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The Search for a Good Approach

Last week I explored the strategic effect of seeing more pitchers per plate appearance. I love the ten-pitch walk as much as the next guy, but what I love even more is seeing a guy be able to change that approach to beat a scouting report. Let’s take a look at June 5, 2014, when the A’s went to see Masahiro Tanaka for the first time. The first batter is Coco Crisp:

M. Tanaka
C. Crisp
Speed Pitch Result
1 91 Sinker Ball
2 90 Sinker Ball
3 91 Fastball (Four-seam) Ball
4 90 Fastball (Four-seam) Called Strike
5 91 Fastball (Four-seam) Foul
6 92 Fastball (Four-seam) In play, out(s)

So Crisp doesn’t get the best of Tanaka, but he makes Tanaka labor a bit through six pitches. If you’re going to make an out to start the game, it might as well be a long one. For the next batter, John Jaso, Tanaka decides to go right after him:

M. Tanaka
J. Jaso
Speed Pitch Result
1 90 Sinker In play, run(s)

I may be looking too deeply into the narrative here, but I love to imagine Tanaka getting a bit frustrated here. Perhaps the scouting report said that both Coco is aggressive early, while Jaso’s running 15% walk rates in 2012 and 2013 suggest that he’s more patient.  Tanaka has to throw six pitches in order to get Crisp out, but after deciding to go right after Jaso, he gets taken deep.

So I wondered if there are players who are able to fulfill both ends of this spectrum. Are there any players that are capable of prolonging their time at the plate until they see the pitch they want, but are also aggressive and willing enough to hit the gas on the first pitch? I used FanGraphs for the pitches/plate appearance data, but used baseball-reference’s play index to look up all instances of first-pitch hits this season. Originally I was going to use first-pitch swings, but I decided to just stick to times when the pitcher gets punished for trying to get ahead early. After all, if your decision is to get ahead early in the count, and the guy swings but all he does is foul it off or hit into an out, then that doesn’t change your approach as a pitcher. I wanted to see guys whom the book isn’t written on yet.  Advance Warning: These stats will be about a week old by the time you see them, as I am a slow, slow man.

Best P/PA Rank + FPH Rank (I have no idea how to pitch to them) FPH% P/PA FPHR PPAR FPHR + PPAR wOBA
Scott Van Slyke 5.940594059 4.143564356 26 45 71 0.385
Eric Campbell 4.2424242424 4.248520710 117 18 99 0.326
Jesus Guzman 4.294478528 4.17791411 111 33 144 0.247
Daniel Murphy 4.577464789 4.111842105 87 58 145 0.305
Joey Votto 4.044117647 4.334558824 135 12 147 0.359
Mark Reynolds 5.037783375 4.0375 59 91 150 0.307

(For Reference: FPH% = First Pitch Hit Percentage, or how often a batter gets a hit on the first pitch they see.  P/PA = Pitches per Plate Appearance. FPHR = First Pitch Hit Ranking, or how they rank in this category compared to the rest of the league.  PPAR = Pitches per Plate Appearance Ranking.  FPHR + PPAR = The addition of these two numbers.)

I like this table!  I have wondered at times what has caused Scott Van Slyke‘s resurgence this year. Perhaps this table gives us a bit of a clue.  Van Slyke is the only person in the MLB to rank in the top 50 in both FPHR and PPAR.  That’s pretty neat.  Daniel Murphy is also quite balanced, but he’s been much more consistent over the last few years.  He’s particularly interesting in that he doesn’t have a particularly high walk rate or strikeout rate.  I guess he’s just selective at times.  Jesus Guzman‘s presence on this list goes to show that a good approach doesn’t necessarily mean success; it just means that he may not head back to the bench in any predictable fashion.  I stretched out the table one spot to include Mark Reynolds, because his name on this table makes me feel better about drafting him in Fantasy Baseball for past five years.

I also wanted to look at the flip-side.  Who are the guys who don’t tend to take a lot of pitches, but also don’t tend to make any decent contact on first pitches?

