It has not been a very good year for pitchers aspiring to reach the Hall of Fame. Two of the four starters widely perceived to have sealed the deal have yet to throw a single pitch in the majors thus far — one hasn’t even signed and may in fact be done — and the starter who entered the year with the most momentum didn’t debut until June 19 due to (gulp) an elbow injury. Just one Cy Young Award winner from the past decade has pitched a full season, while four are in various stages of recovery from Tommy John surgery. Meanwhile, the three most-likely relievers have all been erratic to some degree or another; one of them isn’t even his team’s regular closer.

With the Hall of Fame Induction Weekend circus having left Cooperstown following Sunday’s festivities to honor Adrián Beltré, Todd Helton, Jim Leyland, and Joe Mauer, it’s a good time to ponder which active players are on their way. But particularly since the last time I took stock about a year ago, the picture is less rosy for just about every starter except Paul Skenes, and it’s far too early to talk about him. Even at a time when pitching seems to be winning the daily battle — scoring and slugging percentage are near their lowest marks in the last decade, and batting average is in a virtual tie (with 2022) for the fourth-lowest mark since 1900 — pitchers are losing the war against longevity.

This isn’t exactly a new topic, of course, and while I’ve spent a lot of time thinking about how Hall voters will adjust their standards in the coming years, and how we might differently evaluate pitchers through tools such as S-JAWS (which reduces the skewing caused by the heavy-workload pitchers of the 19th and early 20th-centuries) and rolling WAR leaders, I don’t have a clear answer. The main problem is that if we decide to lower the standards by which we judge more recent starters, we are left with literally dozens of pitchers from past eras with similarly impressive resumés, and logistical roadblocks to honor an equitable share of them. If the recently retired Adam Wainwright (45.2 career WAR/36.5 adjusted peak WAR/40.7 S-JAWS) is worthy of a spot in Cooperstown, then how do we reckon with the careers of Luis Tiant (66./41.3/53.7), David Cone (62.3/43.3/52.8), Dave Stieb (56.4/41.8/49.1), and Johan Santana (51.7/45.0/48.3) — to name just a few aces from the past half-century? Given the ability to fit just eight candidates on an Era Committee ballot, with Negro Leaguers, managers, and executives also in the pre-1980 mix, and the deck generally stacked against candidates who fell victim to the Five Percent Rule, there’s little chance of catching up anytime soon. Read the rest of this entry »

At last we reach the end of my annual series spotlighting the weakest positions on contenders. While still focusing upon teams that meet that loose definition of contenders (Playoff Odds of at least 9.5%), I have also incorporated our Depth Charts’ rest-of-season WAR projections into the equation for an additional perspective. Sometimes that may suggest that the team will clear the bar by a significant margin, but even so, I’ve included them here because the team’s performance at that spot is worth a look.

At the other positions in this series, I have used about 0.6 WAR or less thus far — which prorates to 1.0 WAR over a full season — as my cutoff, but for the designated hitters, I’ve limited the list to the teams below zero, both to keep the length manageable and to account for the general spread of value. In the third full season of the universal DH, exactly half the teams in the majors have actually gotten 0.0 WAR or less from their DHs thus far, four are in the middle ground between 0.0 and 1.0, eight are between 1.0 and 2.0, and three are above 2.0. DHs as a group have hit .245/.321/.421 for a 109 wRC+; that last figure is up three points from last year, and seven points from the last time I did this list, via a slash line that’s virtually identical (the majors’ slugging percentage as a whole has dropped 17 points from last season).

This year, we’re seeing a greater number of teams invest more playing time in a single DH. Whereas each of the past two seasons saw three players reach the 500 plate appearance threshold as DHs, this year we’re on pace for five; similarly, 11 player are on pace to reach 400 PA as DHs, compared to eight last year. That said, many of the teams on this list are the ones that haven’t found that special someone to take the lion’s share of the plate appearances.

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Today the Killers list turns the corner — or rather turns to the teams receiving less-than-acceptable production in the outfield corners. While still focusing on teams that meet the loose definition of contenders (Playoff Odds of at least 9.5%), and that have gotten about 0.6 WAR or less out of a position thus far — which prorates to 1.0 WAR over a full season — I have also incorporated our Depth Charts’ rest-of-season WAR projections into the equation for an additional perspective. Sometimes that may suggest that the team will clear the bar by a significant margin, but even so, I’ve included them here because the team’s performance at that spot is worth a look.

