Category: Uncategorized

Pacing Yourself

One of the many tangibly intangible things that a pitcher can do to endear himself to umpires, his defense, and their adoring TV viewer public is to work fast. Pitchers also benefit themselves by working fast, as one of the basic tenets of successful pitching is to interrupt a hitters timing — by controlling the pace of an at bat, the greater chance a hitters innate cadence and timing for each pitch can be oh so slightly interrupted.

Even with some of these tiny advantages to working fast, some pitchers just…








One of the many side stories of this year’s World Series that exemplifies this was Clay Buchholz‘ pace to pitch. Glacier-like was the overarching sentiment as to how quickly a Buchholz outing went; given the age-old complaint that any Boston Red Sox game takes longer than most, this wasn’t a new revelation.

So was it all in our heads? And how do Washington Nationals pitchers do in this arena of pitching?

FanGraphs can help us out with this — with the pace statistic.

Pace tells us, on average, how many seconds a pitcher take in between pitches of an at bat. For 2013, the average time between pitches was 22.9 seconds, when you include all players who made an appearance as a pitcher (*waves at Skip Schumaker and John McDonald*).

Again looking at all pitchers, starter or reliever, but using an innings pitched cutoff of 10 innings and we find that the fastest pitcher was New York Yankee Vidal Nuno, at a 17.2 second pace; on the other side of the coin, Tampa Bay Rays reliever Joel Peralta was the slowest, at 31.9 seconds.

However, this doesn’t tell the whole story; while time between pitches is obviously a hindrance to a quick game, so are the number of pitches thrown. More pitches thrown, the more time in between pitches, the longer the inning is — simple math. So with that in mind, let’s pull out our abacuses, TI-82 calculators, and perhaps some scratch paper, and figure out who are the yin and yang of pitching pace.

So, we have pace, innings pitched, and total pitches, courtesy of FanGraphs. From there, we simply need to calculate pitches per inning, then multiply by pace, then divide by 60 to get a rough estimate of how long an inning is for a given pitcher, in minutes.

Doing all of this voodoo brings us to this:

Screen shot 2013-11-01 at 1.55.49 PM
*minimum of 10 IP

Cool? Kinda, I guess; to circle back to the Buchholz reference and close the book on that, he comes in at a 24.2 second pace, 15.04 pitches per inning, which gives him an average inning pitched in 6.09 minutes. This ranks him 54th among 146 pitchers with at least 100 innings pitched and fourth out of the five Red Sox starters with at least 100 IP. Yes, Clay is a quick worker, compared to his carmine brethren.

Enough of that, let’s talk WASHINGTON NATIONALS BASEBALL. Remember that? Barely, I know. Sarcasm aside, let’s have a look at how the Nats staff pans out with this whole pace thing. A priori, we are led to believe that Jordan Zimmermann is a very fast worker and Stephen Strasburg kind of plods along.

Any truth to this?

Screen shot 2013-11-01 at 1.55.37 PM

Well, yes and no; ZNN appears to be a quick worker, for sure — not too far behind the pace setter (pun intended) Nuno at 4.79 minutes per inning, but Strasburg isn’t too far behind him. So we have a wee bit of a misconception of Strasburg’s pace, even when pitch count is factored into a pitcher’s overall pace. We also find Nathan Karns conspicuously absent from our list; for whatever reason, Karns and two other players’ paces were not listed by FanGraphs.

Yunesky Maya? Yeah. Moving on…

The bottom part of the list — let’s lovingly dub them DAWDLERS — are primarily relievers. While we know that Tyler Clippard enjoys long walks around the mound, blowing into his pitching hand, licking his hand, and doing a number of sundry things on his pre-pitch checklist before dealing, we also see another quirk about the pace stat and an underlying component of it, courtesy of hitters, with the dawdlers — home runs.

Yes, the more home runs you give up, the more time you have to wait for the hitter to get around the bases before you can throw your next pitch. While I will save the rigorous statistical analyses for the effect of home run rate on pace for another day — and as we can see in the above table, it isn’t something that appears to be highly correlated — it is an unfortunate aspect of pitcher pace.

Keeping with eyeballing trends, we also see with the Nats that relievers are a tick slower than starters, in general. While homers do play a role, the fact that relievers are in-game during typically higher leverage situations — a fancy way to say there are men on base with the game on the line — the need to change your timing to the plate and even throw over to first base on occasion to keep a runner close takes precedence over keeping your pace number low. Strategery at its finest.

So again doing some quick eyeballing, the Nats average a 6.03 minute inning; countering Cubans outliers and using the median, Nats pitchers come in at about 5.7 minutes per inning. Comparing that to the MLB overall (and again using a 10 IP cutoff) and an average 6.3 minute inning or 6.2 minute median inning, and we see that Nats hurlers are a tad quicker than the average team.

