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Let’s talk about the power of myth. A myth, simply put, is a story that is meant either to explain why something is, or to tell us how something ought to be. (Strictly speaking, myths are religious in nature, but we’re going to go ahead and stretch the word just a bit here.) It’s a story that teaches us something—a parable, if you will. But it starts off with a story.

Baseball, I think, lends itself particularly well to stories. And I have a fondness for baseball stories. Consider, for instance, this game between the Red Sox and the Devil Rays back in ’04, the second game of a late-April double-header. It wasn’t a particularly dramatic game, I’ll grant you that. The Sox scored seven runs in the first inning, and the D-Rays never seriously threatened after that. Still, a seasoned baseball fan can go over the box score and construct a story from it. It’s something you pick up with practice.

Still, you can find other kind of stories, too. Here’s a quick little excerpt from novelist Stewart O’Nan, a Sox fan, who was at the game:

I realize the girls have forgotten to take my glove—for protection, seriously—and hustle down [from the right field terrace to the dugout seats]. I’m underneath the grandstand when I hear the crowd cheer for Johnny. I guess that means he’s on base. Another cheer, this time for Bill Mueller. So probably a single. A bigger cheer (it’s a long way), and I catch a monitor by a concession stand in time to see Johnny scoot home with our first run. I reach the seats as Manny’s batting. The girls think I’m nuts, bringing down the glove, but I insist. “Lindsay,” I say, “you’re getting a ball tonight.”

Moss is all over the place. He throws one to the backstop, moving Bill Mueller and Ortiz over. “Watch the ball,” I tell the girls, because it’s scuffed. The ump tosses it to Andrew, who looks back and sees me and the girls. Lindsay stands and Andrew throws it right to her—only to have this linebacker-sized guy in a muscle shirt in the front row reach back and snatch it away from her. The section boos, and the poacher realizes what he’s done and dumps it in Caitlin’s lap. So Lindsay gets her ball.

That’s a story. (It’s from Faithful, an account of the ’04 Red Sox season by O’Nan and Stephen King. If you like baseball stories for their own sake, it’s worth your time.)

Baseball stories have a tendency to spill over into myths, but what’s interesting–to me at least–is that this isn’t usually done with intent. Nobody set out to turn Babe Ruth into a mythic figure; they certainly meant to celebrate him, but he turned into myth on his own. This, I think, gives a lot of insight into why steroids send people into great spasms of moral righteousness, while amphetamines do not–the so-called steroid era was a sort of Gotterdammerung for some of our greatest baseball myths, as mere humans toppled the records of the pantheon of baseball immortals. Sportswriters can forgive many sins, but not that one.

One of baseball's great myths, I’m sorry to say, is the myth of the closer. This is not to say that closers don’t exist, or that they can’t be valuable, but their role has taken on mythical qualities. We are told that these are the players that save the game, as though the game were some damsel in distress tied to the railroad track or hurtling over Niagara Falls in a barrel. They are, in short, the heroes.

Yet nobody ever stopped to ask—did the game ever really need saving?

Has the closer changed the game of baseball?

Baseball experienced a change in Oakland, starting in 1988–that’s when Dennis Eckersley became the first pitcher that we’d recognize as the modern closer, as opposed to the more traditional “fireman” sort of ace reliever. Now it’s nearly unthinkable that a team would go without a designated closer, a pitcher whose primary role is to pitch in the ninth inning when his team has a lead of three runs or fewer.

An interesting side note here–managers of course are doing this to bring in their closer during official save situations. So who decides what an official save situation is? The guidelines for what are and are not a save spot were first conceived by Jerome Holtzman, a beat writer covering the Cubs at the time. It was introduced in the Sporting News, later becoming an official MLB statistic, and now managers organize their entire bullpen around the idea of it. Isn’t that something? Is any sabermetrician so slavishly devoted to the precise definition of any one stat as managers are to the save?

So now we have a battalion of pitchers whose sole purpose is to preserve close leads in the ninth inning. Has this innovation, in fact, made those close leads any more secure?

What I did was take a look at how often a team allowed zero runs in an inning–call it the “clean rate.” Then I looked at clean rate only in the ninth inning when the batting team trails by exactly one run. The ratio of the two provides us with a measure of pitching effectiveness in potential save spots–-the toughest kinds of saves, even–-that controls for changes in run environment over time. So, going back to 1950, we can see a very slight uptick in our normalized clean rate:

Clean rate

Let’s use 1988 as our boundary year. From 1950 to 1987, the average normalized clean rate was 1.03. From 1988 to 2010, it increased to 1.06. From 1993 to 2010 (in other words, the current era of offense), it was 1.07.

