Contracts For Relievers: Paying For Consistency

Very few things in baseball receive quite as much derision as large contracts given to relievers. Relievers have come to be seen as fungible, volatile assets who are poor investments. Many view the contracts given to established closers as being entirely based on saves, a stat that is rightfully maligned and makes a poor basis for a multi-year multi-million dollar contract. However, the logic underlying these complaints has holes large enough to push Phil Hughes through, and a closer look suggests that the truly large reliever contracts may actually make a modicum of sense.

My theory is that general managers who hand relievers big money have not been looking for saves per se. Rather, they have been looking for pitchers who have provided consistent performance on a regular basis. To test this hypothesis, I decided to take a look at the largest contracts given to relievers since 2000, as well as the most consistent performers over the same time period. For the contracts, I limited my search to 3+ year contracts worth at least $7 million per season. 3+ year deals tend to reflect a level of trust by the club in the player, and $7 million struck me as a reasonable cutoff between the deals handed to top players and to those a level down on the talent chain. For measuring performance, I used a simple ERA+ and IP combination to try and isolate the most consistent performers (a search for relievers who have racked up 35+ saves on a yearly basis unearthed a similar list. Players who provide that many saves regularly tend to have strong underlying numbers, so saves can serve as a proxy for performance when addressing a multi-year sample).

Here’s the list of pitchers who had at least 3 seasons with an ERA+ of 150 or better and at least 65 innings pitched:

1 Joe Nathan
2 Billy Wagner
3 Mariano Rivera
4 Francisco Rodriguez
5 Keith Foulke
6 Mike Adams
7 Joakim Soria
8 Carlos Marmol
9 Jonathan Papelbon
10 Jonathan Broxton
11 B.J. Ryan
12 Juan Rincon
13 Brad Lidge
14 Francisco Cordero
15 LaTroy Hawkins
16 Luis Ayala
17 Eric Gagne
18 Jason Isringhausen
19 Octavio Dotel
20 Armando Benitez

It is important to note that when the search was expanded to players with at least 2 seasons of this sort of performance, an obvious drop in quality could be perceived. To my eye, 3 seasons turned out to be a very good parameter by which to evaluate consistent success. Looking at the list, Adams, Soria, and Marmol have not yet reached free agency, while Broxton, Dotel, Rincon, Gagne and Ayala all suffered injuries that hurt their performance and value before they could cash in. That leaves us with 12 pitchers relevant to our purposes.

Here is the list of relievers who have received large contracts, meaning deals for 3 or more seasons at an AAV of at least 7 million dollars (this is the list I was able to construct. It may not be complete. Please correct me if possible):

Jonathan Papelbon
Mariano Rivera
Rafael Soriano
Francisco Rodriguez
Francsico Cordero
Joe Nathan
Heath Bell
Brad Lidge
Billy Wagner
BJ Ryan
Armando Benitez
Jason Isringhausen

Soriano and Bell are the only players on the “got paid” list not on the “consistently performed” list, and Bell has two seasons of requisite performance and a third that falls just short (146 ERA+). Soriano is the only real outlier here, as he has never had a season meeting the performance criteria yet was paid like the more consistent elite performers. Conversely, Foulke and Hawkins are the only two of the 12 relevant players from the “consistently performed” list who failed to make the “got paid” list, and Foulke missed it by .25 million (3 years, 20.75 million).

Basically, when looking at the two lists, we find that the pitchers who have performed at a high level on a regular basis are the ones who are getting the big money. Now, correlation is not causation, but it does seem reasonable to say that large contracts for relievers have been largely reserved for pitchers with established levels of consistency and performance. Now, the next question to ask is whether it makes sense to be giving those pitchers large contracts. The obvious retort to this is that:

1) relievers are a volatile commodity, and
2) past performance does not guarantee future results, and
3) relievers are fungible and good relief can be acquired cheaply.

As for #1, Stephen Rhoads addressed this very issue in this space a few weeks ago:

In any walk of life, one quick way to open yourself up to embarrassment is to assume that those around you are either unable or unwilling to comprehend the complexities of your worldview, to borrow a turn of phrase from Confederacy of Dunces. I’d wager that most General Managers have a pretty good idea that relievers are volatile creatures, and that they are also aware of the failure of these relievers to live up to the contracts given to them. So, avoiding the arrogance that would suggest that they’re just irrational actors, what would drive a GM to pay a premium for a reliever? It boils down to predictability.

