Brooks Raley has been an effective reliever since returning to MLB in 2020 after five seasons as a starter with the KBO’s Lotte Giants. He’s been especially good for the past two. Taking the mound for the Tampa Bay Rays in 2021 and for the New York Mets this past season, the 35-year-old left-hander has logged a combined 2.74 ERA and a 3.21 FIP over 126 relief appearances. Moreover, he’s allowed just 81 hits and fanned 122 batters in 108.1 innings. Working primarily in a setup role, he’s been credited with a pair of wins and nine saves.

Raley is also a bona fide pitching nerd. That wasn’t the case when he got cups of coffee with the Chicago Cubs in 2012 and ’13, but then came a career-altering adoption of analytics when he was overseas. Looking to optimize his talents, the Texas A&M University product schooled himself on how his pitches played best, and what he could add, subtract or tweak in order to attack hitters more effectively. The result was a successful return to the big leagues, and not only has he put up a good FIP and a solid SIERA, but he also knows exactly what those acronyms mean.

Raley discussed his analytics-influenced evolution as a pitcher when the Mets visited Fenway Park this summer.

———

David Laurila: You played five years in Korea. What was that experience like?

Brooks Raley: “I loved it. I learned a lot. We’re talking analytics, and I went over there not very polished. I was a starter but didn’t have a changeup or a cutter, so I started watching YouTube videos of all the different shapes, spin rates, tilts, extension — all that stuff. For a little bit, I tried to throw like Chris Sale. I kind of leaned over and tried to create some different angles and see what kind of shapes I could get. I really got into that side of the sport. I found my cutter, found my arm slot, and then the sinker got better. My slider also got better. That all happened when I was in Korea. It’s how I got back [to MLB].”

Laurila: Why hadn’t you gotten into analytics and begun making changes prior to going to the KBO?

Raley: “I wouldn’t change anything about my career, but coming across analytics and what defines your strengths better… when I was coming through the minors, it was ‘sinkers down and away are safe’ and ‘ground balls over strikeouts.’ But I actually and naturally pitch better inside. That’s to both sides. To righties, I throw the cutter and the slider and have the changeup and sinker to keep them honest. To lefties, I’ve got the running sinker. It’s been inconsistent this year, I can’t really figure that out, but it’s been between 14 to 19 horizontal and probably anywhere from eight to two vertical. It’s kind of a unique pitch because it spins 2,400 [RPMs] or so. It’s got some life and late dart to it.

“I always struggled with changeups before I went over there, because I’d always try to throw the 10 miles an hour off [from the fastball]. Now I throw a Viulcan change, so I don’t really kill spin but I put it on the horizontal axis. I get around 19 and I’m either on the line or under the line. Basically, I found some unique shapes to really broaden my left and right, because I can throw a slider at 22 inches of horizontal and a changeup at 20 [in the opposite direction].” Read the rest of this entry »

When the Pittsburgh Pirates took Henry Davis first overall in 2021, they knew they were making a compromise. No matter what happened, even if he blew away everyone’s expectations, he was destined to only be the second-best hitter in big league history with the first name Henry and a last name that’s also a first name.

More than that, the Pirates took him knowing he probably wasn’t the best player in the draft. Davis received a signing bonus of just $6.5 million, only the fifth-highest number in the top six picks. Going way under slot allowed the Pirates to overpay for highly touted high schoolers with their next three picks, and I guess Bryan Bullington and Tony Sanchez no longer count as “in recent memory.”

Nevertheless, having the first pick is a rare gift, and you don’t want to blow it. Read the rest of this entry »

Once again, it’s time for me to fire up my computer and crank out the yearly team-by-team ZiPS projections. This is where I’d normally do my shtick, but we have a lot to get to, so imagine a quote from a 19th century personality, an allusion to a 13th century battle, and a 1980s pop culture reference, and then cram them all together for your own haute couture Szymborski pablum! We’ve got business to take care of, so no time for shenanigans.