Here’s how the entire MLB pans out; note that this chart does not include data from players who swapped teams during the season and are thus noted as playing for ‘—‘ by FanGraphs.

Pace Per Inning By Team

So there you have it; the Angels are DAWDLERS on average, while the Braves and Cardinals, bastions of all that is unwritten and unheralded, are the quickest. Snark aside, both of those teams more than likely have an organizational mantra that predisposes guys to work fast, and if you look at their team pitching stats, it’s definitely not hurting their stock.

Pace; it’s not just salsa.

Courtesy of

Courtesy of

How Do I Link Dump, v2.0?

It’s been awhile since I’ve last posted here and while I would love to tell you I have spent the time away from HDIB? analyzing the L.O.M.B.O. data and results in preparation for a manuscript that will be submitted to the International Journal of Sport Grit and Want and Desire and Other Things No One Can Truly Measure But Dammit We Try — the IJSGWDOTNOCTMBDWT for short — alas, I have not.

I have however, been busy writing about the Shutdown. Put away the pitchforks and take a look at what Stephen Strasburg and Jordan Zimmermann have done before and after Tommy John surgery and having their innings limited post operatively across a number of stats and categories:

Part One — pitch usage, velocity, and movement

Part Two — pitch sequencing and command

For the Orioles fan in your life, I have lots of prose dedicated to Manny Machado and his MPFL injury and his prospects for a healthy return and what that means for the Orioles in 2014:

Injury discussion, part one

Injury discussion, part two

Looking to 2014, part of a series over at Camden Depot breaking down 2013 and 2014 by position.

I will be helping out Camden Depot with a couple more of these year in review write ups, focusing more on the O’s bullpen; you can also find more of my nerd math writings over at Beyond the Box Score, if you enjoyed the Strasburg/Zimmermann/TJ bits discussed.

Anyone know what IJSGWDOTNOCTMBDWT’s impact factor is? Might have to shop L.O.M.B.O. around…

The L.O.M.B.O – A Newly Devised Measure of Grittiness in Baseball

I like to think of myself as something of a scientist. An out of work scientist, but that’s a whole ‘nuther ball of wax. As such, I look at articles and research such as this with a curious eye. For those click averse, it is an article discussing the virtues of ‘grit’ over IQ as a predictor of success in life.

It’s fascinating research that lends credence to the notion that perseverance and volition will get you further in life and will allow you to accomplish long-term goals more so than just being a Smarty McSmartypants. While the premise of the work is still something I wrestle with in terms of its application to everyday life,  the research and its results did strike a chord in my baseball mind.

‘You gotta have heart’.

‘Gritty, gutty, and scrappy will conquer all’.

You’ve heard plenty of these paroxysms, so I will stop there.

But is there something to having 25 gritty, gutty sons of bitches on a baseball team that might cure all ills, first round draft picks be damned?

Inspired, I devised my own survey for baseball players —  the Longitudinal Obstinance and Moxie Barometer for Organizations, or L.O.M.B.O.

With it, I hope to determine whether there is something to a gritty personality. It’s just recently devised, so I need some help acquiring data. In fact, consider this an invite to take the survey yourself — you can find it here.
Give it a go and see how gritty of a player YOU are. Here’s a quick and dirty breakdown of the scoring:


0-2: Lazy. No heart. You don’t run out ground balls and pimp home runs, while also possibly peeing in pools in the process.

3-5: Occasionally inspired, when the mood strikes. You are Adrian Beltre in a contract year.

6-8: You’re full of mettle, but you don’t bring your lunch pail to work every day. You’re not just having fun out there. You lack the will to win.

9-10: You’re a member of the Eckstein family. Holy shit, you’re covered in dirt even after showering and eat New Hampshire granite for breakfast, you’re so fucking gritty.

*EDIT* Since I am nicht so gut with Survey Monkey and it doesn’t look like they have an automated scoring system, here is the scoring rubric:

1 Yes = 1 No = 0
2 Only lefties = 1 Often As I Can = 2 Stroke = 0
3 One = 0 Two = 1
4 Laser = 0 On a Hop = 1
5 Weight = 1 Batting Avg. = 0 Bunts = 2
6 Yes = 3 No = 0

Steve Lombardozzi, Jr.