Paradoxically, the volatile nature of relief pitchers drives GMs to pay big money for relievers whom they don’t believe will be volatile. Thus, relievers with a long track record of health and consistently superb performance are the most likely candidates to get big money.

Essentially, reliever volatility actually makes handing big contracts to those relievers who have proven to be more of a sure thing a logical decision. As for #2 and #3, they can both be answered by the same point. While it is easy to look back at the end of a season and find relievers who provided great results for few dollars, it is much more difficult to identify those pitchers ahead of time. For every Joaquin Benoit there are 10 Buddy Carlyles and Lance Pendeltons, pitchers who are blanks in the game of reliever roulette. Additionally, while some of these large contracts have flopped, that is a risk that comes with any free agent contract. In the right context, it makes sense for clubs to take that risk rather than cross their fingers and hope to stumble upon the right reliever. Although past performance does not guarantee future results, it does make good results significantly more likely and predictable.

Relievers being fungible and volatile does not mean that their talent changes yearly. It means that in a small sample, you can often get statistical anomalies in both directions. Since relieving is by nature a small sample, there is more volatility and more risk. But if you have identified relievers who you think are more talented and more consistent, you lower that risk of volatility. There is value in that certainty, such that it makes sense to pay those relievers more than a pure talent to dollars evaluation might suggest. This added level of predictability is why general managers have been paying a premium for top relievers on the free agent market.

Changes To The Game Suggest Darvish Is The Right Move

One thing Yankees fans are great at is fitting an attractive player for pinstripes before he is a free agent. We see a Joe Mauer or Cole Hamels or Felix Hernandez on the horizon, and we start dreaming up the various ways in which the player will become a Yankee. We often take it as a given that the Yankee will acquire the players they need, whether via trade or free agency. In recent seasons we have added prospect hype to the equation, assuming that the farm system will eventually produce a big bat or a top of the rotation starter who will allow the Yankees to eschew free agency. Somehow, the Yankees will end up with the great talent necessary to continue contending on a regular basis.

However, recent events have seemingly conspired to make the acquisition of top young talent more complicated for the Yankees.  The new CBA will make it more difficult for the Yankees to pursue elite talents in the later rounds of the draft, as well as entirely destroy their ability to target top international free agents. They can no longer buy Austin Jackson types out of scholarships in the later rounds by going well over the recommended slot money, nor can they throw big contracts at the next Jesus Montero or Gary Sanchez. Furthermore, while the new luxury tax might actually help the Yankees in the short-term, its lack of adjusment for inflation makes it likely that it will curtail the Yankees ability to expand their budget in the middle of the decade. With a number of aging players slated to earn large paydays during that period, the Yankees might find their ability to compete on the free agent market hindered to some extent.

Finally, from a purely anecdotal perspective, it seems like more and more teams are locking up their young stars before they ever hit free agency. Contracts that buy out a few years of free agency and give the player some financial security are all the rage, and the ramifications of that trend are obvious. Most of the players who make it to free agency are of the CJ Wilson, Zack Greinke, or Francisco Liriano ilk, players with elite talent who have some questions surrounding them that make teams fearful of handing them huge contract extensions. There are fewer elite talents hitting the free agent market, and when they do make it to free agency, the competition for them is likely to be significantly stiffer.

However, with all of these factors suggesting that the Yankees will have a difficult time acquiring exciting young talent, there is one loophole that could allow the Yankees to make a splash. As Mike said in the CBA post linked to above:

Players under 23 years old and with less than years of professional baseball experience will be considered amateurs and count against the spending cap. That means guys like Yoenis Cespedes and Japanese veterans will be treated as a true free agents. Japanese players run through the posting system will not count against the cap.

