Archive for July, 2013

Jason Marquis, Expectations, and Reality

On the surface, Jason Marquis looks like he’s having a good season. He’s 9-4 with  a 3.77 ERA for the San Diego Padres and if you’re looking at how well his team performs collectively during his starts and how effective he has been at limiting runs, you might even say Jason Marquis is having one of the best seasons of his career. If you look more closely, however, he’s actually having one of the worst seasons in baseball history.

That’s a crazy juxtaposition. We’re used to evaluating players by advanced statistics like FIP, xFIP, WAR, and others, but it’s pretty rare that they tell us something totally different from the basic descriptive stats. Usually we look at a player’s FIP and think their ERA might be due for some regression. We don’t often look at a player’s FIP only to find that their ERA is propped up with toothpicks and Scotch tape.

Such is the case with Jason Marquis. His numbers this season are actually quite remarkable. He’s 48th among qualified starters in ERA, good for an ERA- of 104, which is just a bit below average. If you turn to FIP, he’s dead last at 5.70, good for a 156 FIP-. His xFIP is better, but it still remains fourth-worst in MLB at 4.77 to go along with an MLB-worst 125 xFIP-.

No qualifying starter’s ERA is outperforming their FIP as much as Marquis’ is this season. Jeff Locke and Jeremy Guthrie are in the conversation, but Marquis is decidedly ahead. Perhaps even more noteworthy is that Jason Marquis’ 156 FIP- is the second-worst number for a qualifying starter since 1901, and the record is within reach at 159.

Marquis is essentially having an all-time worst season in terms of strikeout rate, walk rate, and home-run rate when adjusting for park and league average. Yet he’s allowing a very average number of runs in a very respectable number of innings. Only two players in history have had their FIP- outperform their ERA- by more than Marquis’ difference of 52 and they both played before 1910.

I don’t mean to belabor Marquis’ 2013 season among the all-time clunkers in MLB history, but rather to simply set the stage for the remainder of this analysis. Marquis is doing a pretty decent job preventing runs, but is doing a terrible job at the aspects of preventing runs a pitcher can most control. What’s going on here?

First, let’s consider the Padres defense. By DRS, UZR, and UZR/150, the Padres rank between 15th and 21st in MLB this season. They aren’t a terrible defensive team, but this doesn’t appear to be a club that should systematically deflate their pitchers’ ERA. It’s possible that they are playing amazing behind Marquis and not for everyone else, but that seems unlikely. If you consider the Padres starters as a whole, their ERA is higher than their FIP and have individual starters on both sides of the divide. Additionally, it doesn’t appear as if any of this can be explained by the GB/FB ratio of each pitcher, which might have pointed to a particular aspect of the Padres defense.

Sometimes it’s just about the situation, but on the surface it doesn’t look like this is a good explanation either. Marquis allows a .318 wOBA with the bases empty to go with a .380 wOBA with men on and a .306 wOBA with men in scoring position. He’s more or less the same pitcher with men in scoring position as he is with no one on so pitching from the windup versus the stretch isn’t the answer. Let’s look at each base situation.

Split PA BA OBP SLG
294 0.225 0.320 0.395
1_ _ 78 0.422 0.500 0.656
_ 2 _ 32 0.269 0.406 0.385
_ _ 3 5 0.200 0.200 0.200
1 2 _ 39 0.188 0.316 0.344
1 _ 3 15 0.222 0.429 0.556
_ 2 3 10 0.000 0.500 0.000
123 18 0.143 0.222 0.214

Obviously, some of the samples are really small, but notice how much worse Marquis is when a runner is on first base, but not also on second base. Could this have something to do with holding the runner? A couple of possibilities spring to mind. One, Marquis is distracted by the baserunner. Two, having the first baseman holding the runner creates a hole where Marquis often allows hits. Three, the presence of the baserunner and location of the runner cause Marquis to pitch differently in order to avoid the hole on the right side, resulting in pitches that get smashed. I’m not sure if any or all of these are factors, but they are possible factors. If something like this is the case, it’s possible that Marquis isn’t actually as bad as his FIP tells us overall, but rather just really terrible in certain situations and reasonably average most of the time.

Some of this timing argument is dispelled if we consider that he’s actually allowing a higher percentage of his home runs with men on base (48%) than league average (40%) so his high walk rate and high home-run rate should be costing him dearly. But they are not. Marquis is pitching like he should allow close to 6 runs per 9 innings but he’s allowing fewer than 4.

His strikeout rate is 12th-worst in baseball at 14.7% and his walk rate is easily the worst at 13.2%. Only 1o pitchers have a higher HR/9. Yet he’s right around league average in ERA. Metrics like SIERA don’t rate him any better, as he comes in 2nd-worst at 5.11.

He shouldn’t be doing this well. He’s leaving runners on base like he’s Felix Hernandez, but walking guys like he’s Carlos Marmol, giving up home runs like Jose Valverde, and only striking guys out like he’s Bronson Arroyo. He’s getting a lot of ground balls, but he has a low BABIP against.

If you look at Lucas Harrell and Jason Marquis, most of the stat line is nearly identical.

Name IP K/9 BB/9 HR/9
Jason Marquis 112.1 5.77 5.21 1.44
Lucas Harrell 108.1 5.57 4.74 1.25

 

Name BABIP LOB% GB% HR/FB
Jason Marquis 0.256 79.70% 53.20% 19.60%
Lucas Harrell 0.304 70.40% 52.70% 16.00%

 

Name ERA FIP xFIP WAR
Jason Marquis 3.77 5.70 4.77 -1.4
Lucas Harrell 5.07 5.37 4.78 -0.3

If anything, based on K/9, BB/9, and HR/9, Harrell should be doing better. But somehow, Marquis is getting a much lower BABIP and a higher LOB% despite getting pretty much the same number of ground balls and having a worse HR/FB rate. They have essentially identical xFIP and Marquis has a worse FIP. The fact that Harrell has a 5.07 ERA and Marquis has a 3.77 ERA defies understanding (the story is the same with park-adjusted numbers).

This is likely just one of those small sample size mirage/miracles. Marquis has lost a tick on his fastball this year and his changeup is acting more like a splitter according to Pitch F/X, but nothing appears fundamentally different that would allow him to actually sustain this low BABIP (last year it was .311). Perhaps baseball fans who watch the Padres more regularly can offer some insight into what exactly is the driving force behind his low BABIP this season.

If you’re someone who likes to look at FIP, you’re looking at one of the worst seasons in baseball history. If you’re someone who cares more about overall run prevention, you’re looking at an average year. Granted, it’s not uncommon for a player to over or under perform their peripherals over 100 innings, but it is amazing how dramatically it is happening for Marquis.

