GM's OFFICE: The fracturing saves market

I was on vacation a couple of weeks ago. At the beach and (mostly) unplugged from email, I had a bunch of reading material backlogged when I got home. Amid the otherwise-tedious task of cleaning out my inbox, I had the distinct pleasure of catching up on several editions of the Joe Sheehan Newsletter. Joe is a recurring guest on our podcast, presenter at First Pitch Arizona, and one of the smartest baseball analysts around. His newsletter is a must-read for any serious fan of the game.

(Hopefully the above endorsement is sufficient remediation for blatantly lifting his work. Thanks in advance, Joe... )

On August 23rd, Joe dropped an edition of his newsletter entitled "The Hoffman Peak," in which he discussed the changing model of closer usage, primarily driven by this chart:

Closing Out Closers? (Fewest 30-save seasons, 1998-2017)
2017  11
2003  12
2001  14
2010  14
2008  15 
2012  15

There were 21 30-save seasons just three years ago, the most on record. Since then we’ve had 16, 11, and now on pace for about a dozen. 


Joe's writing isn't (generally) focused on fantasy implications, but obviously we fantasy players take a keen interest in saves. Piggy-backing on Joe's findings here, I decided to run a deeper study of saves distribution, using the same general model that I used in analyzing the catcher pool a couple of weeks ago.

The evolving closer role

Here's a 10-year scan of MLB-wide saves distribution by pitcher. The rows are inclusive, so each row includes all of the players who qualify for that row and all rows further down in the table. In other words, the >15 Sv line includes all of the >20, >25, etc saves guys for that year as well.

        2018   2017  2016  2015  2014  2013  2012  2011  2010  2009  2008
======  ====   ====  ====  ====  ====  ====  ====  ====  ====  ====  ====
> 5 Sv    50    51    52    44    46    41    46    44    45    44    44
>10 Sv    35    36    41    35    38    36    36    34    35    34    35
>15 Sv    22    28    28    31    29    32    31    29    30    29    27
>20 Sv    17    22    21    27    25    28    26    27    27    26    22
>25 Sv    11    16    18    22    20    22    18    21    18    21    20
>30 Sv     8    10    15    19    17    19    15    18    13    15    12
>35 Sv     4     6    12    11    12    14    10    13    11    12     8
>40 Sv     1     3     5     4     7     6     5     7     5     4     6
>45 Sv     1     1     4     2     3     3     2     3     2     2     1
>50 Sv     1     0     1     1     0     0     1     0     0     0     1

That's a lot of data. Let's try a graphical representation:

That's a bit of an eye chart. For reference, the years are arranged left-to-right in each cluster, with 2018 at left. You can see a couple of Joe's points pretty evidently: On the >5 saves cluster (left-most), note that the first three bars (most recent) in that cluster are the tallest... and the 2018 (blue) bar still has three weeks to grow. As you scan across each cluster, note how within each successive cluster (more saves), those first blue and orange bars (most recent) are consistently the shortest in each cluster.

Let's break that chart in half so we can see it a little better. First, the lower saves totals:

Clearly, the population of pitchers getting >5 and >10 Saves is on the upswing. But keep in mind that still includes the pool of full-time closers. Let's zoom in on their side of the chart:

Again, 2018 still has a few weeks to close some of the gap against prior years. But three weeks of saves aren't going to move the needle that much. The decline of the >25 and >30 save reliever is hard to deny from this view.

Of course, league-wide saves aren't going down, so those missing saves have to get redistributed somewhere.

Given how I set up these tables to be inclusive of all larger totals, even these two views still sort of obscure the overall impact. Let's look at saves distribution by tier of saves total, in a non-inclusive view:

To digest this view, just look at the "lean" of each cluster. The recent ones (left side of the chart) are all "leaning" to the left: the first two bars (lowest saves totals) are the tallest. As you move across subsequent clusters, toward the middle and right of the chart you see much less "lean" in the clusters: they are fairly well-balanced, even leaning to the right in a in a couple of cases (2013, 2015). What we're seeing in 2016-18 is very different from just a few years ago.

To be even more explicit, my main takeaway here is that we're seeing the emergence of a new class of reliever. In this age of "Openers", etc, we're going to need a name for this guy. I'm going to call him the "Par-closer":


There are any number of strategic implications for our games. In no particular order:

  • The way we project saves needs an overhaul. There are no longer as many relievers getting 80%+ of their teams saves as we project every preseason, and it's time we steered into this skid and acknowledged that in our projections process.
  • A more fractured talent pool for saves contributors should mean that it takes fewer saves to compete in the category, which in turn further opens the door to creative strategies to try and manage the category.
  • The model for how we pay for saves needs to change to reflect this. If you are confident that a particular reliever is a 35+ saves guy, then you should be willing to pay even more for him, because of what he gives you relative to that category target/need. But if you don't believe in a guy, there's less incentive than ever to pay for him just because he has the "closer label" in March.
  • How do you plan your bench, and manage your FAAB, in terms of positioning your team to cycle through these par-closers as they emerge (and subsequently disappear)?
  • Looking at pitcher skills, overall bullpen composition, and managerial tendencies, can we do a better job of predicting in advance which relievers are going to work their way into this tier... both from above (projected closers) and below (projected non-closers)?

Consider this a seed planted in your mind as you go through your own reflections on 2018 and begin planning for 2019. We'll certainly have more to say on this in the offseason ahead.

In the meantime, please chime in with any other thoughts, or additional implications, in the comments area below.


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  For more information about the terms used in this article, see our Glossary Primer.