Cespedes is something of a wild card whose price seems to be rocketing out of control, and I simply do not know enough about him to advocate that the Yankees throw a ton of cash at him. Yu Darvish, however, is an exciting 25 year old Japanese pitching prospect who is likely to be posted this offseason. Unlike Cespedes, Darvish fits an obvious need for the Yankees, as they have a hole near the front of their rotation that Darvish should be able to fill even if he is only 75% as good as he was in Japan. Furthermore, while his total cost will be prohibitive (likely in excess of 100 million dollars), a large chunk of that money (the posting fee) will not be counted against the luxury tax. That makes Darvish a cheaper long-term option than a guy like CJ Wilson.

There are obvious risks associated with a large outlay for Darvish. Japanese pitchers have not exhibited sustained success in the majors, and some have suggested that the routine for pitchers differs enough between NPB and MLB to make the transition a difficult one. Furthermore, any large amount of money spent on a pitcher who has never thrown a major league pitch represents a major gamble, particularly when reliable veterans such as Mark Buehrle and Roy Oswalt can be had at a significantly cheaper rate.

Despite the risks, the changing nature of the game makes taking a chance on Darvish the right play for the Yankees. They will have a more difficult time acquiring top draft and IFA prospects, making the development of elite talent significantly more complicated. Throw in the fact that the alternative is the shrinking free agent pool, and taking a risk on a 25-year old with Darvish’s stuff is something the financially powerful Yankees should strongly consider. This is one area where the club can still throw around their dollars to grab a young player, and it would behoove them to jump at the opportunity.

Looking At The Yankees’ Sac Bunts

(AP Photo/LM Otero)

Baseball is a game without an official clock. In its stead, the 27 outs each team receives serve as the timekeeper, pushing each game to an inevitable conclusion. Avoiding those outs has become the name of the game over the last ten years, and one of the strategic moves that has come under fire due to this philosophy is the bunt. The sacrifice bunt draws a team one out closer to the end of the game without greatly increasing the chances of a run scoring. A look at run expectancy tables, which tell us how many runs are expected given a particular situation, confirms that bunting usually decreases the number of runs expected to score. While there are a few situations where a bunt is actually the statistically prudent move, on balance it is seen as the misused weapon of weaker, backwards-thinking managers, and is the hobgoblin of sabermetricians everywhere.

All that said, there is at least one study that suggests that managers tend to outperform run expectancy tables when it comes to bunting. This means that on average, managers have a reasonably good sense of the moment and of context, and they bunt in situations where it will produce more runs than one might expect given the post-bunt base/out status. While the numbers still suggest that these bunts decrease run expectancy, it is illuminating and encouraging to see that managers are utilizing the bunt reasonably efficiently.

All of this brings us to the manager of the local nine. One of the most common complaints about Joe Girardi‘s managing is that he bunts too frequently, playing for one run with an offense that can put up a crooked number in a hurry. I thought it would be instructive to look at every Yankee sacrifice bunt in 2011 to see how many runs Girardi actually cost his club with his small ball sensibilities. I broke the bunts down by player and then calculated three numbers:

  1. Expected runs before the bunt. This number tells us how many runs were expected to score given the base/out situation prior to Girardi working his managerial magic.
  2. Expected runs after the bunt. This tells us how many theoretical runs the bunt “cost” the club.
  3. Actual runs. This should tell us how Girardi’s move actually worked out.

Now, a few caveats.

  • Run expectancy is not perfect. It does not account for the score or the quality of offense or opponent, nor does it account for the skills of the hitter at the plate. However, it is a reasonable estimate of how the game has been impacted by a move, and I’ve broken things down by hitter so you can mentally adjust your evaluation based on the quality of the batter.
  • This study does not include the attempted bunts that failed and caused batters to fall behind in the count. However, it also does not include bunt singles or bunts in which the batter reached on a fielder’s choice or error, which help to greatly increase run expectancy (I also excluded Nick Swisher‘s bunt against Boston where he lost track of the number of outs and bunted on his own). The analysis is limited to successful sacrifice bunts. I’ve also removed all bunts by pitchers, as I think most of us can agree that bunting with an American League pitcher is almost always the correct move.
  • We cannot calculate what would have happened if Girardi had chosen not to bunt. To provide an example of why this is an issue, imagine an inning where Brett Gardner bunts a runner over and then Curtis Granderson homers. While we can figure out the run expectancy before and after the bunt and can observe actual runs scored, we can’t know what would have happened if Gardner had not bunted. So if one run was expected and two actual runs were scored, there is still the possibility that without the bunt, three runs would have scored (because Gardner could have reached prior to the home run). If we assume that everything would have been different and Granderson may not have homered had Gardner reached, the expected runs v. actual runs analysis is relevant. As such, this study is making the assumption that the bunt changes the entire inning, such that whatever happened afterward is connected to (but not necessarily caused by) the base/out state created by the bunt. Discarding that assumption does not make the conclusions irrelevant, but it does sap them of some of their power.