It’s not unusual for BABIP to drive over- and under-performances by 20 or so points in on the ERA/FIP- scale, but what Marquis is doing is beyond the typical variation. For every qualifying season since 1901, the mean FIP-/ERA- differential is around 2.3 and the standard deviation is about 13.8. Marquis’ 2013 season is 3.6 standard deviations above the mean. (For just 2013 those numbers are a mean of 1.3, SD of 17.6, and Marquis is 2.8 SD above the mean)

The simple takeaway of this entire exercise is this. Jason Marquis is over-performing his peripherals this season and there isn’t a clear explanation for why this might be the case other than standard variation in BABIP. It’s a perfectly reasonably explanation. Marquis is getting some good fortune regarding where baseballs have been hit during key moments that have allowed his ERA to stay relatively low despite the fact that based on his other numbers it should be much higher. That happens. What is so amazing about this is the degree to which it is happening.

We’re all open to the idea that some players will over- and under-perform, but Marquis is over-performing at such a rare level. He’s in the top 0.25% of all over-performances when comparing ERA- and FIP-, which are statistics that control for league average and park effects. When you strip away the context, Jason Marquis’ 2013 season stands out as the third-biggest over-performance in the last 113 years, which includes more than 8,000 individual seasons.

Everything I know about baseball tells me Jason Marquis won’t maintain this ERA if he maintains these K, BB, and HR levels, but part of me is really hoping that he does. I like when things make sense and can be easily explained, but sometimes it’s a lot of fun to watch a player defy the odds for no other reason than that the Gods of probability have chosen that player to be the exception that proves the rule. Jason Marquis and Padres fans are  hoping he can keep it up. Anything can happen, but as we should note, it usually doesn’t.


A Defense of Jay Bruce

As a Jay Bruce owner and sympathizer — or maybe that’s Jay Bruce-owner sympathizer — I feel compelled to at least take a half-hearted hack at Dave Cameron’s trade value rankings.

While I’ve agreed with his rankings thus far — not that my assessment means much to anyone other than me — I must at least challenge Mr. Cameron on his omission of the mighty Bruce.

To be fair, Cameron spent just a couple of sentences on the Cincinnati slugger in his Just Missed the Cut post, so a detailed reasoning wasn’t available. Regardless, I spent some time looking through Bruce’s numbers in an attempt to craft a credible, albeit tentative argument against his exclusion.

Here’s what I found:

Truth be told, the Reds outfielder has not done a whole lot to help his cause recently. While his power numbers remain streakily Brucian, they do not make up for his sliding peripherals: His strikeouts are way up. His walks are way down. His good-not-great batting average is buoyed by a career-high and likely unsustainable BABIP, and his defense has gone from Gold-Glove caliber to doesn’t hurt to have him out there.

So, what reasoning could I possibly have to combat that mountain of evidence? Well, let me channel my inner Hawk Harrelson and talk about Bruce and The Will to Win … Don’t stop reading! I was just kidding!

Bruce’s value truly begins with his durability. From 2010 to the 2013 break, he has played in more than 95 percent of Cincinnati’s scheduled games, almost 10 percent more than Cameron’s No. 50 — I told you this was tentative — Austin Jackson and +10 percent more than No. 43 Jason Heyward

I know 10 percent doesn’t seem like a whole lot, but when the Tigers and Braves have to plug in replacement level players like Andy Dirks and Reed Johnson for a month, the loss stings.

Complementing Bruce’s durability is his age. Despite six seasons in the bigs, he turned 26 years old a few months ago, and it can be argued he has yet to enter his peak years.

I’m not trying spin any yarns about the mythical breakout of players turning 27, but I am saying Baseball-Reference lists Reggie Jackson as Bruce’s No 1. comparable player through their age-25 seasons. A quick look back at the HOF’s numbers tells us it took him quite a few years to get those strikeouts under control.

Maybe Bruce never will, and maybe he, as many predict, becomes Adam Dunn (No. 7 on the same list), but let’s not be so quick to dub him Big Donkey Part Deux just yet. He still has plenty of time to right the ship and develop into a more well-rounded player.

Finally, Bruce’s contract is relatively team-friendly, considering the two-time All-Star has been in the majors in this his sixth season. This year, he’s a bargain at $7.5 million, and while his contract jumps to an average of about $12 million per season for the next three — and a team-controlled fourth — years, that’s not out of line for what sluggers of his caliber are paid.

Consider No. 45 on Cameron’s list, Edwin Encarnacion (breakout age, 29, by the way), whose track record is essentially 2012, is making about $10 million the next three seasons.

So, are these factors and his strong counting numbers evidence enough for Bruce’s inclusion on Cameron’s list? Maybe. However, more convincing arguments admittedly could be made for Max Scherzer and Jordan Zimmerman.

But without a doubt, Bruce is a fringe top-50 trade value player; his durability, youth and contract certainly warrant the debate, if not a spot on Cameron’s list.


Yoenis Cespedes: Worst to be Best in Home Run Derby

On Monday night, Yoenis Cespedes became the 26th player to win Major League Baseball’s Home Run Derby, joining the ranks of such elite power hitters as Barry Bonds, Mark McGwire, Ken Griffey Jr. and … Wally Joyner.

Cespedes edged Bryce Harper in the finals and put on one of the most impressive performances the Derby has seen, starting off by hitting 17 home runs in one round and hitting 32 overall, both feats which tie for third-best in the Derby’s history.

This year’s lineup featured, as it always does, some of the game’s premier power hitters, including robot humanoid Chris Davis and two-time Derby champ Prince Fielder.

Behold, a fully functional (however unsortable, to the great dismay of the author) table of this year’s Home Run Derby participants and some relevant first-half batting/power statistics:

 

Player G PA HR ISO wOBA wRC+
Chris Davis 95 393 37 .402 .458 193
David Wright 90 399 15 .225 .389 154
Michael Cuddyer 74 317 16 .239 .409 149
Bryce Harper 58 242 13 .259 .381 145
Robinson Cano 95 409 21 .266 .351 127
Pedro Alvarez 85 334 24 .266 .351 127
Prince Fielder 94 422 16 .190 .355 123
Yoenis Cespedes 79 341 15 .195 .307 94

American League captain Robinson Cano was given the liberty of choosing three men to represent his team in the world’s annual derby of batsmanship, and he chose Cespedes. An interesting choice, as Cespedes has not been even a league-average hitter this season according to wRC+, but probably not one unwarranted through the eyes of Bud Selig as Cespedes taps into the Cuban market and is still one of the game’s more exciting young players.

And so, in the true nature of sport, Cespedes – the most unlikely of victors given his struggles this season – went out and won the whole damn thing.

Upon Cespedes’ win, I naturally went to his FanGraphs page and noticed his wRC+ was under 100, provoking me to silently think to myself: “I wonder if any other Home Run Derby champion failed to be even a league-average hitter at the time of his crowning?”

