Breaking Down wOBA

Weighted On-Base Average (wOBA) is considered one of the best stats to quantify batting performance.  Per Fangraphs, wOBA combines all the different aspects of hitting into one metric, weighting each of them in proportion to their actual run value. But there are a number of questions about wOBA. Is it more important to have a strong BB/K rate or to produce when making contact? Is production when hitting fly balls more important than hitting ground balls and if so by how much? In order to answer these questions and more, I used 2013-2015 data from ESPN Stats and Information and Pitch FX to see what correlates best with overall wOBA.

The first test I ran used data from ESPN Stats and Information. I measured players wOBA based on contact against pitches thrown in the strike zone, wOBA on contact against pitches not in the strike zone and wOBA based on at bats that ended in either a hit by pitch, strikeout or unintentional walk. Then, I determined a given player’s percentage rank for each of these three categories from 2013-2015 as well as his rank for the likelihood of each of these events occurring.

I found that the average wOBA for pitches put into play in the strike zone was .385, for pitches out of the strike zone was .290 and for pitches not put into play was .204. I expected pitches hit in the strike zone to be the most productive type, but I was surprised to see that contact made against pitches thrown outside of the strike zone was more productive than at-bats not resulting in contact.

This indicates that batters are stuck in a game theory situation since they want to make contact as often as possible. Swinging aggressively may result in higher contact rates but also more strikeouts, fewer walks and potentially less productive contact. This means they need to decide whether to swing at a bad pitch early in the count. Ideally, batters would never walk or strikeout because they have their best results when making contact. On average, they should be willing to give up roughly 11 walks in order to prevent 9 strikeouts.  For comparison, a player like Adam Jones roughly strikes out 5 times for each time he earns an unintentional walk.

A stepwise regression analysis suggests that wOBA for pitches hit inside the strike zone percentile rank is the variable with the strongest relationship to actual wOBA percentile rank. The next most influential variable was wOBA on pitches which weren’t put into play. On average, 85% of all at bats end in one of the two above scenarios. There is a weaker relationship between actual wOBA rank and the percentage of balls in each of the three categories, suggesting that this has some relevance but not a huge amount. In general, the percent of pitches resulted in strikes or balls put into play had a positive impact on total wOBA (obviously, putting strikes into play is better than putting balls into play) while failing to put a ball into play had a negative impact.

The R^2 for this analysis was .9225 indicating that these wOBA categories accurately describe overall wOBA. This is expected but important to verify.

There is a high year-to-year correlation between how often a batter puts a pitch in the strike zone (.746) or out of the strike zone into play (.725) or alternatively fails to put the ball into play (.836). There is some year-to-year correlation between a batter’s ability to produce when putting pitches in the strike zone into play (.544) or when not putting the ball into play at all (.639), but only minimal when putting pitches not in the strike zone into play (.169). This suggests that players largely have the same outline from year-to-year but their production is considerably more variable. It also suggests that production on pitcher-friendly pitches is considerably more variable than production on hitter-friendly pitches. It also suggests that while these results have some predictive value, they’re more helpful for illustrating actual results.

The second test I ran used PITCHf/x data from 2013-2015 and studied players that faced at least 1000 pitches in a given season. I then used zone information to determine whether a pitch was a clear strike, a clear ball or unclear defined as being within 1 inch of the strike zone in any direction. Then I determined a players’ overall wOBA percentile rank as well as his wOBA rank for pitches that are strikes, balls and unclear as well as the likelihood percentile rank of him putting a ball, strike or unclear pitch into play.

Unsurprisingly, batters were most successful against pitches in the strike zone with a .411 wOBA, worse against pitches that were questionable with a .342 wOBA and worst against pitches that were clearly balls with a .284 wOBA. It’s pretty clear that batters are most successful when swinging at strikes.

Roughly two-thirds of balls put into play were strikes. As a result, it should not be surprising that a regression analysis indicated that how a player does against strikes has the largest impact on his wOBA by a significant margin. Performance against pitches that are unclear or not in the strike zone are significant variables but with minimal impact. The model’s R^2 was .96 suggesting that these components do accurately describe what occurred.

As with the ESPN data, a players’ year-to-year profile stays reasonably static. There’s a strong correlation of about .73 between a players current “In Play Percentile Ranks” and his rankings the following year for pitches in the strike zone or pitches not in the strike zone. There is a smaller correlation of .516 between a players’ current “wOBA against strikes” percentile rank and his rank in the following year. All in all, it shows that we can be reasonably certain that a player who swings at good or bad pitches will continue to do so in the future, but that this dataset is better used to describe what happened rather than to predict what will happen. This chart can be found below:

The third dataset that I looked at was also PitchF/x data from 2013-2015 based on players that faced at least 1000 pitches in a year. For this dataset, I determined their wOBA percentile rank based on batted ball type (fly ball, ground ball, line drive and pop up).