Happy Feet – A Look at Bryce Harper’s Last Second Adjustment

While last night’s Washington Nationals game against the St. Louis Cardinals will be remembered for the almost no-hitter for rookie starter Michael Wacha (and rightfully so), there was an interesting side story in the 7th inning, courtesy of Bryce Harper.
Jimmy, roll the tape:

(Click to unleash the gif)
Did you see it? Did you notice the last second hop/skip/jump in the box towards Wacha before he swung at a 96 MPH fastball?
Here’s a different angle of the swing, which really gets the point across:
(Click to unleash the gif)
First of all — wow. In a game determined by milliseconds, Harper takes something already tough to do and laughs in the face of it, making an adjustment as Wacha is throwing a pitch. A 96 MPH FASTBALL.
Second — why? My thought is that Harper was guessing changeup — Wacha’s biggest secondary pitch, and one that was especially good last night in his 8.2 innings of one-hit ball. His 32 changeups last night came in at a 62.5% strike rate and a 15.6% whiff rate. When you also consider that Wacha threw just three curveballs and one cutter, you get a better appreciation of Harper’s mindset in this at bat. Already down in the count 1-2 and knowing he wasn’t going to get anything breaking, he assumed he wouldn’t get something hard, so he set up in his usual fashion in the batter’s box, then scooted up to get to that assumed changeup before it darted out of the zone.
Here’s a plot of the pitches he saw in the at-bat; as you can see, Harper was one step ahead of Wacha as far as getting that changeup, eventually striking out on the pitch:

Pretty darn impressive. To not only be able to move the feet, keep your swing mechanics intact while doing so, look for and react to a changeup, but then get a high-90’s fastball, and still be able to catch up to it enough to just foul it off is all sorts of amazing and impressive. But you know what? It’s been done before.
Remember Hal Morris?
While his church league softball batting stance wasn’t as egregious as Harper’s, Morris also employed a foot shuffle before getting the bat through the zone. With a .304 batting average, relatively low 12.3% strikeout rate, and 14.6 fWAR over a 13 year career, Morris was surprisingly effective with the approach. Also to note is while Harper all but leaped towards Wacha with his swing, Morris’ was more of a shuffle up towards the plate, with a small step towards the pitcher; small difference, but an important one.
While the end result wasn’t terribly desired — Harper ended up striking out — it nonetheless was an interesting look at Harper’s approach and how he is able to not only make adjustments, but make them in real-time; a very rare feet feat.

The Doctor Is In…?

How do I load thee?

Let me count the ways, with the help of Atlanta Braves reliever (and former Washington National) Luis Ayala:

Screen shot 2013-09-19 at 11.24.47 AM

First, a little from the brim, like bullpen buddy Craig Kimbrel

Screen shot 2013-09-19 at 11.29.12 AM

Gotta have some on the opposite shoulder, just in case….

Screen shot 2013-09-19 at 11.30.16 AM

Can’t forget some on the side of the pants, where the ball rests when you’re pitching from the stretch….

Screen shot 2013-09-19 at 11.43.00 AM

It looks totally natural.

But let’s not stop there!

Screen shot 2013-09-19 at 11.41.43 AM

We also need some on the front of the pants, so when we pick at our pants after every pitch, like below:

Screen shot 2013-09-19 at 11.40.49 AM

…or rest the ball atop our thigh like this for a brief moment:

Screen shot 2013-09-19 at 11.39.17 AM

…it doesn’t look suspicious.

While I don’t have any gifs of Mr. Ayala because it would break my laptop, let’s just say he’s a fidgety dude in between pitches. A brief paraphrasing is provided below:

Rub the brim of the hat, tug at the back of the hat, take off hat, rub head, take off glove, rub ball, pick at back of jersey, wipe off ‘sweat’ on opposite sleeve, pick at side of pants, rub front of pants, wipe face, rub ball again…

…and now we’re ready to make a pitch!

While I stop short of making any inflammatory claims about Ayala’s pre-pitch rituals and any possible rule bending aspects of it, we have plenty of instances of pitchers looking for an advantage from an array of substances; the Nats even had a run-in last year with another former reliever of theirs, Joel Peralta. It happens. It happens a lot, truthfully. However, it struck me last night during the Braves – Nats game that Ayala’s uniform sure did have a lot of curiously stained areas, more than what you’d expect from a pitcher who just came out of the bullpen. While the life of a reliever can be dull and oftentimes the bullpen is a playground of the mind as far as coming up with ways to stay in the game, even in-game bullpen shenanigans usually don’t lend themselves to the impressive array of uniform stains seen on Ayala. Add to it Ayala’s success on the movement of his pitches more so than their velocity and you have an environment where a little extra stickiness can provide a little more tail or dip to an otherwise average pitch. Even MASN’s FP Santangelo mentioned during the broadcast how Ayala’s fastball acted essentially like a slider from a lefty, it had so much late arm side tail.

Again, it’s not my place to place blame on a guy who has never been reprimanded for doctoring balls; Ayala’s arm slot and pitch selection have remained relatively consistent throughout his career and they lend themselves to throwing pitches with a lot of late life and movement to them.

However, if one were to want to do that sort of thing, ‘for entertainment purposes only’, well… it might look a lot like this.

