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Last season, one of my favorite baseball reads that became useful fantasy knowledge was this piece by Rich Lederer at Baseball Analysts.  What he laid out is something that I’ve recommended and used in previous years as a quick and dirty way to look for potential targets at the end of drafts. If you believe in simple regression to the mean, it makes sense to target pitchers that were well below their personal and/or league average, since logic dictates they should do better the following season. As Lederer put it:

While strikeouts, walks, and home runs play a large part in determining ERA, the latter is also a function of defensive and bullpen support, as well as performance with bases empty vs. runners in scoring position. As a result, the difference between ERA and FIP is almost entirely accounted by strand rate (LOB%*) and batting average on balls in play (BABIP). Each variable has a coefficient correlation of nearly 80 percent with the delta between ERA and FIP.

When you put the two together (LOB% divided by BABIP), the coefficient correlation jumps to 90 percent. Accordingly, the coefficient of determination or R² is 81 percent. In other words, more than four-fifths of the difference between ERA and FIP is due to LOB% and BABIP. As such, in addition to SO, BB, and HR rates, it makes sense to study LOB% and BABIP to understand why a pitcher's ERA may be better or worse than his FIP.

The graph below shows the 138 pitchers who threw at least 100 innings last season. The red lines represent the league averages for BABIP and LOB% while the slanted line is the line of best fit and represents a correlation coefficient of -0.43.

Quadrant I represent the pitchers who had both a BABIP and a LOB% that were better than league average. The table below shows the most extreme members of this group:

PITCHER

2011 BABIP

2011 LOB%

CAREER BABIP

CAREER LOB%

ERA-FIP

Jered Weaver

.252

83%

.276

77%

-0.83

Jeremy Hellickson

.224

82%

.230

82%

-1.52

Justin Verlander

.237

80%

.285

73%

-0.63

Josh Beckett

.249

80%

.290

72%

-0.72

James Shields

.260

80%

.299

73%

-0.63

Ricky Romero

.245

79%

.285

75%

-1.31

Cole Hamels

.259

78%

.280

77%

-0.23

Johnny Cueto

.254

76%

.283

75%

-1.11

Hellickson’s career numbers mean nothing since his career is nearly entirely comprised of 2011 statistics. That said, he and Weaver are very similar in many ways. Both are mainly fastball/changeup pitchers that induce plenty of swings and misses along with bad contact in the form of infield pop-ups.  Largely as a result, Weaver has had a BABIP below the league average for most of his career, and Hellickson has shown a propensity across one season to do that. Hamels is another pitcher who has been able to out-perform the league average several times, and he has been a Quadrant I pitcher for two straight seasons. Also worth noting is that five of the pitchers above also feature one of the best changeups in baseball, which helps them with both swings and misses as well as inducing weak contact.

The ERA-FIP column shows why many seem to be running from Hellickson in drafts this month and why his BABIP has been quite the talking point in recent weeks.  If you regress Hellickson’s BABIP to league average using the 3700 balls in play figure both Tom Tango and our own Derek Carty found to be correct, his BABIP comes out to .282. However, if you regress it to the Rays’ team BABIP of .266, Hellickson’s BABIP would have been .260. There is no doubt that Hellickson’s BABIP will climb in 2012, but looking at numbers like that should help lessen the worry about it climbing all of the way back up to the league average (especially since, as an extreme flyball pitcher who induces pop-ups, his BABIP should be expected to be lower to begin with).

The largest ERA-FIP differences in Quandrant I were:

When pursuing pitchers in Quadrant I, some will come at a discount because people fear regression, but the bigger names often find their way into that quadrant because they are simply that good. Conversely, Quadrant IV present bargains in the form of pitchers coming off rough seasons thanks to worse-than-average BABIP and LOB%. The table below shows the most extreme cases in that area:

PITCHER

2011 BABIP

2011 LOB%

CAREER BABIP

CAREER LOB%

ERA-FIP

John Lackey

.340

64%

.309

72%

1.67

Derek Lowe

.332

66%

.295

70%

1.38

Ricky Nolasco

.337

66%

.309

68%

1.17

Brian Duensing

.334

66%

.301

73%

0.92

Joel Pineiro

.324

66%

.298

70%

0.67

Jo-Jo Reyes

.326

65%

.317

64%

0.63

Jaime Garcia

.326

65%

.302

71%

0.63

In the case of Reyes, he was essentially pitching to his typical (poor) career averages, but the rest of the pitchers were much worse than their career averages. Lackey is out for the 2011 season, so he is out of consideration, but Lowe changing to a better infield defense, Nolasco moving indoors, and Garcia all present intriguing options to pick up at a discount.

Here are the 12 best ERA-FIP totals in Quadrant IV: