No, I was saying that Suppan's career xFIP and FIP probably aren't that meaningful at this point. If I were just looking at HR/FB I'd probably look at career rates for it since even with age it jumps all over the place but in this case the two are pretty much even, his 3 year average is 11.7% and his career is 11.8%. Not sure what you are getting at here. His career ERA is 4.68 and his career xFIP is 4.65 so at this point I'd guess that xFIP is a pretty good way to measure the quality of his seasons. There isn't a bunch of noise between the two stats like you'll find with a few isolated pitchers. For a single season the HR/FB has such a huge effect on FIP that it just doesn't mean much to me, why would I correct 2 out of 3 high variance stats and completely ignore the 3rd, just makes no sense. Both FIP and xFIP have various flaws and I still think it is useful to always look at ERA as well because if you look at the ERA trend vs the xFIP trend you can figure out the real story usually. BABIP, LOB% and HR/FB% are all skills, just skills that have a pretty narrow range and that are subject to extremely high variance year to year. Imo that is exactly the opposite of how you should look at it. With a large sample you can ignore the context, with a small sample you pretty much have to look at because the data itself is pretty useless without it. This is basically what regression is, it is assuming a big jump outside of the norm isn't going to be sustained. That Chone projection is assuming that Suppan was significantly worse last year and that trend will continue and he will be even worse this year. Looking more closely at the sample I don't really agree with it, I think it is a bad projection. Something between his 3 year average and last season I could see, but not a jump worse than last year.