Over the last several decades, with the platoon effect becoming more widely understood and exploitable, a flood of pitchers with otherwise weak skills in the broad strokes have found employment in the major leagues. No aspect of the sport has undergone as thoroughgoing a transformation as bullpen usage, and while the idea of a structured relief corps may in fact be inefficient in terms of roster management, it has certainly paved the way for the rise to prominence of a number specialist relievers. Those referred to as LOOGYs-courtesy of John Sickels, who coined the catch-all term for Lefty One-Out GuYs-comprise the vast majority of this new group, entering into the latter stages of a game to try to face a same-handed hitter or two. Pitchers assigned to the role generally dominate lefty batters; approximately three-quarters of the pitches that a batter will see over the course of a season are thrown by right-handers, and a pitch delivered from a southpaw to a left-handed batter can be thrown from a more deceptive angle, altering the perception of the hitter.
Since these specialists meet and greet so few batters per appearance, evaluating their performances can be very tricky. As is, the stats for relief pitchers tend to be unreliable as stable summations of skill due to smaller innings totals; this only gets worse with LOOGYs, who accrue even less playing time. It’s very common to see a specialist experience a large disconnect in his appearances and his innings pitched totals, logging, for example, only 40
Unfortunately, such research proves to be meaningless because of its lack of context, which is key in any study or evaluation, but is often ignored as confirmation biases reign supreme and proper evidence which contradicts a previously determined point may be dismissed. The single-season home-run record of 73, set by Barry Bonds in 2001, becomes significant only when compared to all other seasonal totals. Without knowing about previous records, or the context in which the figure matters, his home-run total becomes nothing more than an ambiguous data point. The stats-related misstep of leaving context by the wayside occurs far too frequently, and can happen even more when evaluating LOOGYs. To begin rectifying this issue, we must first define specialist relievers for the purpose of our database classification.
One of the tables in my database contains a row for every game from each pitcher-season. I queried this table to count the number of times that a pitcher faced a maximum of three hitters in an appearance, and the number of total games for each season. Simple division, with the specialist count as the numerator, provided the percentage of total appearances in which a pitcher, well… specialized. Anyone with a specialist percentage south of fifty percent was removed, so for the sake of this study, a pitcher is considered to be a specialist if he saw three or fewer hitters in at least half of his appearances. The cutoff point can be debated, but it’s far from arbitrary, as certain pitchers may not serve in the role all season long, while others may take on two jobs during the season, simultaneously serving as mop-up men.
Since the goal here involves evaluating LOOGYs and placing their numbers in the proper context, all right-handed pitchers were also removed from the table. Before delving deeper into the data, here is a breakdown of the specialist percentages relative to all games pitched, be they starts or relief appearances, going back to 1955:
Span SpecGP Spec% 1955-59 3,811 13.5 1960-64 5,656 15.1 1965-69 6,922 16.0 1970-74 7,450 15.7 1975-79 7,066 14.2 1980-84 7,881 15.3 1985-89 10,072 17.1 1990-94 12,946 22.4 1995-99 19,860 25.0 2000-04 23,568 26.6 2005-08 21,750 28.9
Here is a graph displaying the trend over time. Note that specialists appeared in their lowest percentage (in the Retrosheet Era) from 1955-59, but they also experienced a drop-off from 1975-79, before seeing their opportunities increase in each subsequent span.
The biggest jump occurred right around the time that Nirvana and Pearl Jam burst onto the scene in the early ’90s. Percentage increases in this area are still being observed, making it clear that managers have bought into the LOOGY strategy. How did these pitchers fare against same-handed hitters? Once the lefties meeting the specialist-percentage benchmark were pooled together, a separate table was created that consisted of their results against each lefty batter faced during their specialized seasons. This is important to keep in mind, in that specific pitcher-seasons are of interest here, not their entire careers. The reasoning for breaking each pitcher-season down by hitter will make more sense presently, but the idea deals specifically with context-based evaluations, primarily since LOOGYs should not be compared to themselves or evaluated using our own uninformed theories. Rather, these specialists must be compared to the rest of the league.
Take, for instance, former Giants reliever Jack Taschner, who now earns his keep as a member of the Phillies‘ bullpen. When the defending champs acquired his services to replace the suspended J.C. Romero, some Phillies fans, myself included, questioned the validity of the move given that lefties hit .279/.339/.394 against the southpaw last season. His Raw EqA (REqA), sans stolen-base components, hovered around the .765 mark against same-handed hitters. Without context, these numbers lack meaning, and they tend to become skewed when personal biases or ideas are factored into the mix. Since a .279/.339/.394 line doesn’t exactly imply dominance, some felt that the Phillies should have looked elsewhere. What really needed to be asked was how Taschner’s line compared to the rest of the league, making the methodology here quite clear: take all of the batters faced by a specialist in a particular season, and calculate the numbers for non-specialist pitchers against the very same batters. This sort of matched-pair analysis aids in placing specialist performance in the proper context.