Now, from ’93 on, the average clean rate was 71 percent. So if we apply the pre-closer rate, we are led to think that roughly 73 percent of all one-run leads in the ninth would be safe. Applying the rate observed over that time period, we get 76 percent. On average a team had 15 such close leads to protect over the course of a season, so the modern innovation of the closer has allowed teams to preserve one additional one-run lead in the ninth inning every two seasons or so.

Of course, this doesn’t look at two- and three-run saves (excuse me while I get in just one more eyeroll at the idea of a three-run save), extra-inning saves, or managers who have the audacity to bring in their best relief pitcher in some inning other than the ninth. Of course, we also haven’t accounted for the fact that sometimes a team will come back to win after allowing a team to tie up a one-run game in the ninth.

Moreover, it doesn’t count the lost opportunities that come when you cut the innings you’re willing to use your best reliever in half. While teams have gotten better at holding close leads in the ninth, they’ve gotten worse about having a close lead to protect in the ninth–looking at the number of one-run leads in the ninth inning per game:

Close games

The games we’re asking closers to save just aren’t there anymore. Now, plenty has changed in baseball over the past 60 years–I’m not sure this is attributable at all or in part to the change in reliever utilization–but the fewer close games teams take into the ninth inning, the less valuable your typical closer can be.

Now, this is probably a bit of an exercise in flogging a dead horse; Baseball Prospectus readers over the years have been told early and often that saves are overrated and a poor method for evaluating relievers. What interests me, though, is why so many people ever embraced the save to begin with. I think the save is a reflection of how we feel; the last out of the game is a collapsing state, where we know whether a team has won or lost. There is a great emotional impact to that certainty–joy in the win, frustration with a loss. But the cold hard fact is that you need 27 outs (with, of course, a lot of caveats) to end a ballgame, and each of them is just as important at the end of the day.

The real problem isn’t the save rule. As an official stat, it’s far from dead, but there’s little profit in continuing to defang it. It shall expire on its own, in the fullness of time. The trouble is that, in the effort to urge the save’s demise along, sabermetrics is in danger of instead recreating it.

Great Expectations

Let’s talk win expectancy. Win expectancy, to state the obvious, is how many wins you expect, given what you know at the time. A typical win expectancy table will include the inning, which side is batting (home or away), the score differential (home runs minus away runs), the number of outs in the inning and the configuration of the runners on base. Going from this point forward, we’ll be looking at it in terms of the home team’s win expectancy (although you could certainly do it the other way around).

Here a truncated sample of a win expectancy table from our stat report:

Inning

Outs

Runners

TM_BAT

RunDiff=0

RunDiff=1

RunDiff=2

RunDiff=3

1

0

0

0

0.441

0.472

0.529

0.769

1

0

3

0

0.636

0.667

1.000

1.000

1

0

20

0

0.526

0.750

0.333

0.750

1

0

23

0

0.391

0.571

0.667

1.000

1

0

100

0

0.486

0.667

0.625

1.000

1

0

103

0

0.609

0.571

1.000

1.000

1

0

120

0

0.575

0.722

0.333

0.750

1

0

123

0

0.656

0.818

0.500

0.500

1

1

0

0

0.417

0.404

0.615

0.652

1

1

3

0

0.562

0.591

0.800

0.500

1

1

20

0

0.478

0.492

0.615

0.375

1

1

23

0

0.600

0.563

0.778

1.000

1

1

100

0

0.422

0.579

0.571

0.778

1

1

103

0

0.486

0.594

0.900

0.500

1

1

120

0

0.436

0.698

0.550

0.778

1

1

123

0

0.525

0.667

0.556

0.000

1

2

0

0

0.406

0.526

0.533

0.633

1

2

3

0

0.435

0.600

0.769

0.500

1

2

20

0

0.437

0.524

0.643

0.577

1

2

23

0

0.442

0.433

0.833

0.833

1

2

100

0

0.433

0.554

0.561

0.727

1

2

103

0

0.456

0.575

0.556

0.556

1

2

120

0

0.454

0.551

0.636

0.750

1

2

123

0

0.472

0.515

0.636

0.600

A full listing of run expectancy at every game state would take up pages and pages–this is just a smattering. (Since we’re looking at the top of the first, we can helpfully exclude all scenarios where the home team is trailing, as negative runs simply aren’t possible.)

