For the 20th consecutive season, the ZiPS projection system is unleashing a full set of prognostications. For more information on the ZiPS projections, please consult this year’s introduction and MLB’s glossary entry. The team order is selected by lot, and the next team up is the Kansas City Royals.
Batters
Bobby Witt Jr. is the saving grace of this lineup, the only player on the Royals with a high chance of being elite at whatever it is he does. If the team isn’t preparing a large extension for Witt before he hits arbitration, they’re doing something seriously wrong. Sadly, given that it’s the Royals, there’s a good chance of them doing something seriously wrong. Read the rest of this entry »
For the 20th consecutive season, the ZiPS projection system is unleashing a full set of prognostications. For more information on the ZiPS projections, please consult this year’s introduction and MLB’s glossary entry. The team order is selected by lot, and the next team up is the Baltimore Orioles.
Batters
If you’ve looked at the depth chart or glanced down at the projections — if you haven’t, this is a weird article to be reading — you ought to be impressed with just how much offensive talent the O’s have. Of course, some spots are brighter (catcher, third base) than others (first base), but there’s really no gaping hole anywhere in this lineup. This reflects the success the team has had developing offensive prospects in recent years. While practically none of the players picked up in the 2018 selloff have worked out all that well, the Elias-era front office has a great record with minor league hitters. The O’s had our top prospect in 2022 (Adley Rutschman) and 2023 (Gunnar Henderson, though ZiPS had him second to Corbin Carroll), and Jackson Holliday, currently no. 1 on The Board, looks to be the heavy favorite to be the top prospect in 2024. Heck, it’s not outside the realm of possibility that someone like Coby Mayo or Samuel Basallo ends up the top prospect in 2025! The O’s eke out a few more wins than the depth chart here simply because of their depth; players like Mayo, Joey Ortiz, Colton Cowser, and Connor Norby all project to be positive contributors without an obvious place to lock up playing time right now. It’s only a slight exaggeration to say that I’d rather have a lineup of all the Orioles who don’t make their team’s 25-man roster out of spring training than all the Washington Nationals who do!
The Ryans O’Hearn and Mountcastle project as the weakest part of the lineup, but offense is in short supply in free agency, and I don’t expect Baltimore to make any changes here. It was always extremely unlikely that the Orioles would return to being one of the league’s payroll heavy hitters, but comments from John Angelos suggest that they’re not even going to be a middle class team, with spending more in line with Tampa Bay or Pittsburgh. If the least valuable parts of your offense project for a wRC+ around 110, you have bigger needs elsewhere. Before anyone calls shenanigans on some of the top comps, Mike Scioscia broke into the majors as a really good hitter before his radiation poisoning and Grady Hatton was a really good hitter when he was young, too. But when your top prospect gets two Hall of Famers in his top three comps, plus a third player who ought to be a Hall of Famer, you shouldn’t be too greedy.
This is one of the best offensive teams in baseball. While that’s never a guarantee of success, it’s a great place to start!
Pitchers
While the O’s have developed a lot of hitters, they haven’t had the same luck with pitchers outside of Grayson Rodriguez. Very few of the large stable of no. 4-ish starter prospects they had a few years ago really developed further, with Kyle Bradish and Dean Kremer being the primary success stories. Suspicions surrounding the pitching are what held Baltimore back in the ZiPS projections last year, and while the computer has come around on a number of pitchers, Bradish most notably, it’s still a rotation that’s begging for one high-end starter in free agency. I’d love to see the O’s go after Shōta Imanaga in any case; he’s gotten a lot less press than Yoshinobu Yamamoto, but he should come cheaper and there’s a lot to like about him. Plus, he’s a fly ball lefty whose weakness is being occasionally gopher ball-prone, and Camden Yards these days is very friendly for that type of pitcher.
Some of the Bradish gain is counteracted by ZiPS’ crush on Kremer being a bit more chaste than last year, but the rotation is at least acceptable so long as they don’t have poor luck with injuries. The team had been pretty lucky until late in the season when Félix Bautista went on the IL, where he’ll stay in 2024 thanks to Tommy John surgery. The bullpen ranked second in team WAR in 2023, but nearly 40% of that total was Bautista. If the O’s stand pat on the overall accomplishments of their 2023 ‘pen, they might regret it.