Spanning Is the New Santangeloing: A Brief Review of Washington Hit Streaks

There have been many impressive offensive feats performed in the last few weeks by the Washington Nationals in the midst of their hot streak, which now has them four and a half game out of the last Wild Card spot, currently held by the Cincinnati Reds. Arguably the most impressive of said feats is the 24 (and counting) game hit streak by center fielder Denard Span, which is good for fourth in Washington Nationals/Montreal Expos history, right behind just-retired Vladimir Guerrero and current teammate Ryan Zimmerman, and has propelled the Nats to a 19-7 record during the streak.   Here’s how Span’s streak looks:

Rk Strk Start End Games AB R H 2B 3B HR RBI SO BB SB CS BA OBP SLG OPS Tm
1 Denard Span 2013-08-17 2013-09-13 24 101 16 38 5 2 2 7 12 6 2 1 .376 .413 .525 .938 WSN
Provided by View Play Index Tool Used Generated 9/14/2013.

Not too shabby, eh?   Now, let’s take a walk down (recent) memory lane and take a look at how Span’s production — batting average (BA) and on base plus slugging percentage (OPS) — during his hit streak compares to similar Nats (as in Washington, not Montreal – sorry Canada!) hitting streaks. Moving forward, I am only considering hit streaks of 15 games or more, courtesy of Adam LaRoche, Cristian Guzman, Span, Ian Desmond, HDIB? great Nick Johnson, and Zimmerman:
WSN 15+ Game Hit Streaks By BA and OPS
Not surprisingly, Span’s batting average is reasonably high, with his OPS reasonably low compared to his fellow Nats streakers, which makes sense, given Span’s lack of power and so-so (for a top of the order hitter) on base percentage. Fair enough.  
Something’s missing.  
I seem to recall an 18 game hitting streak in there somewhere, in the annals of Washingreal history.  
Ahh, yes, F.P. Santangelo told me many many times over the course of Span’s hitting streak once he had an 18-game hitting streak.  
Ribbing aside, let’s take a look at Nats 15+ game hitting streaks — along with Santangelo’s 18-gamer — again by batting average and OPS:  
WSN 15+ Game Hit Streaks By BA and OPS (and FP)
OK, cool — we see some interesting trends here, namely, these guys are going out of their minds not only with their batting averages, but their overall power. Now, let’s break down OPS into its constituent parts — on base percentage (OBP) and slugging percentage (SLG) and add that to AVG and OPS and then look at these streaks in comparison to each player’s career averages for these four stats, yes?  
Difference Between Hit Streak and Career AVG, OBP, SLG, and OPS
With this, we see that while Santangelo’s hitting streak was impressive, it is definitely the outlier in comparison to the other streaks; his streak production was in such great contrast to what he normally accomplished hitting-wise, even when compared to his fellow streakers. Conversely, Span’s hitting streak, as well as Johnson’s, more closely trend with their career averages.  
What does this mean? Probably nothing; while it would be easy to say that the differences between streak averages and career average is some reflection of each player’s inherent hitting talent, that is a bit of a slippery slope and something that the data as presented can’t really speak to. Variables such as opponent defense and even pitching match ups all cloud the data enough to not warrant too many brash statements made about the data here. What is interesting are Zimmerman’s streaks and how he went about each — while some were driven more by his ability to make contact and not much else, others were marked by his ability to generate runs with his swings.  
Taking one more step back historically, how does the Washingreal data compare to other teams?  
Let me tell you, with the help of Baseball Reference’s Play Index. Looking at the modern era — 1916 to current day — I provide below the number of 15 game or more hitting streaks for each organization. I then averaged them over the years of interest to give an idea how frequently over the franchise’s modern era a big hitting streak occurs:

Team Yrs 15+ H Streaks Strk/Yr
STL 93 170 1.83
BOS 94 170 1.81
DET 96 171 1.78
CLE 94 166 1.77
MIN 97 162 1.67
NYY 95 155 1.63
COL 20 31 1.55
TOR 36 54 1.5
BAL 96 142 1.48
SEA 35 49 1.4
TEX 52 72 1.38
LAD 97 132 1.36
MIA 20 27 1.35
SFG 96 127 1.32
CHC 96 125 1.3
OAK 97 125 1.29
CWS 97 123 1.27
CIN 97 121 1.25
LAA 52 63 1.21
ARI 15 18 1.2
KCR 43 51 1.19
ATL 93 109 1.17
MIL 44 51 1.16
PHI 97 111 1.14
WAS 42 42 1
HOU 51 50 0.98
SDP 44 43 0.98
NYM 51 42 0.82
TBR 15 8 0.53

Not that Span’s streak wasn’t impressive enough, but the data provided, especially the table above, confirms how special the streak is to the organization; these kinds of streaks, while seen more frequently in the last few years, thanks to Zimmerman, haven’t been a hallmark of Washingreal hitters, to say the least. Between that and the context of Span’s streak — in the middle of a wild card run in the waning days of the season — only adds to the enjoyment of the streak and its importance to the success of the Nats’ 2013 season.

