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.
| 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 | 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 | 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.
| 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.
| 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
| 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.
| 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
| 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 twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.
Do you have any data on the incumbent closers and how they performed? Did they keep the job?
I didn’t do any in-season work. It was a pain to pull together the preseason data. Maybe if I have a week of my life to completely waste, I will look into it.