But just to pull out an example, a team with runners on second and third, no outs, at the top of the first with one run already scored has a 57 percent win expectancy. Loading the bases after that increases the odds of a victory to 82 percent. The difference between the two is the change (statisticians like to use the fancy word “delta”) in win expectancy, or in this case, 25 percent. (Note that I’m just subtracting, not taking the product or anything.)

What I want to emphasize is that win expectancy is a prediction–it expresses the probability of a win. And that probability will tend to go up as the game goes on. Consider the average distance of the current win expectancy from .500, according to the number of batting outs the home team has recorded:

Win expectancy change

Over the course of a game, win expectancy tends to grow closer to either one or zero, depending of course on whether the home team is faring well or poorly. This is because our certainty in the outcome becomes higher the closer we get to the final out.

What I want to emphasize is that the arrow of causation runs in one direction. Consider the very start of a game where the batter leads off with a double. That gives us a change in win expectancy of .085. Now suppose the next batter also hits a double; the change in win expectancy is .224. In other words, the second double appears to be about 2.6 times as valuable as the first.

It helps if we remember what win expectancy is: a prediction of the final outcome of the game. The second double tells us much more about the final outcome of the game than the first does, but in terms of scoring that one run, each is equally as valuable; if that one run is decisive, each double is equally responsible for the outcome. If you replaced the first double with an out, it has the exact same impact on the game outcome as if you replaced the second double with an out.

But because of the way we’re measuring things, there’s no way for us to account for the way the second double changes the value of the first, and no way to avoid attributing some of the value of the first double to the second. This isn’t necessarily a flaw in win expectancy–it is accurately reporting the current probability of a win, given its input parameters–but it is a flaw in attributing the entirety of the change in win expectancy to the player currently standing at the plate.

So we’ve looked at how the first plate appearance of the game affects the second, in terms of in expectancy–but isn’t limited to that. You have effects of the first plate appearance on the second, but also the third, fourth, fifth… there's a cascade all the way down the line. The more PAs you add to the chain, the harder it is to discern the effect of one from another.

The Archimedes Problem

Another way to consider the problem is in terms of the potential change in win expectancy in any given plate appearance–it’s the idea of leverage. There are a few different ways of calculating leverage; here at BP we’ve used LEV, while at Fangraphs and Baseball-Reference.com they use Tom Tango’s Leverage Index. While the methods do differ in some regards, the core principles we’re discussing here remain the same.

What leverage (in whatever form it comes in) tells us is how much of an effect that plate appearance can have on the prediction of the game outcome. Plate appearances in close games (especially close and late) have a greater effect on our expected outcome than plate appearances in games with a large run differential between the two teams, and this is truer the later in the game it gets.

Leverage is derived from win expectancy, so everything we’ve said about that carries over to leverage. Leverage travels in only one direction; players can create or destroy leverage for the players after them, but they cannot benefit in the same way from the actions of the player after them.

That’s the most important point about leverage: it isn’t a fixed quantity. If it were, it would be as simple as looking at high-leverage situations and who performed well in them. But there’s an additional consideration, and that’s how well a player did in creating leverage for his teammates. Closers, by the very nature of their role, pitch largely in high-leverage situations. But they rarely, if ever, contribute leverage to their teammates.

Which brings me to the power of myth-making. Metrics that incorporate a relief pitcher’s leverage but ignore his ability to create leverage for others paint a skewed picture of how relief pitchers create value. Teams that hold their most valuable bullpen arms in reserve waiting for save chances may be winning more close games (although not as many as they may think), but the cost may well be staying closer in fewer games to begin with.

Thank you for reading

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BurrRutledge
1/19
Colin, another kick-ass article.

I also think that Cashman & Co. have already come to the same conclusion, as they are now paying their closer the same amount as their best set up guy. Good job, Yankees!
dianagramr
1/19
Well, the Soriano decision wasn't Cashman's, but you are right.

Also, if you can't find a decent #3/4/5 starter, you best try and build the strongest, deepest bullpen you can.

The issue with the Yanks is ... did they already have the bullpen answers in house? Does Moneyball's "reliever fungibility" still exist?
BurrRutledge
1/19
I agree completely.