Wasting Away: Adam LaRoche’s Slimming Offense

The 2013 season has been a lost one for the most part for Washington Nationals first baseman Adam LaRoche. Lost, not only from a production perspective, but also when it comes to his weight, as it was brought to light that his medication regimen for his attention deficit disorder has caused a tremendous amount of weight loss in the last month or so, causing him to cut back on his pregame activities in order to save energy.

With the alterations in medication and batting practice routine seems to have come a bit of a power outage for LaRoche — since August 1, ALR has hit four home runs in 130 plate appearances and in general, has produced scant power. In spite of the drop in homer production, LaRoche still appears to be relatively productive — does the sudden weight drop drastically affect LaRoche’s numbers this year, or compared to his previous years averages?

With an assist from Fangraphs, we can find that out. First, two tables. The first looks at ALR’s numbers in August in three different ways — across his career, his career best 2012 season, and this season — the second is the same thing, just for September and October. I picked these due to them roughly paralleling the length of time LaRoche has felt that he was losing weight and possibly energy due to his meds.

Is 2013 such a huge anomaly for LaRoche?

Season Split BB% K% LD% AVG OPS ISO BABIP wRC+
2012 Aug 8.7 % 14.3 % 18.8 % 0.239 0.691 0.150 0.247 87
2013 Aug 12.5 % 20.2 % 27.5 % 0.233 0.737 0.167 0.262 96
Career Aug 9.9 % 21.1 % 19.1 % 0.294 0.891 0.232 0.332 132


Season Split BB% K% LD% AVG OPS ISO BABIP wRC+
2012 Sept/Oct 9.8 % 18.7 % 22.7 % 0.324 1.057 0.342 0.333 182
2013 Sept/Oct 23.1 % 15.4 % 25.0 % 0.316 0.883 0.105 0.375 153
Career Sept/Oct 8.4 % 24.3 % 23.2 % 0.293 0.888 0.243 0.350 128

By the looks of it, not really — in fact, ALR appears to be righting the ship, if the handful of Sept/Oct at bats for 2013 are anything to hang your hat on. While the sample size is limited, his 2013 walk rate (BB%), strikeout rate (K%), and batting average on balls in play (BABIP) betters his career and 2012 averages, to name a few. Looking back at the August numbers, while he did definitely a drop in numbers due to the weight loss, it wasn’t anything precipitous.

Looking at the raw data, it nothing really jumps out at you — yes, LaRoche is having a rough stretch, but nothing that hasn’t been seen previously in career. Let’s now look at his productivity with some help from PITCHf/x and Brooks Baseball.

With this first graph, we look at ALR’s plate approach across his career in the hopes of answering whether his recent weight woes has made him change his approach at the plate:

In general, 2013 has seen LaRoche be a little more even keeled with his approach, but as of late, has shown some passiveness, especially with breaking and offspeed pitches. Is this in response to some sort of innate admission that he doesn’t have the energy/power to get to a particular pitch or a part of the strikezone to drive the ball? Or, perhaps it’s a reflection of pitchers pitching him differently, trying to take advantage of a weakness in his approach or swing.

The next two charts can help answer some of this. The first is a look at the percentages of pitches ALR has seen over his ‘career’ by month. I write ‘career’ simply because it only includes seasons where PITCHf/x data were available. With that disclosed, how are pitchers working LaRoche?

There aren’t too many huge trends popping up across LaRoche’s career. However for this season, we do see a good jump in the number of hard pitches — fastballs (twoseam, fourseam, and cut) and sinkers — along with a concomitant drop in breaking pitches in August and September versus earlier months.

How has LaRoche responded? This next chart shows if he is missing pitches via whiff rate:

While he seems to be handling hard stuff just fine and making good contact (low whiff rate), LaRoche does seem to be swinging and missing quite a bit as of late on the increased number of offspeed pitches sees. With the weight loss, he also seems to be whiffing a little more as of late on breaking pitches, but overall, does seem to be doing a decent job of handling the offspeed pitch in 2013. In general, LaRoche does appear to do a better job of connecting with pitches of any type as he ages.

OK, so he’s getting his cuts and save for some rough going with offspeed offerings, is putting the ball in play. Where’s the ball going, now that he’s had to ration his energy and swings?

First, I provide ALR’s spray chart for 2013 up until roughly when he noticed the weight loss — right around August 5th:

…and here’s what he’s done since then, a waist size or two smaller:

It appears he isn’t hitting the ball quite as far as of late, and seems to not be going the other way quite as frequently as he was before the weight loss. Also, it doesn’t appear that he is putting a good swing on breaking pitches in recent weeks and isn’t driving the ball as far as he once was.

