Tagged: Washington Nationals

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:

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…and Strasburg:

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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.

2013:

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

2012:

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:

Split PA H XBH R RBI BB% K% AVG
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?

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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

Closing By Committee Poll: The Results

In my previous post, we discussed the Washington Nationals and their closer situation and did a quick poll/psychology test on who people felt should be closer, based on the statistics of four relievers, Nats or otherwise. If you need to catch up and read part one, you can check it out here.

Go on, I’ll wait.

Did you read it? You didn’t, did you. It’s OK. We’ll move on without you. Thank you to the 21 folks who did vote, even if you did vote for Kenny Powers. To those who ignored my pleas for participation, all I can do is shake my head in mild disappointment:

jim-head-shake

Are you thoroughly shamed? Yeah, didn’t think so.

Undeterred, let’s move on to find out the results of said poll and see who Nats fans think has the stats of a closer.

Let’s briefly recap some things — first, I presented the statistics of four relievers. Two are previous All-Stars, two are current closers, two are non-closer short relievers, and three have 30+ save seasons under their respective belts. A little more information: two are current Nationals and two are non-Nats. So far, so good? OK, the results:

Screen shot 2013-08-24 at 5.15.48 PM

Player 1 is the resounding winner and it isn’t even close. It appears his combination of stuff, in the form of a good strikeout and swinging strike rate, and success, in the form of his shutdown/meltdown numbers, are what set him apart and led to his vote of confidence by the bullpen committee of you, the readers.

So who was it? Who are the mystery closer candidates?

Player 1 is Sam LeCure of the Cincinnati Reds

Player 2 is Jim Johnson of the Baltimore Orioles

Player 3 is Rafael Soriano of the Nationals

Player 4 is Drew Storen of the Nationals

…and ‘Other’ is the aforementioned Mr. Powers.

Are you wowed? Surprised? Ready to flame me on twitter?

Before flaming, let me discuss the fine gentlemen and the reason why I included the likes of Johnson and LeCure to the discussion.

LeCure, as we learned in my previous post, is similar in style to Storen, not only in approach/stuff, but also place in the bullpen. While from a pure talent perspective, he doesn’t have Storen’s repertoire, he does have a similar pitching style, in the fact that he uses 3-4 pitches and can throw them all for strikes with respectable command of them all. He doesn’t have Storen’s velocity; yet, both pitchers are a rare bullpen breed in using 3+ plus pitches to get batters out. They both also are victims(?) of their situations, in that their managers both manage to the save; they have a designated closer (for the Reds, it’s flamethrower Aroldis Chapman), and from there, the bullpen roles are filled in. Both managers have displayed tremendous amounts of confidence in and leeway to their closers in terms of using them only in save situations and letting them pitch their way out of jams. So, to the 6th through 8th innings, LeCure goes and he has excelled in said role. He has quietly become one of the more reliable relievers in the game and has done so out of the limelight and without much quibbling about where he pitches.

Johnson is not only similar in approach to Soriano in terms of pitching style, but also being oft maligned by his team’s fans. Known to blow a save here and there (he currently leads the AL in blown saves), he still is his manager’s guy, for the most part. While Orioles manager Buck Showalter has shown a propensity to go to the hot hand or to matchups more frequently than Reds manager Dusty Baker or Nats manager Davey Johnson when it comes to managing the ninth inning, he still has publicly confessed that Johnson is his closer. Much like Soriano, Johnson gets by more on contact in the form of a devastating two-seam fastball with a ton of movement and will not induce too many swinging strikes or strikeouts. In this situation, a closer with this approach will be more dependent upon inducing ground ball contact and relying upon his defense to bail him out of tights situations more so than a pitcher who can go to a strikeout pitch to get him out of trouble, so again, we see Johnson and Soriano paired up.

So we have a quartet with a number of similarities and a number of disparities, both within and out of their control. Remember the FIP/xFIP table from the last article? Let’s look at it now, including each player’s ERA:

  ERA FIP xFIP
LeCure 3.12 3.00 3.34
Johnson 3.51 3.94 3.77
Soriano 3.79 3.91 4.17
Storen 5.70 3.84 3.46

Let’s look at this a little closer now and compare/contrast the values here. Previously, we spoke of FIP and xFIP and their relation — when FIP is lower than xFIP, we can infer that a pitcher is pitching better than what his stats project; of course the converse of this is true when FIP is greater than xFIP.

Now, let’s add ERA into this. ERA can be affected more greatly by what the defense does behind you, so when compared to FIP and xFIP, you can get a decent understanding of how much outside forces play a role in a pitcher’s performance. With that in mind, what has each of our four guys done thus far in 2013? First, some quick associations:

LeCure: ERA > FIP < xFIP

Johnson: ERA < FIP > xFIP

Soriano: ERA < FIP < xFIP

Storen: ERA > FIP > xFIP

LeCure has not only outperformed his xFIP, his ERA shows that he might even be a little unlucky in certain instances, but only slightly. Johnson and Storen have both struggled when compared against their own expected performances (FIP > xFIP), but where Johnson has been bailed out by his defense — arguably one of the more talented in the majors — Storen has suffered from the miscues of his teammates at times. Add to it a propensity to give up home runs more so than the other three and you have in a nutshell some of Storen’s  problems this season. Soriano, while not performing to usual standards, is getting a decent amount of help from his defense (ERA < FIP); add to it a low K rate and the occasional home run, and well… I won’t belabour the point.

