For the 18th 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 today’s team is the Washington Nationals.

Batters

If there’s any silver lining for a team that will likely be at the bottom of the division, it’s that this is a fairly decent floor for a last-place squad, unless it faces particularly bad injury luck. There are no projected stars remaining anywhere on the roster, but the Nationals do have a pretty good front line of fringe options at most positions. When we mash-up the ZiPS projections and the current iteration of the depth charts, no individual position combines for three wins, but no position comes in at under a win either. Players like Victor Robles, Joey Meneses, and Jeimer Candelario may not have exciting upside, but they’re at least major league players. I’d be midly surprised to see Washington lose 107 games, which it did last season even with a half-season from Juan Soto and Josh Bell.

ZiPS still sees CJ Abrams as risky and is just about out of hope for Carter Kieboom. There’s a bright spot in the form of Jake Alu, who destroyed pitchers in the high minors, even when you take the 2022 helium out of those numbers in the form of a translation. ZiPS doesn’t see him being a near-star offensive player, but the probabilistic measure I use had him as one of the best defensive minor league players; he’s listed as +5 runs at third base, and if ZiPS had been as confident about the translated defense estimate as it is about MLB defensive measures, the projection would actually be +12. Meneses gets a better projection than similar veteran surprise Frank Schwindel got after 2021, and ZiPS sees Alex Call as a legitimate stopgap corner outfielder of the Anthony Santander variety. Abrams, along with Keibert Ruiz and Luis García, has significant upside, and it wouldn’t take much to see any of these projections blow up in a positive way with some real steps forwards from these youngsters. Read the rest of this entry »

For the 18th 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 today’s team is the San Diego Padres.

Batters

When you look at the Padres’ depth charts, there’s a kind of clarity when trying to decide what the team needs to do this winter. The strengths of the offense are obvious: Juan Soto, Manny Machado, and a healthy Fernando Tatis Jr. enter any season as top-notch MVP contenders. And unlike a certain seraphim-themed organization I won’t name with a few mega-stars at the top, there isn’t a huge drop-off to the next tier, whether it’s Jake Cronenworth, Ha-Seong Kim, or Trent Grisham after you’ve threatened him with torture if he tries to bunt for a hit at an awkward moment.

The team’s needs here are also quite obvious; I can’t imagine the Padres actually enter the season with Taylor Kohlwey and José Azocar splitting playing time in left field. The problem is, I also couldn’t imagine Nomar Mazara actually getting 41 starts in 2022, but that’s just what he did.

San Diego would also benefit from some figuring out what to do about Tatis’ position long-term. Right now, we have him splitting time in several places, but I think that the Padres are best served by figuring out whether Cronenworth or Kim are the answer at second, determine where they can put Tatis, and then find a full-time upgrade over Eguy Rosario or Brandon Dixon, whom I see more as complementary talent.

Another thing that is obvious here is that the Padres do need to spend some time this winter fattening up their organizational depth. The high minors are fairly empty at the moment — a combination of graduating talent, traded talent, and a bunch of minor league veterans now in free agency or in other organizations. Most of the players here who look like “break in case of fire” emergency options like C.J. Hinojosa or Domingo Leyba are no longer in the organization. This isn’t necessarily an expensive thing to do, either, and adding a left fielder and a couple of pitchers wouldn’t hinder this. Read the rest of this entry »

12:01

Dan Szymborski: And started, the chat has!@

12:02

Dan Szymborski: Remember, it’s the 80th percentile projection overall, not the 80th percentile projection of a specific aspect

12:02

Dan Szymborski: If he hit the 80th percentile for all his measurables then it would be a higher than 80th percentile projection!

12:02

Dan Szymborski: Four or five a week

Read the rest of this entry »

For the 18th 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 Pittsburgh Pirates.

