A story in the New York Post last week indicated that principal Mets owner Fred Wilpon isn’t likely to hire an “analytics-driven GM” to replace the current three-ring circus and that “there is thought among team officials that perhaps the Mets became too analytics driven in recent seasons under Sandy Alderson’s watch.”
This is a patently ridiculous statement, given both the moves the Mets have made in recent years and the fact that, even under Alderson, the team has a smaller analytics department than other major league organizations. To highlight that first point, let’s run down some moves that weren’t indicative of an analytics-driven approach.
Michael Cuddyer signing pre-2015
The Mets infamously rushed out to sign Cuddyer after the Rockies inexplicably made a 36-year-old with injury issues a qualifying offer. In doing so, the Mets forfeited the 15th overall pick in the 2016 draft for someone who had been a poor defender and relied on sky-high BABIPs over his previous two seasons. A cursory knowledge of the value of first-round picks and a 30-second analysis on Baseball Reference showed that this move was ill-advised.
Lo and behold, the Mets gave someone projected for fewer than 1.5 wins over the life of the contract a deal that should have bought them something more like 3 wins (at the $7 million / win market price at the time), and the deal turned out poorly.
Trading for Tyler Clippard in 2015
Looking to bolster their bullpen at the deadline, the Mets acquired Tyler Clippard for Casey Meisner. At the time, Meisner was a legitimate prospect who has since struggled, but he’s the sort of piece that teams should be willing to move for relief help. The problem was more with the reliever the Mets were acquiring. Clippard had a shiny 2.79 ERA and was a Proven Closer, but he also had a BB/9 of 4.89, a FIP of 3.96 and the worst xFIP in the majors at 5.51.
There is some subtlety here, because people will argue that elite relievers have a repeatable skill to control balls in play. Even with that factor, however, Clippard had glaring flaws that made him an objectively mediocre pitcher, and certainly not the sort of arm you acquire to bolster a playoff bullpen. It fits right in with Alderson’s quoted method of finding relievers to trade for: sorting a leaderboard by ERA.
Trading for Jay Bruce in 2016
At one point, Jay Bruce was one of the rising stars in baseball, coming up as a powerful bat in Cincinnati after being a first round pick. Then, a knee surgery after the 2013 season turned him into a shell of his former self, and he was totally unable to play the outfield or hit at a respectable level for two years. In 2016, the offense rebounded, as Bruce hit for a .295 ISO with the Reds and a .301 tAV, his best mark since surgery.
Despite that, Bruce was still so bad in the field that the value of his offense was totally negated, and he was basically a replacement level player. Beyond that, peripheral metrics about his exit velocity and batted ball distribution suggested harsh regression was in order. Even without understanding that second point, he made no sense as a trade target, due to his horrific defense. Instead, the Mets traded Dilson Herrera and Max Wotell and watched Bruce flail down the stretch and continue to play horrific defense, then doubled down on their mistake and exercised the $13 million option on Bruce for 2017, despite already having Michael Conforto and Yoenis Cespedes around to take the corner outfield spots.
Signing Jay Bruce after 2017
Continuing the Bruce saga, the Mets managed to finally get Bruce off the team in the midst of a disastrous 2017 season, sending him to the Indians for reliever Ryder Ryan. Of course, that meant the Mets no longer had Bruce, so they rushed to hand him a three-year, $39 million contract in the offseason. Analytics teams around the league had established that one-dimensional sluggers who aren’t actually elite offensively and don’t play any sort of defense are basically worthless, but the Mets were, as usual, behind the curve.
Oh, and they still had Yoenis Cespedes and Michael Conforto (even with the latter coming back from a shoulder injury). The only real CF on the roster was Juan Lagares, but the Mets chose to sign Bruce instead of signing Lorenzo Cain for only $3 million more in AAV. Bruce was projected for roughly three wins over the life of the contract, which should have bought the Mets closer to five wins on the free agent market.
Signing Jason Vargas
This basically boils down to WINZZZZZ. Vargas wasn’t particularly good for the Royals in 2017, running a 4.44 DRA. Spending two minutes to look at his splits shows that he was basically cooked after June, and he posted an ERA of 6.38 in the second half. The Mets’ analytics department was on the ball with this one, cautioning decision makers against signing the left handed. Someone in the front office saw Vargas’ 18 wins, however, and the statistical warning signs were ignored.
To say that this signing has worked out poorly is an understatement, and the Mets are still on the hook for another $8 million next year, along with a $2 million option.
Rostering Jose Reyes
Jose Reyes has been legitimately awful at basically everything since the start of 2017, but is still rostered largely due to “positional versatility.” He was projected to be worth less than half a win in 2018, and the Mets gave him $2 million just so he could play every position on the infield poorly and block younger, more important players. Since then, he’s been the fifth worst player in baseball with at least 184 PA, and all four players below him (Chris Davis, Victor Martinez, Dexter Fowler and Alcides Escober) have significantly more at bats.
The nightmare might not be over either, since Reyes has stated he’d love to be back in 2019.
The track record here is clear; the Mets make bad moves that even a cursory analysis using publicly available stats tells you are misguided. Predictably, these moves almost always blow up on them. The Mets don’t scout or develop particularly well either, so this isn’t an organization focusing on a strength that makes them stand out from the league. Meanwhile, the powerhouses in baseball – Yankees, Red Sox, Dodgers, Cubs and Astros – all have significantly larger and better respected analytics departments, as do most of the more exciting, rising teams like the Phillies and Brewers.
Somehow, management is either delusional or clueless enough to think that putting less emphasis on analytics solves this problem. If you were hoping for an analytically inclined GM hire that could modernize the franchise, I wouldn’t hold my breath.
Photo credit: Adam Hunger – USA Today Sports