ZiPS is a computer projection system I initially developed in 2002–04. It officially went live for the public in 2005, after it had reached a level of non-craptitude I was content with. The origin of ZiPS is similar to Tom Tango’s Marcel the Monkey, coming from discussions I had in the late 1990s with Chris Dial, one of my best friends (my first interaction with Chris involved me being called an expletive!) and a fellow stat nerd. ZiPS quickly evolved from its original iteration as a reasonably simple projection system, and now does a lot more and uses a lot more data than I ever envisioned it would 20 years ago. At its core, however, it’s still doing two primary tasks: estimating what the baseline expectation for a player is at the moment I hit the button, and then estimating where that player may be going using large cohorts of relatively similar players.

So why is ZiPS named ZiPS? At the time, Voros McCracken’s theories on the interaction of pitching, defense, and balls in play were fairly new, and since I wanted to integrate some of his findings, I wanted my system to rhyme with DIPS (defense-independent pitching statistics), with his blessing. I didn’t like SIPS, so I went with the next letter in my last name, Z. I originally named my work ZiPs as a nod to CHiPs, one of my favorite shows to watch as a kid. I mis-typed ZiPs as ZiPS when I released the projections publicly, and since my now-colleague Jay Jaffe had already reported on ZiPS for his Futility Infielder blog, I decided to just go with it. I never expected that all of this would be useful to anyone but me; if I had, I would have surely named it in less bizarre fashion.

ZiPS uses multi-year statistics, with more recent seasons weighted more heavily; in the beginning, all the statistics received the same yearly weighting, but eventually, this became more varied based on additional research. And research is a big part of ZiPS. Every year, I run hundreds of studies on various aspects of the system to determine their predictive value and better calibrate the player baselines. What started with the data available in 2002 has expanded considerably. Basic hit, velocity, and pitch data began playing a larger role starting in 2013, while data derived from StatCast has been included in recent years as I’ve gotten a handle on its predictive value and the impact of those numbers on existing models. I believe in cautious, conservative design, so data is only included once I have confidence in improved accuracy; there are always builds of ZiPS that are still a couple of years away. Additional internal ZiPS tools like zBABIP, zHR, zBB, and zSO are used to better establish baseline expectations for players. These stats work similarly to the various flavors of “x” stats, with the z standing for something I’d wager you’ve already guessed.

How does ZiPS project future production? First, using both recent playing data with adjustments for zStats, and other factors such as park, league, and quality of competition, ZiPS establishes a baseline estimate for every player being projected. To get an idea of where the player is going, the system compares that baseline to the baselines of all other players in its database, also calculated from whatever the best data available for the player is in the context of their time. The current ZiPS database consists of about 140,000 baselines for pitchers and about 170,000 for hitters. For hitters, outside of knowing the position played, this is offense only; how good a player is defensively doesn’t yield information on how a player will age at the plate.

Using a whole lot of stats, information on shape, and player characteristics, ZiPS then finds a large cohort that is most similar to the player. I use Mahalanobis distance extensively for this. A CompSci/Math student at Texas A&M did a wonderful job showing how I do this, though the variables used aren’t identical.

As an example, here are the top 50 near-age offensive comps for World Series MVP Corey Seager right now. The total cohort is much larger than this, but 50 ought to be enough to give you an idea:

Ideally, ZiPS would prefer players to be the same age and position, but since we have about 170,000 baselines, not 170 billion, ZiPS frequently has to settle for players nearly the same age and nearly the same position. The exact mix here was determined by extensive testing. The large group of similar players is then used to calculate an ensemble model on the fly for a player’s future career prospects, both good and bad.

One of the tenets of projections that I follow is that no matter what the projection says, that’s what the ZiPS projection is. Even if inserting my opinion would improve a specific projection, I’m philosophically opposed to doing so. ZiPS is most useful when people know that it’s purely data-based, not some unknown mix of data and my opinion. Over the years, I like to think I’ve taken a clever approach to turning more things into data — for example, ZiPS’ use of basic injury information — but some things just aren’t in the model. ZiPS doesn’t know if a pitcher wasn’t allowed to throw his slider coming back from injury, or if a left fielder suffered a family tragedy in July. I consider those sorts of things outside a projection system’s purview, even though they can affect on-field performance.