As one might suspect, batters were most productive hitting line drives with a .732 wOBA, flyballs ranked second with a .354 wOBA, grounders were third with a .251 wOBA and pop-ups were fourth with a .022 wOBA.

A regression analysis suggested that fly balls were more predictive of future wOBA than line drives. Hitting a larger percent of fly balls and line drives resulted in a higher wOBA while hitting grounders and pop ups resulted in a lower wOBA. An R^2 of .91 suggests that these categories accurately describe what occurred.

I found a moderate year-to-year correlation for the likelihood of a player being ranked at a given percentile for his profile type. I also found a reasonable year-to-year correlation for a player hitting fly balls, line drives and pop-ups but only a minimal one for a player hitting ground balls. A chart summarizing this data can be found here:

All in all, these datasets largely show things that are obvious. They show that hitters do better against pitches in the strike zone than against pitches that aren’t. They show that hitters are more productive when hitting line drives than when hitting ground balls. But they also show a few things that aren’t obvious. They illustrate how strikeouts, walks and hit by pitches relate to balls put into play. And they also can illustrate a player’s strengths and weaknesses.

Being able to visualize the data like this can lead to some surprising findings. Hopefully I’ll get a chance to show you some.

Ubaldo Jimenez Keeps Stealing Strikes

In Tuesday's game against the Nationals, Ubaldo Jimenez looked to garner his 100th career win (I know, I know). When the night concluded, he had six innings, one run, and that elusive W to his name. To an extent, Jimenez struggled with control in the outing, issuing five free passes to Washington hitters. Despite that — and despite a second half in which he's walked one out of every ten men to come to the plate — he's improved significantly from last year in this regard, lowering his walk rate from 13.9% to 8.7%.

How has Jimenez arrived here? To cherry-pick a few representative examples from the aforementioned game, he's done this...

...and this...

...and this:

(Props to Nate Delong for the GIFs.)

According to Brooks, all three of those fell outside the strike zone — and yet, all went for called strikes. This continues a trend that has assisted Jimenez all season: He's received far more strikes than his peripherals would suggest.

For 2015 as a whole, 62.1% of Jimenez's pitches (excluding intentional balls) have gone for strikes; 45.9% of his pitches have landed in the PITCHf/x-defined strike zone; and 26.9% of his pitches outside the strike zone have induced a swing. Do some basic arithmetic with the latter two numbers, however, and you discover a 60.5% expected strike rate — 1.6 percentage points lower than his actual mark. That difference ranks tenth among AL pitchers with 100 or more innings:

Rank	Name	O-Swing%	Zone%	xStr%	Str%	Diff
1	Dallas Keuchel	32.8%	40.0%	59.7%	63.4%	3.7%
2	John Danks	30.1%	47.1%	63.0%	65.7%	2.7%
3	Wade Miley	30.3%	40.9%	58.8%	61.4%	2.6%
4	Jose Quintana	30.4%	46.0%	62.4%	64.9%	2.5%
5	J.A. Happ	26.7%	45.8%	60.3%	62.5%	2.2%
6	Chris Sale	35.4%	47.6%	66.1%	68.2%	2.1%
7	Tommy Milone	31.6%	42.8%	60.9%	62.9%	2.0%
8	C.J. Wilson	26.0%	44.7%	59.1%	61.0%	1.9%
9	CC Sabathia	32.4%	45.6%	63.2%	65.0%	1.8%
10	Ubaldo Jimenez	26.9%	45.9%	60.5%	62.1%	1.6%

It's also important to note that Jimenez has never excelled here. In fact, he used to underperform significantly:

This meshes with the view most fans (myself included) hold of Jimenez: He's a wild pitcher, and as such he won't receive many borderline calls — because he most often won't hit the borders. Indeed, in terms of Edge%, he hasn't improved at all from his horrid 2014 season, maintaining a 16.4% figure by that metric. Somehow, though, he's pulled this off.

Certainly, Jimenez owes much of this success to Caleb Joseph, for catching 131.1 of Jimenez's 171.0 innings in 2015. Although he hasn't sustained his incredible framing numbers from last season, Joseph has still saved about seven runs with his receiving ability — one of the better marks in the majors. But Joseph has served as the primary catcher for Wei-Yin Chen, who has posted a lower-than-predicted strike rate (68.2% xStr%, 67.9% Str%). Some of this goes beyond the catcher.

Baseball Savant gives some clues about where Jimenez has picked up those extra strikes. This plot shows his called strikes on pitches outside the strike zone, for his career (from 2008 onward):

This plot shows the same, but for 2015 alone:

And finally, this GIF helps to illuminate the change:

Umpires have seemingly always given Jimenez calls on the outer edges. Recently, though, they've started to do so for lower pitches as well. (The pitch to Werth above perhaps epitomizes this better than anything else this season.) These pitches at the knees have played the largest role in Jimenez's elevated strike total.

This explanation jives with what we already know about Jimenez. As Matt has noted previously, Jimenez has thrown more sinkers this season; most of those have, predictably, gone to the bottom of the zone. Overall, Jimenez has thrown lower than ever before:

Historically — as well as for 2015 — hitters haven't offered at Jimenez's pitches down in the zone. Targeting this area more heavily, he's thus seen more called strikes there, both legitimate and illegitimate. Essentially, Jimenez has thrown a bunch of crap (low pitches) at the wall (batters), and some of it has stuck (strikes outside the zone).

Jimenez is no Greg Maddux. His ability to capture strikes on the plate's outer regions most likely stems from poor umpiring; moreover, baseball as a whole has seen more low strikes this year than ever before, meaning Jimenez doesn't stand out incredibly. Nevertheless, he has undeniably progressed in 2015, partially on the back of these swiped calls. If he can continue to maintain his new delivery — and if Caleb Joseph sticks around — he'll probably keep up the thievery.

All data as of Thursday, September 23rd.

Microtrends: Kevin Gausman's Weak Contact

Since he moved into the Orioles' rotation again, Kevin Gausman has pitched to mixed results. He's put up an uninspiring 4.26 ERA in his ten starts, albeit with a 3.78 FIP. His strikeout rate has jumped from years past, to a solid 21.0%, and he's issued free passes at a meager 4.7% clip; however, poor sequencing (as evidenced by a 67.5% strand rate) has done him in. Taking into account his past performance, though, I found one element of his 2015 starts especially interesting.

Gausman only started five games in 2013, all of which went pretty disastrously — he allowed 21 runs in 24.2 innings, chiefly because of a .351 BABIP. Becoming a starter full-time in 2014, he improved considerably in terms of preventing runs, with a 3.57 ERA across 20 outings. That came despite a subpar .304 BABIP, indicating that hitters still hit the ball hard against him. Over his first 25 career starts, Gausman gave up a hit on 31.3% of the balls put in play against him, a rate that didn't bode well for the future.

The future, as they say, is now. Gausman's 2015 starts have seen him limit the opposition to a .264 BABIP — tremendously lower than we'd expect based on his history. Unlike strikeouts and walks, balls in play take a long time to stabilize, so this could dissipate over a larger sample. The descriptive measures here, though, would suggest that Gausman's weak contact will remain.

By the various batted-ball statistics FanGraphs provides, Gausman has upped his game in virtually every regard:

Starter	LD%	GB%	FB%	PU%	Soft%	Med%	Hard%
2013-2014	24.2%	40.5%	32.4%	2.9%	14.6%	54.3%	31.2%
2015	18.8%	41.9%	33.3%	5.9%	26.3%	46.8%	26.9%

Fewer line drives and hard-hit balls, along with more popups and soft-hit balls, will generally lead to a depreciated BABIP. That's held true for Gausman, whose process has changed to create these results.

In his 2013 and 2014 starts, Gausman relied primarily on three pitches: a four-seam fastball, a slider, and a splitter. The former occupied 68.3% of his overall pitches, while the usage rates for the latter two came in at 8.0% and 18.0%, respectively. He's thrown the fastball just as often during his 2015 starts — a 68.2% clip doesn't differ much at all from the mark he established prior. His shiny new curveball has slid in nicely, replacing the slider with a clean 8.0% usage rate. And the splitter has remained a solid secondary offering, at 16.2%. Which of these three pitches has helped him the most?

The four-seamer, and it's not very close. Hitters battered the slider for a .392 BABIP, and their current .375 figure against the curveball conforms to that. The splitter's .298 BABIP before 2015 has also remained stable, at .290. By contrast, 31.1% of Gausman's four-seam fastballs in play used to go for hits, whereas 24.8% of them have done so thus far. That massive drop accounts for almost all of the variation in Gausman's BABIP, meaning that fastballs have made the difference.

Earlier this year, Jeff Sullivan observed that Gausman had started to throw more high fastballs. That trend from Gausman's bullpen time has carried over to his tenure in the rotation:

First image includes all 2013-2014 appearances.