Two more hitting charts. These look at ALR’s isolated power, pre- and post- weight loss, as it relates to his zone profile:


Here, we see that LaRoche’s ‘sweet spot’ for generating runs has shrunk as he has — in the last few weeks, if it isn’t in the traditional left-handed hitter’s hit zone of down and in or right down the middle of the plate, he isn’t able to drive the ball and generate some of the much-needed runs that the Nats offense in general has been lacking all season long.

While LaRoche does seem to be pulling out of his slump, what we see is that, while concerning due to where the power outage arose from, a late season drop in productivity isn’t anything new to ALR historically. Beyond that, we see that LaRoche has struggled to maintain his typical power numbers in spite of doing an admirable job of maintaining his approach and not becoming overly aggressive with his swing. Despite the lack of power, LaRoche is still making good, albeit weaker, contact.

With a medication change or tapering of his current dosage, LaRoche should be able to finish the season strong and hopefully give the Nats offense the lift it needs as it continues to knock on the door of a playoff berth.


Offspeed Offerings and the Effects of Release Point

Earlier in the week, Harry Pavlidis had an article in the WaPo breaking down the changeups featured by the Washington Nationals and a breakdown of each into one of four categories that evolved from whether the changeup generated lots of swings and misses (called a ‘whiffer’) or groundballs  (a ‘grounder’). If a pitcher’s changeup did both, it was a ‘double threat’ pitch and a ‘no threat’ if the whiff and groundball rates generated by the pitch were sub par. It comes as no surprise to anyone who watches Nats games that Stephen Strasburg‘s changeup is a double threat and one that Pavlidis admits to arguably being the best in baseball. Also garnering high marks but ultimately labeled a grounder type of changeup was Tyler Clippard‘s change of speed, which he pairs with a fastball that he keeps up in the zone to get batters to produce a large number of strikeouts and flyballs. This pairing as well as the part of the strike zone Clippard lives in is not a common approach to get hitters out, but Clippard’s track record is plenty of proof that it can be effective.

Getting back to the changeup, I had a look at the differences between Clippard’s and Strasburg’s changeup, looking for what made Stras’ a double threat and Clip’s just a grounder. Both fantastic pitches, but what was the secret to Strasburg’s offspeed success? While the velocity differences do show some significant disparity — Clippard’s changeup is of the ‘Bugs Bunny’ variety, with a ton of velocity bled off of it compared to his fastball, while Strasburg’s is closer to his fastball velocity, occasionally touching the low-90’s — perusing the PITCHf/x data of each brought to light another difference between the two elite Nats changeups.

First Clippard:


…and Strasburg:


What each of these gifs shows is the overlay of the release points of each of the changeups and fourseam fastballs thrown by each pitcher in 2013. With Clippard, we see a bit of a disparity between the fastball and changeup release points, while with Strasburg, we see all pitches essentially coming out of the same arm slot — both pitches are leaving Strasburg’s hand at essentially the same spot every time, making it difficult for hitters to distinguish between the two, making the changeup even more effective. It isn’t until the hitter has committed to swing at what is believed to be a fastball that they realize it’s not a fastball, but a changeup. From there, the hitter is not only victim to the change of speed, but also the arm side tail and movement of the pitch that makes Stras’ changeup so devastating. While Clippard’s changeup is no slouch, we do see two relatively distinct clusters, which can possibly make his changeup a tad easier to pick up versus Strasburg’s. Could this tiny difference in release point be the difference between a good changeup — either a whiffer or a grounder — versus a double threat? Possibly. Yet, like with so many other aspects of pitching, there’s more than one way to do things and do them well, and with the two Nats pitchers discussed, we see a difference in philosophy and approach that leads to the same result — a bad swing from a confused hitter.

Tyler  Clippard

Tyler Clippard (Photo credit: Wikipedia)

Bunting With the Devil

There has been much ado over Bryce Harper‘s bunt in last night’s game against the New York Mets — a bunt that came with runners on first and second with no outs, in the eighth inning, with the Washington Nationals down by two runs. Much ado over the notion that Harper would resort to a sacrifice bunt, despite the notion that the situation was in his favour to take a mighty hack or two, as he is wont to do. Also much ado over the underlying theme that Harper’s struggles against left-handed pitching has left him to a last resort to put together a good at-bat — to bunt.

To bunt against Scott Rice, a journeyman rookie who, while admittedly not a comfortable at-bat for a lefty due to his arm slot and quirky delivery, is still Scott Rice, journeyman rookie LOOGY.

While many have lauded the play as a smart move, and one that shows his fastidious and superior baseball IQ, many haven’t:

I will admit that I am in the always occasionally annoying and vocal crowd that doesn’t really like the bunt overall as a smart play, I do admit that there are occasions where a bunt is a good idea; however, I do feel that it is used way too often and those occasions where it is warranted are few and far between.