I suppose I should have said, "Steinbrenner Siblings" but I prefer the ring of "Cashman & Co" regardless of whether the decision originated in Tampa.

I suspect that fungibility of relievers does still exist, as much as it ever has. Given enough opportunities (ie sample size), if a guy can get batters out in the 7th, he can do it in the 9th.

And, just to expound on the point, the reverse is also true. If a guy in today's game is 'closing' in the ninth, then he damn well can come into the game in the 7th with the game on the line in the playoffs (note to Girardi). Get your best guy in to put out the fire.

Can we create and publicize a new LEV-based award (i.e. "Fireman" or "Rally-killer"), and publicize it? The guy who pitches in the highest LEV situations outside the 9th inning wins the award.

How can we see that LEV leaderboard with the sortable stats?
MWSchneider
1/19
I have never understood the strategy that many managers use on the road in saving their "closer" for a situation where they have the lead, even if it means potentially losing the game before. If the closer is theoretically your best relief pitcher, what sense does it make to leave him on the bench (e.g. during an extra inning game) and possibly let an inferior pitcher lose the game. The idea seems to be that only the "closer" can actually close out the game and, apparently, that it would be much worse to lose the game after you get the lead than to lose it, say, in the bottom of the tenth of a tie game. That drives me nuts; if you get the lead, there are potentially many ways to piece together three outs, if you have already used the closer, but if you lose the game before, what have you saved the closer for?
cwyers
1/19
Yeah, that's pretty much the most frustrating thing you can see a baseball manager do, in my book.
nateetan
1/19
I'm pretty sure that a huge part is that nearly 100% of the players believe the maxim that the final three outs of the game are the hardest.
LynchMob
1/19
What does "hardest" mean? Isn't a large part of that being "mental" ... ie. if players believe it to be "hardest", then doesn't that make it true?
studes
1/19
Excellent article, Colin. I think that's the best job of articulating the issue I've seen--not the issue of "after the game, everything is the same," but the issue of "diminishing leverage for those who come later in the game." Different things, I think.

Anyway, I'm someone who is okay with the way WE works. Guess I'm an "in the moment" kind of guy. But I wonder if there is some way to develop another system that accounts for "game impact" in the moment but also incorporates the idea of "creating leverage."

I've done a few things along those lines, such as writing about giving weights to batting and pitching events based on how close each game turned out to be, but that's probably just the tip of the iceberg.
cwyers
1/19
I'm okay with the way WE works, too - if you ask it a question, it'll give you the correct answer (given the inputs, that is). And there are a lot of applications of win expectancy that I love, like the live win probability graphs. It's just a matter of making sure we ask good questions and understand the answers we're getting.

As far as a different framework - I mean, I think it may be possible. I don't really have any good ideas on how to DO it, is the sad part.
TangoTiger1
1/19
Studes' solution here is one of the best ones actually. He should link to it...
studes
1/19
Here it is. I forgot that it was inspired by a BPro article.

http://www.hardballtimes.com/main/article/long-live-baseball-analysis/
BurrRutledge
1/20
Very nice article! Thanks for sharing. Makes me wish there was more cross-posting among the leading sites.
mikefast
1/20
1. Agreed. I'm happy to see studes here and always love reading his stuff.

2. I know Tommy used to do links roundups both back when he was at Beyond the Box Score and since he came here to BP. Is there a desire to see more of that?

3. A lot of the sharing of links and ideas among saber folk from different sites happens on Twitter these days.

4. The different leading sites tend to have different philosophies about things which leads to certain ideas/topics being popular on one site and relatively ignored on another.
BurrRutledge
1/20
I remember the links that Tommy would put up with the one sentence blurbs. To be honest, that was rarely enough of a hook to get me to click through (though I did from time to time).

I'd suggest that BP reach out to a few of the other sites and see if they would be interested in cross-posting to BP for a "best of" series. Each site would agree to submit a couple paragraphs as a hook to an article, with a link to the rest of the article. All topics would be fair game. Perhaps, in exchange, the other sites would do the same for one "best of" BP article. If it's pay-only content, perhaps they publish the whole article, for discussion at their site.

I know I would certainly be interested in that, especially since BP no longer adds new content on the weekends.

Obviously, this only works if other sites are interested, or if they are interested in cross-publishing a link to a BP article.