Highest P/PA Rank + FPH Rank (Pick your poison) FPH% P/PA FPHR PPAR FPHR+PPAR wOBA
Joaquin Arias 0.6451612903 3.55483871 370 400 770 0.221
Ben Revere 1.629327902 3.563636364 365 368 733 0.307
Endy Chavez 0.9345794393 3.674311927 321 393 714 0.301
Conor Gillaspie 2.168674699 3.587112172 359 329 688 0.353
Jean Segura 2.564102564 3.42462845 396 289 685 0.262

Here we have a much less impressive list.  Joaquin Arias has been one of the worst hitter in the majors this year, and his dominance atop this leaderboard makes a bit of sense.  However, Conor Gillaspie is having an excellent season for the Pale Hose, despite the fact that he doesn’t seem to excel in either of the areas this article is interested in.  One pecuilar note is that this group is pretty poor at hitting for power in general; these 5 guys have 13 home runs between them on the year, and six of those are Gillaspie’s.

So now let’s look at the weird ones.  I would think that it stands that if there are certain players who tend to take a lot of pitches and who also never seem to square up the first pitch, then we know our game plan.  Get ahead early on these batters.  We can try to view that by simply looking at each players FPH Ranking minus their PPA ranking.  This is the same at looking at the absolute value of their PPAR minus their FPAR.  Here are the top five in that respect:

Worst in FPHR, Best in PPAR (Groove it Early) FPH% P/PA FPHR PPAR FPHR-PPAR wOBA
Jason Kubel 1.136363636 4.471590909 387 4 383 0.278
Aaron Hicks 0.641025641 4.224358974 401 21 380 0.286
Mike Trout 1.217391304 4.418965517 385 6 379 0.401
Matt Carpenter 1.376936317 4.357264957 380 8 372 0.343
A.J. Ellis 1.181102362 4.255813953 386 17 369 0.264

Golly; I’ve figured out Mike Trout!  Mike Trout ranks very highly on our list of PPAR but is unfortunately relatively average when it comes to the first-pitch punish.  All of these guys actually fit this mold.  We have three relatively poor hitters accompanied by the best player in baseball and an above average infielder on a winning team.  So we can tell that being patient isn’t necessarily a good or bad thing; it’s just that hitter’s style.  Now let’s take a look at the reverse:

Best in FPHR, Worst in PPAR (Don’t throw it in the zone early) FPH% P/PA FPHR  PPAR PPAR-FPHR wOBA
Jose Altuve 8.159722222 3.175862069 5 407 402 0.355
Wilson Ramos 7.169811321 3.293680297 6 405 399 0.327
Erick Aybar 6.628787879 3.347091932 12 401 389 0.312
Ender Inciarte 8.360128617 3.471518987 3 391 388 0.284
A.J. Pierzynski 6.413994169 3.391930836 16 399 383 0.283

It’s always satisfying when the data shows what you expect it to.  I imagined Jose Altuve as being among the more aggressive hitters, and this shows that at least.  Altuve ranks 5th in the league in FPH% and is rather mediocre in the PPA category.  Interesting to see that this top five is also sorted by wOBA; Altuve is the best hitter on the list, and Pierzynski is the worst.  So there’s nothing necessarily wrong with an aggressive approach, but it does give us a clue as to a possible plan of attack.

So all this is to say, like my last article, that no particular approach is best.  One can look to swing at the first pitch, or one can be patient and wait for their pitch to come.  That said, everybody does have an approach, and that means they’ve got something they’re not looking for.  Stats like FPH and PPAR may just give us more clues as fans as to what teams put together with scouting reports.

So to conclude by going back to our first example, perhaps Tanaka should have read this data before his start against the A’s.  Coco ranks 266th in the league in FPHR, but a respectable 76th in PPAR.  Conversely, Jaso ranks 80th in the league in FPHR, but just 225th in PPAR.  Tanaka might have been better served by going after the aging Crisp and saving his energy for the somewhat aggressive Jaso.

Pitches Seen: Baseball’s Boring Inefficiency

I think I might be the biggest fan of the world of the Ten-Pitch Walk.  I don’t know why, but I get overly excited when I see a player really battle for a long time, against everything the pitcher has, only to win the battle through patience.  Perhaps it’s because it’s so contrary to the spirit of what’s actually exciting about baseball; seeing players run around and field a batted ball.  It’s wholly a battle of attrition.  It’s the baseball equivalent of watching somebody run a marathon; you may not think the act itself is exciting, but it’s certainly an impressive feat in a vacuum.

