Mets starting pitcher Clay Holmes.

Mets starting pitcher Clay Holmes. Credit: Newsday/J. Conrad Williams Jr.

It’s April, Max Kranick is doing well, and after Mets pitching coach Jeremy Hefner talks about the adjustments the young reliever has made, he adds, “you can talk to Clay about that.”

Clay would be Clay Holmes, the pitcher who’s gone from starter to middle reliever to closer to starter again, and is having success in his newest role. He’s also known to be analytically curious – the type of guy who talks about seam-shifted wake and supination bias like he’s casually sipping tea with Isaac Newton.

“Some people learn by watching and some people learn by physically doing it,” reliever Reed Garrett said. “I think just having [Clay] around, his knowledge with baseball has been huge for us. He’s good with analytics, good with understanding approaches and stuff like that.”

There are plenty of reasons the Mets' pitching staff went into Thursday with an MLB-best 2.82 ERA. But, while Holmes isn’t the ace, he’s indicative of the approach the team is taking – and it’s helping solve the mystery of how a unit that was thought to be a liability coming into the season is proving to be its life preserver, even as the offense struggles.

They know how and when to use data, and they know how to optimize the tools they have. A number of them are reclamation projects, or pitchers who’ve yet to make their mark, and invention and reinvention is easier when unemployment is the only other option.

Said Hefner of Kranick's success after he was DFA'd last year: "I think he wants to be great and that part of him bubbled up."

But let’s start with Holmes, who has a 3.13 ERA, introduced a wicked kick changeup this season, and has helped buoy a rotation that’s outkicked its coverage. He is, at times, still a reliever at heart, Hefner said, and is happy to share his knowledge with the class.

“He’s super smart and he’s got a ton of experience in the bullpen,” manager Carlos Mendoza said. “Clay is one of those unicorns. The more [information], the better for it. Not only does he know what every metric means, he knows how to digest it and apply it to his game…He just wants to make sure that people know and understand that there’s a lot more information that’s available.”

Asked about helping the bullpen, Holmes demurred. Asked about data analysis, he…did the opposite of that.

“A lot of pitchers now, whether you’re in the bullpen or a starter, there’s a lot of information out there and I think there’s always that conversation going on of what to make of what,” he said. "Ultimately, it’s a tool to help you become the best version of yourself. I think there’s a lot of different routes to it but it’s definitely one way to go about it. I’ve always been curious.”

And it is difficult, by the way – balancing how to use the glut of biometric data being fed to professional athletes who rose through the ranks because they threw a leather sphere really well, and to a really precise place. But to their credit, Mets pitchers have adapted.

Look, for instance, at Huascar Brazoban, who, at nearly 36 years old, is having a career year, pitching to a 0.90 ERA in 22 appearances.  He pitched a scoreless 2 1/3 innings, allowing one hit with no walks and four strikeouts Wednesday against the Red Sox. He also came into a bases loaded situation in the fifth and struck Alex Bregman out swinging to end the inning.

After, Brazoban was asked what’s changed, and he essentially said it was the knowledge he was given - whether through experience, age, or data.

“I’m an older pitcher,” he said via an interpreter. “I’ve used [data] in the past…[but] as I’ve been here, the analytics team, the coaches have helped me gather more information, more data on how my pitches work, so I’ve been able to take that to the mound and have more success.”

He added an important part: He’d faced Bregman before. He knew his tendencies. It was the pitching version of nurture and nature. Use the analytics, but use your instincts, too. It’s a clever but difficult alchemy, but the Mets have seemingly tapped into a slew of wizards.

“The guys that are thinkers, [the data] feeds right into them, but you have to get into the meat and potatoes of what makes you good,” Holmes said. “Some people like finding that on their own. Some people need somebody alongside to say, hey, if you do this and this all this other stuff will take care of itself. We’ve got a lot of good people here who do that.”

He appears to be one of them.

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