The point is that the low OBP for Dawson can’t be looked at in isolation, as something he has to overcome. It’s one piece of the puzzle, that’s all.This is spot on, and it's something that I've been dwelling on over the past few months (and not just with respect to baseball).
We have a tendency as humans, excelling as we do at pattern recognition, to prefer discrete classifications to continuous valuations. This is a mistake most of the time. There isn't some hard and fast line at which an on-base percentage becomes acceptable for a Hall of Famer. Any low on-base percentage can be made up for by sufficiently greater production in another area.
It's so easy to get caught engaging in this kind of analysis. We think "Player X can't possible be productive! He only gets on base 32% of the time and he's a singles hitter!" We may be right: Player X may not be productive. However, if Player X is also the best defensive shortstop in the league, there's a great chance that he is actually a highly valuable player.
At the same time, simply being the best defensive shortstop in the league doesn't automatically make Player X valuable. If his offense is poor enough, it doesn't matter that he's better at defense than his peers. In order to perform a proper valuation of Player X we need to quantify every single factor that we can and then see where our evaluation fits within the continuum of baseball players.
Now this isn't an excuse to fudge the numbers. Far from it. Just because we need to whole picture to make correct valuations doesn't mean we can suddenly start assigning arbitrary value to things like "intangibles" or "hustle" or "grit" or "heart." We still need to place analysis within the proper scientific framework.
We need to realize that things rarely fall into discrete buckets. When we bucketize continuous data, we leave ourselves open to error. That is the lesson.
No comments:
Post a Comment