The higher fastballs have consistently gone for fewer hits when put in play, so increasing their quantity means Gausman's been able to suppress the BABIP against him. Even at the major-league level, most hitters really can't make solid contact on a high heater in the upper 90s; Gausman appears to have realized that, at long last.

Gausman will take the hill tonight against the Rangers, hoping to sustain Baltimore's faint postseason dreams. He may allow some hits on balls in play — over the long term, very few (if any) starting pitchers can maintain a BABIP in the .260s. But this profile shows that he can continue to turn balls in play into outs; if he starts to strand runners as well, he could become Baltimore's next overperformer.

How Has Miguel Gonzalez Gotten So Many Whiffs?

A swinging strike is, objectively, the best possible outcome for a pitcher. They account for most of the variation in his strikeout rate, which in turn accounts for most of the variation in his ERA. In the immortal words of Carson Cistulli, "...they're awesome to watch". Thus, when a pitcher dramatically increases his whiff rate, it generally means he'll pitch better overall.

By runs allowed, Miguel Gonzalez has done about as well in 2015 (89 ERA- in 68.2 innings) as he did in the years that preceded it (85 ERA- in 435.2 innings). That's a shame, because his present xFIP- of 100 beats his career mark by a wide margin. A higher strikeout rate has caused this improvement — he's punched out 20.8% of the batters he's faced, as opposed to 17.0% in the three seasons prior. The cause for this? You'll never guess:

Year	Gonzalez SwStr%	MLB SwStr%	Gonzalez SwStr%+
2012	8.9%	9.3%	95
2013	8.2%	9.5%	87
2014	8.1%	9.6%	84
2015	10.5%	9.7%	108

Yes, Gonzalez owns a notably above-average rate of swinging strikes — higher than any other starter on Baltimore's staff. Most pitchers who struggle to top 90 don't post numbers like that; how has Gonzalez done it?

Well, he certainly hasn't used his fastball, since its whiff rate hasn't budged much from previous years. Instead, he's ridden a better slider and splitter to this success; we'll analyze each individually.

Let's start with the splitter. It's always possessed average velocity and movement, which is more than Gonzalez can say for his other pitches. He's also consistently blown it past opposing hitters, but to varying extents by year:

Its swing-and-miss rate has gone from phenomenal to very good to phenomenal again. (Per Eno Sarris, an "above average" splitter gets whiffs 16.3% of the time.)

Zone maps explain this variance. In its first sensational campaign, Gonzalez buried it in the dirt all the time:

He then began to elevate it slightly in the next two years...

...before returning to his original recipe this season:

Low splitters have always excelled for Gonzalez, accumulating many more swinging strikes than anything up in the zone; thus, he now relies on them much more. These pitches have brought him a lot of his overall success this season.

But, lest we forget, he's also bettered his slider, which has never dominated like it does currently:

What's behind this rise? While Gonzalez's slider actually has more velocity and movement than the MLB average, it's only begun to fulfill its potential this year. And as with his splitter, the difference here comes down to location. Through the first three years of his career, Gonzalez threw the splitter low:

He deceived hitters the best, however, when he moved it low and to the left — which he's therefore done much more often in year four:

Hence, the more effective slider, elevated to great heights by a lack of elevation.

As Baltimore's pitchers — chiefly their starters — have struggled somewhat out of the gate, Miguel Gonzalez has pitched better than ever before. Sure, he's sacrificed a lot of home runs, but once his HR/FB% regresses from its current 16.3% mark to something around 11-12%, his ERA could fall even further with it. In the past, he's proven that he can outperform his subpar peripherals to post solid results; if those peripherals become even average, we could see a star.

What Happened to Bud Norris's Strikeouts?

When Bud Norris came to the Orioles at the 2013 trade deadline, many pundits censured the deal, because Norris appeared to no longer possess the stuff that brought him to the show. In a representative post at FanGraphs, Eno Sarris noted:

In 2010, he threw 93.6 mph and struck out 23.1% of the batters he faced. This year, he's down to 92.4 mph and 16.6% respectively.

Although Norris would finish the year with a 19.0% strikeout rate, that still came in far below his previous norms, corresponding with the aforementioned velocity decline:

Season	K%*	K%+
2009	21.2%	124
2010	23.1%	131
2011	22.1%	125
2012	22.5%	120
2013	18.9%	100

*As a starter

Unsurprisingly, his xFIP- in 2013 (106) was notably worse than from 2009 to 2012 (100). Because of the negative nature of pitcher aging curves, most suspected that he'd never be the same again.

