I experience baseball in many different forms. Writing is obviously one of them. Watching (both in person and on television) is another. Playing doesn’t happen as much as I’d like to, but it’s still one of them. The last one, which has become the most accessible to me, is through data: performance, expected stats, projections, etc. Data serves as a conversation starter or a thought provoker for me, and I rely on it heavily in my writing to tell the story of a player’s triumphs or struggles, especially Statcast data.

When working with Statcast information, it’s important to understand the inputs that create the data points. For example, I know that xwOBA is formulated using a combination of exit velocity and launch angle (and sometimes sprint speed). Perhaps it would be helpful if there were more inputs such as batted ball spin or spray angle, or perhaps it would complicate things. But what is important is that I know those are not included in the formulation — knowledge that I can use when assessing players for whom those inputs could be statistically important. I’m specifically thinking of the profiles of Isaac Paredes and Cody Bellinger.

Neither Paredes nor Bellinger have big power in terms of raw exit velocity, and neither is a batting average king (although Bellinger is over .300 at this moment in time). Instead, they rely on consistent contact to the pull side in the air to make up for their lack of raw power. I have an idea in my head of what a good hitter is. One of my most general criteria is the ability to hit the ball consistently hard, but it’s important to leave wiggle room there so you don’t exclude the edge cases, like Bellinger and Paredes. Both are below the 20th percentile in terms of average exit velocity and below the 10th percentile in HardHit%, but both have ISOs over .200 with double-digit home runs and doubles. That’s unusual, but it brings me back to stressing the importance of spray angle for a certain group of hitters. Read the rest of this entry »

We began this series with Craig Kimbrel striking out José Ramírez to close out the All-Star Game, and I’ll admit, my original intent was to cover all of the pitchers in Part II. But as anyone who reads (or edits) my work knows, when it comes to the Hall of Fame and its candidates, I can go on, and on… and on. In part that’s because I like to use this series as an annual clearinghouse, covering the vast majority of the active players whom readers most frequently ask me about during the course of the year. It may not be a one-stop shop, but with the added volume comes some context for comparisons (Has Freddie Freeman caught up to Paul Goldschmidt? Who has a better shot, Carlos Correa or Francisco Lindor? And what about Trea Turner?) In part, it’s also because in the 20 years (!) since I introduced it, my JAWS system has become more complicated and more nuanced, requiring a bit of additional introduction. That’s particularly true when it comes to pitching, where during the 2022 election cycle, I formalized S-JAWS for starting pitchers and R-JAWS for relievers.

I had been messing with the latter since the 2019 cycle, in the context of Billy Wagner’s candidacy. The short version of the story is that while Baseball Reference’s flavor of WAR (which I use in JAWS) features an adjustment for leverage — the quantitatively greater impact on winning and losing that a reliever has at the end of the ballgame than a starter does earlier — to help account for the degree of difficulty, it’s not the only way to measure reliever value. Win Probability Added (WPA) is a context-sensitive measure that accounts for the incremental increase (or decrease) in the chances of winning produced in each plate appearance given the inning, score, and base-out situation. WPA can be additionally adjusted using a pitcher’s average leverage index (aLI) for a stat variably called situational wins or context-neutral wins (referred to as WPA/LI). Both of those are now in the sauce; R-JAWS is the average of a reliever’s WAR (including his time as a starter and a hitter, if any), his WPA, and his WPA/LI. The rankings, which I used to have to create by hand, are now on Baseball Reference, and Wagner, who ranks sixth and is the best reliever outside the Hall, is trending towards election after receiving 68.1% on the 2023 ballot, his eighth year of eligibility. Read the rest of this entry »

The full midseason run of the ZiPS projections have been completed, and while the standings updates are always a lot of fun, they tend to move in a similar direction to our FanGraphs standings, so they’re usually not the most shocking. What I find the most interesting are the player projections, and not even the numbers for the rest of the season — the in-season model is simpler, but improvements in the full model are naturally going to be incremental — but the ones that look toward 2024 and beyond.

For today, we’ll start with the hitters with the largest increases in projected 2024 WAR since my original projections and dig a little into what changed for each player. Sometimes it’s performance, sometimes it’s health, sometimes it’s a change in position. Let’s jump straight into the names, since I assume everyone reading this knows that ZiPS isn’t a cheeseburger or a hoodie. Read the rest of this entry »

Shohei Ohtani is a unicorn. No player in 20th- or 21st-century AL/NL history, not even Babe Ruth in his last two seasons with the Red Sox (1918–19), has been able to sustain regular duty in both a rotation and a lineup over a full season, let alone excel at both endeavors. At this writing, the 29-year-old superstar leads the majors in homers (34), slugging percentage (.665), and wRC+ (179), and he’s got the AL’s second-best strikeout rate (32.2%) and lowest batting average against (.191). He currently ranks among the AL’s top 10 in Baseball Reference’s position player WAR (4.0, fourth) and pitching WAR (2.5, ninth), and just over a full win ahead of Ronald Acuña Jr. for the major league lead in combined WAR. Over the past two and a half seasons, he’s been worth 25.0 WAR, 5.9 more than the top position player, Aaron Judge.

