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For your prescription to work, the common event -- say fly ball speed off bat -- would need to be very highly correlated with the rare event -- homeruns. My guess is that to have the correlation be strong, you will need to account for speed and trajectory (or truly the velocity off the bat, which is vector quantity). My guess is once you have a data base full of velocity on fly balls to analyze, I predict that you will need to significantly down select the types of flyball velocities to get a strong correlation to the homerun rate and be back to the same problem. It's a predict, it's not fact, so I could very well be wrong.
Let's consider a fielding F/X for outfielders where I could see it working. We need to know how long it takes the fielder to start moving once contact is made, we need to know how long it takes the fielder to get intersect the flyball, and I guess we would need to know how direct the trajectory of the player to the ball is. But most flyballs are routine, so how fast the fielder moves is dependent on the nature of how hard the ball is to catch. Consequently, the routine plays don't provide useful information. It's only the hard, but potentially makable plays that will provide useful data.
My intuition tells me that common events tell us little about the rare events that drive baseball outcomes. I agree that the number of useful events strongly correlated with the important rare events is larger than the rare events themselves, but not as much larger as you seem to be indicating. It will be fun to find out and I'd be happy to be wrong.