So while the 90% fatality rate in the first year and 98% fatality within 5 years sounded horrible, it is just the trend of the overall population and not indiviually specific.
Trend analyses provide you information about trends more so than about individual specific events. It may look like that for a given event there is X% likelihood of occurring and that would be correct for a trend perspective, but not necessarily correct from a specific event perspective.
Assuming the data are 100% accurate of real life, missing from the equation is also the speed of incapacitation. Over the years, we have discussed several events where mortally wounded people still managed to kill other people before dying. I will see if I can find it, but I seem to recall a midwest cop who was victorious, but killed in a gunfight with multiple bad guys (2, I think). One badguy was killed and the other seriously wounded and handcuffed by the cop. This was pre-ballistic vest and it was winter. He did not realize he had been shot, thought he was fine, had told people he was unharmed, and collapsed while talking with late arriving officers about the event. So he was incapacitated and incapacitated by 2 wounds which were inflicted early in the fight and after suffering the wounds, killed one guy, wounded and handcuffed the other, and then stood around talking about the event.
It is for reasons such as that that the Secret Service trains its protection detail to run their hands over the President after a shooting as the person shot (such as Reagan) doesn't always know it. Of course in Reagan's case, the hand inspection missed the wound the first time which delayed Reagan getting to the hospital. Reagan did feel pain, but thought was from being essentially dogpiled into the limo with him on bottom.
Anyway, so time to incapacitation is also significant and extremely difficult to model for things other than shots producing immediate and significant high CNS damage.