Then came 2014, in which a funny thing happened. The velocity returned...

Year	Fourseam	Sinker	Change	Slider
2009	94.2	0.0	86.9	87.7
2010	94.3	93.6	86.2	87.9
2011	93.6	93.3	83.9	87.0
2012	92.6	92.6	85.8	84.9
2013	93.6	93.2	86.2	85.3
2014	94.5	94.4	86.6	87.7

...but the results remained subpar:

Year	K%	K%+	xFIP-
2014	20.2%	104	105

His lucky ERA notwithstanding, Norris didn't do much in 2014. But why? If his velocity made a comeback, shouldn't the punchouts have come with it?

First, let's check his peripherals. They support the decline fully: While hitters didn't offer at this pitches any less than they used to (his 45.9% Swing% in 2014 didn't diverge much from his 45.5% mark from 2009 to 2013), they didn't miss nearly as often when they did (his 83.5% Contact% departed significantly from the 76.7% figure he theretofore posted). So an absence of whiffs caused this, but what caused that?

Entering the majors in 2009, Norris only had three pitches: a four-seam fastball, a changeup, and a slider. As the above velocity chart shows, all three of those quickly lost velocity, leading him to integrate a fourth pitch: a sinker. In 2010 and 2011, he threw it less than 7% of the time, but by 2012 — when his velocity hit its nadir — it had become a full member of his arsenal:

Unsurprisingly, Norris's sinker doesn't accrue many whiffs — for his career, it has a SwStr% of 4.3%. So its rise (or sink, I suppose) accounts for some of the disappearance in strikeouts. But most of it is due to the latter of the three aforementioned pitches.

Norris's slider has always been good. Like, really good. According to Jeff Zimmerman, an above-average slider has a whiff rate of 14.4%; Norris's has resulted in a swing-and-a-miss 18.5% of the time. Two years ago, however, that took a turn for the worse, and it hasn't recovered yet:

At 30.7%, Norris's usage rate on the pitch had never been lower.

Remember, Norris regained velocity on every pitch — including his slider — in 2014. That means speed didn't create this, which indicates it may be something within Norris's control. But what?

His location of the pitch stayed the same, as did the rate at which batters swung at it. One thing did change, though: his sequencing. Earlier in his career, he relied on the slider to get tough outs; by 2014, that had changed:

Year(s)	Slider% — Batter Ahead	Slider% — Even	Slider% — Pitcher Ahead
2009-2013	27.3%	36.4%	42.8%
2014	27.5%	29.9%	34.6%

In a hitter's count, Norris relied on the slider as much as ever; when he had the advantage, though (or when he was close to having the advantage), he decided to eschew it. Its replacement came in the form of his new favorite pitch — the sinker:

Year(s)	Sinker% — Batter Ahead	Sinker% — Even	Sinker% — Pitcher Ahead
2009-2013	8.5%	10.6%	8.7%
2014	11.2%	14.4%	14.3%

To put batters away, Norris no longer leans on his slider, as he's deemed his sinker a worthy substitute. Of course, this means fewer whiffs — a batter won't swing and miss as often in a hitter's count, when he has room with which to work, as he would in a pitcher's count, when he's more desperate. Nevertheless, that tantalizingly low ERA from last year (7% better than average, the best level of Norris's career) might convince him that it's a worthwhile tradeoff.

So, there you have it. If Norris ever decides to get strikeouts again, he can probably do so; all he has to do is decide to put batters away with his slider, instead of his sinker. The stuff is there, but if the mind isn't willing, it won't come to fruition.

Darren O'Day's Surprising Splits

Once again, sidearm specialist Darren O'Day in the midst of another productive season for the Baltimore Orioles. Currently boasting a 1.08 ERA/2.90 FIP/3.27 xFIP pitching slash line and staying neck and neck with the likes of closer Zach Britton and ground ball specialist Ryan Webb for the Orioles reliever lead in fWAR—Britton currently sits a 1.0 fWAR, with O'Day and Webb not far behind at 0.9 and 0.8 fWAR, respectively—O'Day is also leading the bullpen with a 19.08 RE24, which is bested only by New York Yankees All-Star setup man Dellin Betances (24.20) in MLB.

What has gone somewhat unnoticed this season—if there's such a thing with sidearmers—is O'Day's ability to get lefthanded hitters out, something that is typically the downfall of pitchers of his ilk. Over his career, O'Day has a left/right wOBA split of .304/.251, a surprisingly respectable split, given his arm angle. However, this season, O'Day has one-upped himself, keeping righthanded hitters to a .246 wOBA and lefthanded hitters to a .241 wOBA.