So what do we have in the end? Overall, there aren’t too many differences between success and perceived failure or struggles; this is where this becomes more psychology experiment than poll. In many ways, labels are just that — labels, and not true definitions or evaluations of worth. It is the perceptions of roles and general success that can sometimes blind a person to a player’s true worth or success — I perceive myself to be the closer, therefore, if I don’t close, I am not successful. My ERA is X, when it should be X-1, therefore, I am struggling. Player X is my closer, therefore, I should not use Player Y in the ninth inning. Player X is my closer, so I shouldn’t use him in the seventh in a bases loaded situation where the batter up to bat is 0 for 25 against my closer, because, it’s the seventh inning. That and no one really likes Soriano.

While my exercise here will potentially fall on deaf ears, it hopefully opens eyes to the notion that success can be found in and defined by many  different combinations of statistics and situations; it’s just a matter of being open to alterations in your perception and the notion that high performers and success come in all shapes, sizes, innings, counts, and pitch types. The fact that many felt a non-closer displayed the most closer-ish stats, even when compared to pitchers labeled as closers, just speaks to this and also speaks to the promise that is left to be fulfilled by pitchers that may not necessarily pitch in the ninth inning.

Closing By Committee Poll

There has been much ado about the status of the Washington Nationals closer role as of late, with the resurgence of Drew Storen, post-AAA assignment and mechanical tweak, and the concomitant tanking of Rafael Soriano, he of the 11.37 ERA, .435 BABIP, and 3 home runs given up in the past six appearances.

While is has been hotly debated as to whether Storen should become re-acquainted with the ninth inning closer’s role that he was so accustomed to and successful in back in 2011 in lieu of the apparently out of gas Soriano, whose efforts thus far in the closer’s role have him tied for second place in the National League for saves, the ultimate answer is sure to conjure up Abraham Lincoln’s quote about not pleasing everyone, every time (I’m paraphrasing here).

The Nationals are a team with an embarrassment of bullpen riches and in reality, they have easily three players who can and have successfully closed games. However, the third member of this trifecta — Tyler Clippard — has been quasi-relegated to setup man duties, so the showdown for the ninth inning comes to these aforementioned flawed fellows. While Storen has shown gumption and some nasty stuff upon his return to DC, his body of work hasn’t impressed in general, and has apparently made manager Davey Johnson a bit gun-shy when it comes to letting him work out of jams. Soriano, while accumulating nice save stats, does not have the fastball/cutter/splitter combo as sharp as has been seen in previous years; overall, Soriano’s repertoire has looked flat in the last few appearances, much to the chagrin of the Nats side of the scoreboard and to the delight of hitters looking for a pitch to drive.

So who wins this arms race? Should there be a changing of the guard? Should things stay as is? Some very emotional and vocal Twitter cries had me thinking about the predicament and I thought this situation is ripe for a poll. Teams have closers by committee, let’s have a closer by poll, yes?

First, let me lay down the groundwork and throw a curve or two just so it doesn’t become a ‘Coke vs. Pepsi’ type of endeavour. I have selected four pitchers — three of them have had seasons with 30+ saves, two of them have been All-Star selections. Two are currently their team’s closer, while two of them toil in the later, non-ninth innings. Who, in your mind, should close? Who, by virtue of their stats, makes you think, ‘yes, this guy can shut things down in the ninth inning’?

On to the stats!

K/9 BB/9 HR/9 BABIP LOB% HR/FB GB/FB
Player 1 9.92 3.31 0.73 0.304 79.00% 8.00% 1.02
Player 2 6.87 2.72 0.8 0.323 77.60% 12.50% 2.38
Player 3 6.75 2.14 1.15 0.300 76.80% 9.20% 0.72
Player 4 9.32 2.66 1.33 0.333 60.10% 13.20% 1.17

 
Here, we look at each player’s outcome relevant stats — while they each do things differently in terms of their pitch types and velocities, we can get a good view of where things end up once they release their pitches. Players 1 and 4 strike out a ton of folks. Players 2 and 4 seem a bit unlucky judged by their 2013 BABIP’s. Player 2 gets a LOT of groundballs (GB/FB), but also a lot of home runs (HR/FB%), and Player 4 seems to give up a big, run scoring hit more frequently than he would like, judged by his left on base percentage (LOB%). OK, that’s a nice start, let’s look at some more numbers:

  ERA FIP xFIP
Player 1 ??? 3.00 3.34
Player 2 ??? 3.94 3.77
Player 3 ??? 3.91 4.17
Player 4 ??? 3.84 3.46