As noted previously, some of these situations are more dire than others, particularly when taken in the context of the rest of their roster. I’ve batched the two corners together into one supersized roundup because three of the seven teams below the WAR cutoff for left field also make the list for right field, and because there’s plenty of crossover in play with regards to personnel. The capsules are listed in order of their left field rankings first, while noting those three crossover teams with an asterisk. As always, I don’t expect every team here to go out and track down upgrades before the July 30 deadline, but these are teams to keep an eye on. All statistics are through July 14.

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Strength up the middle is important to any contender, but with so many teams still in the hunt for a playoff spot, it’s no surprise some of them are have some weak spots. Sometimes it’s easier for a team to convince itself that the metrics aren’t fully capturing the strength of a light-hitting player’s defense if they’re playing a premium position, which seems to be the case with the shortstops and some of the center fielders in this year’s batch of Killers. On the flip side, occasionally it’s easier to justify shaky defense if there’s at least a hope of getting adequate offense. Then there are the times that guys get hurt and somebody has to stand out there in the middle pasture looking like they know what’s going on.

While still focusing on teams that meet the loose definition of contenders (a .500 record or Playoff Odds of at least 9.5%), and that have gotten about 0.6 WAR or less out of a position thus far — which prorates to 1.0 WAR over a full season — I have also incorporated our Depth Charts’ rest-of-season WAR projections into the equation for an additional perspective. Sometimes that may suggest that the team will clear the bar by a significant margin, but even so, I’ve included them here because the team’s performance at that spot is worth a look.

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Today, we have a two-fer of Killers lists covering a couple of key defensive positions, specifically the hot corner and behind the plate. While still focusing on teams that meet the loose definition of contenders (a .500 record or Playoff Odds of at least 9.5%), and that have gotten about 0.6 WAR or less out of a position thus far — which prorates to 1.0 WAR over a full season — I have also incorporated our Depth Charts’ rest-of-season WAR projections into the equation for an additional perspective. That may suggest that some of these teams will clear the bar by a significant margin, but even so, I’ve included them here because their performance at that spot thus far is worth a look.

Cubs

Following the free agent departure of Willson Contreras, last year the catching corps of Yan Gomes, Tucker Barnhart, and rookie Miguel Amaya ranked 21st in WAR. Heading into this season, it made at least some sense on paper to have the 25-year-old Amaya — a former Top 100 prospect who lost significant development time to the pandemic and November 2021 Tommy John surgery — get more playing time while moving the 37-year-old Gomes, whose framing metrics had declined, into a backup role. Unfortunately, both have been terrible. Amaya has hit just .201/.266/.288 (59 wRC+) with average-ish defense (good blocking, poor throwing) en route to -0.1 WAR. Gomes was even worse both at the plate (.154/.179/.242, 15 wRC+) and behind it (-5 DRS, -4 FRV, -3.9 FRM) before getting released on June 21, replaced by Tomás Nido, who had just been released by the Mets. Nido has hit .202/.229/.331 (57 wRC+) overall but is just 4-for-41 as a Cub. Defensively, he’s got a mixed bag of metrics, though he’s been a whisker above average framing-wise. Read the rest of this entry »

Today, we turn our attention to the second base Killers. While still focusing on teams that meet the loose definition of contenders (a .500 record or Playoff Odds of at least 9.5%), and that have gotten about 0.6 WAR or less out of a position thus far — which prorates to 1.0 WAR over a full season — I have also incorporated our Depth Charts’ rest-of-season WAR projections into the equation for an additional perspective. Sometimes that may suggest that the team will clear the bar by a significant margin; as you can see by the table below, four of the six teams listed here project to receive more than a win from their current cast of second base options. Even so, I’ve included them here because the team’s performance at that spot is worth a look, and the incumbent may no longer appear to be the best option.