Behold, a fully functional and regrettably still unsortable table, this time of past Home Run Derby winners and their relevant first-half batting/power statistics:

 

Winner Year G PA HR ISO wOBA wRC+
Luis Gonzalez 2001 87 388 35 .391 .483 192
Frank Thomas 1995 66 305 21 .333 .472 189
Prince Fielder 2009 88 387 22 .299 .442 174
Jason Giambi 2002 86 381 22 .283 .438 174
Ken Griffey Jr. 1994 87 383 33 .368 .453 172
Cal Ripken 1991 80 353 18 .248 .433 172
Juan Gonzalez 1993 75 316 23 .317 .438 171
Mark McGwire 1992 87 368 28 .321 .419 170
Ken Griffey Jr. 1998 88 395 35 .380 .436 165
Barry Bonds 1996 86 385 23 .276 .422 162
Ryne Sandberg 1990 83 370 24 .272 .427 161
Ken Griffey Jr. 1999 85 384 29 .310 .425 156
Tino Martinez 1997 84 376 28 .317 .411 151
Bobby Abreu 2005 89 397 18 .220 .409 148
David Ortiz 2010 74 305 18 .299 .398 145
Vladimir Guerrero 2007 85 368 14 .222 .398 144
Garret Anderson 2003 92 388 22 .281 .394 144
Justin Morneau 2008 95 412 14 .189 .386 138
Sammy Sosa 2000 86 394 23 .269 .399 135
Prince Fielder 2012 86 371 15 .206 .373 135
Robinson Cano 2011 87 368 15 .225 .368 129
Ryan Howard 2006 84 352 28 .304 .380 125
Miguel Tejada 2004 85 341 15 .195 .364 121
Yoenis Cespedes 2013 79 341 15 .195 .307 94

The answer is no, and it really isn’t even close.

Since the Derby changed to its current format in 1990, no winner has been within 20% of being “just” league average, and a full 57 points of wOBA separates Cespedes from Miguel Tejada’s 2004 first-half campaign.

In fact, Cespedes is only the fourth player to have entered the Home Run Derby as a below-league-average hitter. That’s right, even in the years that Hee-Seop Choi and Damion Easley competed, they had been at least league-average.

In 2005, Ivan Rodriguez had a wRC+ of 97, Rafael Palmeiro came in at 96 in 2004 and you have to go all the way back to 1994 for Ruben Sierra to “top” Cespedes with a first-half wRC+ of 92.

Interestingly enough, they all performed fairly well in the Derby, despite walking away as losers – or, not winners. Each advanced past the first round, with Pudge finishing runner-up to Bobby Abreu’s monster performance. Palmeiro and Sierra each took third.

Similar to how people say the Derby can throw locked-in power hitters into second-half slumps, maybe it can also get struggling power hitters into a groove again. Probably not, but it was an intriguing observation nonetheless.

Robinson Cano had to choose three men to represent his team of lumber swingers to hit dingers, and he threw caution to the wind by choosing Yoenis Cespedes, who had a worse first half at the plate than Cano’s teammate Lyle Overbay. But this wasn’t a first-half regular season baseball game and Yoenis Cespedes doesn’t play first base for the New York Yankees (and now apparently sometimes right field, too). It was the Home Run Derby, and Yoenis Cespedes reaffirmed Robinson Cano’s bold choice by making history.


Trade Chris Sale? Odds Say No

I have a bone to pick with Fox Sports’ Ken Rosenthal, and it’s not about the bow ties. I respect a man who can rock a bow tie, especially when he’s doing it for some great causes.

I do, however, have a problem with his column encouraging the White Sox to deal Chris Sale.

It’s not that the idea is without merit; he provides some solid reasoning, but when you consider all of the factors at play, moving the youthful all-star doesn’t make enough sense.

Sale, 24, has less than 500 innings on his resume, a career K/9 rate near 10 and an ERA sitting at 2.89 to boot. Even if the return has the seductive appeal Rosenthal calls for in a proposed swap, the possibility of whiffing is too high for the Sox.

Pitching – young pitching – is the lifeblood of a successful franchise. Ask the low-budget Rays and Athletics how they stay competitive with baseball’s Big Boys. Or if hardware is more your thing, take a look at San Francisco and St. Louis.

For clubs, like the Rays with limited capital, sustained success starts with two integral aspects: assembling a farm system with a deep stable of arms to develop (David Price, Matt Moore, Alex Cobb) or deal (James Shields) and identifying your studs from your duds and controlling their futures into their free agent years (Evan Longoria). The better teams are at accomplishing those goals, the sooner they’ll be annually competitive.

Now the White Sox, not exactly an organization needing to pinch pennies, but certainly tightening the purse strings with an average home attendance of 14,000 fans fewer than in 2005 (as per Rosenthal’s column), have sort of skipped the stockpiling arms part, but with Sale, have correctly located a stud. The southpaw is in the first year of team-friendly 5-year $32.5 million contract, including two club options that would keep him in a White Sox uniform until he’s 30.

That gives the Sox – if they start right now – 6-1/2 years to rebuild around their ace. Plenty of time. The Giants were a last place, 71-win team in 2007. In 2010, behind former farmhands, Tim Lincecum, Matt Cain and Madison Bumgarner, they won their first of two championships. I understand the Giants already had those guys in their system, so it might take the Sox longer, but again, many teams have reversed their fortunes in fewer than 6-1/2 years.

But if you’re not convinced, I understand. I’m hoping this next section might do the trick. Let’s take a look at the specifics involved in the risk Rosenthal suggests the Sox take.

In 2011, Royalsreview.com writer Scott McKinney provided some wonderful insight into the success rate (using WAR) of baseball’s top prospects. Here’s the link to the article, but I’ll do my darndest to summarize it justly.

McKinney – piggybacking some work done by Victor Wang in 2007 – studied the production of Baseball America’s top 100 prospects from 1990 to 2003, giving each prospect a seven-year span to produce.

Here’s what he found: Right off the top, 70 percent of top prospects are destined for failure – qualified by an average per-season WAR below 1.5.

But we already know there is risk in dealing proven stars for prospects, even premium guys. That’s an inherent part of the game. It happens every season, and it always will.

Sure, but let’s look at the success rate of top 100 pitching prospects, which is what the White Sox should demand — even though GM Rick Hahn disagrees — to restock Baseball America’s 29th-ranked cupboard, which is practically barren of difference-making hurlers.

According to McKinney’s study, pitching prospects have a much smaller chance at success that position players. In fact, a pitcher ranked from 21-100 on Baseball America’s list fails at least 70 percent of the time with odds of failure increasing as the list moves toward #100.

In other words, the White Sox would have to land a Dylan Bundy- or Gerrit Cole-type pitcher (Baseball America’s preseason #2 and #7 prospects) in the deal to give themselves a better than 30-percent chance of succeeding at the major league level. Why would the Sox roll the dice on an arm like that when they have Sale’s locked up, if they choose, for the next 6-1/2 years?

In short, they shouldn’t. His contract is extraordinarily reasonable, and the frontline prospect(s) they’d receive in return would likely only be a couple years younger than Sale with no guarantee they’ll produce or sign a team-friendly contract.

OK. Now let me address the glaring hole in this argument: The Sox would surely receive more than one elite prospect in such a deal.

