Table of Contents

Wednesday, September 24, 2014

The Misery of Jay Bruce

I hadn't looked at FanGraphs' Cincinnati Reds team page lately.  Too painful.  But I popped over there tonight to have a look.  After momentary smiles at what Devin Mesoraco and Todd Frazier have managed this year, and a nod of "yeah, pretty solid" at Billy Hamilton, I found myself scanning through the rest of the numbers with predictable dismay.  I knew it would be bad, and hence my need to stay away until now.  But it is a story of despair and agony.  Cozart's .259 wOBA.  Phillips' injury-shortened season with rate states still down from last year's disappointment.  Votto's 272 PA's.

As I scanned, though, I realized that I was missing Jay Bruce.  I looked again, and couldn't find him.  Finally, I realized that he was on page 2.  Jay Bruce.  -11.7 offensive runs vs. average.  -16 runs in the field by UZR.  -1.3 WAR.  

To call it the worst season of Bruce's career is a massive understatement.  Bruce has always been at least "solid."  This year, he hasn't just been average or disappointing.  He's been disastrous.  With the exception of his base-stealing totals (I haven't looked, but I'm guessing that was from earlier this year?), everything in his line has shown decline.  Walk rates are down.  Strikeout rates are up.  OBP is down.  ISO is down.  BABIP is down.  HR/FB is down.  It goes further:

Bruce's ground ball rate is WAY up.  His fly ball rate is down.  His line drive rate is down.  Bruce has become a groundball machine, which prevents his power from helping him do anything productive...and hence the low ISO.

Earlier this season, he was talking about trying to improve his approach, becoming more selective and looking for his pitch to hit.  His plate discipline profile doesn't match that anymore:

This year, Bruce has swing at more pitches outside the zone, and fewer pitches in the zone, thanany year of his career.  His overall swing rate is down, but that's mostly because pitchers aren't throwing the ball in the zone as often as they did in 2013--if he'll swing out of the zone, they don't have to challenge him.  He's making contact at a decent rate, but it's clearly not hard contact; he's hitting the ball into the ground.

Pitchers aren't throwing that much differently to him.  

A few more fastballs (by pitchf/x, that increase is mostly two-seamer fastballs).  A few more change-ups.  Fewer sliders.  It looks to me like pitchers just aren't as concerned about him this year.  One of the classic ways to get Bruce out was to bury a slider down and in on him, but it's as if pitchers no longer have to rely on that pitch to get through the at-bat.

Earlier this season, I wrote about how Bruce was going to the opposite field more often in 2013.  This year, well:

It's pretty tough for me to say without some summary statistics, but it looks like more of a pull-oriented distribution this year.  For one thing, while he had a nice number of home runs scattered between center field and left field in 2013, every single one of his home runs this year was to his pull side.  Similarly, his ground ball outs (purple) to the infield are all clustered to the pull side.  In the outfield, I'm not sure that I see a specific pattern, and looking only at ground balls, line drives, or fly balls didn't really help (not shown here).  

::sigh::  There's no insight here from me (as usual).  It's been a miserable season, and I certainly don't see anything here that I can identify as something that Bruce needs to do to get better.  He just needs to get better at everything.  My hope is that a big part of the problem has been his leg injury, as Bryan Price has alluded to several times this month.  With an offseason to heal, hopefully Bruce can be in line for comeback player of the year honors in 2015.  If he doesn't I don't see a way to expect much improvement from the Reds' offense...even if they are able to bring in some help.  

How pessimistic should we be?  Well, Bruce's ZIPS projection entering the season was for him to hit .254/.329/.485 with a .344 wOBA.  His updated projection?  .240/.312/.444 with a .328 wOBA.  According to the algorithm, there's still reason to expect him to be a solid hitter.  That's encouraging, despite how bad he's been this year.  But that's a far less intimidating line than he projected to be before his struggles this year.

...I'm not even going to talk about his fielding.  I'm just hoping that's short term injury + fielding stat volatility.  The key word there is hoping.

Thursday, September 11, 2014

Using Sound to Scout Players

Sorry for my absence.  Part of it is that the Reds have frankly been rather hard to watch over the past month.  But the issue is that my family and I are living in France for the semester.  We arrived a few weeks ago, and are starting to find our way.  I'm traveling with my university's students in their study abroad program.  It's an amazing experience, but it definitely is hard to keep up on baseball when 7pm EST games start at 1am local time.

In any case, I was listening to Effectively Wild today.  Robert Arthur was on a few weeks back talking about his study that evaluated how the audio signature of the crack of the bat related to the result of the batted ball.  It's great stuff.  His principle finding was that the peak frequency (i.e. pitch) differed substantially between ground ball outs, ground ball hits, line drives, and home runs.  Better-struck balls result in higher frequency sounds.  That makes sense, because those sounds are the result of faster bat speed and more energy being put into the ball.  It's really exciting stuff, and indicates that there's probably quite a lot to the claims that we hear from Baseball People about the sound of balls coming off bats.

The potential applications of these data are really exciting.  The most exciting thing is that these data could be used as another way to evaluate hitters.  Bat crack data should be able to tell us some combination of how hard, and how squarely, batters are hitting balls.  Only those with exceptional power should be able to achieve the highest pitch of bats cracking, once we controlled for bat type and (maybe) pitch type.  Better hitters should have consistently higher pitch than poorer hitters.  My guess is that pitch data should be less noisy than BABIP data, and so they might be useful when we're trying to make "Bonafide or Bonifacio" judgements.

This could be used to evaluate pitchers as well.  Are pitchers really inducing weaker contact?  Or are hitters squaring up the ball well, but just hitting it to defenders unusually more often.

The challenge is the data collection.  MLB compressed games will help, but it's still a lot of data to gather, isolate, sort, and then analyze.  Hopefully some young, enterprising people will go after this, as it has enormous potential.