Huston, We Have A Problem

It was bound to happen.  He had been flirting with disaster all season.  The law of averages finally caught up with him.  On Saturday closer Huston Street blew his first save as a Padre.  Making it especially galling, the winning rally began with two out and no one on base.  Walk.  Home Run.  Boom.  Thanks for playing.

I didn’t see the game, but I’m willing to bet Longoria hit a slider.  Why?  Because Street’s slider has been getting tattooed this year.  Some graphical proof after the jump.

Luke Gregerson’s slider is the stuff of legend, as Geoff expertly reminded us last Friday.  Street’s slider is pretty good too.  Last season Gregerson had the best slider in baseball, among relievers, by wSL.  Street’s was not too shabby, comin in at 17th, behind Alexi Ogando (Texas) and just ahead of Andrew Miller (Red Sox).  This year?  Among relievers that have thrown at least 10 innings so far, Street’s wSL is seventh-worst in baseball.  Guys right around him on this list include Pat Neshek (jettisoned by the Padres 2 years ago), Mitchell Boggs (currently in AAA after losing the closer job in St Louis), and LaTroy Hawkins (now in a lousy Met bullpen after years in a lousy Cub bullpen).

Is Street using his slider more or less than in year’s past?  Slightly less, actually.  The curves below show his historical pitch usage rates.

street curves

The next two tables indicate that Street is using his slider more against LHH so far this season than in years past when ahead in the count.  His usage against RHH has remained fairly constant, with Street more likely to throw it after the first pitch of the at-bat.

Huston Street historical usage Hutson street 2013 usage

The rest of his curves, so far in 2013, look a lot like they have his entire career.  Two of them stand out.  One is whiff percentage.  Hitters are missing his sinker at the highest rate since 2010, but swing-and-miss rates on the slider and change-up are way, way down.

whiffs per swing - street

The other is percentage of line drives on pitches hit into play.  Street’s LD percentage off his sinker in 2013 is consistent with his career trend, and his change-up is reprising it’s 2012 effectiveness, but look at the slider.

LD per BIP

Hitters are swinging and missing Street’s off-speed stuff less than ever before.  They aren’t making great contact on his change-up, but they are absolutely hammering his slider.  Three of the 5 home runs Huston’s surrendered so far in 2013 came on a slider.  Clearly his slider is not the effective weapon it has been in seasons past.

Street’s vertical and horizontal movement on his pitches looks consistent with how he’s thrown throughout his career.  Based on the graphs I reviewed, there isn’t an appreciable change in release point to the hitter, nor the amount of bite on the pitches as they move towards the plate, that could explain why his slider has been hit so hard this season. His velocity is also consistent with that of years past on all his pitches (within 0.5 MPH, according to Fangraphs).   So what’s causing the dramatic shift?  Small sample size?  Possibly.  So far in 2013 he’s thrown 252 pitches.  Last year he threw 581.  Year before that, almost 1000.  The line-drive rate on the slider has trended down every year since 2009, until the start of this year.  One begins to wonder if he’s tipping his slider in some fashion.  Yes that’s rank speculation.

I’m sure Street will figure out what’s changed and correct it.  He certainly doesn’t want what happened last Saturday in Tampa to continue, nor does he want to continue giving up HR at this clip.

wSL rankings pulled from Fangraphs.  Other graphical and tabular data from BrooksBaseball.net.

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  • Patrick

    Great article. I’m concerned that Buddy Black and Darren Balsley aren’t thinking about this problem as much as they should be. Perhaps they are, but sometimes I fear that managers perceive these things as “flukes” or “slumps”. Who knows, maybe it is, but I like what this article makes me think about.

  • Melvin

    Good stuff. I have trouble looking at the massive amount of this kind of data and making a consistent narrative out of it.