So how do the O’s look right now? You can add up the depth chart numbers (despite my warnings) and get them right around 90, and the current ZiPS sim has them at around 92 wins, the best record in the division. But that number will be revised as the winter progresses, and if teams like the Jays make any big additions and the O’s don’t, this standing could erode somewhat, despite the depth. It’s tempting to consider Baltimore’s 101 win-total in 2023 to be the team’s “starting point,” but that’s a path to disappointment, as a team exceeding its Pythagorean record and playing well in extra-innings/one-run games isn’t very predictive. Nor is it explained by bullpen quality; the r-squared between ‘pen quality, best reliever quality, and best three-reliever quality and Pythag/extra-innings/one-run game record is under 0.05 historically. And even then, the O’s don’t project to have as good a bullpen next go-around, thanks to the loss of Bautista. And no, projection misses aren’t predictive of future projection misses, even for very young or very old teams (since the projection systems already factor in age).
This is a very good team. The question is whether ownership is willing to invest enough for the Orioles to really find their ceiling.
Ballpark graphic courtesy Eephus League. Depth charts constructed by way of those listed here. Size of player names is very roughly proportional to Depth Chart playing time.
Players are listed with their most recent teams wherever possible. This includes players who are unsigned or have retired, players who will miss 2024 due to injury, and players who were released in 2023. So yes, if you see Joe Schmoe, who quit baseball back in August to form a Belgian Death Metal Skiffle Band that only plays songs by Franz Schubert, he’s still listed here intentionally. ZiPS is assuming a league with an ERA of 4.33.
Hitters are ranked by zWAR, which is to say, WAR values as calculated by me, Dan Szymborski, whose surname is spelled with a z. WAR values might differ slightly from those that appear in the full release of ZiPS. Finally, I will advise anyone against — and might karate chop anyone guilty of — merely adding up WAR totals on a depth chart to produce projected team WAR.
For the 20th consecutive season, the ZiPS projection system is unleashing a full set of prognostications. For more information on the ZiPS projections, please consult this year’s introduction and MLB’s glossary entry. The team order is selected by lot, and the next team up is the Toronto Blue Jays.
Batters
None of the projections here will blow your socks off, but on the plus side, very few of them will get your socks wet (and then you’re walking around all day with your feet wet and clammy, and every time you step it makes a little squishing sound, and you think there’s a bit of dirt in there and you’d like to take off your shoes, but that’s why you’re not allowed in Kroger anymore, so you can’t). If social media is any indication, Matt Chapman might be underrated at this point. He was terrible in the second half, but I haven’t found that to be very predictive, and overall, he still gave the Blue Jays about four wins that they now have to replace. Right now, third base, along with left field and designated hitter, looks to be an amalgamation of role players, though I don’t expect that situation to persist through Opening Day, if for no other reason than active rosters aren’t large enough for Toronto to start the season with all three of those unwieldy chimeras. Read the rest of this entry »
For the 20th consecutive season, the ZiPS projection system is unleashing a full set of prognostications. For more information on the ZiPS projections, please consult this year’s introduction and MLB’s glossary entry. The team order is selected by lot, and the next team up is the Washington Nationals.
Batters
Let’s get the bad news out of the way first. One isn’t the loneliest number on this depth chart, which features the most ones you’ll see outside of a singles mixer. CJ Abrams is the only player to get a two-win projection, and as for any threes, fours, or even something spicier (read: higher)? Well, they’re not invited to this party. We can also dispense with the other bit of bad news: ZiPS is actually more optimistic about a lot of these players than Steamer is.
I was thinking about just ending this writeup there, but that’s too cruel even for me. The good news is that even though the Nationals are unlikely to be very good in 2024, they’re not really supposed to be, and much of this roster is made up of players either still at the start of their career or who nobody in the organization expects to be playing an important role by the time the team is good again. Lane Thomas was a great story this year, as was Joey Meneses in 2022, but does anyone really expect either to be a big part of Washington’s 2027 World Series championship, should that come to pass? The Nats are using this time wisely, and it’s better to look at interesting minor league veterans than washed-up 35-year-olds for the spots you don’t have better prospects to fill. Read the rest of this entry »
For the 20th consecutive season, the ZiPS projection system is unleashing a full set of prognostications. For more information on the ZiPS projections, please consult this year’s introduction and MLB’s glossary entry. The team order is selected by lot, and the next team up is the Tampa Bay Rays.
