How Teams’ Initial Closers Performed

Over the past week, I have collected information on how spring training closers battles have worked out from 2013 to 2016. Today, I go over the results. It’s now time to release the tables.

The first set of data shows how the team’s initial closer fared.

Eventual Results for Season’s Initial Closers
Season Count %
Closer from beginning to end 47 39%
Lost to injury 26 22%
Poor performance 29 24%
Traded away 9 8%
Traded for 3 3%
Suspension 2 2%
Replacement returned 4 3%

Just 40% of closers were able to make to the season’s end. About the same percentage lost their jobs to injury and poor performance.

The next table shows how these closer groups were projected to perform according to their Steamer projected ERAs.

ERA and Results for Initial Closers
ERA Average Median
Closer from beginning to end 3.03 3.08
Lost from injury 3.17 3.16
Poor performance 3.37 3.33
Trade away 3.47 3.51
Traded for 3.37 3.43
Suspension 3.29 3.29
Replacement returned 3.21 3.24
Overall 3.19 3.24

The closers who kept their jobs were about 0.15 runs better than the average and 0.30 runs better than those who lost their job because of performance. Additionally, the pitchers who got injured were close to the overall average. Finally, many of the closers moved at the trade deadline were below average. It seems like teams want to add a closer but not pay for a good one.

Now, I will examine the same data points but group by ERA.

ERA Range and Results for Initial Closers
ERA Range Whole Season Poor performance Injury Other Count
< 2.50 70% 10% 10% 10% 10
2.50 to 3.00 48% 9% 39% 4% 23
3.00 to 3.50 35% 31% 18% 16% 55
>3.50 31% 28% 19% 22% 32

First, closers with an ERA over 3.00 are three times more likely to be replaced for poor performance than those with an ERA under 3.00. Additionally, there is a nice steady drop in pitchers making it as a full season closer as their ERA increases. I found the average ERA of each group and determine two best-fit equations from the data.

Equation #1 (r-squared = .93): Full season closer chances = -0.2454*Projected ERA + 1.1888
Equation #2 (r-squared = .98): Full season closer chances = 2.137*Projected ERA^(-1.488)

Instead of using the formula, here is a chart with some simple rates.

Projected Full Season Chances for a Projected ERA
ERA Equation #1 Equation #2
2.00 70% 76%
2.50 58% 55%
3.00 45% 42%
3.50 33% 33%
4.00 21% 27%
4.50 8% 23%

Time to put these numbers to use. Here are the chances a pitcher (10 or more projected Saves) will keep the closer’s role if he starts with the job.

Projected Full Season Chances Potential Closers
Name Team SV ERA Equation #1 Equation #2
Andrew Miller Indians 12 2.04 69% 74%
Aroldis Chapman Yankees 35 2.33 62% 61%
Zach Britton Orioles 34 2.38 60% 59%
Kenley Jansen Dodgers 33 2.38 60% 59%
Wade Davis Cubs 30 2.48 58% 55%
Mark Melancon Giants 34 2.63 54% 51%
Edwin Diaz Mariners 33 2.76 51% 47%
Seung Hwan Oh Cardinals 32 2.92 47% 43%
Kelvin Herrera Royals 33 3.00 45% 42%
Craig Kimbrel Red Sox 32 3.01 45% 41%
Ken Giles Astros 30 3.03 45% 41%
Jeurys Familia Mets 25 3.07 44% 40%
Cody Allen Indians 16 3.10 43% 40%
Roberto Osuna Blue Jays 34 3.13 42% 39%
Alex Colome Rays 31 3.13 42% 39%
Shawn Kelley Nationals 30 3.20 40% 38%
Cam Bedrosian Angels 27 3.21 40% 38%
Raisel Iglesias Reds 18 3.23 40% 37%
A.J. Ramos Marlins 28 3.33 37% 36%
Tony Watson Pirates 30 3.35 37% 35%
Addison Reed Mets 12 3.36 36% 35%
Joaquin Benoit Phillies 10 3.38 36% 35%
David Robertson White Sox 29 3.46 34% 34%
Sam Dyson Rangers 30 3.54 32% 33%
Greg Holland Rockies 23 3.56 32% 32%
Arodys Vizcaino Braves 22 3.58 31% 32%
Francisco Rodriguez Tigers 33 3.59 31% 32%
Drew Storen Reds 16 3.68 29% 31%
Jim Johnson Braves 14 3.71 28% 30%
Adam Ottavino Rockies 14 3.73 27% 30%
Ryan Madson Athletics 25 3.78 26% 30%
Fernando Rodney Diamondbacks 28 3.85 24% 29%
Brandon Maurer Padres 26 3.90 23% 28%
Brandon Kintzler Twins 24 4.00 21% 27%
Neftali Feliz Brewers 27 4.12 18% 26%
Jeanmar Gomez Phillies 20 4.32 13% 24%

Now that the chances are known, the ‘when’ can be examined

Here are the average and median date for a pitcher losing his role

Average and Median Dates When Closer Replaced
Change that happened Average Date Median Date
Poor Performance 06-04 05-18
Injury 06-18 06-05
Trade involved 07-23 07-27
All 06-16 06-11

On average, owners can expect a non-trade move to happen around June 1st with trades happening at the trade deadline (rocket science). Besides the average and median dates, here are the accumulated rates by month.

Accumulated DL Chances Over the Season
Month Injury Change Poor Performance Change All Change
March/April 23% 23% 31% 31% 25% 25%
May 42% 19% 52% 21% 42% 18%
June 58% 15% 79% 28% 60% 18%
July 81% 23% 83% 3% 84% 23%
August 88% 8% 86% 3% 89% 5%
September. 100% 12% 100% 14% 100% 11%

Changes happen early and stay steady for the first four months. Then for some reason in August, no one gets hurt or performs badly. I am still wrapping my head around this finding. I wouldn’t be surprised if the drop involved teams being stuck with their closers after the trade deadline.

One final piece of information for today, here are some numbers for teams with a closer competition going into spring training

Results For Closers Who Started Spring Training In Competition
Stat Value
Average ERA 3.43
Median ERA 3.57
Full season role 31%
Average date for change 06-12
Median date for change 06-07

The reasons teams have a closer competition is their talent sucks. Remember, these are the pitchers who initially won the closer’s role. The other canidates were probably worse. Additionally, the 31% survival rate is right in line with the formulas which project a 31% to 35% rate of holding the job for a full season.

I am sure I can tease some more tidbits out of the data, but I am done for today. Please let me know if there are any additional pieces of information you would like to have available. For now, I am just going to let the information stew around in my brain and will look at the data at a later date.





Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR once, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.

25 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments
You've Been Uniac'd
5 years ago

Do you have any data on the incumbent closers and how they performed? Did they keep the job?