And many would justly argue that the best way for organizations to produce a high quantity of talent is to load as many proverbial bullets into the chamber as possible, hoping one or two’s projectile is a major league rotation/starting lineup.

I understand that mentality. In fact, normally, I agree with it, but that 70 percent failure rate for top prospects looms large, especially when trading the caliber of pitcher Sale is.

Let’s look at Baseball America’s top 10 prospects from 2006 (giving them seven years to produce, just like the study): No. 1 Delmon Young; No. 2 Justin Upton; No. 3 Brandon Wood; No. 4 Jeremy Hermida; No. 5. Stephen Drew; No. 6 Francisco Liriano; No. 7 Chad Billingsley; No. 8 Justin Verlander; No. 9 Lastings Milledge No. 10 Matt Cain.

I see this list and think: There was a time when the consensus was that Chad Billingsley was a better pitcher than Justin Verlander; that Brandon Wood was more a highly regarded shortstop than No. 25 Troy Tulowitzki; and that Lastings Milledge wasn’t playing in Japan.

In all seriousness, what this says is that dealing with prospects, all prospects, is a crapshoot. And it’s a crapshoot not worth playing for the Sox who already have their silver bullet.

Rosenthal suggests in order for the Sox to pull the trigger on such a deal, they would have to hold out for the kind of haul Texas Rangers brought in when, in 2007, they traded Mark Teixeira for Atlanta’s farm system. In the trade, widely considered a coup for Texas, the Rangers received Baseball America’s preseason No. 36 prospect Jarrod Saltalamacchia, No. 65 Elvis Andrus, No. 90 Matt Harrison, unranked Neftali Feliz, who was 17 at the time, and unranked  Beau Jones.

Since the trade, the highest-rated prospect of the bunch, Saltalamacchia, has accumulated a career (Baseball-Reference) WAR of 4.2. Andrus, despite two All-Star appearances, has never produced at an All-Star level with just one season with a WAR above 4. The lefty Harrison has produced a 9.2 WAR in his career; not bad, but not Sale. And finally there’s Feliz, whose impact was felt in 2010 and 2011 but whose value — WAR has never eclipsed 2.5 — was limited in a relief role. Add it all up, and Salty, Andrus, Harrison and Feliz have combined for 34.4 Wins Above Replacement in a combined 20.5  major league seasons (2008-today), giving the foursome a 1.67 WAR per season average, just barely avoiding failure by McKinney’s standards. Not exactly the steal it appeared to be a few years ago.

Sure, the players acquired in the trade did help the Rangers reach back-to-back two World Series, but what was the thing the Rangers were desperately chasing in 2010? An ace, and they unloaded their farm system to acquire one, getting Cliff Lee from the Mariners for Justin Smoak, Blake Beavan, Matthew Lawson and Josh Lueke.

Sorry for the reminder, Seattle fans, but the White Sox should see how this deal worked out for the Mariners and stash Sale with Eric Snowden.

The Sox should sell whatever they can to begin the rebuilding process. Sell Jake Peavy. Sell Jesse Crain. Sell Alex Rios. But hold onto Chris Sale, the most effective and polished pitcher in the American League under 25 (1.01 WHIP, 1st; 9.8 K/9, 1st; 4.85 K/BB, 1st; Opponents OPS .597, 1st) who will lead their pitching staff for years to come.

The lefty has already produced a 14 WAR in 3-1/2 major league seasons — one abbreviated and one as a reliever. For comparison, Cy Young-winner Clayton Kershaw produced 18.1 WAR in his first four seasons, but pitched 716.1 innings, 300 plus more than Sale thus far.

And let me address what I’ll call a minor consideration Rosenthal makes as an argument for why the Sox should trade Sale. The sidewinder has an awfully violent motion and a rather slight frame; what if he breaks down?

My answer: It doesn’t matter. The risk involved in the trade remains far greater.

Even if the worst happens, and Sale tears his UCL and needs the king of all pitching surgeries, the Tommy John, there is a very good chance he comes back from it and pitches like he did pre-surgery. I’d cite such successful examples such as Stephen Strasburg and Adam Wainwright, but I know there are examples to the contrary.

So, I’ll call upon an expert witness: Dr. Christopher Ahmad, an associate professor of orthopedic surgery at Columbia University and head team physician for the New York Yankees.

Last year, he told FoxNews.com, “… the success rate of having Tommy John surgery is between 70 and 80 percent to full level of throwing.”

That’s not perfect. There are no guarantees. This is still a major injury and surgery is required, but it is still superior to the 30 percent success rate for prospects we looked at earlier. I understand what Rosenthal was getting at. Why let a stud toil on a middling team? Look at Felix Hernandez. Weren’t all those years in Seattle wasted? Yes. I can’t argue against it. And that might happen to Sale if the White Sox keep him around and don’t embark on a successful rebuilding mission. But what the Mariners knew and White Sox should know is rebuilding shouldn’t come at the cost of a Cy Young caliber 24-year-old. He’s the ground floor. He’s the building block. He’s where you start.


Mythbusters: Home Run Derby Edition

If you watched the Home Run Derby on ESPN, you saw Yoenis Cespedes and his raw, yet explosive swing, hit 17 home runs in the first round of the derby. You also saw Chris Davis staying true to his swing and swinging at any pitch that he thought he could handle, hitting the ball where it’s pitched, and even swinging at some pitches that were borderline balls. If there was anyone to be concerned about changing his swing to fit the Derby, it was Davis–the guy who has so much strength that all he needs to do is stay within himself and swing easy to hit a homer. One might worry that Davis would swing too hard or try to pull everything, thus regressing into the “quadruple-A” player as he was once labeled, swinging and missing at a such a rate that he became a liability.

Anyone who has played baseball at a high level knows that a successfully executed sacrifice bunt, or grounder to the right side of the field with a man on second and nobody out, is frequently celebrated as much as a hit. Quality “team baseball” seems to be more effective than a mere amalgamation of flashy superstars that doesn’t mesh (I’m looking at you, 2012 Red Sox or 2013 Blue Jays). The Home Run Derby is kind of counter-intuitive to many MLB managers. Old-schoolers like Mike Scioscia would rather his players did not participate, saying, “I haven’t seen somebody come away from that derby and be a better player for it.”¹ The Home Run Derby turns the team game into an individual competition. Players exhaust themselves and risk tweaking their swings, but has the derby really affected the second-half performance of its participants?

To answer this question I looked at what goes into a player’s stats. There is a lot of luck involved in baseball, so I took a look at the differences in the way players hit the ball before the derby compared to after the derby. Looking at the past five derbies, I calculated the average batted-ball flight for players that were healthy for both halves of the season (38 players, excluding only Rickie Weeks in 2011 and Jose Bautista in 2012).

