I've decided to continue my research into xBABIP and it's impact on the Colorado Rockies. If you haven't already you'll probably want to read my original article here since I won't go over the individual processes again, but instead focus more on it's implications in today's fanpost.

So first, a little review, from last week's chart shown below. I identified Helton, Fowler, and Scutaro as being the 3 most likely players for positive BABIP regression due to their BABIP being at least .050 below both their expected BABIP(xBABIP) and career BABIP (cBABIP).

Out of those three, we've already seen Scutaro's BABIP regress back to .292 while Helton has shown a slight increase to .217, and Fowler's BABIP has pretty much stayed steady at .269

The most obvious candidates for regression was a bit tougher, but Cuddyer and Colvin probably stuck out the most, even though their BABIP's were backed up with solid xBABIP they were still way higher then their career BABIP. This most likely meant that though their high BABIP was a direct result of good hitting they'd probably just cool off in their hitting approach more then anything. Cuddyer has regressed a bit to a still solid clip of .349 while Colvin decided to bribe the BABIP dragon and now has a BABIP of .440!

So here's the updated table for Rockies games played through Wednesday. For simplicity's sake, I calculated xBABIP for all Rockies that have 20 or more plate appearances.

I won't discuss every single player and the implications of their xBABIP, I'll leave that for below in the comments, but here's a few observations. Helton and Fowler are both still due for positive regression, even though Fowler's not hitting the ball as well as his cBABIP suggest he can. Tulo also seems due for some positive regression, as well as everybody's favorite Herrera and also both catchers. EY2's xBABIP is obviously a factor of small sample size and a ridiculous 38.5% LD rate among other factors like his IFH% but still it is impressive none the less. Colvin actually raised his already ridiculous xBABIP from the previous week even more. And finally, Cargo seems to be the definition of neutral luck as his BABIP has matched his xBABIP almost perfectly both weeks, though I'd expect his current hot streak to continue a little longer until he's at his cBABIP.

A final note on comparing BABIP/xBABIP to cBABIP is I put more stock in players regressing to it if they have more plate appearances. Obviously this might not hold true if a player is having age based regression in play as well, but for example I don't put a lot of stock in Rosario's cBABIP as it is such a small sample size and s heavily affected by his BABIP from this year. An opposite case would be Cuddyer his cBABIP is probably pretty close to what we should expect over time though I'd expect a bump in it due to park factors.

Finally, I calculated the players' expected batting average (xBA), on-base percentage (xOBP), and expected slugging percentage (xSLG%) for their new expected triple slash. xSLG% is the one new addition from last week and I thought I'd attempt it after doing some reading, I'm taking a player's ISO and adding it to the xBA. This idea was suggested by Jeffrey Gross in his article found here, which I found this past week in which he did a lot of the same things that I did last week. Obviously his was published earlier, though I didn't find it until after my fanpost from last week.

Once again, I hope you enjoyed this and thanks for reading. Feel free to ask any questions or discuss any of this in the comments. I'll try to answer as many of them as I can.

CITF