Please take it under consideration. Thanks!
TangoTiger1
1/20
Is there a reason that BPro members can't email each other directly (we can setup our profile to allow us to be reachable or not). Anyway, BurrRutledge: email me a tom~tangotiger~net , and replace ~ as appropriate.
cwyers
1/20
Well, there are any number of hurdles. You want to make it a system that isn't giving people unwanted e-mail - either from spammers or from other commenters. I mean, that isn't to say those hurdles can't be solved, but it's an opportunity cost - time spent working on that is time that can't be spent elsewhere. My feeling is that there are quite a few things that readers would appreciate more, so I think we'll focus on those for the time being. Doesn't mean it won't EVER happen, of course.
BurrRutledge
1/20
I'm also reminded of the article BP posted last year with research (by Bradbury, if I remember correctly, where he posited a peak year much later than others have demonstrated, but he had a sample-bias where he was limited his sample to players who would qualify for the Hall of Fame).

At any rate, publishing the article was hailed as a leaf-turning moment, and we were led to believe that more of this kind of work would be featured at BP. Whether or not there was follow through on that aspiration last year, this could be an extention of it now...
mikefast
1/20
I'm on board with the basic idea (though, I'm not on staff, so implementation is not strictly my purview), but I hate the example.

I personally was very disappointed when BP published Bradbury's work on aging after its deficiencies had been identified and thoroughly discussed by the rest of the sabermetric community. To me that was a low point for BP. I know some people felt otherwise, but for my part, I would much rather see examples of the best work from around the sabermetric community published here rather than the poorest quality work.

Lest it be unclear, I'm not advocating that everything published at BP must have the same mindset. Far from it. I think different viewpoints are great, and ideas that challenge the mainstream thought are valuable. My own ideas about how baseball works and what is important for sabermetrics don't fit very well with a lot of mainstream sabermetric thinking these days. But there is no sense in getting controversial viewpoints while abandoning the principles of sound logic. Or even a step back from that, publishing outside viewpoints that may have some support in the sabermetric community but which the bulk of the leadership at BP believe are fundamentally flawed.
BurrRutledge
1/20
Agreed re: the Bradbury piece. Interesting research, bad conclusions because he over-reached given his experimental design.

What I meant regarding the publication of that piece was that Kevin (I think it was Kevin) had indicated that there would be the first of many "outside" sabermetric pieces to get included at BP, though no others stand out in my mind at this time (though I'm also open to the possibility that they were there and I just don't remember them.)
bornyank1
1/26
I'm late to this thread, having been buried in BP2011-related tasks, but stay tuned for some (hopefully) exciting news on this front in the very near future.
ScottBehson
1/19
Joe Poznaski wrote on this topic about 2 weeks ago and showed that the % of games teams won after leading close in the 7th and 8th innings have barely budged from the "pre-closer days" to the "modern closer days". For example, "Teams held 95.5% of their ninth-inning leads in 2010. Teams held 95.5% of their ninth-inning leads in 1952."

http://joeposnanski.si.com/2010/11/26/the-age-of-the-setup-man/
ostrowj1
1/19
I realize that Poznaski is not a researcher (something he admits to in the referenced article), but 1952? Why 1952? Because it is the data point out of 70 or 80 that makes his point the best. It is hard to make observations from cherry picked data.

One thing that has not been mentioned here (or in Joe's article) is the (what I assume to be) increase in the use of pinch hitters that coincide with "closer". The last 3 outs may be "harder" (better quality of hitter verse the closer) than 3 outs made in a random inning. My hunch is that the first graph minimizes the true impact of closers (to what extend, though, I do not have any idea).
ScottBehson
1/19
Yes, but the number has bounced from 93-97 percent through baseball history.
juiced
1/19
Trevor Hoffman's entire hall of fame case is built around the mythical power of the save statistic instead of an objective evaluation of whether he caused his team to win more games than all but 1% of the baseball players in history. He didn't do the latter, not by a long shot.
gyoung858
1/20
The 1% standard effectively eliminates the HOF case of every reliever in history. I can see merit in that argument, although it has nothing to do with Hoffman beyond the fact that he is part of the subset of players which such a standard would exclude.
chaneyhey
1/19
The article fails to take into account that the utilization of the "closer" may be an adaptation to modern offenses. Stated another way, in order to keep things status quo, the "closer" was a necessity. Just playing devil's advocate.
cwyers
1/19
Well, no, that was accounted for. That's why the "clean rate" was baselined against the league average. The change in clean rate, after accounting for changes in offense, doesn't strike me as having practical significance.
joelefkowitz
1/19
Was going to post this, but was beaten to the punch. Can we necessarily conclude that if bullpen usage hadn't changed, the numbers would have been what they are?
Schere
1/19
Does the second chart say anything of value? The incidence of one-run leads looks to be correlated to the overall run-scoring environment.
Schere
1/19
oh, sorry to post a quick negative...I do like the article & find it thought-provoking. The chart is hardly central to your work here...all the more reason for me to wonder why it's there.
studes
1/19
Yes, that is my reaction, too. The point would be that closers have more value in low-scoring environments.
LynchMob
1/19
Such as Petco ...
tbwhite
1/19
I'm having a hard time accepting this argument.