LD% GB% FB% IFFB% HR/FB
Pre HR Derby 19.1 40.8 40.1 8.5 .204
Post HR Derby 19.5 41.0 39.2 9.3 .166
Difference <1% <1% <1% <1% .038

The consistency in the way players hit the ball is incredible. Derby participants hit the ball almost the same before and after the derby as a group. The HR to FB ratio drops considerably, and could explain a decrease in batting average and slugging percentage, as well as on-base percentage. It seems that players hit the ball the same way, just with slightly less power. Here are some of their standard stats from the second half:

  K% AVG OBP SLG OPS ISO BABIP
Pre HR Derby 17.87% 0.302 0.385 0.570 0.956 0.268 0.322
Post HR Derby 19.60% 0.282 0.369 0.499 0.869 0.217 0.316
Difference 1.73% 0.020 0.016 0.071 0.087 0.051 0.006

Isolated Power (ISO) measures a hitter’s power in extra bases per at-bat (2B+3Bx2+HRx3)/AB. The large drop is ISO shows that indeed power does decrease for derby participants in the second half, and the overall line shows that players do perform worse. It’s not merely a function of hitting the ball to the wrong place, as the .oo6 drop in Bating Average of Balls in Play (BABIP) is not really significant. Players strike out a little bit more, but the notion that players change their swings and have trouble hitting the ball the same way after participating in the derby seems misguided when considering the small change in K% along with the consistent batted-ball percentages outlined in the first table.

Data suggests that players do perform worse in the second half of the season after participating in the HR derby, but that their performance isn’t due to a change in their swings. There have, however, been some significant changes in performance for some individuals. Taking a closer look at some of them, the poor performances can be explained without blaming the Home Run Derby.

2008 Total derby HR pre/post AVG SLG OPS ISO BABIP HR/FB
Dan Uggla 6 pre 0.286 0.605 0.978 0.319 0.341 21.30%
 FLA post 0.226 0.396 0.739 0.17 0.295 13.60%

Uggla has a reputation as a streaky player, but he went from an MVP candidate in the first half to a guy who didn’t belong in the starting lineup after the derby. Taking a closer look, however, Uggla began slowing down in late June, and suffered a leg injury that kept him out nearly two weeks just prior to the All-Star Game. He only lasted one round, anyways, so it’s hard to blame the derby for his drop off, although it was certainly a big one.

2008 Total derby HR  pre/post AVG SLG ISO BABIP IFFB% HR/FB
Lance Berkman 14 pre 0.347 0.653 0.305 0.37 2.80% 20.60%
HOU post 0.259 0.436 0.177 0.298 13.20% 10.30%

By 2008 Berkman had been a good hitter for many years. His second half was hurt by the amount of pop-ups he hit. a 10.4% increase in infield fly balls mean close to a 10% increase in outs, and his average decrease supports that notion. His increase in pop-ups could have been a result of an uppercut swing that developed in the derby, but his average had dropped 20 points in 16 games prior to the derby, and his career IFFB% is 11.5%, not too far off from his second half percentage. Perhaps the derby hurt Berkman’s swing, but more likely  he was finally coming back down to earth after his torrid start.

2009 Total derby HR pre/post K% AVG SLG ISO BABIP HR/FB
Brandon Inge 0 pre 24.60% 0.268 0.515 0.247 0.304 .22
 DET post 29.10% 0.186 0.281 0.095 0.247 .08

Brandon Inge? Yeah, Brandon Inge was in a Home Run Derby. He only has a career HR/FB ratio of .10, and a career batting average of .233, so his second half was closer to what Inge’s career looked like. Plus Inge didn’t even hit one out of the park, so could ten swings really ruin his season?

2009 Total derby HR pre/post AVG SLG ISO BABIP IFFB% HR/FB
Ryan Howard 15 pre 0.257 0.529 0.272 0.301 1.10% .23
 PHI post 0.305 0.621 0.316 0.352 0.00% .28

Wait a second…? Was Ryan Howard better after participating in the derby? Yes! After the slugger hit 15 big flies in the derby, he went on to hit more homers in less at-bats afterward. With zero infield flies in the second half of the season, his swing was just fine.

2011 Total derby HR pre/post K% AVG SLG ISO BABIP IFFB% HR/FB
Jose Bautista 4 pre 14.40% 0.334 0.702 0.368 0.321 11.50% 27.40%
TOR post 20.40% 0.257 0.477 0.22 0.291 20.50% 15.40%

After a hot start in April and May, Bautista had his worst month of the season in June, before the HR Derby. While Bautista was better overall before the derby, he was better in the two months following the derby than he was before it.

2012 Total derby HR   AVG SLG ISO HR/FB
Prince Fielder 28 pre 0.299 0.505 0.206 16.10%
 DET post 0.331 0.558 0.227 20.00%

Prince puts a lot of power into his swings, and when he hits 28 balls out of the park, he exerts a lot of energy. Prince won the derby in 2012, and continued winning games for the Tigers after the All Star Break. Hitting for a better average, and with an improved HR to FB ratio, Prince shows that the derby can kick start a player’s second half.

____________________________________________________________________________________________

Conclusion: The notion that participating in the Home Run Derby leads to a drop off in performance is a myth. Although data suggests that Home Run Derby participants do indeed regress in the second half of the season, the derby is not to blame. As baseball is a game of superstitions, players are aware that the derby can have harmful effects if they aren’t careful. Even Chris Davis was wary, saying, ”I wanted to be conscious of not changing my swing at all… I tried to stay up the middle and let the ball travel and not try to get pull heavy. But it looks a lot easier on TV than it really is. Once you get out there and start swinging and your adrenaline wears off, you realize how tough the Derby really is. It’s exhausting.”² While the derby curse isn’t real, it’s hard to continue chasing a 60-home-run season with a popped blister. Get some treatment on that hand, Chris.

1 http://www.latimes.com/sports/sportsnow/la-sp-sn-angels-relieved-mike-trout-not-in-home-run-derby-20130709,0,7051643.story

2 http://mlb.mlb.com/news/article.jsp?ymd=20130715&content_id=53853822&vkey=news_bal&c_id=bal&utm_source=twitterfeed&utm_medium=twitter

All data from Fangraphs.com


Adam Wainwright: Efficiency is the Name of the Game

Adam Wainwright has been absolutely phenomenal this season. If you prefer old school stats: 12-5, 2.30 ERA, with an 8.06 K/9 ratio. If you prefer advanced statistics, he looks even better: 2.12 FIP to go along with a 2.69 xFIP. My favorite stat about his season so far though is his K/BB ratio which in mid July now stands at a staggering 9. For every 9 strikeouts he walks 1 batter. You don’t need me to tell you how good that is. The pitcher nearest his efficiency is Cliff Lee and he isn’t even close.  I decided to compare Adam Wainwright’s impeccable ratio to some of the greatest pitchers in the past 20 years. I’ll take their best season (regarding K/BB) and see how it stacks up to the masterful performance Wainwright is putting up this season.