Batters

There’s a lot not to like about this organization, much of which concerns ownership and its commitment to investing in the Pirates’ on-field product. Contrary to the opinions of a surprising number of people, I don’t think the Frank Coonelly/Neal Huntington era was a failure, at least in terms of their contributions. In sharp contrast to the prior efforts of Dave Littlefield or Cam Bonifay, Coonelly and Huntington built up the Pirates in the down years and there was even a brief moment when the team was a real contender. Problem is, when it was time to push the team over the top, to spend all those savings from the leanest of the slash-and-rebuild years on a contender, the investment in the roster never actually came. It turns out that in the eyes of ownership, an even better use of the savings was to not spend it at all and simply keep it. Those Pirates were left to die as ownership served up the Requiem aeternam.

But looking at the players the Pirates have currently, there are some things to like. Now, not a lot of things to like, but there are players scattered throughout the roster who are very good at major league baseball, and the guys who aren’t are at least interesting rather than 32-year-old journeymen (with a couple exceptions that I’ll get into). Read the rest of this entry »

For the 18th 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 today’s teams is the Cincinnati Reds.

Batters

The story of the origin of the name of Cincinnati is an interesting one. Many cultures have stories of semi-mythical legend involving historical rulers attaining great feats of martial valor or living absurdly long lives. But the tale of Lucius Quinctius Cincinnatus, counsel for Rome in 460 BC and briefly dictator on two occasions, is a rare one in that it’s a tale surrounding the virtue of civic duty. While the reality was far more complicated, Cincinnatus is not famous so much for vanquishing his foes but for, with the strength of the Republic on his back, voluntarily giving up power and returning to his farm, twice, having done his duty to the Republic. The later Roman Republic was not so lucky; contrast the behavior of Cincinnatus with that of Lucius Cornelius Sulla Felix, known in history as Sulla, who, after victory at the Battle of the Colline Gate over the Marians, seized… what? Oh, right. I’m going to have to talk about this offense, aren’t I?

If owners have any civic duty owed to the cities that pay for their stadiums, not much of that has been displayed by Reds ownership over the last 18 months or so. Coming off an 83–79 season in which Cincinnati was in wild-card contention at the deadline and with most of the core of the roster intact, the team folded its hand extremely quickly, trading most players with significant trade value and slashing the budget by around $50 million, despite playing in a weak division without any truly aggressive teams or profligate spenders. The team shed 13 points of wRC+, dropping from fourth in the NL in runs scored to 11th. To find a season more than a couple points worse than that combined wRC+ of 84, you have to go back to the early 1950s.

There aren’t really any bright spots in the offense, just OK ones. Noelvi Marte gets a very promising projection over the long-term (and how about that top comp!), and both Spencer Steer and Matt McLain get surprisingly optimistic projections that see them as real league-average players. Jonathan India gets sort of a comeback-ish season, and Tyler Stephenson can be a three-win player if he stays healthy and the Reds turn his off-days into DH days. Not a single position player gets 4 WAR at their 90th-percentile projection, though there’s still a good chance that someone does hit that mark because, well, that’s how probability works. The starting outfield basically looks a B-squad spring training roster. Read the rest of this entry »

For the 18th 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 today’s team is the Chicago White Sox.

Batters

Imagine you’ve just built your dream home. You had an architect come up with a custom design that you absolutely loved. You hand selected the building materials, from the hardwood floors to the Spanish tiles in the roof. You’re ready to move into your endgame house! But wait, almost forgot, you have to furnish the house too, huh? OK, let’s head down to Crazy Joe’s Discount Furniture and find four dining room chairs without cigarette burns. The maroon couch behind the abandoned Caldor next to the bowling alley that still uses a sign from 1973 looks nice. I’m sure the smell will come out of that Craigslist mattress, and it’s not like you need all of the springs.

The White Sox did so many things well while building up the team, but they face-planted as soon as it was time to compete. Once the fun began, the discipline in the team’s decision-making disappeared. Want the 1980s manager for no reason? Sure! Need to solve the problem of two of your best young bats both essentially being designated hitters? Split the difference and have neither of them be the DH! Surely all that money you were going to use to sign Manny Machado will go towards other budgetary needs? Nope? Well, you’ve got Leury Garcia. Read the rest of this entry »

For the 18th 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 to go this year is the Boston Red Sox.