Batters
With the sudden collapse of the Cardinals, the Rays are arguably the holders of the crown in the solid-but-not-spectacular department. With one problematic exception, just looking at the depth chart, you see a whole bunch of twos and threes but no obvious MVP candidates, unless Yandy Díaz finds yet another extra gear in him. But there’s also almost nowhere on the diamond where you expect a huge collapse if forced to find an emergency fill-in. Manuel Margot can capably take any outfield job handily, and elsewhere, Curtis Mead, Vidal Bruján, Junior Caminero, and Jonathan Aranda can cover most anything needed outside of catcher. Read the rest of this entry »
For the 20th consecutive season, the ZiPS projection system is unleashing a full set of prognostications. For more information on the ZiPS projections, please consult this year’s introduction and MLB’s glossary entry. The team order is selected by lot, and the first team up is the New York Mets.
Batters
At the very least, there’s a good sense of clarity when looking at the Mets depth chart. Francisco Lindor and Brandon Nimmo are plug-and-play options — just stick them in, and if they’re your biggest problem, you’re doomed anyway. Pete Alonso qualifies as that as well, though the Mets are not long from having to make a decision on whether it’s better to offer him a potentially ludicrous contract extension or find a new polar bear (they’re endangered after all!). Jeff McNeil will likely have a season somewhere in between his 2022 and 2023. Francisco Alvarez has a hold on the starting catching job now that he’s outlasted his predecessor (Tomás Nido) and the guy who really, really liked playing said predecessor (Buck Showalter). It’s also obvious that this is a crucial season for Mark Vientos and Brett Baty; the Mets don’t have infinite patience. There likely need to be better solutions in left field, and it’s time to start thinking about a post-Starling Marte right field.
While people are looking for the Mets to make big, splashy signings, it’s also a team that could use an extra bat or two in reserve. With questions at third and in left and right, it’s really hard from a roster standpoint to keep a platoon DH with no defensive value hanging around unless he absolutely crushes his side of the platoon (and Daniel Vogelbach really doesn’t). Eduardo Escobar was traded for good reasons, but he was handy to have around. The fixes to the offense might be low-key because of the need in the next section of this article. There aren’t any young phenoms really threatening to seize a roster spot from any of the offensive stragglers; the Mets have four offensive prospects in our Top 100 who are about a year away from making a real impact in the majors. The fifth, Ronny Mauricio, certainly has upside at second, but then the question becomes how much value McNeil really has as a corner outfielder.
Pitchers
There’s a lot of work to be done here. Kodai Senga is written in with permanent marker, and while ZiPS is very lukewarm — to be nice — about José Quintana, he’s certainly going to be in the rotation as well. After that, the Mets have a deep stable of just-a-guy types; the rotation is probably the biggest hurdle preventing the team from having a nice little bounce-back season. Not to pick on Mike Vasil, who I think will be a serviceable fourth/fifth starter for a while, but if Mike Vasil is this high in the projections, you’ve got some slots to fill. The Mets may have been relieved of the worry of Max Scherzer and Justin Verlander’s inevitable aging curve cliffs, but even if their time with the team didn’t go exactly to plan, without them, the rotation looks like a smoking crater. The good news is that while the free agent market has a real lack of impact bats, starting pitching is well-stocked, even before you consider the availability of Yoshinobu Yamamoto and Shōta Imanaga.
A healthy Edwin Díaz is a boon for the bullpen, though he’s not enough to single-armedly make this a plus unit. The relief corps is less of a smoking crater than the rotation, and ZiPS is more or less is cool with the rest of the group in Brooks Raley, Drew Smith, Trevor Gott, and Phil Bickford. ZiPS sees Josh Walker as a pretty decent swingman option, if a very low-ceiling one. Still, there’s room to improve. I don’t think the starters who fail to make the rotation next spring have electric enough stuff to be overly enthused about their bullpen chances, so the Mets will likely need to find an arm or two here. It doesn’t have to be a Díaz-like arm — good luck finding that — but a couple of mid-tier relievers might keep the wheels from coming off this apple cart.