Yes, Darren O'Day, righty sidearmer extraordinaire, is more effective against lefties than he is righties in 2014.

Compounding the confounding is O'Day's 2013 splits, which had saw lefties and righties hit at a .394 and .206 wOBA, respectively, a disparity typically seen (and accepted) from sidearmers. While many pitchers with O'Day's approach and style will often look for an additional weapon to counter opposite hand hitters, be it a another pitch or honing of their command of both side of the plate, it is exceptionally rare to see such a dramatic about-face in such short notice, even with the knowledge that O'Day's career splits aren't as eye-popping as his 2013 season's. However, O'Day did in fact add a little wrinkle to his repertoire in 2014, adding a changeup to his four-seam fastball, sinker, and slider mix, using it exclusively against lefthanded batters. While it would be easy to hoist the explanation for O'Day's suddenly superb pitching against lefties on the new pitch, the fact that he has thrown ten in total all season, most recently in mid-May (per Brooks Baseball), speaks to his success against lefties being a result of something else.

Speaking of Brooks data, let's look at some more, in particular, his career, 2013, and current season numbers with changeup data removed, to see if anything jumps out as a potential cause for O'Day's success against lefties:

Year	Pitch Type	Freq	Velo (mph)	Hmov (in.)	Vmov (in.)	H. Rel (ft.)	V. Rel (ft.)
2013	Fourseam	33.42%	87.32	-7.19	2.48	-3.25	3.53
	Sinker	19.54%	86.47	-7.71	-3.82	-3.21	3.31
	Slider	47.04%	79.77	4.51	1.23	-3.3	3.51
2014	Fourseam	32.00%	88.57	-8.01	3.39	-2.98	3.68
	Sinker	30.18%	87.85	-8.56	-3.67	-2.89	3.45
	Slider	29.68%	80.23	4.77	1.3	-3.04	3.56
Career	Fourseam	28.11%	87.5	-7.42	2.79	-3.06	3.61
	Sinker	35.08%	86.28	-7.15	-3.71	-2.93	3.33
	Slider	35.75%	79.12	4.56	1.23	-3.13	3.49

In terms of pitch selection, it looks like 2013 saw O'Day deviate mildly from his career averages, going less with the sinker in place of more sliders. This season, he has returned to a more balanced approach, throwing all three of his primary pitches (along with those ten changeups), with each pitch showing a little extra oomph to them, velocity-wise. Also, the sidearmer's release point (H. and V. Rel) is a touch higher vertically and a little closer to body body horizontally in 2014 compared to least season or over his career. This minor tweak has also added a little extra horizontal movement to his pitches (Hmov), with his four-seam and slider also seeing a little boost in movement this year.

Let's now turn our attention to what happens once O'Day releases the pitch:

Year	Pitch Type	Strike	Swing	Whiffs
2013	Fourseam	22.31%	50.77%	17.69%
	Sinker	27.63%	43.42%	6.58%
	Slider	33.88%	40.98%	8.20%
2014	Fourseam	20.43%	62.37%	18.28%
	Sinker	34.52%	40.48%	7.14%
	Slider	34.52%	35.71%	5.95%
Career	Fourseam	18.68%	54.50%	14.77%
	Sinker	28.57%	45.31%	5.44%
	Slider	36.18%	40.45%	8.28%

The extra wiggle and velocity seen from the four-seam fastball has been especially kind to O'Day in 2014, with the pitch generating more whiffs and swings than last year or over his career. This is combined with this season's improved ability to throw the sinker for strikes and get a few mores whiffs, with the slider apparently being thrown for called strikes, given the increase in strike percentage and concomitant drop in swing rate.

Batted ball data show similar changes in 2014:

Year	Pitch Type	GB	LD	FB
2013	Fourseam	3.85%	4.62%	6.92%
	Sinker	10.53%	1.32%	7.89%
	Slider	6.01%	1.64%	3.83%
2014	Fourseam	3.23%	5.38%	4.30%
	Sinker	22.62%	1.19%	2.38%
	Slider	2.38%	4.76%	2.38%
Career	Fourseam	2.72%	4.24%	6.28%
	Sinker	16.46%	2.99%	5.58%
	Slider	3.87%	2.40%	5.47%

The sinker again provides O'Day a lot of success in the form of ground balls and a drop across all three pitches in fly balls rates. However, it does appear to possibly come at the cost of some bite to his slider, as the drop in ground ball rates to go along with an increase in line drive rate—a crude measure of how hard a ball is hit—show that the slider has maybe lost a little magic this season. However, these purported decreases in effectiveness of the slider could simply be a result of O'Day flipping the pitch over in first pitch counts, working backwards to get ahead in the count. Some of this notion if reflected when looking a first pitch slider percentages, with 2014 seeing him throw a slider first pitch 47% of the time; this pales in comparison to his 2013 average of 59.5%, but is up from his career average of 40% sliders in 0-0 counts.