**disclaimer: WAR total is from their best K/BB season. Wainwright’s is still counting**

Adam Wainwright is having a phenomenal year. His 9.00 K/BB is surpassed only by Cliff Lee’s and Curt Schilling’s most efficient seasons, respectively. I’m not really counting Smoltz, due to his best K/BB ratio coming as a closer with only 60+ innings pitched. Here are the following seasons since 1900 where someone had a K/BB greater than or equal to 9.

  •  Bret Saberhagen (11 K/B 1994)
  • Curt Schilling (9.58 K/B 2002)
  • Cliff Lee (10.28 K/BB 2010)

That’s it. Adam Wainwright is on pace to have the 4th best season since 1900 in regards to strikeouts-to-walks. Three pitchers have accomplished this feat in last 113 years. It’s hard to fully recognize in the moment, but you truly are witnessing greatness when watching Adam Wainwright go to work this season.

What is making him this successful?

For one thing, control is the last aspect of a pitcher’s game to return after Tommy John. Wainwright had a mediocre season in 2012. (his words, not mine) This season the control is completely back to match the velocity. In a podcast visit with Matthew Berry and Nate Ravtiz, he credited his efficiency to first-pitch strikes. He said he made a concerted effort to get ahead, because batters gradually get statistically worse the further down in the count they get. Adam Wainwright does a great job of getting ahead; according to FanGraphs he throws a first pitch strike 65.6% of the time. That 65.6% is the best for starting pitchers in the MLB.  Wainwright’s recipe seems pretty simple once you look at the data: get ahead early then force hitters to chase out of the zone. He also leads the majors in O-Swing% (swings at pitches out of the zone) with a 38.2% rate.

 Adam Wainwright is also phenomenal at mixing his pitches. According to Brooks Baseball Wainwright’s first-pitch mix breaks down this way: 15% four-seam fastballs, 37% sinkers, 2% changeups, 18% curveballs, and 30% cutters. Wainwright uses the hard stuff to get ahead. Once he’s ahead 0-2 the mix stays relatively the same except for the fact that curveball becomes the go-to pitch. He throws his curveball 48% of the time when he is ahead 0-2. That might seem like it would make it easy to guess what’s coming, but good luck touching it. 20% of the swings taken on his curveball in that count ends in a big fat whiff. Wainwright’s curveball has a horizontal movement of 8.21 inches on top of moving 9.33 inches on a downward trajectory. In other words, if Wainwright gets ahead of you, you’re screwed


Three More Albert Pujols Bunts

Mea culpa. After posting an in-depth look at Albert Pujolslone sacrifice bunt, readers both friendly and unfriendly pointed out to me that there is record of three more major-league Pujols bunt attempts, two for hits and one a squeeze (but no other known sacrifice attempts). The only satisfactory way to own up to my mistake is to follow up with a new essay asking: why did Pujols bunt those other times? Any errors in this new post are the responsibility of Session Lager the author.

Bunt No. 2: May 23, 2003

What was the bunt? Albert Pujols had a good day. He struck out in the first inning and then racked up five hits (two doubles), including one in the top of the tenth inning. It’s the 10th inning we’re looking at here.

With two outs and a runner on second base, J.D. Drew hit a triple to deep center field; the runner scored, giving the Cardinals a 9-8 lead. Next, Albert Pujols singled on a bunt to third base, scoring Drew and making the lead 10-8. The Pirates couldn’t recover in the bottom of the inning.

Was it a good idea? This was a squeeze play with two outs. In the tenth inning. Using a batter who had only bunted once before. On the other hand, the Cardinals already had the lead they needed. It was a daring mad-scientist gamble. The bunt had to be perfect.

Did it work? The bunt was perfect.

Bunt No. 3: July 27, 2003

What was the bunt? Only two months later and against the same Pirates, Pujols attempted to bunt for a hit and failed in the 8th inning. His Cardinals were losing 3-1, and there was one out and no runner on base.

Was it a good idea? Albert Pujols was facing Brian Boehringer (5.41 FIP, 4.33 BB/9, -0.7 WAR that season). He may have been emboldened by the memory of his recent success, but given how good Pujols was at not-bunting, and how bad Boehringer was at pitching, this attempt is only understandable if it was an attempt to take the enemy by surprise. Pujols bunted on 0-1; whether he showed bunt on the first pitch (a called strike) is lost to the sands of time.

Did it work? No, but in the next (9th) inning, with two outs, Pujols had a walk-off single to win the game.

Bunt No. 4: August 25, 2004

What was the bunt? It came on another good day: Pujols singled, doubled, and homered. And the single was a bunt to third base on a 1-0 count in the 8th.

Was it a good idea? See, this is the thing with bunt-for-hit attempts; without seeing the defense at work, and without understanding the state of play, all we have to go on is hindsight. John Riedling was another troubled pitcher, almost identical to Boehringer (5.24 FIP, 4.64 BB/9, -0.7 WAR that year); both also suffered from inflated home run rates. They were, presumably, easy pickings. And, indeed, Jim Edmonds brought Pujols home on a game-tying line drive over the fence.

Did it work? Yes.

Conclusions (Again)

What can we learn, aside from that the author needs to be a little more diligent? That Albert Pujols has done okay as a bunt artist. His first try, as a rookie, remains incomprehensible, but he then executed a flawless two-out squeeze play and went 1-for-2 in tries for a hit. I’m inclined to believe that the tries for hits represent opportunism, and that the lone sacrifice and the squeeze play represent Tony La Russa’s management philosophy at work. On my last post, reader Tim A wondered if that first bunt was La Russa simply testing Pujols’ ability to lay the ball down.

It’s still kind of weird that the then-best (or best non-Bonds) hitter in baseball tried a squeeze bunt on two outs. It’s definitely weird that a rookie with 20 homers would be called upon to bunt from the cleanup spot. But hey, we discovered a new wrinkle: Pujols is pretty good at yet another part of baseball. And in games in which Albert Pujols bunts, his team is 4-0.

Possible Teasers if I Decide to Write More of These at Some Point

According to the batted ball data (except where this data is incomplete, starred*), here are some more career bunt attempt totals: Adam Dunn 3, Manny Ramirez 2*, David Ortiz 11. In 2009 Jack Cust went 3-for-3 on bunt hit attempts. That same year, 3 successful bunt singles were laid down by Pablo Sandoval.


Craig Biggio: Double Play Escape Artist

Craig Biggio came about 7% of the vote shy of spending late July of this year in Cooperstown giving a tearful speech about his playing career, but it’s likely he’ll get a chance to make that speech sometime in the next couple of years. Biggio was a very good major-league player over 20 seasons and ranks 83rd all time in WAR. He has 3,000 hits, which is generally a gold standard among voters, and ranks higher than a number of other current Hall of Famers in WAR such as Tony Gwynn and Roberto Alomar.

Certainly, some of Biggio’s value is based on longevity and the second half of his career was not nearly as productive as the first. Even if Biggio doesn’t make the Hall of Fame by your own personal standards, he’s likely to get in and is at least worthy of a conversation on the subject.