So this has also lead to a fascination with pitches seen per plate appearance.  I’ve long wondered if certain teams place an emphasis on teaching their players to see more pitches per plate appearance.  It seems fairly self-evident that seeing more pitches is, in a microcosm, better than seeing fewer pitches.  You tire the pitcher out quicker, you see more data for your next at-bat to work with, and you give your team a chance to see what the pitcher has, and how he’ll react in different situations.  I hypothesized, purely based on colloquial wisdom, that the A’s would be good at this and the Blue Jays would be bad at this.  That’s not to say that one approach is better than the other, but just that some teams seem more patient than others.

Fortunately, FanGraphs has data available per hitter as to how many pitches they see.  I pulled that data out and found out each player’s average pitch per at bat since the year 2003 (the earliest we have this data, from what I can tell) and restricted the findings to active players only.  Then I ran some regressions to see if there was any correlation between pitches per at bat and useful batting stats.  Here’s what I found:

We see a slightly positive correlation between P/PA and wOBA.  It’s not really anything to write home about, but it’s more than negative.  It doesn’t seem immediately that seeing more pitches relates heavily to overall performance at the plate.  What about on base percentage?

Slightly better here, but still not great.  Seeing more pitches does have a little more correlation to getting on base, but there are plenty of aggressive swingers that don’t follow that model, so it means the correlation is loose at best.  What if we talk just about taking walks?

Here we have a real correlation.  .59 is a fairly strong correlation, and that makes sense.  The more pitches you see, the more likely you are to take a walk.  If you can successfully foul off anything in the strike zone, you will eventually walk (or the pitcher will die of exhaustion, either way, you win).  This is reasonably useful.  If you’re trying to find a way to make your team walk more, maybe you can invest in some players that see more pitches per plate appearance than normal.  This strong of a correlation makes me think about strikeout percentage too, though, because every pitch you foul off makes you closer (or just one whiff away) from striking out.

There is a positive correlation here, but not nearly as strong as between BB% and P/PA.  It’s stronger than the other useful stats like wOBA, but it’s interesting to know that seeing more pitches relates much more strongly to taking a walk than it is to striking out, at least on a grand scale.  There is some research to be done here to see what the odds are of a plate appearance as the pitch count increases, but I’ll leave that for another day.  My next thought was to see if there are, in fact, any teams that are better at this than other teams.  Here’s what we’ve got on a team level:

1 Red Sox 4.0506764011
2 Twins 4.0396551724
3 Cubs 3.9222196952
4 Yankees 3.9142662735
5 Pirates 3.9037861915
6 Astros 3.9028792437
7 Padres 3.9021177686
8 Mets 3.9009743938
9 Marlins 3.8916836619
10 Indians 3.8914762742
11 Athletics 3.8899398108
12 Phillies 3.8839715662
13 Blue Jays 3.8685393258
14 Cardinals 3.8634547591
15 Rays 3.8511224058
16 Rangers 3.8489497286
17 Dodgers 3.8480325645
18 Tigers 3.8314217702
19 Angels 3.8280856423
20 Diamondbacks 3.8161904762
21 Nationals 3.8146927243
22 White Sox 3.811023622
23 Giants 3.8038379531
24 Reds 3.8015854512
25 Orioles 3.8014611087
26 Braves 3.7944609751
27 Mariners 3.7358235824
28 Royals 3.7310519063
29 Rockies 3.7244254169
30 Brewers 3.6745739291

Well, my original hypotheses were not great ones.  The A’s and the Blue Jays, at 11 and 13, are both decidedly middle of the road teams.  I find it most fun in times like this to look at the extremes; in this case, the Red Sox and the Brewers.  The difference in pitches seen per plate appearance between these two teams is 0.38.  That may seem small, but it adds up.  If we assume the average pitcher faces 4 batters per inning, that’s an additional 1.5 pitches per inning, and 9 pitches by the end of the sixth, just purely by the nature of the hitters.  In a tightly contested contest, that may mean the difference between getting to the bullpen in the 7th rather than the 8th, or even the 7th rather than the 6th.

