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Saber-Friendly Blogging 101: Pitching RAR

(Short version: download the 2008 RAR data for starting pitchers.)

Saber-Friendly Blogging 101 is my attempt to give team-specific bloggers article ideas and the data necessary to write their own saber-friendly articles -- the articles I want to read, but can't find enough of.  In the first installment, I took a look at BABIP, and what it can tell you about which pitchers were possibly lucky or unlucky in 2008.  Michael Taylor of Tribe Report did a nice job running with the concept.  But we can go a step further than just looking at BABIP -- actually a few steps further.  By taking all the things we know are under a pitcher's control (and only those things), we can estimate what a pitcher's ERA should have been, all else being equal*.

One basic statistic that estimates true-skill ERA is FIP (Fielding Independent Pitching).  It was created by Tom Tango and uses a basic arithmetic formula using K's, BB's, and HRs: (HR*13+(BB-IBB+HBP)*3-K*2) / IP + 3.20.  It works quite well and is available at both The Hardball Times and Fangraphs.  The Hardball Times has another similar statistic called xFIP, which uses a modified home run total instead of actual home runs.  As the semi-accurate cliche goes, pitchers allow fly balls, but hitters turn those fly balls into home runs.  Therefore xFIP uses the league-average home run-per-flyball rate combined with each pitcher's fly ball rate to estimate how many home runs a pitcher "deserved" to give up.

But the most advanced pitching statistic available just popped up this summer over at StatCorner, although there has yet to be a study to show that it's actually better than FIP or xFIP or even ERA.  (Many people assume it is, though.)  It's called tRA and uses eight categories of outcomes that are strongly under pitcher control: Ks, BBs, HBPs, HRs, GB%, LD%, OF FB%, and IF FB%.  In one sentence, tRA credits pitchers for their ability to induce those eight events, without caring about the actual outcomes of the balls hit into play.  And everything's park-adjusted.  For a longer explanation, read this.  For a no-numbers explanation, try this.

Ok, so let's assume we have this special number, tRA, that best represents a pitcher's true demonstrated skill.  (I actually add two adjustments -- one to account for NL pitchers not facing a DH and another to put it on the ERA scale -- and call it tERA.)  What can we do with it?  Well, we can value the production of pitchers, of course.  If tERA is our measure of quality, we next need to measure quantity.  Inning pitched is the obviously solution, although I prefer Statcorner's expected innings pitched (xIP).  Why?  Because if a pitcher is unlucky and extra balls are falling in for hits, he's getting docked outs and being credited with fewer innings than he deserves.

To measure a pitcher's total production over replacement-level, we compare his tERA to the replacement-level tERA of 5.75, divide by nine to put the savings on a per-inning basis, and multiply by the number of expected innings he pitched.  For example, Cliff Lee had a 2.64 tERA and 222 xIP in 2008.  His RAR is (5.75 - 2.64) / 9 * 222 = 77.  That production compares favorably to every position player except Albert Pujols, by the way.

What's that?  You want all the relevant tERA, xIP, and RAR information for your favorite team's starters?  Well, here you go. The data tab separates out contributions to different teams (thus, CC Sabathia will be listed twice) and the player pivot table allows you to select just the pitchers on any one team.  The team pivot table shows the total value provided by each team's rotations.

Ideas for a team-specific article:

  • Explain why tERA is a better measure of pitcher value than ERA (it removes fielding, ballpark effects, luck, etc.)  Also explain it's limitations (see below).
  • Present the xIP, tERA and RAR info for all starters on the team.
  • Present the same data for the projected 2009 rotation.  You can pro-rate the RAR numbers to different innings totals based on 2009 projections.  Or compute them yourself given whatever ERA and IP projections you want and the RAR formula.
  • Take a look at how your team's rotation stacked up against the other teams in MLB or in their own league in 2008.
  • Discuss any potential free agent signings or trade targets in terms of their 2008 value.  Compare their 2008 tERAs to their actual ERAs to see if they're coming off seasons that were underrated or overrated.

For fun, here's the majors' best rotation in 2008, the Arizona Diamondbacks'.  Remember, their park is one of the more hitter-friendly parks in the majors, and their fielders were below average by thirty runs according to UZR. 

Brandon Webb 231.3 3.10 68
Dan Haren 219.3 3.22 62
Randy Johnson 193.3 3.35 51
Doug Davis 151.0 4.36 23
Micah Owings 103.3 4.86 10
Max Scherzer 38.7 3.76 9
Yusmeiro Petit 40.7 4.27 7
Edgar Gonzalez 28.3 5.26 2

* "All else being equal" is a decent, but imperfect, assumption.  For example, some pitchers allow groundballs that are easier to find than other pitchers.  And some pitchers better adapt to situations and can change their approach when needed.  The effect of these other things are generally small, but they can become significant at the etremes.  The next stage of research will probably be aimed at picking apart these issues.