May 28, 2014; Washington, DC, USA; Washington Nationals starting pitcher Jordan Zimmermann (27) pitches during the first inning against the Miami Marlins at Nationals Park. Mandatory Credit: Tommy Gilligan-USA TODAY Sports

Nationals Starting Pitching Below Average? Afraid So.


When a team enters a season with high expectations like the Nationals, and through a third of the season plays below .500, people tend to search for reasons why.  Is it the hitting?  Oh boy, these guys stink.  What about the defense?  That guy handles second like he fields with a pizza box.  Recently, a lot of the talk has focused on the Nats pitching and how they haven’t lived up to their lofty preseason billing.  Is this true?  Has the pitching been suspect this season?  If so, is it the starters, the relievers, or both?  And if so, just how bad has the pitching been relative to both the league and to prior seasons?

So, in an effort to answer this question in my own mind, I begin to review the starting pitching, a group targeted by many as underachieving.  Note that all statistics were gathered via FanGraphs.

Year ERA K/9 BB/9 K/BB H/9 WHIP
2012 2.96 8.54 2.57 3.33 7.32 1.10
2013 3.41 6.97 2.20 3.17 8.53 1.19
2014 3.87 8.14 2.44 3.34 9.39 1.31

Nationals Starting Pitching

Of all the statistics presented in the table above, I find ERA to be the least informative for the purposes of evaluating a staff’s effectiveness.  A lot can go into ERA, and sometimes it can be attributed to plain old bad luck.  On the other hand, while most of the numbers have remained relatively steady from year to year, there are marked jumps in both H/9 and WHIP over the last two years.  Is it related to luck, though?  2014 definitely shows the highest BABIP (.329 in March/April and .306 in May) and batting average against (.306 in March/April and .271 in May) in the last three years.  Without comparing those numbers to league averages, however, we’re left with an incomplete picture.

Year ERA K/9 BB/9 K/BB H/9 WHIP
2012 28.44 -21.52 13.64 -40.72 17.69 16.68
2013 17.72 3.97 23.20 -25.04 4.29 8.89
2014 0.69 -9.74 14.53 -28.40 -6.38 -1.27

Starting Pitching Relative to MLB Averages

In 2012, that staff was world beaters compared to the Major League average.  While they were worse in K/9 their H/9 and WHIP were significantly better.  Look how those numbers drop throughout the following years, however.  As of right now, in 2014, the Nats starters are 1.27% worse in WHIP relative to the average.  Their walks are still held to a minimum in comparison, so obviously it’s how badly they’ve been hit.  Well, have they been unlucky there?  The Major League average in 2014 for BABIP is .296 and .294 (March/April and May) and average is 250 and .254 respectively.  Perhaps the Nats have been a little unlucky, but the real explanation is that they just haven’t pitched that well.

And how do those numbers compare to the NL averages?

Year ERA K/9 BB/9 K/BB H/9 WHIP
2012 32.52 -15.96 10.63 -24.03 19.29 17.04
2013 13.42 2.74 22.93 -26.20 1.37 6.72
2014 -4.67 -8.86 9.36 -20.10 -8.22 -4.06

Starting Pitching Relative to NL Averages

While the Nats have held their own when you account for the strength of offenses in the AL, in a NL only comparison the numbers look much worse.  In 2012, this staff dominated in comparison, but now in 2014 they are largely below average across the board.  K/9, K/BB, H/9, and WHIP are all below NL averages.   Just to be thorough, the NL only averages for BABIP .290 and .291 (March/April and May) and batting .246 and .251 still are well below what the Nats have produced so far this season.

My initial reaction to this breakdown is so what?  It’s clear that the BABIP numbers are approaching league levels, dropping from .329 to .301 as April turned to May, but the batting average against has climbed?  What gives?  If anything, I would think average would lower when Doug Fister replaced Taylor Jordan in the starting rotation.  Fister has been an improvement to be certain, but the problem isn’t with any replacements.  As an improving Fister joined the Nats rotation, the regression of Jordan Zimmermann truly began.

For the season, the Nats righty has allowed a .306 batting average with an unusually high BABIP of .369.  Stephen Strasburg too has an extremely high BABIP of .357, but his average allowed sits at .261.  For Strasburg, I don’t worry all that much since he’s had his moments like this in the past (in May of 2012 he allowed a .356 BABIP with a .253 average), and he has the ability to strike batters out and mitigate the damage.

Zimmermann?  In the last three years, working through the month of May, he’s been below league average in both categories.  While his FIP is a respectable 3.27, and in all fairness it is second for the starters behind only Strasburg’s 2.60, can anyone say with confidence that Zimmermann has pitched to that line?  Watching him over the last month or so, Zimmermann leaves a lot of balls over the heart of the plate and has failed to put away batters with two strikes.  I’m a numbers guy, but this seems to be a case where the numbers don’t necessarily correlate with what the eyes are telling me.

All of Zimmermann’s numbers such as K/9, BB/9, and HR/9 are within career norms.  The one number that jumps out at me is his LOB% (percentage of base runners a pitcher strands), which is 3 points lower than his career average.  That means he’s been allowing more batters to reach, and he’s had a tougher time keeping them there.  He’s been particularly atrocious over the last month, allowing 33 hits in 22 2/3 innings with the LOB% never topping 70% in a particular game and hitting in the 50’s twice.

It’s easy to single out Zimmermann as the cause of the Nationals’ starting pitching woes, and inconsistency from the other starters and a late arrival for Fister have certainly added to the diminished effectiveness, but a return to form for Zimmermann would certainly bolster a starting rotation that has been increasingly vulnerable.  Over the first two months, it’s not as though Zimmermann has turned into an especially bad pitcher.  I just wonder if we’re seeing his regression into an average one.

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