Keeping all that in mind, let’s take a look at the sac bunts Girardi called for in 2011.

Brett Gardner

# of sac bunts: 8

Expected runs, before the bunts: 7.0173

Expected runs, after the bunts: 5.4602

Actual runs: 11

Loss of run expectancy: 1.5571

Actual impact: Gain of 3.9827 runs over expected runs

(To be fair to Girardi and his predilection for bunting with Gardner, it is important to note that all of Gardner’s bunts but one came in the late innings of a tight game, when playing for one run is acceptable. The lone exception came against Justin Verlander, which represents another understandable, if not entirely defensible, use of the bunt.)

Eduardo Nunez

# of sac bunts: 6

Expected runs, before the bunts: 5.5296

Expected runs, after the bunts: 4.4064

Actual runs: 3

Loss of run expectancy: 1.1232

Actual impact: Loss of 2.5296 runs under expected runs

Derek Jeter

# of sac bunts: 4

Expected runs, before the bunts: 4.1974

Expected runs, after the bunts: 3.4954

Actual runs: 2

Loss of run expectancy: 0.702

Actual impact: Loss of 2.1974 runs under expected runs

Curtis Granderson

# of sac bunts: 3

Expected runs, before the bunts: 3.7157

Expected runs, after the bunts: 3.2358

Actual runs: 6

Loss of run expectancy: .4799

Actual impact: Gain of 2.2843 runs over expected runs

Ramiro Pena

# of sac bunts: 2

Expected runs, before the bunts: 1.701

Expected runs, after the bunts: 1.3028

Actual runs: 1

Loss of run expectancy: 0.3982

Actual impact: Loss of 0.701 runs under expected runs

One each for Russell Martin, Frankie Cervelli, Chris Dickerson, and Brandon Laird

# of sac bunts: 4

Expected runs, before the bunts: 3.402

Expected runs, after the bunts: 2.6056

Actual runs: 1

Loss of run expectancy: 0.7964

Actual impact: Loss of 2.402 runs under expected runs

Conclusion

# of sac bunts: 27

Expected runs, before the bunts: 25.563

Expected runs, after the bunts: 20.5062

Actual runs: 24

Loss of run expectancy: 5.0568

Actual impact: Loss of 1.563 runs under expected runs

Regarding that actual impact number, I am uncomfortable concluding that the bunts were always directly responsible for what happened after them. For example, I do not think Granderson’s lone “successful” bunt actually caused all 6 runs that subsequently scored in the inning. That said, I think it is fair to conclude that Girardi’s proclivity for bunting did not hurt the Yankees much in 2011. In terms of run expectancy, all of the bunts over the course of the season only cost the Yankees five runs, and that ignores the fact that many of them came in situations where playing for one run at the expense of a big inning is actually the right thing to do. Furthermore, the team outperformed the “runs expected after the bunts,” suggesting that Girardi may have utilized the strategy in optimal situations. Taking into account the fact that the actual runs scored was about the same as the number of runs expected, it seems clear that Joe Girardi’s bunting problem was not much of an detriment to the Yankees in 2011.

