There's nothing flukey about Gio Gonzalez's hot start. (Getty)Small sample sizes still abound. But we have decisions to make and the season for some of us just cannot wait.

Perhaps we can isolate some randomness out of the numbers by looking at who has the best and worst fielding independent ERAs while also comparing them to their actual ERA's. We've noted some limits to FIP here in the past. It has a bias against extreme fly-ball pitchers. It's doesn't factor in pop-ups as 100 percent outs, or near it, as they are. But we can't let the perfect be the enemy of the good and FIP is a good stat.

Thanks to Fangraphs for the data, which is through April 25th. Let's start with the pitchers with the best FIP ERAs.

Player	Team	K/9	BABIP	LOB%	ERA	FIP	ERA-FIP
Gio Gonzalez	Was	10.27	.228	80.0%	1.52	1.51	0.01
Johan Santana	NYM	12.0	.311	63.6%	3.00	1.57	1.43
Zack Greinke	Mil	10.65	.381	62.9%	4.56	1.72	2.84
Clayton Kershaw	LAD	8.87	.288	78.3%	1.61	1.74	-0.13
Stephen

Read More »from Pitching by the Numbers: Getting a grip on FIP

Clayton Kershaw is the king of getting Strike One. (REUTERS)The most important thing that pitchers can do is get ahead of batters with the first pitch. But it's not as easy as it sounds: throw a fat strike on the first offering and you get hammered.

This year after a 0-1 hole, hitters have a .590 OPS and just a .276 average on balls in play. Compare that to the overall rates of .714 and .289. But when hitters put that first pitch in play, bad things tend to happen – .820 OPS this year (through Wednesday's action) with a .293 BABIP.

It's early and the usual sample-size caveats apply. But we have to start somewhere with this year's stats and the time is now given that most starters have three games. So let's see who is best and worst at putting batters in the hole. The speculative play here is to target pitchers who are winning the first pitch at a high rate but who are somehow getting pounded after getting ahead 0-1. Of course, there may be reasons for this but they are very hard to rationalize so I would defer to the base rates generally and Read More »from Pitching by the Numbers: Getting ahead

We talk about big things all the time here in Pitching by the Numbers and are eager to dive into 2012 numbers at the earliest reasonable opportunity. But that time has not yet arrived.

Kyle Lohse has done a good job of not beating himself.But to paraphrase Dave Edmunds by way of Bruce Springsteen, "(From Small Things) Big Things One Day Come." By that I mean things about pitchers that often escape our attention because they are not directly counted in our fantasy game. I'm talking mostly hit batters, wild pitches and especially stolen bases allowed (that's mostly a pitcher stat, not a catcher stat). The pitchers who pile these things up have a harder time preventing runs and, thus, wining games. Doing them well, I believe, allows pitchers to overachieve. We're also throwing in balks, too. Errors are another factor that could be considered but I'm not comfortable with equating them with relative fielding strength so I've ignored it here.

Let's start with the guys who do the small things the best, meaning they have the lowest number Read More »from Pitching by the Numbers: All the small things

I've crunched the 2011 numbers and have made related recommendations all spring. But now is time to officially go on record and name the pitchers I think will be bargains and busts relative to Yahoo! average draft position (in parentheses).

Grab 'em:

Chris Sale, White Sox (203.4): I like so many things about Sale that I don't know where to start. Let's begin with demonstrated big-league dominance (111 Ks in 94.3 innings). He's also left-handed and has even dominated righties. He's s flame thrower (95.3 mph average fastball last year) and has a plus change-up and one of the game's most effective sliders. Yes, he's converting from the bullpen, where he moved immediately after being drafted less than two years out of college, where he was a dominant starter. Projection: 175 innings, 190 Ks, 1.15 WHIP.

Anibal Sanchez, Marlins (149.9): We now begin the bias in favor of NL pitchers. Why swim against the current if you don't have to? Sanchez is the poster boy for the benefits of the

Read More »from Pitching by the Numbers: Bargains and busts

Elite skills translate into elite production and fantasy stats. For pitchers, the best way to measure skills is to look at the pitches in their repertoire and assess how dominant they rank by measuring how frequently batters swing and miss at them.