Some day, Hall of Fame voters will have to reckon with Ohtani. If he reaches the kind of career numbers that Dan Szymborski’s ZiPS system forecast for him over the winter — 1,809 hits, 404 homers, 124 OPS+, 158 wins, 2,329 strikeouts, 122 ERA+, and 72.1 WAR — the decision will be a no-brainer. I’m already of the mind that if he gets to his 10th season (2027) and is still doing double duty, he’ll have my vote when he lands on the ballot regardless of what the numbers say, because what he’s doing is so utterly remarkable. WAR and JAWS weren’t really built to handle a case like his, and not only because his ability to save his team a roster spot is probably worth some uncounted fraction of a win per year, too. Read the rest of this entry »

Trevor May is a Miguel Cabrera fan. Moreover, he has some favorite Miggy moments. I learned as much when I caught up to the always-engaging 33-year-old right-hander on the Sunday leading into the All-Star break.

“I got my first jersey from another player in our last series,” said May, who broke into the big leagues with the Minnesota Twins in 2014 and now plays for the Oakland Athletics. “We were in Detroit and I got a Miggy Cabrera jersey signed. I’m not a huge memorabilia guy, but he was my first, ‘Oh wow, I’m in The Show.’ It was like, ‘That’s Miguel Cabrera in the box!’ He’s one of the greatest of this generation.”

Nine years later, both players are nearing the end of the line. Cabrera, whose career has him Cooperstown-bound, is set to retire after this season. May, whose accomplishments have been far more humble, faces an uncertain near-term future. He has a 5.32 ERA in the current campaign, as well as a career-low 17.0% K rate.

May’s post-playing-days future is media-focused, and he’s already begun establishing himself in that realm. The Longview, Washington native has been an active podcaster and streamer — gaming is a noteworthy interest, Pat McAfee a notable influence — and just this past week he was part of MLBNetwork Radio’s All-Star Game coverage. His newly-signed jersey is ticketed for his home studio. As May explained, “the background has been kind of sparse, and I wanted to make sure that baseball has a spot there, along with all the nerdy stuff I’m into, whenever I’m in front of the camera.”

May has pitched in front of ballpark cameras many times, and while that includes more than two dozen appearances against the Detroit Tigers, a few of his Miggy moments likely weren’t captured. Even if they were, they went unnoticed by the vast majority of viewers. Read the rest of this entry »

We’re now three months past the last ZiPS projected standings, which ran before the season, and as one should expect, reality has caused a whole lot of changes to the prognostications. Most of the times when I run ZiPS standings, I use data from the in-season player projection model, which is simpler based on the fact that a full batch run of the 3,500 or so players projected, even if I split it up among my two most powerful computers, would take a total of about 30 hours to finish. But I always do the whole shebang in the middle of every month, and baseball’s pause for All-Star Week provides me an opportunity to run projected standings with the best possible model I can come up with, and not have it be a couple days out of date.

So that’s what we’re going to do. With one exception, the methodology remains identical to the one described in the final preseason projections.

I’ve spent the last week working on and testing an addition to the ZiPS standings model to factor in the problem that preseason projections have with temporality. Basically, you can project teams based on who they have in the organization at the time of the projection, but you can’t easily do it for players not in the organization who will eventually be. If I knew at the start of 2022 that the Padres would have Juan Soto for most of the summer, it would have had an effect on the preseason projections! Like any model that people continually work on, ZiPS doesn’t have substantial bias in almost all categories: there’s no systematic tendency to overrate or underrate any specific type of team (bias in exercises like this is easier to iron out than inaccuracy). But there’s an exception: ZiPS in the preseason slightly underrates teams that will eventually add value to the major league roster in the form of trade and overrates those do the opposite.

This is something I’ve long wanted to try to deal with in as effective a way as I could. So what I’ve done is gone back and re-projected every team at June 15, July 1, and July 15 since I started ZiPS, then, with the data of players each team added at the major league level, used the playoff projections at that date, the team’s payroll (it does have a factor), the weakness of the team’s worst positions, the time since last playoff appearance, and the team’s farm system ranking (where possible) to make a probabilistic model of increases and decreases in roster strength due to the trade deadline. Overfitting is a concern, so I’ve cross-validated to do my best to ensure that isn’t an issue, and while it’s less than a half-win in final accuracy, any shaving off of error is a helpful thing. So these standings represent some increased chances that teams like the Orioles and Rangers have a slightly stronger roster than what is currently available from August 1 on, and that teams like the A’s and Tigers have weaker ones. The changes in projections are small because this is a noisy, inaccurate thing, but I’ll be tracking in future years both standings with and without this model to see how they fare. Read the rest of this entry »

Having reached the post–All-Star break world, you may find yourself perusing various stat leaderboards trying to get a grip of who has performed to, above or below expectations. I consider myself a relatively positive person, so when somebody isn’t performing to par, I like to explore their profile in search of a hint of their previous self, or in the case of a prospect, their best future self.