Update (12:28 p.m.): I am new to play index, but I just figured out how to get bunt singles and bunt outs listed properly(still no foul bunts, however). Here are the results for the 18 sac bunt attempts that ended without a sac bunt:

10 runners reached base
8 made force outs or popouts

On the outs:

RE before the bunts: 7.5994
RE after the bunts: 4.431
Actual: 7
Loss of RE: 3.1684
Actual impact: 0.5994

On the hits:

RE before the bunts: 9.9545
RE after the bunts: 16.1122
Actual: 17
Loss of RE: Gain of 6.1577
Actual impact: Gain of 7.0455

New total:

RE before the bunts: 43.1169
RE after the bunts: 41.0494
Actual: 48
Loss of RE: Loss of 2.0675 runs
Actual impact: Gain of 4.8831

Locking Up Russell Martin

(AP Photo/Charlie Neibergall)

Over the last few months, the sabermetric community has made a number of advances in the area of catcher defense. Studies by Max Marchi and Mike Fast on pitch framing and a study from Bojan Koprivica on pitch blocking have begun the process of quantifying the more difficult to measure elements of a backstop’s defense. While these studies are still in their infancy and are likely to be tweaked and altered in the coming months and years, they do provide us with one reasonable concrete lesson: Good defense from a catcher is likely more important than we had previously thought when trying to measure catcher value.

In the past, catchers tended to be put into one of two groups: good defender or weak defender. Sure, you had one or two Gold Glovers at the top and a handful of guys who were execrable enough to be known as terrible at the bottom, but the vast majority of catchers were placed into those two groups. Without any way to truly quantify defense, these broad categories had to suffice, and this resulted in most people evaluating catchers based on their offense. Catcher defense was thrown in at the end of conversations as an aside, possibly with caught stealing numbers and some passed ball data, but little tangible data that would shift an evaluation in either direction. Only those known as excellent catchers would get any sort of boost from their perceived defensive value.

Now, with these new studies, we can begin to quantify catcher defense, and use that to reevaluate the worth of a catcher who performs well behind the dish. As I noted above, one lesson that can be taken from these studies is that defense behind the dish is quite important. Let’s use Russell Martin as an illustration.

While I am far from the biggest proponent of WAR, these new metrics are expressed in terms of runs saved, making WAR a convenient way to weigh the impact of Martin’s defense. Before considering defense, Russell Martin was worth 3.1 wins last season (FanGraphs). However, once you add 1.5 runs saved by controlling the running game, 0.1 runs saved blocking pitches, and 15 runs saved by being among the best at framing pitches (Fast’s research consistently places Martin near the top of the league in this area), you suddenly have an incredibly valuable 4.6 win player. While the first instinct of many is to flinch at the idea that the “unmeasurable” aspects of catcher defense can add that much value, it is important to note that the very best defenders gained at most two wins due to their gloves. That is not much different than the value added defensively by the best at other positions, and catchers are involved on almost every pitch.

The suggestion here is not that Russell Martin is a 4-5 win player, but that he is a very good defender and that has definite value exceeding what some of the value metrics would suggest. Accepting that hypothesis leads me to my point: If the Yankees do not believe that Jesus Montero is their catcher of the future, it would make sense for them to offer Russell Martin a 2-3 year contract extension, either now or at the end of the 2012 season.

While he certainly showed improvement relative to 2009-2010, Martin had a decent but unspectacular season offensively, such that his value is probably not incredibly high at this point. Although he has a reputation as a solid defender, he is not known as one of the best in the sport, which makes it unlikely that he would get a major salary bump on the open market due to his glove. Essentially, if he was a free agent at this moment, he could market himself as a adequate offensive catcher with a solid glove, which is relatively unsexy and would not bring him a major financial windfall.

Being that the market almost certainly will not value his defense quite as much as it should, the Yankees could have the opportunity to lock Russell up at a reasonable rate relative to his value. They could wait until after the 2012 season to sign him, although they might want to avoid the possibility that his price goes up either because 1) he bounces back to 2006-2008 levels offensively, or 2) teams begin to see him as a great defensive catcher. While the latter seems like a long shot, another season of the Yankees getting good performances out of retread pitchers could shine a light on the work that Martin does behind the plate.

Of course, there are downsides to signing Martin to an extension a year early, such as a major injury or a significant decline with the bat that would turn the contract into an albatross. Couple those risks with the fact that the team rarely hands out extensions, and I would bet on the Yankees waiting until after this season to address Martin’s contract. That said, once he does sign on for a few more years, he should provide enough defensive value to help any contract avoid disaster status. Russell’s glove is undervalued, and unless the Yankees believe they already have their catcher of the future knocking on the door, he would serve as an good option to fill the position for the next few seasons.