 
I will reveal ERAs once I get some poll results as they can possibly reveal who each player is (and what’s the fun in that?), so for now, let’s look at their fielding independent pitching (FIP and xFIP) numbers; xFIP is expected fielding independent pitching, which you can read more about here, if you so desire. In general, pitchers whose FIP is less than their xFIP are outperforming what was expected of them, with the converse being true with their xFIP being less than their FIP. Cool. So Players 1 and 3 are doing better than what FIP expects them to, while 2 and 4 are underperforming. We can take that knowledge and compare it to ERA (once revealed) to look at how much of an effect the pitcher (or defense) has on their performances — typically, if FIP and xFIP are less than ERA, you tend to believe that the defense behind a guy is hurting him a tad. If ERA is lower than both FIP and xFIP, it leads you to possibly think that a pitcher is outperforming his stats, and that the defense behind him has bailed him out a few times. Still with me? Thanks! A couple more tables:

  Swing% Contact% Zone% SwStr%
Player 1 41.00% 73.70% 44.90% 10.70%
Player 2 45.60% 82.40% 42.80% 7.80%
Player 3 49.60% 81.30% 47.00% 9.10%
Player 4 49.70% 78.40% 49.10% 10.40%

 
Here we are looking at how well each pitcher is pitching, with respect to the batters results — are they throwing strikes? Are they good strikes? Do they have a great pitch that generates swings and misses? — and overall, we see Player 1 and 4 are getting swings and misses (SwStr%), typically a hallmark of a good pitch (or pitches). All four players throw pitches in the strike zone less than 50% of the time (Zone%). By the looks of it, Players 2 and 3 generate a lot of contact (Contact%), while 3 and 4 get batters to swing quite a bit (Swing%). When you look at these data compared to the first table, we see a trend — players 1 and 4 have a good bit in common as far as their approaches, while Players 2 and 3 seem to be a comparable pair. Overall, the 1/4 combo have more swing and miss stuff, while the 2/3 combo look to get more hitters out by inducing contact and letting their defense help them out.

  Shutdown Meltdown Pct
Player 1 20 5 80.0%
Player 2 28 11 71.8%
Player 3 22 8 73.3%
Player 4 19 10 65.5%

 
…and last, the shutdown (SD)/meltdown (MD) table. I will leave you to your own devices to read up on what each means (which you can find here); for those click averse, here is the Fangraphs breakdown of the stat:

Screen shot 2013-08-24 at 10.47.11 AM

 
So, fellow budding managers, who closes? If you had a choice of one of these players, who would it be for the Nats?

Please note, not all of these players are currently on the Nats, but were chosen for their similarities in terms of bullpen role, success, and fan perception of their success in their given roles.

 

Once I get a few results, I will update the post.

***

All stats courtesy of Fangraphs

Fanning the Flames

Just when you think a team is on the cusp of putting it all together and playing to their potential and even saying as much, this happens:

images

The dumpster fire I speak of is last night’s convincing 11-1 loss at the hands of Jeff Samardzija and the Chicago Cubs. Convincing in just how toothless the Nats offense can be in generating any runs besides those that come from a home run, which inspired me to do some sleuthing and tweet this:

Just to clarify, since 140 characters can sometimes not be enough to truly express your thoughts on something as big of a train wreck as the Nats offense has been this season – even with a great winning percentage in games when someone hits a homer, the Nats are still about 30 points below league average when it comes to securing victory after securing said runs. When they don’t hit a home run the situation is even more miserable, suffering a terrible record as well as being almost 70 points worse than league average when runs are needed from other sources. Essentially, the Nats offense has devolved, if these numbers are to be taken as ground truth, into one that subsists solely on home runs.

Is that the case? Are the Nats that hapless with bats in their hands — can they generate offense without their power hitters?

Let’s Baseball-Reference surf. First, the good stuff; a table showing Washington’s place in the National League for homers:

Screen shot 2013-08-20 at 6.12.54 PM

8th place in a 15 team league – not so bad. OK, so we have an adequate homer hitting team. What else do the Nats have, compared to their NL foes?

Screen shot 2013-08-20 at 6.13.21 PM

For OPS+, they only outpace the Miami Giancarlos Marlins in terms of overall value of the team’s offense. Ick. Let’s look deeper; how about situational hitting, and some of the more nuanced aspects of hitting that might show the Nats being an adequate small ball team. For this, let’s look at productive outs, which are defined by the PrdOut stat as a sacrifice by a pitcher with one out, any runner advancing with no outs, or driving in a base runner with the second out of the inning. Gritty, gutty, small ball.

How does Washington size up?
Screen shot 2013-08-20 at 6.19.20 PM

Oh. Dead last in productive out opportunities, and, while not pictured, 13th in the NL for productive out success rate (31%). Add to it the 13th best sacrifice bunt rate in the NL in the third most attempts (a sign that the team is truly trying to find creative ways to get runners on base and to score), and we have a decent explanation for this table and its highlighted stat, runs created per game (RC/G):
Screen shot 2013-08-20 at 6.16.13 PM

…which again shows the Nats towards the bottom of the pile, but not egregiously so. That’s promising…right?

If you consider that 4.2 value and peek over at the runs scored per game column (R/G) and compare the two, you notice a disparity to the detriment of the Nats — even with the decent number of opportunities to score, they are not all getting converted in the form of plating base runners.