For this piece, I’m going to dive into a group of these players. The criteria aren’t too strict; I’m generally looking for players who are roughly 15 points or more of wRC+ below their preseason ZiPS projection. Other than that, there is some combination of batted ball data, mechanics, and a splash of subjectivity affecting my choices. With that said, let’s jump into it, starting with a former top five prospect. Read the rest of this entry »

Lance Lynn was phenomenal in his final start before the All-Star break, going seven innings, striking out 11 batters, and allowing just three baserunners. By game score, his outing against Toronto was among the top 20 starts of the year. But if you prefer to focus on factors solely within a pitcher’s control — strikeouts, walks, and home runs — it wasn’t even the best of Lynn’s season. By FIP, his most dominant performance was a 16-strikeout gem against the Mariners a few weeks prior. Over seven frames, he walked only two and kept everything in the ballpark. Even more impressive, all but one of his strikeouts came on a swing and miss, as Lynn collected 33 whiffs on the evening, the most by any pitcher in a single outing this season. His 16 strikeouts were also the most in a single game this year; no other pitcher has topped 13.

Lynn has two more double-digit strikeout games this year, one each against the Rays and the Twins. Only eight other pitchers have four or more double-digit strikeout games, and only four have multiple starts of seven-plus innings, double-digit strikeouts, two or fewer walks, and zero home runs: Kevin Gausman, Zac Gallen, Logan Webb, and Pablo López. (The White Sox, being the 2023 White Sox, went on to lose all four contests, but that’s hardly a reflection of Lynn’s efforts on the mound.) Read the rest of this entry »

One of my favorite kinds of baseball trade is the one that sends major league talent both ways, between teams ostensibly interested in being competitive, each giving from surpluses to meet immediate needs. It’s certainly the safer option for a front office just to take the passive route and stick with the guys you’ve got, but I appreciate the boldness of swapping a player who’s poised to contribute to your club for one you think might give you more, solve some piece of the positional puzzle, or be able to be a more significant part of your plans down the road.

Such was the case for the Marlins and Twins in January when Luis Arraez (who seems poised to defend his title) was dealt to Miami in exchange for Pablo López and prospects Jose Salas and Byron Chourio. This wasn’t a straight big leaguer-for-big leaguer swap, but both teams were trading for the present. López, 26 at the time, had been the Marlins’ second most productive starter in 2022 and a stalwart of their rotation for the better part of five seasons; the 25-year-old Arraez was coming off a batting title and had been one of the game’s truly elite contact hitters over four seasons of his own. The Twins needed pitching, the Marlins an offensive jolt, and a deal was struck.

If it weren’t a fun enough swap to begin with, it got better when López and Arraez represented their new clubs at the All-Star Game, with Arraez staying true to form with a 2-for-2 night on the winning NL side and López throwing a scoreless ninth inning for the AL. In doing so, the duo became the first pair of players to be dealt for one another and make the next season’s All-Star Game since Josh Hamilton and Edinson Vólquez, who were swapped by the Reds and Rangers in 2007 and emerged as All-Stars the following summer. Read the rest of this entry »

Dane Dunning is excelling in Texas. Now in his third season with the Texas Rangers after debuting with the Chicago White Sox in 2020, the 28-year-old right-hander is 8–2 with a 2.84 ERA over 92 innings. And though he’s fanned just 59 batters, that suits him just fine. It’s not that he doesn’t like strikeouts; he very much does. It’s just that he lacks the power profile of your prototypical modern-day ace. Epitomizing the term “crafty righty,” he effectively limits damage by mixing and matching with one of baseball’s most expansive repertoires.

Dunning discussed his atypical approach, and the arsenal that goes along with it, when the Rangers visited Fenway Park prior to the All-Star break.

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David Laurila: Let’s start with your repertoire. How many pitches do you throw?

Dane Dunning: “Sinker, four-seam, cutter, changeup, slider, curveball. So six. I guess you could say that I’m a jack of all trades, master of none.”

Laurila: How long have you had such a diverse repertoire?

Dunning: “Well, the four-seam is kind of new this year. I’ve thrown it on certain occasions, probably in my last four, five outings. The cutter I started focusing on last year, and this year it’s kind of come into its own. The sinker and slider I’ve had my entire life. The curveball has kind of been my entire life. I’ve always thrown a curveball, but it’s been like, ‘Let’s throw the curveball, let’s not throw the curveball.’ It’s sort of gone back and forth. I brought it back this season, because last year I was throwing two different sliders and they kept blending together. I had to get rid of that.” Read the rest of this entry »