It should be noted that I limited this data set to 2014 (in contrast to the earlier data which was 2003 onwards) just so we could get a realistic look at roster construction, and to see if any teams are, right now, putting any particular emphasis in this area. The BoSox are carried by the very patient eye of Mike Napoli (4.51 P/PA), but hurt by the rather hacky eye of AJ Pierzynski (3.42 P/PA). Even on one team, that’s more than a pitch per plate appearance, which is pretty startling. The Brewers don’t have nearly the same difference; their best is Mark Reynolds with 4.04 P/PA and their worst is Jean Segura with 3.42 P/PA. As an aside, Chone Figgins is by far the best in this with a whopping 4.99 P/PA, though it was in just 76 PA. Kevin Frandsen brings up the rear with 3.16 P/PA in 189 PA. A lineup of all Mike Napoli‘s would see 24.3 more pitches than a lineup of Kevin Frandsens before the leadoff Napoli even comes up a third time. I would feel bad for that pitcher.

The talk about teams possibly emphasizing this data made me wonder if I could make a huge difference if I compiled a team solely to do this; just make sure the pitchers throw a ton of pitches.  With that, I present to you the 2014 All-Stars and Not-So-All-Stars in this area, with a PA minimum thrown in to eliminate Figgins-like outliers:

All-Stars P/PA wOBA
C A.J. Ellis 4.344444444 0.311
1B Mike Napoli 4.353585112 0.371
2B Matt Carpenter 4.20647526 0.362
3B Mark Reynolds 4.179741578 0.341
SS Nick Punto 4.033495408 0.293
LF Brett Gardner 4.305959302 0.332
CF Mike Trout 4.219285365 0.404
RF Jayson Werth 4.399714635 0.364
DH Carlos Santana 4.297962322 0.356


Not-So-All-Stars P/PA wOBA
C A.J. Pierzynski 3.33404535 0.32
1B Yonder Alonso 3.603264727 0.318
2B Jose Altuve 3.266379723 0.321
3B Kevin Frandsen 3.41781874 0.296
SS Erick Aybar 3.415445741 0.308
LF Delmon Young 3.450895017 0.321
CF Carlos Gomez 3.517879162 0.321
RF Ben Revere 3.544046983 0.296
DH Salvador Perez 3.366071429 0.331

Despite the fact that there isn’t a strong correlation between wOBA and P/PA directly, it’s worth noting that the P/PA All-Stars are significantly better than the Not-So-All-Stars. Their difference in wOBA is .328 as compared to .314. The Not-So-All-Stars certainly present a fine lineup though; the All-Stars just have the benefit of having Mike Trout in their lineup. It’s nice to know that this is one other area that Mike Trout simply is amazing at, confirming the obvious. The All-Stars have a collective P/PA of 4.26, while their counterparts sit down at 3.43. That’s .83 pitches per plate appearance, which over the course of two turns through the lineup is 14.94 pitches; that’s definitely something notable.

So, it appears this is a demonstrable skill with some value, though not a ton. We can see that some teams are better at this than others, and we see some positive benefit from this, most notably in walk rate. While we see plenty of players on both sides of the scale who are excellent ballplayers, the data does seem to suggest that seeing more pitches is better than not doing so, though only marginally on a league wide scale. When we isolate leaders in this area vs. those more aggressive, we can see some startling differences though, suggesting that perhaps there is an advantage to be gained here.

The A’s Declining Offense

Take a turn around Twitter or any major baseball news source and you’ll hear a familiar echo about the former best team in baseball; the offense hasn’t been the same since the deadline.  When the A’s traded away Yoenis Cespedes for Jon Lester, the impact to the lineup was noticeable.  They wagered they could get the same level of production out of some combination of Jonny Gomes, Stephen Vogt, and Sam Fuld.  In the first half of the season, the A’s were a top-six team in wOBA, OBP,and wRC+ all while being second to last in BABIP.  It’s safe to say they were rolling. Now they aren’t.  Since the deadline, the A’s have become a bottom-third team in all the aforementioned stats.  It’s easy to look at these stats and say that Cespedes was clearly the catalyst of something in the offense.

