Closers are probably the most exciting, frustrating position to deal with from a fantasy perspective. No other position is as fundamentally shaped by managerial discretion. No other position sees player value fluctuate so wildly. Last year, baseball’s most dominant closer, Mason Miller, lost his job to  Robert Suarez at the trade deadline, for reasons wholly unrelated to performance–Suárez simply had performed admirably as closer, and the Padres preferred not to mess with their bullpen hierarchy, even if Miller was their best reliever. This offseason, Suárez himself appears to have already lost his closing job for reasons unrelated to performance, as he has opted for a setup role with the Braves.

This article ranks the closers for saves-only leagues for 2026. These rankings will be updated roughly once a week to reflect the latest happenings. The rankings will shift based on trades, free agent signings, team news, rumors, new projections, sufficiently persuasive reader feedback, and my own arbitrary whims. The list will grow longer as the offseason progresses.

Changelog

• 1/8/2026
  • Angels sign Kirby Yates.
    • Given his extensive closing experience and Robert Stephenson’s trouble staying healthy, Yates vaults to the top of the Angels hierarchy for me, joining the third tier, while Stephenson drops down to tier four.
  • Noteworthy OOPSY projections.
    • This year’s OOPSY projections should be published at some point in the next 24 hours, joining other published FanGraphs projections, Steamer, THE BAT, and (partially) ZiPS. Focusing on ERA projections, here are some relievers OOPSY is bullish on relative to the other systems: Andrés Muñoz (2.51), Griffin Jax (2.68), and Trevor Megill (2.93). OOPSY’s optimism on Muñoz is likely park-related, as it makes use of Statcast park factors that view T-Mobile as more pitcher-friendly relative to FanGraphs park factors. OOPSY’s Jax projection suggests he is one of baseball’s best relievers; he is no lock to lead the closing committee for Tampa, but he has huge upside if he is able to win a large share of the job. Megill’s projection would make him a worthy closer for many MLB teams, but OOPSY is even higher on Abner Uribe. In any case, the Brewers closer situation remains one of the most difficult to parse this offseason.
  • Closer Monkey and RosterResource – Closer Depth Charts disagreements.
    • Closer Monkey and RosterResource are two indispensable sources for understanding bullpen hierarchies and saves situations. They tend to agree more than they disagree, with the two sources currently listing the same name at the top of the hierarchy for 26 of 30 teams. There are four teams where they disagree: the Rays, the Brewers, the Diamondbacks, and the Athletics. I currently side with Closer Monkey on three of those four, also preferring Griffin Jax, Kevin Ginkel, and Mark Leiter Jr. to lead their respective hierarchies, while I am aligned with RosterResource on Abner Uribe over Trevor Megill for now–in large part because I think Megill will be traded to a situation where he may not close. Additionally, I deviate from both sources only on two teams: I have Kirby Yates leading the Angels hierarchy, while both still prefer Robert Stephenson; I also have Kody Funderbunk leading the Twins hierarchy, although that situation is so volatile that I’d guess that their 2026 saves leader is someone that’s entirely off the radar at this point. In any case, from a fantasy perspective, the teams with disagreement are the most interesting–and volatile.
•  12/28/2025
  • Marlins sign Pete Fairbanks.
    • It’s a great landing spot for Fairbanks as he should be the sole closing option in Miami. Accordingly, Calvin Faucher and Ronny Henriquez have been removed from the ranks. Henriquez would have been removed even if he were healthy as a result of the Fairbanks signing, but it was also announced that he is slated to miss the 2026 season after undergoing UCL reconstruction surgery.
  • Kenley Jansen is not guaranteed the closing job.
    • It is still difficult to imagine him not handling most save opportunities given his track record but at this point in his career his projections are less than stellar. I added Will Vest to the backend of the ranks as he has much better projections and was used ahead of Kyle Finnegan to close out games at the end of the 2025 season.
  • The White Sox sign Sean Newcomb.
    • Newcomb will be given the chance to start, but he is still a nice late sleeper option for saves as he is more experienced than Jordan Leasure or Grant Taylor, plus he is coming off a strong 2025 season out of the pen.
  • Diamondbacks are expected to sign a closing option to fill the role until Justin Martinez and A.J. Puk are ready to return in late 2026.
    • The only issue here is there aren’t a ton of great bullpen options left in free agency. Per RosterResource’s Free Agent Tracker, some standout remaining arms that might step in as closer are David Robertson, Kirby Yates, Ryan Pressly, Seranthony Dominguez, and Evan Phillips. If signed by Arizona, I would likely prefer any of these guys for saves over Kevin Ginkel.
• 12/18/2025 – First Release

Ranking Methodology

• ADP is based on 30-day rolling NFBC Draft Champions Leagues.
• $ Values are based on standard 5×5 12-team saves league using the FanGraphs Depth Charts and these Auction Calculator settings. They default to a player’s most valuable position, so if the first base list includes a catcher, it will show that player’s value at catcher.
• ADP and $ Values are updated as of the last update date on this post.
• 5-game eligibility was used for these lists to cast the widest net.