Is letting one of your most productive hitters — ranked first on the team in ISO, second in wOBA and wRC+ — bunt on his own in such a situation ever a good idea?

What would you say if it was Andrew McCutchen? Carlos Gonzalez? Jose Bautista? Would that change your mind? I bring these players up because of their comparable aforementioned stats to Harper — ISO, wOBA, wRC+ — what sort of environment would you see either of those players being in, where the best alternative for them to generate a scoring opportunity was to bunt with no outs?

Let’s talk about environment for a bit. Without a doubt, the game environment is a crucial piece to this puzzle and one that Adam Kilgore, the author of the link above, admits to.  With the help of Fangraphs, here’s a table that lays out the situations at hand for each of Harper’s bunts for 2013; LI is leverage index and is a measure of the importance of the situation and WPA is win probability added, a statistic that measures how much a particular play affects a team’s chances of winning. A play with a LI over one is considered a play with high importance, while a positive WPA is good and provides some sort of benefit to a team’s win. I have also included score, inning, out state as well as the pitcher’s handedness:

Date Score Inning Out Runners LI WPA Pitcher
05/21/13 0-0 T1 0 1– 1.57 -0.015 R
05/21/13 1-2 T8 0 -2- 1.05 -0.002 L
07/02/13 0-0 B6 0 0 1.31 -0.032 R
08/10/13 4-4 B7 1 1-3 4.25 0.046 L
09/01/13 3-5 B8 0 12- 4.38 -0.023 L

…and the same thing, this time for 2012:

Date Score Inning Out Runners LI WPA Pitcher
05/06/12 1-3 B6 0 0 1.35 -0.033 L
06/12/12 1-4 T8 0 0 0.52 0.019 L
07/03/12 2-0 B3 0 0 0.58 -0.014 R
08/14/12 1-0 T4 1 1– 2.09 0.080 L
08/20/12 4-4 B7 0 -2- 1.94 -0.005 L
09/12/12 0-1 T7 0 12- 1.76 0.004 R

…and two more tables the first being for 2013, the second for 2012, just averaging and summing things up for lefty versus righty pitchers.


Runners, Total LI, Avg WPA, Avg
All 6 2.51 -0.01
L 1 3.23 0.01
R 5 1.44 -0.02


Runners, Total LI, Avg WPA, Avg
All 4 1.37 0.01
L 2 1.48 0.02
R 2 1.17 -0.01

So what do these four tables tell us? Quite a lot, actually. Here are some quick hit bullet points:

  • Harper in 2013 is bunting with more runners on base, especially against lefties
  • Harper in 2013 is more likely to bunt in later innings as compared to 2012
  • The difference in leverage situation for lefties is HUGE and has grown in 2013
  • While it is a small difference, Harper *is* providing a positive WPA when bunting on lefties
  • In general, Harper’s bunts don’t bring much to the table (very low WPA) in high leverage situations

So we have a good idea of when Harper is likely to bunt — late in the game, either tied or losing, in a high leverage situation, normally with a lefty on the mound. Just to tie things together somewhat nicely, let’s describe Harper’s lack of success against lefties thus far in 2013:

vs L 131 21 9 2 12 14.5% 23.7% 0.196
Home vs L 62 9 0 2 6 16.1% 25.8% 0.180
Away vs L 69 12 9 8 6 13.0% 21.7% 0.211
High Leverage 31 4 2 14 9 12.9% 32.3% 0.167

One note — High Leverage here is against both lefties and righties, but adds context to the LI numbers seen previously. In general, Harper hasn’t done much production-wise in high leverage situations in 2013, regardless of who is throwing.

So where does that leave us? Where does that leave Harper? It leaves him and the Nats in a tough situation; when environment is taken into consideration, one of the their top hitters (and one of the NL’s top hitters to be exact) feels that his only resort against lefties is to square around and take one for the team and let a teammate pick him up.

It also leads to this:

Screen shot 2013-09-02 at 11.10.12 AM

The two highest leverage at bats for Harper in 2013 have come this past weekend, both against Scott Rice, both in the bottom of the eighth with runners on first and second, losing to the Mets. While both were ‘bad’ plays — both provided negative WPA — they had different results.

With one, Harper’s hustle was questioned in a loss, as he jogged to first after a weakly hit grounder. The other, a bunt in a situation that hardly ever calls for one, led to a runner scoring and eventually to a win.

While this isn’t the way most expected Harper to contribute to the offensive success of the team, right now, this is about as good as it gets for him against lefties in high leverage situations. In a September for a team fighting for a wild card spot, all of the remaining games become crucial, and the parade of lefties coming out of the bullpen to face Harper will only grow in size. Does Harper keep bunting, dancing with the alluring devil that has ever so briefly shown the bunt to be a good idea?

When you dance with the devil, you have to expect to get burnt; do the flames engulf the Nats chances of a playoff berth in the process?