It’s also important to remember that the bottom-line projection is, in layman’s terms, only a midpoint. You don’t expect every player to hit that midpoint; 10% of players are “supposed” to fail to meet their 10th-percentile projection and 10% of players are supposed to pass their 90th-percentile forecast. This point can create a surprising amount of confusion. ZiPS gave .300 batting average projections to three players in 2021: Luis Arraez, DJ LeMahieu (yikes!), and Juan Soto. But that’s not the same thing as ZiPS thinking there would only be three .300 hitters. On average, ZiPS thought there would be 34 hitters with at least 100 plate appearances to eclipse .300, not three. In the end, there were 25; the league BA environment turned out to be five points lower than ZiPS expected, catching the projection system flat-footed.

Another crucial thing to bear in mind is that the basic ZiPS projections are not playing-time predictors, at least with players without firm possession of a full-time job in the majors. By design, ZiPS has no idea who will actually play in the majors in 2024. ZiPS is essentially projecting equivalent production; a batter with a .240 projection may “actually” have a .260 Triple-A projection or a .290 Double-A projection. But telling me how Julio Rodríguez would hit in a full-time role in the majors in 2022 was a far more interesting use of a projection system than it telling me that he would only play a partial season (in the end, quite obviously, he played a full year). For the depth charts that go live in every article, I use the FanGraphs Depth Charts to determine the playing time for individual players. Since we’re talking about team construction, I can’t leave ZiPS to its own devices for an application like this. It’s the same reason I use modified depth charts for team projections in-season. There’s a probabilistic element in the ZiPS depth charts: sometimes Joe Schmo will play a full season, sometimes he’ll miss playing time and Buck Schmuck has to step in. But the basic concept is very straightforward.

What’s new in 2024? Outside of the typical calibration updates, there’ll be an extra table in this year’s projections. Don’t worry, the 80/20 splits are returning, but I’m adding split projections into the team-by-team rundowns as well. Usually I create these for the benefit of companies using my projections for their baseball games and calculate it sometime in February. But this year, I successfully integrated that model into ZiPS and, after repairing all the things I broke doing so, platoon splits are now being spit out with the usual array of numbers.

Have any questions, suggestions, or concerns about ZiPS? I’ll try to reply to as many as I can reasonably address in the comments below. If the projections have been valuable to you now or in the past, I would also urge you to consider becoming a FanGraphs Member, should you have the ability to do so. It’s with your continued and much appreciated support that I have been able to keep so much of this work available to the public for so many years for free. Improving and maintaining ZiPS is a time-intensive endeavor and reader support has enabled me to have the flexibility to put an obscene number of hours into its development. It’s hard to believe that ZiPS is now 20 years old. Hopefully, the projections and the things we’ve learned about baseball have provided you with a return on your investment, or at least a small measure of entertainment, whether you’re delighted or enraged.

Ben Lindbergh and Meg Rowley banter about a low-suspense awards week, the vastly varying paths to being a major league manager, the latest sign of the Angels player-development apocalypse, Brian Cashman on Giancarlo Stanton, the death of Padres owner Peter Seidler, Michael Jordan’s baseball career on For All Mankind, how much holding runners matters, and how to judge how many championships a franchise “should” have won, then Stat Blast (1:08:56) about postseason baserunning, scoring first in October, winning rings without playing a lot, and players who lost a lot of WAR, plus a PSA (1:31:02) about EW Secret Santa.

Audio intro: Daniel Leckie, “Effectively Wild Theme”
Audio outro: Nate Emerson, “Effectively Wild Theme”

Link to Posnanski on unanimous awards
Link to Meg’s preseason predictions
Link to “Imperial phase” wiki
Link to Sheehan on managers
Link to story on college-coach managers
Link to Blum on Percival
Link to Cashman’s comments
Link to Stanton’s agent’s response
Link to NYT Seidler obit
Link to FAM Jordan image
Link to Petriello on running prevention
Link to the EW wiki on Lester
Link to running prevention leaderboards
Link to BP piece on championships
Link to Topps Now
Link to Rob Mains on October baserunning
Link to Rob on comebacks
Link to “scoring first” sheet
Link to Ryan Nelson’s Twitter
Link to low-playing-time-rings sheet
Link to Bellinger on EW
Link to Gore on EW
Link to “lost WAR” sheet
Link to FG on Doumit’s framing
Link to Secret Santa sign-up sheet

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Earlier today, the Philadelphia Phillies and Milwaukee Brewers made a swap ahead of this year’s 40-man roster deadline, the last day teams have to either add eligible minor league players to their 40-man roster or expose them to December’s Rule 5 Draft. In this trade, the Brewers acquired 26-year-old second baseman Oliver Dunn and added him to their 40-man roster, while the Phillies received two prospects in return, 21-year-old infielder Robert Moore and 20-year-old outfielder Hendry Mendez.