Finally, let's look at pitch locations between 2013 (left) and this season (right). First, the fastball:

...and the sinker:

...and the slider:

For the fastball, we see O'Day pounding the upper part of the zone with the rising heater, but in 2014, he's doing so with better command. Compared to 2013, this season has seen his fastball stay out of the heart of the plate and maybe more importantly, away from a lefty's power—down and in. With the sinker and slider, it's a similar story; better strikes and fewer mistakes making their way over the plate, with pitches that miss doing so out of the zone and away from a lefty's power.

While the odd splits and ridiculous levels of success against lefties will probably be a fleeting thing for O'Day, we do see some changes to his approach that show some promise that he'll be able to face lefties effectively—better command of the strike zone with his offerings and improved ability to change planes and eye levels of hitters with his fastballs and slider. His willingness to throw a changeup to lefties, while a work in progress, is also an encouraging development and could lend itself to eventually becoming a more relied upon weapon to neutralize lefties. For now, better control, a slight change in arm slot, and an uptick in velocity combined with a willingness to work backwards should help keep O'Day atop the AL reliever leaderboards in a number of categories and more importantly, keep lefties as well as righties off of the base paths.

Data courtesy of FanGraphs and Brooks Baseball.

Dissecting J.J. Hardy's Homer Drought

For a player whose offensive value is all but predicated upon the long ball, the lack of pop coming out of J.J. Hardy's bat this season is troubling. Finally getting off the schneid June 21st with a home run off of a 95 MPH fastball, Hardy has followed up this long fly with two more, bringing his home run per flyball rate (HR/FB%) up to 2.9 percent, putting him in the hallowed homer company of Ben Revere (2.9%) and Austin Jackson (3.0%). Sarcasm aside, the dearth of home runs currently has Hardy—whose 25 home runs last season tied him with Troy Tulowitzki for the most hit by a shortstop, and his 12.4% HR/FB rate ranking third for shortstops last year—hitting at a .298 weighted on base average (wOBA) and 84 weighted runs created plus (wRC+), both of which are slightly above American League average for shortstops (.293 wOBA and 83 wRC+). Combine this with a career-worst 3.8 percent walk rate and a slight hike in his strikeout rate (15.7%) compared to last year and his career (14.3% and 11.3%, respectively) and it becomes obvious that Hardy's normal sources of production are beginning to run dry.

There are myriad reasons for Hardy's power outage—injury, age-related declines, a loss of bat speed, a change in how he is being pitched, changes in his batted ball rates, perhaps a change in hitting approach—all of these variables that could be at the root of the problem, working alone, or in unison. While we don't have access to all of the information that could determine whether some of these factors are realistically a piece of the homer puzzle for Hardy, we do have batted ball and PITCHf/x results to work with, which can help discern whether the problems are more hitter- or pitcher- derived. Using last season for comparison here and moving forward, let's start by looking at pitch type linear weights (here, we use PITCHf/x-derived pitch values per 100 pitches) of the pitches Hardy has seen; the more positive a number, the more success Hardy has had with a given pitch:

Season	wFA/C	wFT/C	wFC/C	wFS/C	wSI/C	wSL/C	wCU/C	wKC/C	wCH/C	wKN/C
2013	-0.16	0.56	-2.01	-7.48	2.02	-0.68	3.53	-2.25	-0.28	8.14
2014	-0.83	-1.36	-1.76	-1.68	1.05	2.06	1.71	-5.5	-1.02	-10.08
Career	-0.24	-0.16	-0.94	-2.57	-0.43	-0.2	0.3	0.58	0.35	5.42

 FA=fourseam fastball, FT=twoseam fastball, FC=cutter, FS=split-finger fastball, SI=sinker, SL=slider, CU=curveball, KC=knuckle curve, CH=changeup, KN=knuckleball

Here, we see a slight decline in Hardy's success with fastballs, especially fourseamers, twoseamers, and to some extent, sinkers; cutters and split-finger fastballs are still problematic (hence, the negative values), but this year appear to be less so than in years past. Sliders appear to be quite improved in terms of Hardy being able to put a good swing on the pitch, with this and the decline in fastball success perhaps a tacit indication that the bat speed might be starting to decline in 2014. 

