There are millions of possible scenarios that can occur in a baseball game and many different ways, philosophies and proven methods of handling them successfully. The actual probabilities of such events are only fractionally different in the micro, so much so that haggling over the choice of one method or another is not only a narrow view of how things work, but probably not even always statistically accurate if we could truly measure all the variables involved in the decision.
If it were simple as knowing exactly what is the best decision and what wasn't, we would just play a computer simulation and be done with it.
However, we're dealing with very unpredictable variables. Variables that are humans and not computer models.
The funny thing is that to prove someone did indeed make a "bad" decision to bat someone second in a given game, even statistically, they'd have to run probability for all the possible outcomes and possible alternatives. That's neither practical and only possible with a supercomputer, I imagine. After all, the difference between Renteria's OBP and the other options is no more than 3-4%. And that doesn't include the other important variables such as who's pitching and other circumstances within the game itself which could, theoretically, make Renteria the statistically sound choice in *some* situations. And since each game and each situation is its stand-alone event, that's what really matters...optimizing the situations themselves.
To make any definitive judgments about the quality of a decision in a single game or small subset of games is narrow and oversimplifying matters. We're really debating, in this thread, literally fractions of percentage points in some cases.
Originally Posted by jojo