Let’s start with Milwaukee’s end of this, as we’re most likely to see 2024 big league impact from Dunn, who is coming off an Arizona Fall League stint in which he won the league’s Breakout Prospect award. Dunn, whose brother Ross is in the Twins system, was a Yankees 2019 11th round pick out of Utah. He hit .196 coming out of the lost 2020 season, and spent a significant portion of both 2021 and 2022 on the IL dealing with multiple injuries, including a fractured jaw, an abdomen strain, and a hamstring strain.

The Phillies drafted him in the minor league phase of the 2022 Rule 5 Draft and Dunn had a huge power breakout in 2023 at Double-A Reading, where he hit .271/.396/.506 and slugged 21 homers, more than he had hit throughout his entire career entering 2023. Reading is a hitter’s haven and Dunn was in his age-25 season, so there are good reasons to be skeptical of his sudden change in output, but his underlying power metrics also took a leap, with his average and peak exit velocities (92 mph and 112 mph, respectively) cresting above the big league average. This isn’t gigantic, impact power, but it’s meaningful pop for a second baseman. Dunn swings and misses quite a bit, especially within the strike zone (you can see him struggling with velo up and away from him, a Fall League theme for Dunn, in the video below), but he’s a dangerous all-fields hitter because of his power and ability to catch some fastballs deep in the hitting zone and punish them the other way. Read the rest of this entry »

This post is part of a series covering the 2024 Contemporary Baseball Era Committee Managers/Executives/Umpires ballot, covering candidates in those categories who made their greatest impact from 1980 to the present. For an introduction to the ballot, see here. The eight candidates will be voted upon at the Winter Meetings in Nashville on December 3, and anyone receiving at least 75% of the vote from the 16 committee members will be inducted in Cooperstown on July 21, 2024 along with any candidates elected by the BBWAA.

Hank Peters

In a career that spanned over four decades, from 1946 to ’91, Hank Peters helped lay the groundwork for two powerhouses: the mid-1970s A’s as an executive with their Kansas City forerunners, and the mid-1990s Cleveland squad as the team’s president and general manager from ’87-91. In between those stints, he served as the general manager of the Orioles from 1975 to ’87, navigating the dawn of free agency and making key trades that helped the team win at least 90 games six times, highlighted by a pennant in ’79 and a championship in ’83.

Peters wasn’t particularly colorful, but he was meticulous without being overbearing, with a keen eye for talent. From his Washington Post obituary in 2015: “Patient and unflappable, Mr. Peters did most of his work away from the public spotlight. The Baltimore Sun once likened his laid-back persona to that of a ‘rubber tree plant in an insurance office.'” Within the aforementioned Sun column, from 1985, his admirers found him to be “a rock,” “a great organizer, a great detail man,” and “the consummate baseball man.”

Peters is the only general manager among the eight candidates on this ballot, though Lou Piniella served in that role briefly with the Yankees. He’s one of only two executives on the ballot, along with former National League president Bill White, whose credentials also include stardom as a player and a stretch as a pioneering broadcaster. Read the rest of this entry »

Here at FanGraphs, Ben Clemens ranked Kyle Gibson 25th on our Top 50 Free Agents list, 12th-highest among starting pitchers. I can’t imagine that produced much controversy, and a quick search of the comments section and Ben’s Top 50 Free Agents chat suggests the same.

Of all the other major baseball publications’ top free agent lists, though, none had Gibson ranked as highly. Sports Illustrated was the only other site to feature the veteran righty on its official top 50, ranking him 18th among starters and 33rd overall. To be fair, Jordan Shusterman of Fox Sports had Gibson 22nd on his list of the top 30 starting pitchers, though he left him off the overall Fox Sports top 30. Similarly, The Athletic only included 40 players on its staff consensus list, but Gibson likely would have landed somewhere between 41–50 had they continued on; Jim Bowden and Keith Law each included him as the final starter on their personal rankings.