All stats courtesy of Fangraphs

Getting Napoli’d: The Nationals Run Environment, By Inning

The Washington Nationals offense over the course of the 2013 season has been uninspiring. Uninspiring enough to inspire the firing of longtime hitting coach Rick Eckstein, and to find the Nats wallowing around .500 for most of the season and in the basement of many National League offensive categories, as I have discussed previously here at HDIB?.

August has provided a renaissance of sorts for Nats bats and has propelled the team to a 16-9 record on the wings of a 4.92 runs per game average. Somewhat lost in the shuffle is the renewed ability of Nats pitchers and the defense to suppress runs — in August, the team has allowed 3.8 runs per game, tied with June for the lowest average for the season.

Many point to new hitting coach Rick Schu as the reason for the offensive resurgence, while others look at Jayson Werth‘s fantastic post-DL run, which sees him hitting to a .355/.441/.595 slash line to go along with a 27.97 RE24 and 17 home runs since June 4th; August has been even more unreal for the right fielder, hitting .412/.505/.617 for the month.

Overall, things seem to be clicking quite nicely for the offense as well as the pitching in August, after months of what seemed to be inconsistent bursts of scoring scattered about many innings of zeroes. The offense seems to be more consistent and generating scoring opportunities on a more even keel.

Is that the case? Are things running on all cylinders, or is there something else guiding the Nats to victory?

Let’s take a look at a couple of graphs — the first looks at the Nats runs scored (RS/9) and runs against (RA/9) compared to the NL average (RL/9) for their 2013 thus far:

Screen shot 2013-08-30 at 12.32.39 PM

Here, we are looking at averages per nine innings; I also took the liberty of not including extra inning data, as it can sometimes not be a true indication of a team’s run scoring or prevention abilities, due to erratic lineup switches and position players pitching and the like.

So what do we have here? In general, the best chance for the Nats to score runs is during the first time through the lineup; once players start getting into their second and third at bats, things don’t look so good with respect to generating runs. We do find a conundrum of sorts here, when you consider the team has 27 comeback wins to go along with 25 blown leads. From a pitching perspective, the late innings don’t look so hot, either. As the drop in offense in the later innings comes a propensity to give up runs. Comparing these to the NL averages and seeing that the offense and pitching are on the wrong side of the league average at the same time, we come to the realization that the disappointing season has been a team effort — no one thing can really be pinned as the ultimate reason as to why the Nats have struggled.

OK, enough of that. Let’s see if August looks any different for the Nats:

Screen shot 2013-08-30 at 12.33.34 PM

With this chart, we don’t have the NL average line included because league run scoring averages by inning across month aren’t the easiest things to get your hands on; however, we do know that league averages remain fairly consistent across months, so we can be confident the line would mimic the one we saw in the first chart and will hover around 4 for the most part. More broadly, we see that the Nats are, on average, scoring more runs than they give up in five of nine innings in August, compared to only three of nine for the season overall. That tends to be a good thing. However, we also see the late innings being a bugger yet again when it comes to run prevention in August, with some pretty high runs against average in the eighth and ninth — while Tyler Clippard is as rad as it gets when it comes to relief outings, he can’t pitch them all. Looking at the offense, we see a more consistent pace when it comes to scoring by inning — the chances of a later inning outburst is seen more frequently in August compared to the season overall, which bodes well for either a laugher of a game, or a late inning comeback. While the ninth inning offense looks pretty darn sad, this average is driven by home games — when you’re ahead and playing at home, you don’t hit in the ninth inning, hence the lack of runs here. Confusing, for sure; however, it does bear monitoring, especially in away games or close games, where scoring in the ninth does become a big deal.

Let’s take a quick look at big innings for both the offense and the pitchers. Here, I define a big inning for both as an inning where four or more runs are either scored/given up; obviously, big innings are good for hitters and bad for pitchers.

Here’s what it looks like for the Nats for the season and for the month of August:

Innings Innings/Gm
Hitters, 2013 23 1.56
Pitchers, 2013 22 1.49
Hitters, Aug. 5 1.8
Pitchers, Aug. 3 1.1

Not only has August seen a more consistent offense output, it has also seen the Nats more prone to a breakout inning or two; the pitchers are also doing a better job of not letting things get out of hand, in spite of their late innings still remaining a little shaky. For those curious, the big innings (as defined here) for the pitchers were in the first, fifth, and sixth innings in August.

The upswell in runs and victories seen in the month of August for the Nats has been encouraging to see and has provided a glimmer of hope when playoff hopes are discussed — while it will still take a lot of things to go DC’s way, the effort of the club, in particular the hitters, is becoming less and less of a point of contention for fans. However, the efforts of the pitching staff and their improved ability to prevent runs should not be forgotten and should be heralded as the Nats ride this wave of success.



All statistics courtesy of Baseball Reference