So the team can’t do much of anything in the form of generating runs outside of home runs — is there some bad luck involved, in the form of making contact, but just right at the defense, thereby generating outs? Batting average on balls in play (BABIP) can help us quantify some of that:

Screen shot 2013-08-20 at 6.14.58 PM

…and by the looks of it, there is some bad luck involved potentially with the offensive impotence seen with the Nats bats, in the form of a below average .287 BABIP. Looking at raw balls put in play (not pictured), we find the team puts 68% of balls in play, which is exactly league average. Putting these two stats together and luck may not be as strong of an explanation to the Nats woes — it may just simply be Nats fans are watching a below average offense not taking advantage of the inherently few opportunities it generates for itself.

One last stat, just to tie a bow on this turd blossom of a post. Maybe the error here is looking at the parts of a sum, and that the offensive contributions of each of the Nats truly exceed their sums with respect to the hitting situations we have discussed. Maybe the fact that the team has three players in the top 30 in home runs in the NL (Ian Desmond, Adam LaRoche, and Jayson Werth) is all that we need to know about the offense, and that all of these fancy maths and stats are somehow misrepresenting the true value of the hitters and the value of the hitting situations encountered thus far in the season. Somehow, the true peak of the offense has yet to be reached, and all of these basement dwelling standings are a mirage.

Here, we have highlighted NL adjusted batting runs (BtRuns), which explains how many runs a hitter contributes to his team above and beyond what a league average replacement player would provide. In other words, better than average players will have positive values, players who deserve to be released or be in the minor leagues will have negative values. Add up all of the values of the team and you hope to have something positive.

Screen shot 2013-08-20 at 6.14.39 PM

Well then. Not only is the NL not that great with respect to this statistic, the Nats are atrocious, over 35 batting runs below league average. A lot can be said about what contributes to this overall value — poor play, poor lineup construction, poor situational outcomes, perhaps Dengue Fever, but in the end, when compared to their cohorts, the Nats have not produced, home run, or otherwise. As an aside and as a way to measure things with this BtRuns stat, the 2012 Nats were third in the NL in the category at 18.5, behind the San Francisco Giants (64.8) and St. Louis Cardinals (59.7).

Flame on, phoenix.

***

*all tables/statistics courtesy of Baseball-Reference

I Want a New Drug Hitting Coach: Channeling Your Inner Huey Lewis

Inspiration can, at times, come from surprising places.

Want to run on the field, but need the onus of (electronic) peer pressure to propel you? Look no further than Twitter.

Yes, when you just need that extra oomph to follow through on something, succumb to peer pressure and the tally of a retweet:

The Washington Nationals did a similar thing (in spirit) recently, by firing long time hitting coach Rick Eckstein. In spite of the cries of his followers to keep him on the field, Mike Rizzo let go of Eckstein in the midst of a disappointing season thus far for the Nats, replacing him with minor league hitting coordinator Rick Schu. Like our aforementioned twitter dare, the decision was made in an effort to shake things up, to make the unpalatable a little more exciting, and hope that the crowd would become a little more adoring.

The Nats have just about reached the three-week mark since Schu took over the hitting helm; has it made a difference to the offense? Are the Nats better offensively now that Eckstein was relieved of duties?

Broadly, there doesn’t seem to be much difference in the 20 or so games they have played with Schu as hitting instructor. With Schu, the Nats are 9-10 and averaging 4.2 runs per game. With Eckstein, their record was 48-50 with a 3.7 runs per game average. Judging by the record and the fact that the National League runs per game average is 4.04, and we are only left with that ‘meh’ taste in our mouths as far as the difference Schu has made thus far to the Nats.

Let’s break it down a little further and look at some stats of the Nats starters along with some bench players to see if the changing of the guard has reaped any immediate benefits, or if the aforementioned numbers are as uninspiring as they appear to be.

First a couple of caveats must be discussed. For gathering data, I approached things in a couple of different ways. With Eckstein, I took individual player stats and looked at what they did this season under his tutelage and also in the last 20 or so games before he was fired. I also took player averages under the Schu regime, but throwing out data from the first series that he was hitting coach. I did this just to give the players a clean slate, so to speak, and remove any potential Eckstein biases on their day-to-day activities. Silly? Probably, but I made the assumption that hitters are humans and they too could require a brief adjustment period to their new supervisor. Who knows, maybe Schu was calling Adam LaRoche Andy, putting him in a funk for a few games until he realized he got the wrong LaRoche. Crazier things have happened.

What we are left with are three datasets for each hitter – season total under Eckstein (labeled Eck_tot), two(ish) week total before Eckstein was fired (Eck_2), and two(ish) week total under Schu (Schu). The two(ish) week totals both ended up being around 55 plate appearances (PA), give or take two or three PAs. While I originally included all players that had at least 100 PAs this season, I ended up throwing out data for Kurt Suzuki, Roger Bernadina, and Chad Tracy because they each had less than 15 PAs under Schu, and I didn’t feel comfortable saying anything about a player with that few of PAs.