Moreover, as I’m sure Ben would tell you, the precise ranking for each player isn’t always significant, especially the further you move down the list. I’d argue that the difference between the players ranked one and two on our list is bigger than those ranked 25–50. Following that logic, there isn’t necessarily a meaningful difference between ranking Gibson 25th and leaving him off entirely. Read the rest of this entry »

It’s tough to defend one of the most unpopular trades of the past 10 years, but when Mookie Betts got traded to the Dodgers in 2020, some people tried. One of the most commonly grasped straws involved the centerpiece of the deal, Alex Verdugo. Nobody worth listening to said Verdugo was as good as Betts, who was at that point an MVP, the best player on the best team of the 2010s, and on a bullet train to Cooperstown. But Verdugo was a good player, of a similar type to Betts. He’s also three and a half years younger than Betts, and at the time of the trade had five seasons of team control left to Betts’ one.

And if you squint hard enough, you can see it. Verdugo, at his best, has the same strengths as Betts: hitting for contact, defense in right field, doubles power. Where the comparison falls apart is that Verdugo is merely good at those things, and an average regular overall, while Betts is among the best in the game at defense and contact hitting. And while Verdugo is good for about a dozen home runs a year, Betts averages 32 home runs and 22 stolen bases per 162 games played. Snatch is a pretty good gangster movie, but anyone who tells you it’s as good as The Godfather is trying to get one over on you.

Now, Verdugo does have something more concrete in common with Betts: He’s one year from free agency, and the Red Sox are shopping him. Read the rest of this entry »

As I’ve done for the past few years, I’m grading each eliminated postseason manager on their decision-making. We spend the year mostly ignoring managers’ on-field contributions, because to be honest, they’re pretty small. Using the wrong reliever in the eighth inning just doesn’t feel that bad on June 22; there are so many more games still coming, and the regular season is more about managing the grind than getting every possible edge every day. The playoffs aren’t like that; with so few games to separate wheat from chaff, every last ounce of win probability matters, and managers make personnel decisions accordingly. What better time to grade them?

My goal is to evaluate each manager in terms of process, not results. If you bring in your best pitcher to face their best hitter in a huge spot, that’s a good decision regardless of outcome. Try a triple steal with the bases loaded only to have the other team make four throwing errors to score three runs? I’m probably going to call that a blunder even though it worked out. Managers do plenty of other things — getting team buy-in for new strategies and unconventional bullpen usage behind closed doors is a skill I find particularly valuable — but as I have no insight into how that’s accomplished or how each manager differs, I can’t exactly assign grades for it.

I’m also purposefully avoiding vague qualitative concerns like “trusting your veterans because they’ve been there before.” Playoff coverage lovingly focuses on clutch plays by proven performers, but Adolis García and Josh Jung were important, too. Forget trusting your veterans; the playoffs are about trusting your best players. Nathan Eovaldi is valuable because he’s great, not because of the number of playoff series he’s appeared in. There’s nothing inherently good about having been around a long time; when I’m evaluating decisions, “but he’s a veteran” just doesn’t enter my thought process.

One note: In the pitching section, I took a more specific look at reliever matchups. This 2022 Cameron Grove study measures a repeat-matchup reliever penalty. A recent article examines the issue without focusing on specific matchups, but rather looking at relievers pitching on back-to-back days or on short rest after heavy workloads. Both of these things are, unsurprisingly, bad for reliever performance. Managing the balance between starter and reliever over-work is really hard. I probably haven’t given enough credit to the necessity of balancing bullpen workloads against particular opposing batters in the past, but I’ll make a note of it going forward. Read the rest of this entry »

The first of MLB’s major awards to be announced for 2023, the Rookie of the Year awards, were given out Monday evening, with Arizona’s Corbin Carroll and Baltimore’s Gunnar Henderson taking the laurels in the NL and AL races, respectively.

