The Problems of OPS

OPS has been referred to as the "Ultimate Offensive Statistic". However, beyond not actually being the ultimate statistic (probably that would go to runs created or maybe VORP), it is also simply highly skewed.Problem I: Adding is really crudeAdding the two statistics OBP and SLUG together is a really crude combinatorial method. It's as if someone said "Hey, these are both good statistics; let's add them together so we can compare everything at once." Ok, maybe it's simple, but it has lots of problems, the most obvious of which is that in adding the two together, you lose the precision of each seperate statistic. Several of these problems would be eliminated if the two statistics were multiplied instead of added, but...Problem II: They aren't on the same scaleOBP goes from 0 to 1. SLUG goes from 0 to 4. This makes the weighting of the two components inherently non-equal against each other. A difference of .1 in OBP is huge, but a difference of .1 in SLUG is only significant.Problem III: The intrinsic problems of SLUGMore on this another time...Problem IV: The statistic assumes equal weightingQuite simply, the crude addition of OBP and SLUG gives no weighting to either statistic, but merely adds them in a 1:1 fashion. When combined with Problem II, this essentially actually gives an extra weight to SLUG. I believe that OBP deserves significantly more weighting than SLUG - perhaps an entry on why at some other time. So maybe 2, 3, or 4 times the OBP plus the slugging would be better than OPS. But the real nail in the coffin for OPS is...Problem V: The two components aren't valid over the same situationsSLUG has AB as its denominator. OBP has PA. These are two different, but overlapping sets of scenarios. In my mind, for true validity, or at least effectiveness, in adding two statistics together, you need the same denominator. In this case, I think that that should be PA, as it's more encompassing.