Our first fastball list is dominated by relievers, mostly because relievers throw relatively few pitches per outing and thus can put more effort into each one. So we've supplemented it in the text that follows.

Player	Pitch	# of Pitches	Batter Swings	Batter Miss%	Batter Swings at Ball
Tyler Clippard	Fastball	776	417	18.94%	167
Vinnie Pestano	Fastball	775	402	18.19%	143
Kenley Jansen	Fastball	843	392	18.03%	86
Jonathan Papelbon	Fastball	727	407	17.74%	123
Jesse Crain	Fastball	456	217	14.47%	69
Jason Motte	Fastball	862	457	14.15%	160
Koji Uehara	Fastball	587	319	14.14%	100
Craig Kimbrel	Fastball	890	391	13.71%	102
Aroldis Chapman	Fastball	745	322	13.56%	118
Ernesto Frieri	Fastball	835	409	13.53%	137
Louis Coleman	Fastball	491	231	13.24%	67

Read More »from Pitching by the Numbers: Pitch dominance

It's an axiom that most of baseball (75 percent) is pitching and thus we are all conditioned to believe that ultimately pitchers control outcomes when it comes to the matchups versus hitters.

But the conventional wisdom is wrong. There's little debate among statheads that it's hitters who generally have the most influence over what happens in an at bat. The trick is to isolate the exceptions to the rule – the pitchers who through their talent take most control over their pitching destiny.

A simple way to identify these pitchers, I think, is to look at how they perform against No. 3 hitters – since most teams place their best hitter in that spot. Last year, No. 3 hitters MLB-wide sported an on-base plus slugging percentage (OPS) of .805 vs. the MLB average of .720 (No. 4 hitters compiled a .791 OPS). Of course, there are sample size caveats and some pitchers, due to unbalanced schedules, faced weak-hitting teams that also have relatively weak-hitting No. 3 hitters. Still, I'd much

Read More »from Pitching by the Numbers: Baffling the best

The supposedly sabermetrically savvy are outsmarting themselves when it comes to fly ball pitchers.

Let's start with the king of all the new-age pitching stats – batting average on balls in play (BABIP, but if you pronounce that as one word, you are a dork). I like the stat, generally. Our pitching projections can be much sharper as a result of it. But it's not only less useful in projecting extreme fly ball pitchers, it's actually harmful.

The reason is that fly ball pitchers should be expected to have a much lower BABIP than league average for the simple reason that fly balls are significantly less likely to become hits than grounders. How less likely can be gleaned from this chart of the most extreme fly ball pitchers in baseball last year (minimum 20 starts):

Player	Team	GB/FB	AB	H	HR	K	SF	BABIP
Guillermo Moscoso	Oak	0.49	469	98	14	71	3	0.219
Jered Weaver	LAA	0.66	857	182	20	198	5	0.254
Josh Collmenter	Ari	0.70	530	129	16	89	2	0.266
Ted Lilly	LAD	0.71	723	172	28	158	5	0.268
Colby

Read More »from Pitching by the Numbers: On the fly

Kicking off this year's first Pitching by the Numbers is analysis inspired by Tampa Bay Rays righty Jeremy Hellickson, he of the declining strikeout rate and – largely due to that – a reportedly "very lucky" 2011 ERA (2.95 actual and 4.72 expected, says Fangraphs).

I find this K- and FIP (Fielding Independent)-ERA-driven analysis of Hellickson a little lazy. Wasn't this guy the bedeviling Hellboy just a year ago? Isn't his strikeout resume aside from 2011 top-shelf at all professional levels? There is no denying the K-rate dipped last year. When trying to work all this out with Yahoo! colleague Scott Pianowski in a backstage phone call, we both wondered why someone can't figure out a way to estimate K-rate like they do ERA. Could Hellickson's K-rate last year have been unlucky?

It struck me that percentage of swings that miss would be a good proxy. And it turned out that Fangraphs's Bradley Woodrum had a similar idea earlier. But my methodology is different and is focused precisely on

Read More »from Pitching by the Numbers: Lucky K