Getting inappropriately annoyed with year-end awards — more specifically in 1995, the year Mo Vaughn beat Albert Belle in the AL and Dante Bichette confusingly finished second in the NL — was one of the things that got me reading Usenet. A high schooler at the time, I had little idea that it was the start of a surprising career path. And even back then, I was frustrated that the writers who voted for these awards didn’t always make convincing arguments about their picks and, occasionally, offered no justifications at all.

I still believe that this kind of transparency is crucial for the legitimacy of any type of award. This is ostensibly an expert panel; if it’s not, there’s no purpose for the award to exist. As such, a secret ballot is not appropriate the way I believe it is for, say, a presidential or parliamentary election. So, as usual, this is my explanation (or apologia depending on your point of view) of why I voted the way I did. I don’t expect 100% of people to agree with my reasoning, which I doubt has happened for any opinion I’ve expressed ever, but that doesn’t mean I don’t owe you, the reader, the details of my vote.

This is my fifth Rookie of the Year vote. Previously, I gave my first-place votes to Spencer Strider, Trevor Rogers, Pete Alonso, and Corey Seager. This year, my ballot, starting at the top, was Carroll, the Mets’ Kodai Senga, and the Reds’ Matt McLain. Let’s start at the top. I’m also including preliminary 2024 ZiPS projections because, hey, why not? (They didn’t have any bearing on my vote, nor did the preseason projections.)

The Easy Part: Corbin Carroll

My last two first-place votes were close for me, and it took a while to decide on them. But this one was the easiest since Seager in 2016 (and I’m not forgetting Alonso versus Michael Soroka). Everyone expected Carroll to steamroll the league, and that’s just what he did. And while he didn’t have a Mike Trout-esque rookie season, who does?

For much of the season, Carroll logically was part of the MVP discussion, though by the time September rolled around, Ronald Acuña Jr. and Mookie Betts had an obvious advantage, with Freddie Freeman and Matt Olson being clearly superior, too. But if I had voted for the NL MVP, Carroll would have still landed somewhere in the back of my ballot. He hit .285/.362/.506, clubbed 25 homers and stole 50 bases, and played all three outfield positions at least respectably. He is the type of player for whom the phrase “speed kills” makes sense, because his skill set is broad enough that he can actually weaponize that speed. For the season, he was seventh in sprint speed, had dominating baserunning numbers beyond stolen bases, and in 90-foot splits, he was bested only by Elly De La Cruz.

The Still Pretty Easy Part: Kodai Senga

I’m inclined to like Senga considerably more than his WAR simply because he has a significant history of outperforming his peripherals in Japan as well, so there’s more basis for believing in his ERA than for the typical pitcher in this position. Because of that, I’m closer to bWAR on Senga (4.4) than I am to fWAR. If forced at gunpoint to name the Dan’s Brain WAR for Senga, I’d probably put him at 3.8–4.0 or so. Also, that’s a very weird use of a firearm.

There’s always a writer or two who complains about Japanese players being eligible for the RoY award, but I think the idea that they shouldn’t be is preposterous. Nippon Professional Baseball appears a bit closer to the majors than Triple-A ball in the U.S. is — something like Triple-A 1/2 — but it’s a very different kind of league. While Triple-A hitters may be easier than NPB hitters, you’re also facing a rather different style of play and plate approaches, and now that some of the recent rule changes have hit in the majors, Triple-A ball is roughly a not-as-good MLB.

Despite facing different types of hitters, a spate of different rules, and against the backdrop of New York pressure and a collapsing team behind him, Senga was one of the few players who could really be counted on there. He had some issues with walks early on, and to his credit, he adjusted. But it wasn’t actually his control that was the issue; he actually threw more strikes earlier in the season! Instead, the issue was that after putting up an out-of-zone swing rate above 30% in each of his last two seasons in Japan, he was down in the low-20s early on with the Mets. As time went on, he got a better feel on how to lure MLB batters to their doom; in the second half, his 31.1% out-of-zone swing rate was right where it was in Japan.

The Excruciating Part and the Fifth Wheel: Matt McLain versus Nolan Jones versus James Outman

I don’t see Rookie of the Year as necessarily meaning Most Valuable Rookie, but as Best Rookie. As such, in a kind of small-scale examination of Hall of Fame candidates’ peak versus career numbers, I don’t necessarily think measures against replacement are as important as in the MVP voting, which has directions that more strongly imply an emphasis on quantity.