Let's move your 2 double example to the bottom of the 9th of a scoreless game. What if instead the first batter doubled, and the 2nd batter homered ? Clearly the first batter was irrelevant to winning the game, so he doesn't deserve any credit for the home run. In fact, you could argue that the second batter is punished because the delta in win expectancy is reduced by the 1st batter's double, what's fair about that ? What if after the leadoff single the next three batters strike out ? Shouldn't the leadoff batter be punished somehow ? Why can he only be rewarded for the actions of others ? If I should get credit for doubling to lead off, if the 2nd batter also doubles to drive me in, then why shouldn't I lose extra credit when someone homers after I struck out, after all I cost my team a run ?

Also, what's the deal with the win expectancy table, am I reading it wrong ? It looks like if a batter comes up to leadoff the game the win expectancy is 44%. If the batter homers to leadoff, the win expectancy increases to 47%, but if the leadoff batter triples the win expectancy is 64% ?
WaldoInSC
1/22
In fact, at the risk of nitpicking a splendid piece, the win expectancy table is a disaster.

It says that with two runs in, runners on the corners and no out, the visiting team is a mortal lock to win -- in the first inning! In fact, it claims there are seven first inning scenarios that make victory certain.

It says that the visiting team has a 44% chance of winning to start the game, but open with a triple and the win expectancy rockets to 64%.

It says that if the visiting team juices the bases with one out and three runs in, it is doomed to defeat. With just a two run lead, it would win 56% of the time and with just a one run lead, it's a 2-1 favorite.

This is all patent nonsense, in stark contrast to the rock-solid logic of the accompanying article.
mikefast
1/22
A quick look at some of the numbers suggests to me that the sample sizes in some of the boxes are very small. For example, .636 is 7/11, .556 is 5/9, .375 is 3/8, etc.

If you choose to use the numbers, you have to use them with that understanding, or acquire a much bigger sample if you want all the numbers in all the boxes to be accurate.
rweiler
1/19
You are preaching to the converted. It seems like managers would do better if they always brought in the best pitcher available for a particular situation.
adamst
1/20
I think it relates to sample size -- this is based on actual results from the 2010 season. I'd guess in games with a man on third and no one out, the visiting team won 7 of 9, exactly (maybe 14 of 18).

Also while it notes the chart is home team win expectancy, it looks like batting team win expectancy.
yadenr
1/20
Hold on- are you saying Baseball is not religious in nature?
juiced
1/20
"The 1% standard effectively eliminates the HOF case of every reliever in history"

As well is should. They just dont have enough impact on creating enough wins to get into the HOF as the best of the best players. Leaving someone like Ron Santo, or McGwire, or Palmeiro, or Blyleven before this year out and letting Hoffman in, personality and politics aside, cheaps the "objectively great" standard beyond all recognition.

Now on the other hand if the HOF changed things to allow for votes by position, so you could vote for DHs going in "as DHs", well then I'd vote for Edgar Martinez in a heartbeat. Same with closers or relievers. If there was a separate category I'd vote Hoffman in in a heartbeat.

But there is not a separate category, all players are lumped in together, and if those old school curmudgeons intend to keep anybody who played in the modern era out on the mere guilt by association with roiding, then I say let the closers wait too.
LynchMob
1/21
A concern I have about the "votes by position" is whether or not "backup catcher" is a position? Isn't a reliever just a "backup starter"? Sorta :-)

Could there be a place in the HOF for the best backup catcher of all-time?

Eh, now I'm just getting silly ...
juiced
1/20
sorry for my lousy spellchecking. . is=it, cheaps=cheapens