That leaves us with the following Murderer’s Row – the starting eight along with Steve Lombardozzi. On to some pretty pictures, courtesy of the awesomely rad software Spotfire. The first five charts are stats (BA, OBP, SLG, OPS, BABIP, and RE24) by player, broken down by the three coaching states; I will leave you to peruse, and add some thoughts after your scroll through the data:

Batting Average

On Base Percentage

Slugging

OPS

BABIP

RE24

The biggest surprise looking at the data is the offensive outburst Jayson Werth has enjoyed – he is more than likely the main generator of the increase in runs per game under Schu and that appears to be driven by his ridiculous BABIP the last month or so (as determined by Eck_2 and Schu rates). Ian Desmond overall has had a consistent season and appears to be pulling out of a slump seen in his Eck_2 numbers; could it be a Schu driven intervention? Maybe.

Adam LaRoche seems to be scuffling a little more than his peers with Schu at the helm. He wasn’t having the most stellar of seasons in general, but some offensive hiccups right before Eckstein was fired seem to have been exacerbated by Schu’s arrival. A similar trend is seen with Ryan Zimmerman‘s output, with a negative RE24 seen in his at plate appearances with the new hitting coach. Lombardozzi seems to be hitting his stride with Schu, with both Wilson Ramos and Bryce Harper enjoying an overall positive effect of having Schu around. Knowing that this trio were Nats minor leaguers and have had previous exposure to Schu during his time as minor league hitting coordinator helps explain the possible ‘Schu Effect’ on these younger, home-grown guys.

This final chart is RE24 by coach, and is looking at things at the coaching level versus the player level. Overall, it gives us a quick and dirty way to look at the over effect of the coaching change across the season:

RE24 By Coach

While I leave you to make as many or as few inferences as you’d like with this chart, overall, we see a trend – the last two(ish) weeks of Eckstein and the first two(ish) weeks of Schu look about the same. We have roughly the same amount of guys under performing (a negative RE24) as performing, with a slight nod to Schu overall when comparing things to the final few games with Eckstein. Considering the half run increase in average run output under Schu, the data all jives well with one another.

Despite having our collective hands tied by the chains of sample size, what we have here is a mildly encouraging outlook for the rest of the 2013 season for the Nats bats. While Werth’s BABIP is unsustainable, we do see some players that appear to be on the cusp of breaking out a bit and stringing some good at bats together. While this encouraging outlook is too little, too late for Eckstein, can the same be said for the Nats playoff hopes?

RT for Yes, favorite for No.

Wake up and smell the RE24, Huey.

All data courtesy of Baseball-Reference.

Start-ing Over: Some Thoughts On Drew Storen

It’s never easy to have that closed-door meeting, whether you’re giving the bad news or the one receiving it. I won’t go into painful detail regarding the news of Washington Nationals reliever Drew Storen being optioned to Class-AAA Syracuse last night after a rough 24 hours that included battling the flu and an appearance against the New York Mets in a bit of a blowout which saw him giving up three earned runs and allowing two inherited runners to score in 2/3 of an inning that for all intents and purposes he had no business being a part of. To be honest, others have done a better job of explaining the gruesome details of Storen’s pitching performance that have sung out the S.O.S. that something was wrong, be it a mechanical flaw or otherwise.

No, for once, I am going to set aside that statistics and just wax unpoetic about what comes next.

OK, I can’t do it – I do have a couple of stats, I just can’t help myself; I promise to be brief.

No matter who he is, how nice he treated your niece, no matter when or how he was acquired, when a player does not perform, very tough decisions must be made; these are especially tough decisions when he is one of the faces of your franchise and one of your much heralded first round draft picks. It stinks. Yet, from a strictly baseball performance and productivity perspective, two saves in seven opportunities stinks, as does the 14.40 ERA in blown saves. A 1.49 HR/9 from a guy who pitched 51% of his appearances in games where his team was either up by one run, down by one run, or tied in the seventh inning or later isn’t cutting the mustard. It doesn’t inspire confidence.

However, let’s look at some numbers that make one feel that a little time away from the spotlight and in situations where a successful outing are in Storen’s favour:

Pitch Contact% Zone% SwStr%
Sinker 86.90% 64.20% 7.30%
Slider 69.30% 49.30% 10.90%
Fastball 82.70% 63.80% 9.20%
Changeup 61.20% 42.40% 22.40%

…and…

Courtesy of fangraphs.com

Courtesy of fangraphs.com

…as well as a strikeout to walk ratio of 3.31 this season – a little over 3 for his career – all tell us something. What, exactly?

Let’s start with the first table, which are Storen’s 2013 contact, zone, and swinging strike rates for his repertoire (thanks to Fangraphs). I don’t include his career rates in the table, but overall his 2013 rates are at or a little better than what he’s done over his career. In short, Storen’s ‘stuff’ is still good – he can miss bats and induce poor contact with his pitches.

OK, sounds encouraging, let’s talk about the second table – his PITCHf/x pitch values per 100, or his pitch linear weights. While there are caveats to looking at this data and then running off with exorbitant assumptions being made by using these values, they are useful with the sample size we have with Storen. While I don’t lend much merit to his 2013 values as being the ground truth, I look at these values more broadly – there are more positive than negative values. The point? Storen has at least three, maybe four, MLB above average pitches in his repertoire.