Outman was probably the most valuable of the three hitters I listed above, but he also got a lot more playing time, winning the job from the start. Both McLain and Jones out-hit him from a quality standpoint, with a 128 wRC+ from McLain, a 135 from Jones, and a 118 from Outman. I might discount this if there were evidence from their minor league time that the major league time was flukier, but both played in Triple-A just about how you’d expect from their actual major league performances. Outman was an excellent player and a big part of why the Dodgers survived the loss of a lot of players, but I would have him fifth in a larger ballot because he wasn’t quite as good as McLain or Jones. Per WAA on Baseball-Reference, both McLain and Jones were well ahead of him.

McLain versus Jones was very difficult for me, and I went back and forth on it the entire Sunday I made my vote (the last day of the season). And it still wasn’t an obvious result, more a 51%–49% judgment; if asked on a different day, I might have said Jones instead of McLain. But at the end of the day, I had to pick one. McLain hit almost as well as Jones did and played the hardest non-catcher defensive position. I don’t like deciding based on small things, but it’s inevitable if the big things can’t settle the score. The slight nudge to McLain comes on the balance of having the more valuable defensive versatility (2B/SS for him versus 3B/OF for Jones) and the fact that he played for a team that was playing higher-leverage games all season, with a deep roster of prospects that could push him off a job at any time. The Rockies, meanwhile, were a basement dweller without a lot in the cupboard.

Jones may have just missed my ballot, but it’s no negative reflection on what was an excellent season. I was quite perturbed that he didn’t start the season in Colorado, with the Rockies apparently deciding that Mike Moustakas was nine years better in age than Jones, but they at least weren’t stubborn after he crushed pitchers in the Pacific Coast League. That wRC+ of 135 was an OPS+ of 138 if you like the simpler approach, and both numbers are park-adjusted, so he was Actual Good, not merely Coors Field Good.

Short on Pitching: Bobby Miller, Eury Pérez, and Andrew Abbott

Outside of Senga, no pitcher was close to making my ballot, though these three came closest. The Dodgers should be greatly pleased about having Miller’s services, but his numbers weren’t enough to balance out a rather low innings total. Pérez not being called up until May was a handicap, and while the Marlins being cautious with his workload to the extent of giving him a bit of a mini-vacation in July may be good for his future, it’s hard to give a Rookie of the Year vote to someone who threw less than 100 innings. Abbott’s mid-rotation performance was absolutely needed by the Reds, but again, not quite enough.

The Sixth Man: Patrick Bailey

Of the rest of the field, the closest to making my ballot was Bailey, who was absurdly good defensively in 2023. I could have voted for a player short on playing time; I clearly did with McLain and was close with Jones. But to vote for a hitter at any position who slashed .233/.285/.359 over Outman, McLain, and Jones, I’d need a lot more certainty with defensive numbers than I have. We’ve made great progress in evaluating defense, but it remains extremely volatile, meaning that we simply can’t count on a small sample of defensive data to the same degree as a small sample of offensive data.

I have little doubt that Bailey is an elite defensive catcher, but just how elite is crucial to advancing him over the others with only 97 games played. And it was just a bridge too far for me; if he had been the catcher at the start of the season, there would have likely been a little more flexibility on how to deal with a defense-only candidate.

The Best of the Rest: Spencer Steer, Francisco Alvarez, Elly De La Cruz, Ezequiel Tovar

Steer played the entire season but was basically a league-average starter — something that had value, but he was clearly behind several others in quality. Alvarez hit a lot of homers (25) but was rather one-note in his offensive contributions, though he really surprised with his framing numbers. Tovar was brilliant defensively, and it was nice to see him as a Gold Glove finalist, but his offense was well behind his glove.

De La Cruz was arguably the most exciting of the prospects, maybe even more than Carroll, but he still has some serious holes in his game that were exposed with time in the majors. At the very least, he’s going to need to shore up his plate discipline or become better at effectively connecting with junk in the way Tim Anderson was able to do at his peak.