If a specialist allowed lefties to hit .270/.335/.440, but those same hitters boasted a collective .300/.380/.520 line against all non-specialists, then the LOOGY essentially accomplished his goal by being more effective than the league as a whole. His numbers against may lack sizzling dominance, but they indicate a solid performance that would not necessarily be understood by merely eyeing a seasonal-splits page. The following table shows the slash lines and non-SB Raw EqA for LOOGYs against same-handed hitters, from 1999-2008:
Specialists Year PA Avg/ OBP/ SLG REqA 1999 2307 .237/.322/.373 .723 2000 1684 .225/.306/.358 .698 2001 2756 .238/.306/.380 .711 2002 2892 .220/.292/.353 .672 2003 2729 .234/.301/.353 .679 2004 2388 .241/.312/.381 .718 2005 2939 .233/.304/.361 .691 2006 2833 .235/.307/.371 .703 2007 3437 .233/.307/.336 .675 2008 3162 .215/.285/.333 .648
And here is the data for all non-specialists against those same left-handed hitters, separated by pitcher-handedness:
Non-Specialist LHPs Year PA Avg/ OBP/ SLG REqA 1999 9616 .266/.340/.417 .775 2000 10360 .268/.341/.418 .777 2001 10622 .266/.336/.422 .775 2002 11837 .252/.322/.403 .743 2003 13029 .255/.320/.395 .734 2004 13022 .259/.327/.405 .752 2005 12470 .254/.318/.387 .726 2006 12096 .252/.320/.401 .739 2007 13086 .253/.321/.392 .734 2008 14719 .250/.315/.387 .722 Non-Specialist RHPs Year PA Avg/ OBP/ SLG REqA 1999 44395 .285/.353/.468 .834 2000 46289 .280/.351/.469 .834 2001 45093 .276/.340/.463 .817 2002 45460 .276/.342/.452 .810 2003 42180 .277/.341/.454 .810 2004 43488 .276/.342/.458 .815 2005 42942 .275/.336/.446 .797 2006 40425 .282/.344/.465 .824 2007 41610 .276/.339/.452 .807 2008 45397 .272/.336/.444 .796
Perhaps this data may be easier to interpret in graphic form:
Non-specialist southpaws clearly performed better against same-handed hitters than their right-handed counterparts, relative to the same batters faced by specialists. This makes sense, and is confirmed by the very basis of the platoon effect. A lefty specialist should not be considered successful in a given season for performing better against a group of hitters than a non-specialist righty, or for falling in line with non-specialist lefties. They will only be considered dominant against same-handed hitters when their numbers prove to be better than those of non-specialist southpaws.
Getting back to Taschner, we now have some context when referring to his .279/.339/.394 line, since the non-specialist lefties allowed .250/.315/.387 against the same hitters that he faced. Taschner’s REqA of ˜.765 was actually much worse than the .722 posted by the non-specialist lefties, confirming the opinions gathered at the time of the trade, but arriving at the conclusion in a more statistically accurate manner.
On the whole, LOOGYs bested non-specialist lefties in each of the ten seasons of interest here:
Non-Special LOOGY Year LHP REqA REqA Diff 1999 .775 .723 .052 2000 .777 .698 .079 2001 .775 .711 .064 2002 .743 .672 .071 2003 .734 .679 .055 2004 .752 .718 .034 2005 .726 .691 .035 2006 .739 .703 .036 2007 .734 .675 .059 2008 .722 .648 .074
The 2004-06 seasons are intriguing, as the differences in REqA dropped significantly. In 2004, LOOGYs posted their second-highest REqA; however, in 2005-06, the non-specialists simply performed much better against the very same hitters. Who were some of the best in this span? Some of the worst? Here are the top five and bottom five LOOGY seasons from 1999-2008:
Best Year Avg/ OBP/ SLG REqA J.C. Romero 2008 .102/.189/.193 .392 Damaso Marte 2007 .094/.227/.125 .407 Mike Myers 2000 .120/.198/.207 .431 Arthur Rhodes 2002 .158/.177/.242 .436 Mike Myers 2005 .158/.198/.211 .436 Worst Year Avg/ OBP/ SLG REqA Jim Poole 2000 .448/.438/.897 1.328 John Rocker 2002 .364/.488/.758 1.190 Matt Perisho 2005 .346/.500/.615 1.092 Troy Brohawn 2001 .386/.476/.600 1.055 Scott Forster 2000 .289/.448/.622 1.042
Structured bullpens and specialist relievers aren’t going anywhere, not unless Nolan Ryan magically clones himself and manages to both infiltrate and take over the remaining 29 franchises (and yes, I have already begun work on the screenplay for this film, hoping that Kurtwood Smith will play the lead role).
With all of this in mind, I must again stress the importance of context. Whether you’re evaluating home/road splits, platoon splits, monthly splits, or any other split, comparing a player to himself is an inaccurate route to take even if, in the end, the correct route confirms the predetermined opinion. When a team acquires a specialist, don’t automatically form an opinion based on his career splits against a certain-handed batter without first finding out how those numbers compare to the rest of the league. As the data here indicates, some LOOGYs look worse than they actually are when lacking context, and some can actually look better when the numbers of non-specialist lefties are ignored. Regardless, the message is clear: context is key, and should be incorporated into the statistical repertoires of every interested fan and every analysis involving splits.
Thank you for reading
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