Add this to a very good strikeout to walk ratio, and we walk away a little more confident in Storen’s abilities and future…

…as a starting pitcher.

It doesn’t happen often, but there are situations where a guy like Storen – who spent has his entire collegiate and professional career as a reliever – can make the adjustment, get his arm stretched out, and become a starter. Hell, the Nats have a guy right now in AAA doing that exact same thing – Christian Garcia. While Mr. Garcia’s 2013 hasn’t been as healthy or productive as everyone had hoped, the fact he is down there and getting the chance to make the conversion from relieving to starting still bodes well for Storen. He is in an organization that still believes in him and is willing to let him make the change and redefine himself and his career.

It’s never an easy road back to the bigs, but hopefully with some of the numbers presented here, a small silver lining has been provided in what has been a stormy 2013 for Storen.

While the disappointment of 2012 may or may not still be looming over the former closer’s head, the ability to come back in a different role than the one that has defined his career and the public’s perception of his pitching talent could be panacea that everyone is looking and hoping for.

 

 

Dishing It Out – Pitcher Effects on Catcher Offense

There are few relationships in baseball more steeped in the concepts of symbiosis and reciprocity than the one between a pitcher and catcher. Most of the limelight and publicity of the relationship is aimed primarily at the pitcher and what the catcher can do to benefit the hurler, and for tacitly obvious reasons. For one, the game’s flow and cadence is set by the pitcher – no pitch, no game; the eyes of the viewerdom are locked in and at the mercy of the shake of the pitcher’s head in agreement with his catcher, allowing the start of his delivery. Then there is the general persona of the catcher – behind the mask and the ‘tools of ignorance’, there is typically a player who is more in tune with and proud of his less tangible accomplishments on the field more so than his offensive numbers.

It’s those offensive numbers that I look to dissect a little further and shed a little more light upon; in a relationship that is biased towards the pitcher, I would like to set things in reverse and take a look at how the pitcher possibly helps the offensive fortunes of his catcher. In a time where pitch framing skills, game calling abilities, and catcher’s ERA are used (in varying degrees of frequency) to describe the efforts a catcher takes to enhance his pitcher’s productivity, little time is taken to look at the reverse situation – what does a pitcher do to help out his catcher’s productivity?

While I confess that the answer is much more complicated than the efforts I am about to lay out for you here, I at least hope to set the table for a more harmonious and reciprocating conduit of discussion on the efforts that the pitcher-catcher battery provide one another.

So what am I doing here?

With the Washington Nationals as my statistical muse, I did some number tweaking, to see if there was some sort of effect a pitcher had on the catcher’s offensive output. The idea arose out of a habit that many Nats hurlers have – doing a poor job of holding runners on. While having runners on base is always a precarious situation to find yourself in as the defensive team, the Nats power arms and their very deliberate deliveries exacerbate the issue for the likes of Wilson Ramos and Kurt Suzuki.

So the question is posed – with this additional burden of having to control the running game without much help from the pitcher on top of the usual catcher duties, does a catcher’s hitting suffer?

Before I jump into numbers, let’s get some methods to the madness clarified.

I looked at Washington’s two primary catchers – Ramos and Suzuki – using Baseball Reference for some offensive and catching stats. Because of a small sample size, I chose to leave out the third member of the catching corps for the Nats – Jhonatan Solano. I also did a couple of other things in the name of simplicity – I threw out any games that saw both players get innings and I also looked at each catcher’s offensive numbers for a game as a whole, meaning that I made the assumption that the effect of a starter’s innings had more weight on what his final boxscore would look like than a relievers. In short, I made the leap of faith to say the catcher’s day at the plate, good or bad, is more affected by the starting pitcher more so than the reliever(s). A big leap of faith? Yes. But given this cursory look at the relationship, one I’m comfortable in making, just to get the ball rolling. Last, for stolen base values, I tallied up only those that were on the starting pitcher. So for a game like the one Suzuki had May 19, one which saw him give up five stolen bases, but only two while starter Dan Haren was on the mound, I gave him ‘credit’ for two stolen bases. More on that in a bit.

Thoroughly confused by my caveats and methodology? I thought so; let’s go look at some numbers.

The tables I present show some offensive stats as well as stolen base numbers, broken down for each catcher by starting pitcher. I also include each player’s season averages as a comparison. Each table is sorted by OPS.

Here’s what it looks like for Ramos:

W – L BA OBP SLG OPS SB CS CS%
Haren 2 – 4 0.048 0.091 0.048 0.139 3 0 0.0%
Strasburg 3 – 3 0.222 0.300 0.278 0.578 4 1 20.0%
Zimmermann 1 – 0 0.333 0.500 0.333 0.833 0 0 0.0%
Total, 2013   0.300 0.341 0.513 0.854 11 2 15.0%
Gonzalez 4 – 1 0.474 0.474 0.737 1.211 0 1 100.0%
Jordan 2 – 0 0.444 0.444 0.778 1.222 3 0 0.0%
Detwiler 1 – 0 0.500 0.600 2.000 2.600 0 0 0.0%

…and what it looks like for Suzuki:

W – L BA OBP SLG OPS SB CS CS%
Zimmermann 14 – 4 0.220 0.303 0.186 0.489 8 3 27.3%
Haren 1 – 9 0.194 0.256 0.306 0.562 4 0 0.0%
Detwiler 4 – 6 0.194 0.200 0.389 0.589 2 0 0.0%
Gonzalez 8 – 6 0.220 0.278 0.320 0.598 5 2 28.6%
Total, 2013   0.219 0.281 0.320 0.601 43 6 12.0%
Strasburg 3 – 5 0.241 0.267 0.414 0.680 6 1 14.3%
Jordan 0 – 2 0.500 0.625 0.667 1.292 0 0 0.0%
Karns 1 – 0 0.750 0.750 0.750 1.500 1 0 0.0%

Here’s where I give my usual ‘small sample size’ disclaimer – with the warning being particularly necessary for data on rookies Taylor Jordan and Nate Karns.

So what do we see? For both catchers, we see an interesting association with OPS and stolen bases – as swiped bags go up, down goes catcher OPS, our surrogate for offensive productivity in this exercise. Dan Haren outings seem to have a particular effect on both Ramos’ and Suzuki’s offensive numbers, while in a small number of starts, Jordan appears to do wonders for the bats of his backstops.

Looking at the stolen base numbers is a bit more tricky, simply due to sample sizes. However, we can grasp that with Strasburg on the mound, there appears to be more would-be basestealers, with the same situation being seen in Haren starts; however, Haren’s ability to help out his catcher by keeping runners close either by using an abbreviated delivery out of the stretch or by other means isn’t terribly successful (0% success rate for both catcher against base stealers). On the flip side, lefty Gio Gonzalez appears to do a respectable job of keeping runners honest, as most lefthanders tend to do.

Let’s take a quick look again at the relationship between OPS and SBs with the help of linear regression. If we do a quick regression of OPS against stolen bases, we get some interesting results. For Ramos, we get an R²,  or correlation of determination, of 0.34; for Suzuki, his R² comes out to be 0.58. While both are reasonably strong results, pointing to the potential that the running game has an effect on a catcher’s offensive game, Suzuki’s R² is surprisingly high. Yet, with such a small sampling of data, there is still a lot of possible noise in what we think might be signal. Even if we merge both player’s data, we get an R² of 0.36; nothing terrible, nothing great.

While these results are impugnable at best due to the way I assigned catcher at bats to a starting pitcher (who may or may not have been in the game when a particular at bat was taken), they do expose a couple of interesting points. One, Suzuki seems to be a little more affected offensively by the running game than Ramos; while neither has done an exceptional job of throwing out runners this season, by the looks of our data, Ramos seems to do a better job of not letting the defensive aspects of the game affect his offensive production. Also, each pitcher’s particular quirks have the potential to affect each catcher differently. Take, for example, Jordan Zimmerman. While known to be a quick worker and able to keep the running game at bay reasonably well by changing his looks to a runner and altering his cadence for each pitch, he appears to be downright poisonous to Suzuki’s hitting, as his .489 OPS clearly asserts. It is these idiosyncrasies that, while on the surface seems extraneous and negligible, go a long way towards defining the ultimate success of a particular tandem.

While the offensive contributions that a catcher brings to his team will always remain in the realm of ‘nice to have, but not at the cost of defense’, it is nonetheless an addition that can be accentuated by the efforts of his pitcher, especially with respect to the running game. This is by no means an exhaustive or painfully concise analysis of the relationship between an catcher’s offense while paired with a particular starter, but it is hopefully a reasonable start towards a better understanding the peculiar relationship between the pitcher’s arm and his catcher’s bat.

Splitting Hairs – Taylor Jordan

While I readily admit it can be a blessing and a curse, sometimes I incessantly nitpick at things and scrutinize them, occasionally doing so in a poorly timed fashion. It made me successful* in medicine and research at times, but it also gives people a misconstrued perspective of who I am, especially when I go on Twitter with my thoughts.

‘Why can’t you just be happy with ____?’

‘Are you physically capable of just watching the game?’

The answer to both is a resounding ‘no’, much to the chagrin of my wife.

My target of my well-intentioned ire and (over)analysis today?

Washington Nationals pitching prospect and current rotation member Taylor Jordan.

First, let’s get the good things out of the way – ranked as a Top 20 organizational prospect by both Baseball America and Baseball Prospectus, Jordan has done well, scoreboard be damned, in his brief dalliance as a National. Possessing a very good sinking fastball along with good and developing into very good secondary pitches, he tends to be erratic in the strike zone, but at 24 years old, has displayed scads of maturity and an ability to not let poor play behind him rattle him and shake him from his game. Let’s have a look at some of his major league stats, courtesy of Fangraphs:

Screen shot 2013-07-10 at 3.27.17 PM
Screen shot 2013-07-10 at 3.28.28 PM

The first figure shows us some of the usual statistical suspects – please don’t trouble yourself with the win-loss record – as well as some advanced stats that provide a better gauge of how well Jordan is doing independent of the circus going on behind him; in 15.2 innings pitched, the Nats have made three errors behind Jordan. Defense aside, Jordan is doing his part in keeping the Nats in the game by making hitters pound the ball into the ground, as his 55.2% groundball rate attests; his fielding independent pitching (FIP) is lower than both his ERA and expected FIP (xFIP), which speaks to his ability to keep scoring opportunities at a minimum just by himself (FIP < ERA), while also outpitching some of his peripheral stats and therefore, expectations (FIP < xFIP). While he hasn’t struck many folks out – 3.45 K/9, contrasted by his minor league career K/9 of 7.2 across all levels – he also isn’t walking many, which can offset his lack out strikeouts thus far in the bigs.