While much has been written about the rumors of Oakland emphasizing clubhouse chemistry the last couple years, Cespedes has never really been written as one of the chief leaders in that category.  We typically hear names like Coco Crisp, Scott Sizemore, the aforementioned Jonny Gomes, and Sean Doolittle mentioned there.  Cespedes by all accounts was just a crazy athletic guy who didn’t really cause any trouble, but wasn’t exactly a team leader.  Yet the fact remains: the A’s have refused to hit since the deadline. Sure, 17 games isn’t a gigantic sample size, but it’s pretty reasonable when evaluating team performance.  Baseball Prospectus just three years ago theorized that a reasonable prediction could be made of a team’s overall season after fifteen games,  so we’ve got something substantial to work with.  Is there another pattern, though?  Let’s take a look at the team’s month by month performance.

April 0.339 119 25.2 7.3
May 0.330 113 15.6 5.8
June 0.314 102 2.6 4.1
July 0.312 100 0.2 3.4
August 0.288 84 -11.1 1.5

We see a steady decline here in the A’s performance, not a sudden jump.  The A’s started off really hot, leading the league in most offensive categories in April.  A notable decline can even be seen in May, as the A’s began their meteoric rise to the top, though they held steady in the top three in most categories.  In June, the team dipped even further, down to a mark that was only slightly above average.  They looked to be leveling off there to a rather league-average team in July, which wasn’t encouraging, but maybe suggested a possible rise back up to looking like a playoff team. In August, though, the wheels have come off.  The A’s have dipped below league average in most categories, and their win totals have suffered as well.  Can we blame all of this on Cespedes?  Let’s take a look at some wOBA numbers for chief contributors to the Oakland offense:

It’s a bit cluttered, but the dark blue line in the middle labeled wOBA is the team as a whole; see the steady decline as we’ve noted.  In April, we see all of these guys hovering between a .300 wOBA and somewhere above .420.  Nearly all of them are now either .300 or far below it; the one exception being Josh Donaldson, who has picked it up again since a dismal June.  Even Cespedes, having been traded to the Red Sox, is having an unremarkable August since performing poorly in July.  Let’s take a look at a wRC+ graph, with some of the members removed for clarity:

Here we see six players who routinely batted in the top five in the batting order having horrible Augusts.  Stephen Vogt and Brandon Moss, two lefty platoon bats being pressed into full-time duty in the outfield lately, lead this group with a 91 wRC+, which is below the average line.  John Jaso, Coco Crisp, and Derek Norris have been downright horrible, with wRC+’s in the barely digestible territory. So yes, the A’s have been bad since Cespedes has left the team.  It’s clearly not just the loss of his bat; the vast majority of the team, outside of Josh Donaldson and the surprisingly resurgent Eric Sogard and Josh Reddick, have been really, really bad.

So if the whole team is flailing, perhaps Cespedes was more of a sparkplug than we previously had attributed?  More importantly, did Billy Beane fail to see a trend here?  The A’s were trending downwards in hitting as demonstrated, so why the need for pitching?  Well, the A’s were unfortunately not exactly trending very well in pitching either.  They were third in pitcher WAR through April, but then plummeted to 19th in May, and further dipped to 21st in June before rising a bit to 17th in July. The A’s were a decidedly middle of the road team when it came to pitcher WAR, and FIP seems to agree, ranking them about the same spot everywhere.

So why make the trade?  If anything, this trade has only served to confuse fans.  What do we make of a team with three above-average catchers who all tank right after a trade for a top-flight starting pitcher?  While all the fans are clamoring for Jimmy Rollins to come and help the middle infield, we’ve got Eric Sogard being one of the few bright spots in the offense, and nobody seems to care. All we know is that the A’s are in trouble.  Whether it’s because Cespedes was the glue or because the A’s are peaking at the wrong time, they’re all of a sudden facing down the dire straits of a one-game coin flip at the end of the season, despite being the most aggressive pursuer at the trade deadline. The A’s can cling to a few bastions of hope; maybe their BABIP dropping all the way to .260 in August shows that they’re just a bit unlucky.  It’s either that or face the fact that sometimes the best-laid plans of mice and men fail, and pray that Jason Hammel doesn’t have to start the Wild Card game.