Players are listed with their most recent teams wherever possible. This includes players who are unsigned or have retired, players who will miss 2024 due to injury, and players who were released in 2023. So yes, if you see Joe Schmoe, who quit baseball back in August to form a Belgian Death Metal Skiffle Band that only plays songs by Franz Schubert, he’s still listed here intentionally. ZiPS is assuming a league with an ERA of 4.33.
Hitters are ranked by zWAR, which is to say, WAR values as calculated by me, Dan Szymborski, whose surname is spelled with a z. WAR values might differ slightly from those that appear in the full release of ZiPS. Finally, I will advise anyone against — and might karate chop anyone guilty of — merely adding up WAR totals on a depth chart to produce projected team WAR.
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.
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.
ZiPS Projection – Corbin Carroll
Year
BA
OBP
SLG
AB
R
H
2B
3B
HR
RBI
BB
SO
SB
OPS+
DR
WAR
2024
.279
.362
.485
555
99
155
27
12
21
90
61
141
39
129
10
5.4
2025
.275
.359
.480
571
104
157
28
10
23
94
64
139
39
127
10
5.4
2026
.272
.358
.474
570
104
155
28
9
23
95
65
133
37
125
10
5.2
2027
.273
.361
.479
568
105
155
29
8
24
95
67
129
36
127
9
5.4
2028
.272
.363
.479
566
105
154
29
8
24
94
69
125
33
128
9
5.3
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.
ZiPS Projection – Kodai Senga
Year
W
L
ERA
FIP
G
GS
IP
H
ER
HR
BB
SO
ERA+
WAR
2024
11
8
3.63
3.87
28
28
161.0
132
65
18
76
190
122
3.4
2025
10
7
3.72
3.94
26
26
150.0
126
62
17
69
171
119
3.0
2026
9
7
3.82
4.06
24
24
141.3
124
60
17
63
156
116
2.7
2027
8
7
3.98
4.24
22
22
129.0
118
57
17
58
138
111
2.3
2028
7
8
4.21
4.46
21
21
124.0
118
58
17
56
128
105
1.9
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.
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.
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.
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.
The last of the extant pre-divisional era franchises to not have won the World Series has finally hoisted their own trophy, as the Texas Rangers shut down the Arizona Diamondbacks, 5-0, to score the team’s first championship. Texas’ starter, Nathan Eovaldi, was shaky in the early going, but every last one of Arizona’s runners were stranded on the basepaths, and the shelling of Paul Sewald in the ninth sealed the deal with insurance runs.
If you just watched the starting pitchers, Eovaldi and Zac Gallen, for the first five innings on Wednesday night, you might be surprised that the series didn’t find its way back to Texas. The Rangers entered Game 5 having won all five of Eovaldi’s starts this postseason, but it was Gallen who looked to have the advantage early on. Eovaldi’s control was spotty. He allowed five walks over five innings, the most free passes he’s issued in a decade, going back to when he was a hard-throwing Marlins prospect who had trouble putting away batters. Read the rest of this entry »
On the back of a seven-inning near-shutout from ace Zack Wheeler, three round-trippers, and a Bryce Harper steal of home, the Philadelphia Phillies convincingly beat the Arizona Diamondbacks, 6-1, to push the latter to the brink of oblivion. The Phillies got to Diamondbacks starter Zac Gallen often, scoring two runs in the first, a lead that Arizona never really threatened. The NLCS now heads back to Philadelphia, where the Diamondbacks have to win two games or all that will be left to do is to grab a couple cheesesteaks and a roast pork and fly back home for the winter.
The Phillies got things going quickly with a fun-filled first. The action started with a Kyle Schwarber infield hit and ended with a double steal. Totally Traditional Leadoff Hitter Schwarber’s little dribbler to third against the current iteration of the infield shift was way too far for third baseman Evan Longoria to reach in time, and he legged his way to first. While fans often overestimated the ease with which hitters could magically just go the opposite way during the shift’s heyday — as if that’s so simple against big league pitching — Schwarber actually was fairly good at it. Despite not being quick, even deceptively so, Schwarber ranks 20th since 2015 in groundball hits the opposite way against shifts and shades, with 38 of them in 69 attempts. That .551 BABIP is nearly 100 points above the league average of .460 over the same timeframe! Read the rest of this entry »