Particularly in light of those projections, I don’t expect every team to go out and track down an upgrade before the July 30 deadline, though I’ll note that some of the players cited within for their poor performance are themselves change-of-scenery candidates; one team’s problem may be another team’s solution, albeit not necessarily an ideal one. Either way, I’m less concerned with those solutions – many of which have more moving parts involved than a single trade — than I am with the problems. Unless otherwise indicated, all statistics are through Sunday.

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In a race for a playoff spot, every edge matters. Yet all too often, for reasons that extend beyond a player’s statistics, managers and general managers fail to make the moves that could improve their teams, allowing mediocre production to fester at the risk of smothering a club’s postseason hopes. In Baseball Prospectus’ 2007 book, It Ain’t Over ‘Til It’s Over, I compiled a historical All-Star squad of ignominy, identifying players at each position whose performances had dragged their teams down in tight races: the Replacement-Level Killers. I’ve revisited the concept numerous times at multiple outlets and have adapted it at FanGraphs in an expanded format since 2018.

When it comes to defining replacement level play, we needn’t hew too closely to exactitude. Any team that’s gotten less than 0.6 WAR from a position to this point — prorating to 1.0 over a full season — is considered fair game. Sometimes, acceptable or even above-average defense (which may depend upon which metric one uses) coupled with total ineptitude on offense is enough to flag a team. Sometimes a club may be well ahead of replacement level but has lost a key contributor to injury; sometimes the reverse is true, but the team hasn’t yet climbed above that first-cut threshold. As with Supreme Court Justice Potter Stewart’s definition of hardcore pornography, I know replacement level when I see it.

For this series, I’ll go around the diamond, pointing out the most egregious examples of potential Killers at each position among contenders, which I’ll define as teams that are above .500 or have Playoff Odds of at least 9.5%. That definition covers 20 teams, down from 22 last year. I’ll include the rest-of-season projections from our Depth Charts, and while I may mention potential trade targets, I’m less focused on these teams’ solutions than I am the problems, because hey, human nature. Read the rest of this entry »

The National League Wild Card race is wide open, with eight of the league’s 15 teams separated by a grand total of four and a half games in the standings. Five of those teams are currently below .500, their flaws on display on a daily basis — and some of those teams are at a particular disadvantage when it comes to their defenses.

On Wednesday, I investigated what a handful of the major defensive metrics — Defensive Runs Saved, Ultimate Zone Rating, Statcast’s Fielding Run Value (FRV), and our catcher framing metric (hereafter abbreviated as FRM, as it is on our stat pages) — told us about the teams with the best defenses. Some of them appear to be playoff-bound, while others are barely hanging onto hope thanks in part to those defenses, among them the Diamondbacks. Read the rest of this entry »

The Guardians rate as one of baseball’s bigger surprises. After finishing 76-86 last year — their worst record since 2012 — they’ve rebounded to go 57-33 thus far, and entered Wednesday with the AL’s best record. Their offense is much more potent than it was last year, and despite losing ace Shane Bieber for the season due to Tommy John surgery, they rank second in the league in run prevention at 3.87 runs per game.

While Cleveland’s staff owns the AL’s second-highest strikeout rate (24.2%), a good amount of credit for the team’s run prevention belongs to its defense. By my evaluation of a handful of the major defensive metrics — Defensive Runs Saved, Ultimate Zone Rating, Statcast’s Fielding Run Value (FRV), and our catcher framing metric (hereafter abbreviated as FRM, as it is on our stat pages) — the Guardians rate as the majors’ second-best defensive team thus far this season. The Yankees, who spent much of the first half atop the AL East before a 5-16 slide knocked them into second place, are the only team ahead of them.

On an individual level, even a full season of data isn’t enough to get the clearest picture of a player’s defense, and it’s not at all surprising that a 600-inning sample produces divergent values across the major metrics. After all, they’re based on differing methodologies that produce varying spreads in runs from top to bottom, spreads that owe something to what they don’t measure, as well as how much regression is built into their systems. Pitchers don’t have UZRs or FRVs, catchers don’t have UZRs, and DRS tends to produce the most extreme ratings. Still, within this aggregation I do think we get enough signal at this point in the season to make it worth checking in; I don’t proclaim this to be a bulletproof methodology so much as a good point of entry into a broad topic. Read the rest of this entry »

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