(Thanks to @jaydestro for inspiring this post)

The Danks-Pettitte Comparison

Over the last 14 months or so, the Yankees have had a fairly questionable rotation, with a number of slots they could improve via the trade market or free agency. This has led to a million and one trade proposals from fans that have touched on every decent pitcher in the sport. Other than Felix Hernandez, who is Moby Dick to this fanbase’s Ahab, the most frequently raised name has probably been that of John Danks. In the course of various online discussions about Danks, a number of Yankees fans, myself included, have compared him to former Yankee Andy Pettitte. Whether it’s the fact that both are lefties from Texas, the nature of their repertoires, or their established levels of performance, there is something about these two pitchers that connects them in the minds of some fans. Let’s take a closer look at the two men to evaluate whether the comparison has merit.

Scouting

While Pettitte was actually born in Louisiana, he played his high school ball in Texas like Danks. Pettitte has a larger frame than Danks (6’5/235 v. 6’1/215), but both are reasonably large lefties with durable frames. The real similarity comes in their repertoires, particularly when comparing Danks to the Pettitte who returned to the Yankees in 2007. Both work off a fastball that sits around 90-92 MPH, and use the fastball to set up their breaking pitches. Most notably, they use their cutters more than 20% of the time and experience great success with the pitch. They each round out their arsenals with a curveball and a changeup, although Danks focuses more on the changeup while Pettitte was significantly more dependent on his hook.

Performance

Danks has been in the majors for five seasons, so it would be useful to compare his first five seasons to the first five from Pettitte. In his first five years, Andy Pettitte pitched 1044.1 innings with a 3.92 ERA, for an ERA+ of 119. Danks did not come out of the gate quite as hot as Andy did, with a 5.50 ERA in 2007 resulting in a slightly worse overall line of 917 innings to a 4.03 ERA (111 ERA+). However, when it comes to peripheral statistics, Danks actually comes out slightly ahead, with a better K/9 (7.0 to 6.1), BB/9 (2.9 to 3.2), and H/9 (8.8 to 9.4). Danks allowed a .727 OPS against to Pettitte’s .730, but Pettitte was superior at coaxing double plays (15% to 12%), which was due to his significantly greater penchant for drawing grounders (1.07 GB/FB to .76). Pettitte was better at suppressing home runs (0.7 to 1.1 HR/9), and it is important to note that the peripherals are not adjusted for era, which is important considering that Pettitte was pitching at the height of the steroid era. Overall, this comparison seems fairly close, and it is reasonable to say that these two pitchers performed at a similar level.

Another interesting comparison can be made between Danks and Pettitte’s last five years, which may be the years that are causing people to make the connection between these two hurlers. In his last five seasons, Andy threw 957 innings to the tune of a 4.11 ERA, good for an ERA+ of 109. His peripherals during this period actually look a lot like those of Danks, with a 6.8 K/9, 2.9 BB/9, 0.9 HR/9, and a H/9 of 9.6, and the two players notched these numbers while playing in the same league at the same time. Again, it seems that a reasonable person could conclude that these two pitchers were of similar ability.

While some will surely raise postseason success as a defining element of Pettitte’s career and something Danks lacks, it is hard to blame him for not being on a club that makes the postseason every year. For what it is worth, his one postseason start was quintessential Pettitte, as he allowed a bevy of baserunners (10) but limited the damage to 3 runs in 6.2 innings and notched the win.

Editor’s Note: Danks did throw an absolute gem in Game 163 against the Twins in 2008, allowing just two hits and zero runs in eight shutout innings. It’s technically a regular season start, but we all that know that’s a playoff game.

Conclusion

While the parallels between the two are not perfect, they are close enough to explain why Danks is somewhat reminiscent of Andy Pettitte. Both are lefties from Texas who thrive on a fastball-cutter mix, and both were likely miscast as aces when they performed more like good #2 starters. Neither was much of a power pitcher, succeeding by allowing plenty of baserunners but finding a way to limit the damage and give their teams a chance to win. If Danks ever does end up in New York, Yankees fans might find that he brings back memories of a certain dimple-chinned fan favorite from the South.