The second table lists Jordan’s PITCHf/x pitch values per 100, which is a rough, eyeball-it method of determining how effective a pitcher’s repertoire has been against hitters. The more positive a value, the more effective a pitch, with the opposite true with negative values. So far, Jordan’s slider (wSL/C) is his best pitch, with most of his other repertoire scoring well.

So far, so good, for both us and Jordan; if you’d like more ink to peruse, definitely check out John Sickels’ article at SB Nation. Now, let’s peel off another layer of this onion, and take a look at some visuals.

washington-nationals-v-philadelphia-phillies-20130710-003552-426

OK, next picture…

taylorjordan_wide

Hmm, OK. Next…

taylorjordan_close

Alright, we’re good with pics for the moment – let’s talk about Jordan’s arm slot for a second. It’s high – almost 90 degrees in the last two pictures, awfully close in the first one as well – and is what is considered a high cocked position. The good folk(s) at Driveline Mechanics have a great description of the high cocked position  – go check it out. Briefly, this slot is felt to generate the most potential for maximum velocity on your pitches in some circles. While it’s debatable if it really does provide much added velocity, it definitely can lead to injury, especially if the elbow is consistently cocked at an angle that exceeds level the shoulders – excessive scapular loading. Knowing that Jordan has already undergone one Tommy John surgery, we can see where possibly this extreme arm slot might not be the most advantageous, long-term. That being said, Jordan appears to keep his pitching elbow right at shoulder level, which is less worrisome.

Let’s go back to the first picture and the red circle. Notice his wrist and the ball with respect to the rest of his body and home plate? We have another Cobra; as mentioned before here at HDIB? with Shelby Miller, the Cobra move is not a biomechanically advantageous one, long-term. The extreme forearm pronation necessary to put your hand in this position can be taxing and create additional stresses on the forearm and up into the shoulder, but in particular, the brachioradialis, pronator teres, and pronator quadratus muscles of the forearm are at increased risk of fatigue and breakdown with this amount of pronation. This extreme positioning of the hand and wrist can also lead to timing issues, especially when fatigued, which again can lead to injury arising from a breakdown in proper mechanics. While his Cobra move is a tad different that the one seen in Miller, Jordan’s still bears mention as something that isn’t very mechanically favourable. That being said, this arm slot and positioning are possible tools to the success of his sinking fastball, as his very pronounced hand position over the top of the ball can provide additional vertical movement of the pitch. This extreme arm slot might also have already bit him in the butt, as he has already been told by teammates that he is tipping pitches; considering the slight change in angle in his arm slot in picture #1 (taken in his most recent July 9 start) versus pictures #2 and 3, it appears he has possibly countered the pitch tipping with a slightly lower arm angle at cocked position.

This is a nice segue to another negatively positive aspect of Jordan’s mechanics that works for him and against him – he has a very deceptive delivery and hides the ball well before release, which can add to his effectiveness. Much like his unorthodox arm angle helps, but also hurts (literally in some respects), Jordan’s lower half can sometimes betray him while also helping him.

Again, let’s have some visual evidence:

Taylor Jordan

Here we have a different view of Jordan and a bit of a glimpse of what the catcher and batter see. Here, we will focus on the lower body and I have taken the liberty to add some arrows to better describe an effective mechanical detractor – throwing across the body. The red arrow is the path his stride foot is taking with respect to his back leg and the black arrow is my best estimation using the odd camera angle and some landmarks in the picture of where he should be stepping at pitch release. While stepping across the body in a ‘crossfire’ style can be very effective at hiding the ball and thereby tricking the batter and slowing down his ability to recognize, identify, and track the pitch, it also can cause arm problems due to the arm path essentially blocked by the upper body, thereby creating increased stress and strain on the arm. With this in mind, it’s not a far-fetched to see how he is sometimes compared to Los Angeles Angels of Anaheim hurler Jered Weaver in regards to his deceptive delivery.

In a small sampling of innings, Taylor Jordan has started to meet and at times, exceed the lofty expectations set forth by the experts. While he is still young and still recovering from Tommy John elbow reconstruction – he is apparently on a 130 inning pitch limit this season – he does display some troubling habits that might hinder his progress and effectiveness in the future. While I wish I could be blissfully ignorant of these potential red flags in the spirit of a feel good story in the midst of a disappointing season thus far for the Nationals, my innate and annoying desire to pick apart these sorts of things in the name of knowledge leads me to remember the words of a mentor, who would patiently endure my mental gymnastics, with these words:

Great is the enemy of good.

For Jordan, the mechanics that have made him good could prevent him from becoming great.

*that’s debatable