Batters

The Red Sox finished fourth in the American League in runs scored in 2022, but there’s no denying that removing Xander Bogaerts and J.D. Martinez from the roster is a giant hit for the team to take. They may replace the missing value (if not all of it), but it’s a roster with a lot of work to do to be an elite unit. The projections see the offense as being driven mostly by Rafael Devers and Trevor Story, with Story getting quite the bullish projection. Having Triston Casas on the team would be helpful on average, and he has far more upside than either Eric Hosmer or Bobby Dalbec, but as of right now, the team will unfortunately be able to find quite a lot of playing time for the latter two, at least as the roster currently stands. Read the rest of this entry »

These 2023 projections are guaranteed to be awful, wrong in many ways ranging from tragic to comic. But despite being absolutely premature and littered with horrible misses, projected standings at this point are actually quite useful, and useful is the best description any kind of predictive model can strive for. Standings at this point are a poor predictor of the 2023 season — and even the eventual 2023 projections themselves — but what they are able to do is give a “state of the union” estimate for each team. These standings represent the best estimates ZiPS can make at this point about where a team sits in the league’s pecking order, based solely on the players currently under contract with the team. It’s hard to get where you want to go if you don’t know where you’re starting.

The methodology I’m using here is the same one I use in the regular season, and as such, it isn’t identical to the one we use in our Projected Standings. So how does ZiPS calculate the upcoming season? Stored within ZiPS are the first through 99th percentile projections for each player. I start by making a generalized depth chart, using our Depth Charts as an initial starting point. Since these are my curated projections, I make changes based on my personal feelings about who will receive playing time, as filtered through arbitrary whimsy my logic and reasoning. ZiPS then generates a million versions of each team in Monte Carlo fashion — the computational algorithms, that is (no one is dressing up in a tuxedo and playing baccarat like James Bond).

After that is done, ZiPS applies another set of algorithms with a generalized distribution of injury risk, which change the baseline PAs/IPs selected for each player. Of note here is that higher-percentile projections already have more playing time baked in than lower-percentile projections before this step. ZiPS then automatically “fills in” playing time from the next players on the list (proportionally) to get to a full slate of plate appearances and innings. Read the rest of this entry »

Before we get to the 2023 ZiPS projections, there’s still some unfinished work from 2022 to do. Looking at which projections went the most wayward is definitely an exercise that makes me soul cringe a bit, but in any model, being wrong is an important component of eventually being right. Calibration is a long-term project, and while chasing greater accuracy in mean projections isn’t likely to result in any huge bounty — there’s a reason projection systems are so tightly clustered — there’s still improvement to be had in things like calibrating uncertainty and long-term data.

Let’s start with how teams performed versus their projections:

Teams have gotten a bit more polarized in how they’re run in-season. Looking at the in-season ZiPS projections, roster strength has varied much more in recent years than when I started doing this. It wouldn’t be surprising to see the mean absolute error — for an exercise like this, I want to use the simplest tool that gets the point across — creep up over time. That is the case here, as the MAE of 8.3 wins is above the ZiPS historical average of 7.5 (not including 2020). ZiPS underperformed its usual matchup vs. Vegas, only going 17-13 in over/unders as of the date of release (April 6); historically, ZiPS has averaged 19-11. Read the rest of this entry »

The ghost of 18th-century statistician Thomas Bayes did not see his shadow, so we are about to launch this year’s 2023 ZiPS projections. As usual, this is a space to talk about some of the basics, answer a few common questions, and wax philosophic about the very nature of predicting baseball futures. A lot of the background can be found by reading MLB’s glossary entry for ZiPS, which gives most of the basics except for the origin story.

ZiPS is a computer projection system I initially developed in 2002–04; it officially went live for the 2004 season. The origin of ZiPS is similar to Tom Tango’s Marcel the Monkey, coming from discussions I had with Chris Dial, one of my best friends (my first interaction with Chris involved me being called an expletive!) and a fellow stat nerd, in the late 1990s. ZiPS moved quickly from its original inception 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.

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 reference to one of my favorite shows to watch as a kid, CHiPs. I typoed 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. Read the rest of this entry »