Full Rankings Without Tiers

Katie Stratman-Imagn Images

A few days ago, I asked for help to double-check this season’s initial closers (full 2024 edition).

Here are the results, starting with the initial closers and their performance.

Read the rest of this entry »

In early June, Alex Chamberlain graced us with a FanGraphs article about Brendon Little and a new concept called, “Implied Miss Distance”. Chamberlain, along with Baseball Prospectus writer/researcher Stephen Sutton-Brown, have done some great work utilizing Statcast bat tracking data, giving readers a new perspective on something like a swing and miss. But, back in early July, nearly a month after Chamberlain wrote about Little’s amazing knuckle-curve and it’s ability to make hitters whiff so hard that the outfield flag flutters, hitters stopped chasing the pitch. They were tired of looking silly and would no longer budge, allowing us to imply nothing:

If it wasn’t for Chamberlain’s article, I wouldn’t have known about Little or his knuckle-curve. But that’s why FanGraphs is the best, and when I recently watched the Blue Jays and their relievers’ deteriorating August WHIP, I heard the broadcasters mention Little’s falling O-Swing, or chase, rate.

If you only focused on Little’s knuckle-curve and the damage hitters have done to it in each month of the season, as you see in the table below, you wouldn’t think twice about the pitch’s performance:

Among pitchers who have thrown at least 100 knuckle curves in any of the last five seasons, Little’s 2025 wOBA of .188 is a fringe top 20 (25th) out of nearly 200 pitchers. Last season, Little got even closer to the top 20 mark (23rd) with a .186 wOBA on the pitch. But the broadcast never said anything about Little getting hit; they were focused on the lack of chase and, therefore, an increased BB%:

The chart above includes all of Little’s pitches. By isolating the O-Swing% to only his knuckle-curve, we can see that this overall drop in hitters’ chasing after Little’s offerings wasn’t solely because of them spitting at that specific pitch:

Thanks to the incredible addition of the Pitch-Type Split Leaderboard by the FanGraphs web team, we can now view the averages of individual pitches with ease. In 2025, among all pitchers who have thrown at least 10 knuckle curves, the league average O-Swing% currently sits at 35.5%. Little’s mark on the season is 36.5%. Rolling averages are different from season averages, and when Little’s chase rate rolling average dipped, so did the chase rolling average of his two other pitches:

Chart 4 – Rolling KC, FC, SI Chase% Comps

The straight red line indicates times when Little stopped throwing his cutter. It’s interesting to see how the line stopped running horizontally around the same time his knuckle-curve was at its worst. Unfortunately, it didn’t fill the chased pitch gap, and that 40-50 game mark fell around early to mid-July when Little’s WHIP went upwards:

Hitters weren’t getting boosted wOBA’s from Little’s lack of chase, but the 1.65 WHIP  (5.97 eqiuv. ERA) meant they were hitting his other pitches and walking more. I’ve been rambling on about Little for more than a few paragraphs now, and you’re probably waiting for the point. The point? The point is, pitchers need to adjust when a pitch that used to be chased no longer gets chased. They know that. We know that. Yet, it’s difficult to keep track of on the fan side of things. Pitchers will go about adjusting in all sorts of ways.

In Little’s case, it was really just a blip. If you go back up to the graph showing individual pitch chase rates, you may notice that Little’s usage of the cutter, even if it wasn’t chased, allowed the chase rate on his knuckle-curve to jump back up. Hitters did a great job of laying off Little’s knuckle-curve from around games 30 to 70, but excellence is when a pitcher can adjust in the moment to hitters. That’s robotic. So, let’s!…get!…robotic! For the remainder of this article, I’ll present a detection system that can run daily to capture when a pitcher’s most used fastball and most used secondary are in good or bad rhythm using individual pitch plate discipline metrics. Here’s an example from Little’s 40 to 80 game span:

The table is just a summary of what you see in Chart 4 above, but it’s designed to be placed in an automated system. If chase is up on one pitch and called strike is up on another, that’s good. If both pitches are falling to generate either chase or called strikes, well, that’s bad. Categorizing the balance between his sinker’s called strike rate and his knuckle-curve’s chase rate is as simple as creating rule-based logic:

conditions = [
(final_df['Rolling_Chase%']-3 > final_df['smart_median_chase']) & (final_df['Rolling_CStr%']-3 > final_df['smart_median_cstr']),
(final_df['Rolling_Chase%'] <= final_df['smart_median_chase']) & (final_df['Rolling_CStr%'] >= final_df['smart_median_cstr']),
(final_df['Rolling_Chase%']+3 < final_df['smart_median_chase']) & (final_df['Rolling_CStr%']+3 < final_df['smart_median_cstr']), (final_df['Rolling_Chase%'] >= final_df['smart_median_chase']) & (final_df['Rolling_CStr%'] <= final_df['smart_median_cstr'])
]
# Define the corresponding categories
categories = [
'Excellent',
'Ok (Adjusting)',
'Bad',
'Ok (Adjusting)'
]


Using the pitcher’s median values allows the categorization to detect improvements by each individual. I’m using “smart” medians to call the league median if a player has a zero value. That happens when they haven’t generated any chase or called strikes. If we use Brendon Little’s game logs to isolate his performance during those game periods from the table above, we see some pattern in a very small sample:

Little was at his best when he was in decent balance. This is the type of tracking that could be useful when streaming pitchers or looking for hot relievers. To test this out on a grander scale, I built a dataset that includes data from the last two months. This keeps the sample limited to more recent performance. Furthermore, I limited the data to only pitchers with more than 60 total pitches thrown in that time. Then, I took each pitcher’s most utilized fastball by pitch percentage and used it to calculate their called strike rate. I did the same with each pitcher’s most utilized offspeed, or non-fastball, pitch and used it to calculate their chase rate. I then calculated each pitch’s 15-game rolling rate, called strike for fastballs and chase for non-fastballs, and labelled their performance balance. Finally, I counted the number of days in which a player has been either good (balanced) or bad (unbalanced) and found the current status of players in both groups:

–

The results focus on a pitcher’s most recent stretch. For example, Emilio Pagán has had one of his best K-BB% (22.4%) marks of his career this season, and in his last five games, it’s been even better (26.3%). He’s had recent success thanks to his four-seam and splitter working in unison.

Is there more to do? Always. I’ve only compared fastball called strike rates with offspeed chase rates, but all of these plate discipline metrics could be compared for balance. For example, it may be better to have a balanced swinging strike rate and chase rate. But, fundamental to this analysis is the assumption that it’s hard to get anywhere without a fastball and offspeed pitch that work well together. Does it mean anything? Is the balance even predictive of future success? Maybe, maybe not. What it certainly can do, as I believe I’ve exemplified here, is explain a pitcher’s success or lack thereof. If you are interested in doing this analysis on your own without spending hours calling and pinging pybaseball’s API, you can view pitch-specific plate discipline metrics on our new and totally awesome Pitch-Type Splits Leaderboards. Stay balanced, stay cool.

Happy Friday, and welcome to the first Pitcher Playing Time Changes rundown of September! As always, there’s a lot to go over, with the injury hits continuing to come and teams like the Mets making significant rotation changes.

Happy Friday, and welcome to the last Pitcher Playing Time Changes of August! We’re running out of time on the regular season, which means a lot of pitchers are running out of time to return from injuries. Others, however, like Chris Sale, will come back and at least get the consolation prize of ending the year healthy and having pitched in MLB games.

Welcome to the latest Pitcher Playing Time Changes, headlined by a significant shakeup in the Phillies rotation due to Zack Wheeler’s potentially-season-ending injury. Below are the latest changes.

It’s stretch run time, and contenders are continuing to reevaluate who can best help them win now — even involving some players who teams thought might be more win-later than win-now, like Nolan McLean. Here’s what’s changed in the past week.

In our first Pitcher Playing Time Changes roundup since the Trade Deadline, let’s take a look at how the moves made changed how many starts and relief innings we can expect for pitchers down the stretch:

Below are the latest significant projected playing time changes for pitchers, led by the Cardinals entering something of a new era for their rotation with Michael McGreevy taking over for Erick Fedde 페디.

Below are the latest significant playing time projection changes for starters and relievers over the past week. The biggest news is Cam Schlittler‘s call-up, with his debut coming at the unfortunate cost of Clarke Schmidt’s UCL.