I’ve always been fond of players who play multiple positions like Ben Zobrist (who does it while being an excellent hitter) or Don Kelly (who does it while being something around replacement level). It’s a type of player I enjoy watching, and Biggio’s 428 games at catcher, 366 games in the outfield, and 1989 games at second base put him in that category. As I often do with players who peak my interest, I spent time exploring his career statistics and one particular season stands out as his best, but it also stands out for another reason entirely: Biggio grounded into exactly zero double plays that season.

The year was 1997 and Biggio’s Astros were heading toward an 84-78 record, a Central division title, and a brief appearance in the postseason before being swept at the hands of the Braves. Over the course of the campaign that would end with Biggio finishing fourth in the NL MVP race, he lead MLB with 9.3 WAR narrowly topping players named Griffey, Walker, Piazza, and Bonds. Biggio accumulated those wins with an extremely balanced attack.

In 744 PA, he hit .309/.415/.501 for a .401 wOBA and 148 wRC+. His Total Zone was 19 and his baserunning runs above average came in a 5.2. He stole 47 bases, hit 22 HR, scored 146 runs, and was hit by 34 pitches. Pretty much everything he did that season was his career best or very close to it. It was easily the best season he ever had and one of the most valuable seasons in recent memory, coming in 36th in WAR since 1961.

Biggio’s 1997 season is remarkable because it’s the biggest feather in the cap of a very good player and one of the more balanced and interesting stat lines you’ll see, but it’s also remarkable because Biggio did it without grounding into a single double play.

Baseball-Reference appears to have complete data on the matter going back to 1939 and since then only seven qualifying hitters have gone an entire season without grounding into a double play. This list itself is truly amazing.

Pete Reiser, 1942 (4.4 WAR)

Dick McAuliffe, 1968 (5.2 WAR)

Rob Deer, 1990 (1.2 WAR)

Ray Lankford, 1994 (2.4 WAR)

Otis Nixon, 1994 (0.3 WAR)

Rickey Henderson, 1994 (2.8 WAR)

Craig Biggio, 1997 (9.3 WAR)

First of all, you’ll notice that three of the seven seasons on this list came in 1994 when the season was cut short due to a strike, so while these seasons count they should be taken with a grain of salt because the guys on this list played 85-105 games each instead of 162. Aside from those three, this has only been done four times in major league history and one of the times was by Rob Deer. You can’t make that up.

Reiser and McAuliffe had very good seasons during the years they didn’t ground into any double plays, but they didn’t have the kind of year Biggio did. McAuliffe was four wins behind the leader in 1968 and Reiser was seven wins behind Ted Williams in 1942. Biggio accomplished this feat, which is exceedingly rare, while being one of the league’s very best players. From 1939-2012 there have been 8,636 qualifying seasons and just seven instances of a player avoiding a double play all season long.

Only .08% of all major league seasons have ended with a player not grounding into a double play. Three of them happened in the same strike-shortened season. One during a below-average season from Rob Deer. Two came during very good seasons more than 40 years ago. One came during Biggio’s amazing 1997 campaign in which he did just about everything you could ask a baseball player to do.

In 1997, Biggio came to the plate in 78 situations in which grounding into a double play was possible. In those situations he hit an impressive .403/.487/.677. Of the 40 times he didn’t get a hit, walk, or get hit by a pitch, he hit 13 ground balls. Two of those ground balls turned into errors and he got down the line fast enough the other 11 times to prevent the defense from converting the second out.  It is worth noting, however, that Biggio did line into a double play once during the season, but that hardly seems fair given that it isn’t considered a GIDP and is more the fault of the baserunner than the batter. Additionally, he was the strikeout half of one strike-em-out-throw-em out double play in 1997, so he wasn’t completely without his faults.

Craig Biggio is a likely Hall of Fame player with 3,000 hits who had one of the most impressively balanced seasons in recent memory in 1997. If I were the one responsible for writing the text on his Cooperstown plaque, I would be sure to find room for the phrase, “One of seven players in MLB history to go an entire season without grounding into a double play” because I’m not sure he’s ever done anything on a baseball field more noteworthy than that.


How Hard Is It To Be Successful Without Drawing Walks?

Yasiel Puig has been in the news a lot lately. He’s had phenomenal start to his career, well aside from the Diamondbacks’ catcher Miguel Montero hating him. He’s also had most of his success without drawing many walks, which inevitably has sent him sliding down a mountain into inevitable comparison to known hacker Jeff Francouer. Francouer never tore up the minors the way Puig did, but it’s somewhat of a fair comparison due to how much fanfare Frenchy had after such a quick start to an otherwise poor career. As Jeff Sullivan from FanGraphs noted, the league is beginning to adjust to Puig, now he has prove he can counter those adjustments.

Fangraphs lists the BB% of 7% to be below average, 5.5% is poor, and 4% and lower is awful. Puig’s current BB% in the majors after 36 games is 4.5%. He did post a 9% walk rate in AA this year before his call up, so there’s a little reason to believe he is capable of being more patient than he is right now. I’ll take a look at some guys who had solid careers while also sustaining low walk rates. I took the leader-board at FanGraphs, sorted for year 2000-2013, removed everyone with a walk rate north of 8%, and removed everyone with an ISO (isolated power) below .175. The following players have compiled 15 fWAR since 2000 (players in bold are still active).

That isn’t very many names. Of the 202 position players that accumulated 15 fWAR from 2000-2013 only 58 or 28.7% had walk rates less than or equal to 8%. Adam Jones fell slightly below on a few parameters, but for comparison’s sake he felt pretty accurate. Here is Yasiel Puig at the moment. I included his AA stats and his projections for the rest of the season.

We’ve noticed you can be successful without walks, but it isn’t easy. All of the players from the first table were all good to phenomenal players in their own right. It’s unfair to say Yasiel Puig has to turn out to be as good of a hitter as Carlos Gonzalez or Adrian Beltre to be successful, but he’ll have to follow their lead if he can’t learn to draw walks as he gets experience. Personally I see Puig as a .270/30 homer/15+ steal guy in the future. If he can manage that he should be fine, but I’m sure he’ll never meet the expectations some people have for him at this point. Any player on that list would be a win (maybe aside from Vernon Wells because…ugh). Anything on top of the production these guys have managed is just gravy.


Visualizing Pitcher Consistency

Visualizing Pitcher Consistency

When evaluating starting pitcher performance, fantasy owners and fans alike lament the relative inconsistency of certain pitchers deemed especially volatile (Francisco Liriano will break your heart), while others like Mark Buehrle are workhorses often viewed as among the most steady arms available.  A.J. Mass of ESPN has written about the value of calculating “Mulligan ERAs,” in which a pitcher’s three worst outings are subtracted from his overall ERA. His colleague Tristan Cockroft routinely publishes Consistency Ratings to let readers know which pitchers have remained relatively high on ESPN’s player rater from week to week.

