No problem. I think we mostly agree on the issue anyways, Lincecum is the better pitcher, and the extraneous variables are already beginning to regress to their expected mean. By the end of the season, the likely case is Lincecum’s season will be significantly superior to Cain’s. Cain had a great, but unsustainable start to the season, and he deserves some amount of credit for it because it helped the Giants win games.

“BABIP has reletively very little to do with the goodness of the pitch”

Show me a single place where this has been studied.

“Good pitchers throw more good pitches than bad pitchers, so, if a low BABIP were really just a result of good pitches, good pitchers would consitently have lower BABIP than bad pitchers.”

Well, this very well could be the case, and the variance is just incredibly small. Essentially it’s saying in large samples it regresses to the mean.

“I specifically mentioned that pitchers do have some control over their BABIP, just not as much as hitters, fielders, and random chance do.”

The point is in an individual case, with a small sample caveat, we don’t have the data to actually break up who was responsible for what. It’s useful to assume what holds true in large samples is true here, but that doesn’t mean it’s completely accurate in all cases. The work has been done to study what happens in a large sample across pitchers on average, but in the specific case I’m talking about, we really don’t have any data to go on to suggest how we should break up the credit.

“the “goodness of the pitch” can’t really affect whether a solid grounder will find a hole or not"

Agree here of course, but the point is the pitcher may have induced a number of weak popups or not so solid ground balls or any other situation that resulted in an easy out. These things regress to some mean over time, but can certainly be a major factor in a small time period. Also, we have no idea how the timing of these factors worked. As you pointed out, Cain’s K/BB with RISP was lower than it was without RISP, but do we know the timing of the K’s and BB’s? A K with a runner on third and one out is going to be a big at bat that decreases their chance of scoring by a lot. It may be that he only issued walks when there was an empty base. It may be bases were loaded with 1 out and there was a strikeout and then an infield fly or other poorly hit easy out. A few situations like this can skew the results from a small sample size.

We don’t have data available to study all these possible factors that I’m aware of. Until we do, we’re making assumptions based on what happens in large samples. There will be cases that fit these assumptions, and cases that don’t, and it may be that Cain’s overall numbers really were enhanced by some combination of just luck and defense, but we don’t have the evidence to conclude that for sure. When all the extraneous variables (which we don’t even know how many there might be) regress to their mean, then we can be confident in our conclusion.

“Good pitchers throw more good pitches than bad pitchers, so, if a low BABIP were really just a result of good pitches, good pitchers would consitently have lower BABIP than bad pitchers.”

There seems to be some evidence they do, but the variance is very small. Mostly, though, it should result in more K’s, less BB’s, less HR’s, and maybe a better batted ball profile. That’s not to say over the course of 50 PA, a few times when a guy would have struck out they make a little bit of contact and hit into an easy out.

My overall point is we don’t really have good data to support making solid conclusions in a small sample. The truth is we don’t know exactly what happened and who did/was responsible for what. How much of Cain’s situational pitching, over the first couple months of the season, was because of his pitching, and how much because of defense and luck? I can’t fault you for assuming what he did was what happens on average, I just urge you to be open to the fact that we don’t actually know how all these factors played out.