Staying with PITCHf/x data, let's now turn attention to how often these pitches are seen by Hardy, which will also provide more context to what's he seeing, pitch-wise, as it is one thing to do poorly against a certain pitch, but only see the pitch once or twice a season:

Season	FA%	FT%	FC%	FS%	SI%	SL%	CU%	KC%	CH%	KN%
2013	35.70%	15.60%	6.40%	1.20%	8.20%	14.50%	5.50%	0.50%	10.60%	1.00%
2014	38.30%	17.30%	5.20%	1.40%	7.40%	15.80%	6.10%	0.80%	7.20%	0.40%
Career	44.90%	9.10%	4.40%	0.70%	5.70%	16.70%	8.10%	0.20%	9.40%	0.40%

Hardy is seeing slightly more four- and twoseamers than last year, with a concomitant rise in sliders and curveballs seen; it appears that Hardy is making the most of the increased number of sliders he is seeing, but is doing so at the cost of less success against the hard stuff so far this season. 

So far, we have found some slight deviations in how pitchers have gone about getting Hardy out; have these changes been reflected in the batted ball data, aside from the homers?

Season	LD%	GB%	FB%	IFFB%	HR/FB	IFH%	BUH%
2013	16.60%	45.20%	38.20%	14.40%	12.40%	8.40%	0.00%
2014	17.70%	43.90%	38.40%	16.30%	2.90%	8.40%	50.00%
Career	16.90%	44.40%	38.70%	13.30%	10.80%	7.40%	15.40%

LD=line drive, GB=ground ball, FB=fly ball, IFFB= infield fly ball, IFH=infield hit, BUH=bunt hit 

In a word, no; the Hardy of 2014 appears to be the same as the Hardy of 2013, at least by his batted ball rates, outside from HR/FB. The rise in bunt hits seen this year is courtesy of two bunt hits, compared to zero laid down in 2013. The more commonly referenced and researched numbers of Hardy's 2014—line drive, ground ball, and fly ball rates—are all within a percentage point or two of last year's rates, which saw him enjoy his typical homer-heavy production. Going one step further and calculating fly balls per popup, which provides a rough estimate of how hard a player is hitting the ball—and the results indicated that perhaps it isn't so much the batted ball type at play with Hardy's homer drought, but more the quality, with respect to how hard it's being hit. 

Season	FB%	IFFB%	FB/PU
2013	38.20%	14.40%	2.65
2014	38.40%	16.30%	2.36
Career	38.70%	13.30%	2.91

Overall, Hardy's FB/PU is fairly pedestrian compared to the likes of a slugger like Chris Davis, whose current FB/PU sits a 6.59. However, we do see it in decline, sitting at 2.36, his lowest rate as an Oriole; in his Oriole years, Hardy has averaged a 3.0 FB/PU rate, suffering a career-low 2.05 FB/PU in 2006, while with the Milwaukee Brewers.

Setting aside the tables for a moment, let's look at where in the strike zone Hardy's homers have been hit this season and last, splitting out pitcher handedness:

 While we don't have much 2014 data to hang our hats on, we can use 2013 as a template—Hardy does the most damage on fastballs (here, I collapsed all fastball types into a single 'FA' variable) up in the zone, essentially over the middle of the plate, from righthanded pitchers. Through Brooks Baseball and with a focus on fastballs, we can compare where righties are pitching to Hardy to see if they've become cognizant of this trend and have begun to avoid the high fastball; on the left is 2013 data, on the right, 2014:

Pitchers have appeared to maintain the same or at least a similar approach to getting Hardy out with respect to pitch location, with no significant swings in fastball location from last season to now. 

Using the same PITCHf/x tools, let's take a look at Hardy's tendencies; here, we look at his popup rates over the last season and a half on fastballs from righties:

It appears Hardy has had a little tougher time this year putting a good swing on fastballs in the heart of the plate and slightly elevated, his homer 'sweet spot'. While the statistics previously presented have shown that he has been able to counter some of this in the greater scheme of things offensviely, given that his line drive and fly ball rates have been fairly par for the course in 2014, the PITCHf/x data alludes to a possible slowing of the bat for Hardy, paired with a propensity for hitting balls with less authority this year. 

For Hardy, the sudden decline in his bread and butter offensive weapon is jarring and is made all the more discouraging, given his less than optimal walk rates and ability to hit for average. While the Orioles shortstop still has the potential to finish the season as an above average offensive contributor, the numbers are pointing to the days of 20+ homer seasons being over, unless adjustments are made in his approach.

*** 

Data courtesy of Baseball Savant and FanGraphs, unless otherwise noted.