While these methods focus on pitcher performance from start to start, it may be useful to evaluate pitcher performance against individual batters. If Tommy Milone gets rocked pitching on the road in Texas, we may be less concerned than if he is routinely unable to get out low quality hitters. To this end, we can examine how pitchers perform against different levels of batters. How well does a given pitcher avoid putting low OBP batters on base? How does this compare to his rate of putting a high OBP batter on base? We would expect to see a linear relationship—the Emilio Bonifacios of the world should be easier to get out than the Joey Vottos.

Methods

We begin by examining the 31 pitchers with the most innings pitched for the 2012-2013 seasons. After obtaining batter vs. pitcher data for each of these pitchers during the last season and a half, we can calculate the OBP allowed by each pitcher to any batter with at least 5 plate appearances during this time period (arbitrary cutoff alert!). We can now see how Buster Posey fares against the likes of Clayton Kershaw, Ian Kennedy, and any other NL pitcher in which he has accrued at least 5 PA. It turns out Posey did pretty well for himself.

In order to obtain the OBP of batters in general, not in relation to particular pitchers, we can examine the leaderboards for players with at least 450 PA in 2012-2013. Based on the work of Russell Carleton, we have confidence that after ~450 PA, a batter’s OBP tends to stabilize and represents their long-term OBP skill level.

Batters were then placed in five buckets, lowest, low, medium, high, and highest OBP levels.

Batter On-Base Percentage Classification

OBP Category

OBP

Player Examples

Lowest

0.243-.311

Colby Rasmus, J.J. Hardy, Raul Ibanez

Low

.311-.330

Ruben Tejada, Eric Hosmer, Michael Young

Medium

.330-.338

Elvis Andrus, Jason Heyward, Yoenis Cespedes

High

.338-.349

Brandon Belt, Jason Kipnis, Coco Crisp

Highest

.349-.458

Allen Craig, Andrew McCutchen, Mike Trout

Each batter, assigned a score of lowest to highest, was then matched with the batter vs. pitcher dataset, allowing for us to calculate the mean OBP allowed by individual pitchers to hitters in each of the categories. So, although someone like Zack Cozart sports a .283 OBP in 2012-2013, earning a spot in the lowest category, he does own a .329 OBP against Yovani Gallardo. Maybe this is all the evidence Reds Coach Dusty Baker needs to keep batting Cozart second in the lineup.

Results

If we examine the performance of pitchers across five categories of OBP skill, we can calculate the correlation coefficient of these five points. R2 in this case is a measure of how well the data fits a straight line—if a pitcher allows a low OBP to low OBP hitters, and a correspondingly higher OBP to high OBP hitters, the data points should increase linearly and the value of R2 should approach 1. Conversely, pitchers that are inconsistent in their ability to get hitters of a certain skill level out would have a R2 much closer to 0.00.

 

Correlation Coefficient for OBP Allowed Among Differently Skilled Batters

Name

R2

Adam Wainwright

0.798

Jason Vargas

0.793

Max Scherzer

0.771

Ricky Nolasco

0.740

Matt Cain

0.734

Yu Darvish

0.717

Wade Miley

0.705

C.J. Wilson

0.700

Jordan Zimmermann

0.697

Kyle Lohse

0.660

Bronson Arroyo

0.657

Yovani Gallardo

0.638

Justin Verlander

0.619

Mat Latos

0.617

Cliff Lee

0.553

Hiroki Kuroda

0.536

James Shields

0.469

Justin Masterson

0.443

Homer Bailey

0.377

Ian Kennedy

0.353

Clayton Kershaw

0.329

Cole Hamels

0.159

Gio Gonzalez

0.140

Mark Buehrle

0.105

Trevor Cahill

0.083

Felix Hernandez

0.076

Chris Sale

0.031

R.A. Dickey

0.029

CC Sabathia

0.028

Jon Lester

0.028

Madison Bumgarner

0.025

There is a wide range of R2 values among this list of starting pitchers. Adam Wainwright takes the grand prize for consistency. He is far more prone to putting elite OBP hitters on base than lowly hitters. Madison Bumgarner, on the other hand, strangely performs worse against low OBP than high OBP hitters, and has the lowest R2.  And R.A. Dickey, as you might expect, is sort of all over the place.

 

 

Below is a visual representation of the OBP against pitchers with high and low R2 values. We can see that the pitchers with the highest correlation coefficient have a much more linear relationship overall with OBP allowed than pitchers with low values.

 

 

Additional analyses showed that there was no relationship between a starter’s FIP and their correlation coefficient. A quick glance at the names in the two graphs above confirms this. Jason Vargas, with a R2 of .793 is a worse pitcher, in pretty much all respects, than Felix Hernandez at .076. Interestingly, Jason Vargas has one of the league’s highest HR/9 at 1.28 during 2012-2013, while King Felix sports one of the lowest ratios at .62.

What, then, does pitcher consistency tell us? While it may not tell us much about the overall skill of a pitcher by itself, we can discern from the data which pitchers are doing a good job getting out poor hitters. Pitchers like Adam Wainwright and Max Scherzer are doing extremely well, and their R2 values indicate that they are pitching steady—they are less likely to blow up against poor hitters. Of course, pitcher performance can differ greatly from start to start, but one can have confidence that Ricky Nolasco will probably dominate his former Marlins teammates (30th in team OBP), because he consistently allows a low OBP to low OBP hitters. Conversely, perhaps it’s a good thing Jason Vargas does not have to pitch against his Angels teammates, who collectively have the 4th highest team OBP in the majors.

Oddly enough, Justin Masterson’s OBP allowed has a small range, from .299 in the middle OBP tier to .371 against the highest tier, indicating that when he’s brought his good stuff, he mostly dominates all batters regardless of their level of skill. We can have less confidence that Justin Masterson will dominate a middling OBP team like Kansas City (6.39 ERA this year), ranked 20th overall in the majors, while he has repeatedly humiliated the Blue Jays, who just beat out the Royals at 17th overall.

Despite the comically bad timing of his recent piece on batting Raul Ibanez against CC Sabathia, David Cameron was right to point out the relative worthlessness of individual batter vs. pitcher matchups and the danger of drawing conclusions from such small sample sizes. However, we can use aggregated batter vs. pitcher data to learn more about what kinds of players pitchers are more likely to strike out, or serve up the long ball, or a base on balls. While it’s easy to assume that pitcher X will be less likely to strike out Norichika Aoki than Ike Davis, by studying consistency we may be able to see who deviates from this linear pattern. Are some average strike out pitchers more likely to strike out low strikeout hitters? We can already see from the data above that R.A. Dickey is as likely to put a low OBP hitter on base as a high OBP hitter. While this fact seems to make little sense, these results indicate that the knuckleball can baffle expert hitters as much as less skilled batsmen. It may be worthwhile to use consistency ratings such as these to determine what kinds of pitchers deviate from the expected patterns.

All data courtesy of Fangraphs and Baseball Reference.

Because I’m a big believer in open data, here is a link to the R code used to find Batter vs. Pitcher OBP percentages by quintile.