I really didn't want to wait til the end of the year to skew the data with September call-ups so I'll post this now for your consumption.

For those who don't know, a simple google search on the subject will familiarize you with the concepts here as much work has been done on the subject in just the last year. Several fairly in depth models have been developed but I choose just to keep things simple with a aLD+bGB+cFB model. It isn't as good as the others, but it will still be pretty close and a lot easier to compute. If someone wants to run one of the better models for comparison, I would highly encourage it.

Lastly, this isn't a list of who is good/bad on the team, its an adjustment. Billy Butler is and will be a great hitter, even if he was lucky this year. The list below the jump.

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Just the luck, a major area of baseball statistical interest for me gets a major post by Mellinger and I’m out of town with the Fanpost already falling down the main page.  Well, I want to respond to a couple misconceptions about BABIP and I felt the comments section of our community response wouldn’t do it justice.  This is partly a summation of other’s ideas, partly my take on it, so feel free to correct me if you believe I have misstated some part.

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I thought about just adding a comment to the Aviles/Sickels thread, but as I think Mike Aviles will be the single most talked about person this off-season for RR, I wanted this to be a new post.

So, a lot of you read my look at xBABIP and the royals, but a central theme about some comments was what it really means. When comparing actual versus expected values, how does that translate to more traditional stats which actually tell you about on-field performance. i.e. what does a BABIP-xBABIP of .60 mean?

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kcdc1 recent post on the inherit problems with applying xBABIP to hitters lead me to do some work on if certain hitter types produce different results from batted balls. Obviously as technology improves, individual analysis will be possible, but for now, I still try to group players in well defined profiles. The data I’m using is from 2007 and includes only qualified batters, so this is an analysis of MLB regulars only. Also, home runs and infield flies are properly accounted for this time.

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Let’s take a look at some Royals hitters and how their luck and other factors have fared over the last few seasons.

I’m an economist that does forecasting for a living, so all these stats are a labor of love. Plus, I have become completely sold on this 3 true outcomes approach to baseball. Basically, I’m looking at the difference between BABIP and expected BABIP (an avg of a couple different methods to calculate it) to look for luck, which are the unlabled stats given. Also, I’m looking at line drive rate variance to see if expected BABIP is a reasonable estimation. I also like walk/k rates and isolated power (if all this sounds a lot like PECOTA minus its comparables, it should).

Quick note: of course young guys can improve, but this is a historical stat take on things to see how reliable those stats are for us to judge our guys on.

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quick and dirty question...
does anyone know (or know source) of the eBABIP equation?

I have a link to a guy who quotes .763LD% + .265GB% + .131FB% as the 2006 version.

I ran a regression on 2004-2008 batted balls and got .463LD% + .242GB% + .261FB%
but i know of some errors on that, but I didnt think they were that big of ones to get such a different result.

I have been running some stats on our boys looking for signs of hope, and I am trying to get a better idea of how lucky a team we are.

early results... TPJ very unlucky, but still bad