By Ray Flowers, Special to SI.com, BaseballGuys.com

Sabermetric Alley

Each week we will look at one metric or idea that can be added to your "toolbox" of knowledge to help you capture your leagues championship crown through a simple explanation of what it measures.

COMPENENT ERA
For years pitchers have been judged basically by two numbers; Wins an ERA. Most people have come to the realization that a pitchers Win total is actually totally out of the pitchers control (just because a pitcher hurls a great game doesn't mean he will always get a Win just as every loss or no-decision he earns isn't always the result of a poor performance). The same line of thinking applies to ERA, though I would bet most people who follow baseball would consider ERA to be more reflective of a pitchers talents than his W-L record. While in theory I would agree with that, ERA too has its limitations, which is the reason that the following metric was invented.

Component ERA, or ERC, represents the expected ERA of a pitcher based upon a reading of all of his statistics. Simply put, ERC is a metric which enables you to tell if a pitcher pitched in "good luck" or "bad luck" by telling you what his ERA should have been based upon his actual performance. ERC attempts to allow you to determine what a pitchers ERA should have been, thereby giving you a truer understanding of the type of performance offered (and what should be expected in the future).

In addition to showing how a pitcher should have performed based on his overall numbers, ERC also has the added benefit of equalizing all pitchers so that relievers and starters can be compared to one another more fairly. This comparison is achieved by eliminating the effect that one pitcher has on another such as when a reliever allows an "inherited runner" to score (an inherited runner being a runner put on base by someone other than the current pitcher).

How do we figure out this great tool you ask? Well, ERC is computed by a rather lengthy equation that is listed below. Regardless of the complexity of the actual formula, the end result is that the number it produces is read in exactly the same manner as ERA, so if you know how to read an ERA, you know how to read ERC.

Here are the 2006 ERC leaders as of June 28:

If you have read my work this year you know I have been down on Brad Penny for a variety of reasons. Here is just one more reason to add to the list. Despite 10 wins, 1 loss, and a 2.04 ERA, ERC shows Penny's current ERA to be a bit "lucky" in that his ERC number is actually over four tenths of a point higher. This leads me to the category we will look at next week; ERC Difference. Which pitchers have been "lucky", and which have been "unlucky?" Next week, we will find out when we take a more in depth look at ERC.

Before we leave this discussion, let me spend a moment detailing how you can figure out ERC on your own. In order to come up with ERC, a two-part equation is necessary.

A) PTB = 0.89 x [(1.255 x (H-HR) + 4 x HR)] + 0.56 x (BB+HBP-IBB) *PTB (Pitchers Total Base Estimate)

Let's use Jason Schmidt's 20004 season for this example:

*BFP = Batters Faced Pitchers (total batters against)

PTB = 0.89 x [1.255 x (165-18) + 4(18)] + 0.56 x (77+3-3)
PTB = 0.89 x [1.255 x (147)+72] + 0.56(77) PTB = 0.89 x [184.485+72] + 43.12
PTB = 0.89 x [256.485] + 43.12 PTB = 228.272 + 43.12 PTB = 271.392

B) ERC = [(H+BB+HBP) x PTB / (BFP x IP)] x 9 -- 0.56
ERC = [(165+77+3) x 271.392 / (907 x 225)] x 9 -- 0.56
ERC = [245 x 271.392 / 204075] x 9 -- 0.56
ERC = [66491.04 / 204075] x 9 -- 0.56 ERC = [.326] x 9 -- 0.56
ERC = 2.934 -- 0.56
ERC = 2.374

Therefore, Schmidt's ERC in 2004 was 2.37 (his actual ERA was 3.20).

Short Hops

J.J. Putz has shown remarkable control this year for the Mariners with six BBs in 36.1 IP (he also has a 0.99 ERA and unearthly 0.58 WHIP). However, Putz has a long way to go to match a five-year span in Dennis Eckersley's career. From 1998-2002, Eckersley walked a total of 38 batters, or 0.95 per 9 IP. Over those 359.2 innings, Eckersley went 24-9 with a 1.90 ERA, and 220 Saves (44 per season average). Oh year, he also had a 0.79 WHIP and a 9.95 K/BB ratio thrown in there for good measure.

For the fourth straight year in 2006, Rafael Furcal scored at least 100 runs while hitting 10 HRs and stealing 25 bases, making him the only SS to do that each of the last four seasons. However, he is unlikely to make it five straight years considering he is currently hitting just .270-1-27-34-7 for the Dodgers.

Nap Lajoie is officially credited with the highest single-season batting average of the modern era when he hit .426 in 1901. However the all-time leader is actually Hugh Duffy who hit .440 in 1894. And you thought that Magglio Ordonez, hitting .377, was hot.

June 28, 1939: The NY Yankees hit a total of 13 HR in a doubleheader against the A's, a major league record, led by three each from Joe DiMaggio, Babe Dahlgren and Joe Gordon.

Ray Flowers, a member of the Fantasy Sports Writers Association (FSWA) and the Society for American Baseball Research (SABR), can be reached with comments and questions at: fantasyfandom@yahoo.com. To read more of Ray's work visit Baseballguys.com.