Cold bats hope to warm with luck back on their side

PORT ST. LUCIE — First Data Field carried a regular-season vibe on Sunday afternoon, a near-packed house — replete with spring-breaking New York families — investing emotion into the outcome of this Grapefruit League contest between the Mets and the Marlins.

So when the Mets mounted rally after rally in the early going, only to see each one fall short? Former Met Yogi Berra coined a phrase for this — I’ll look it up at the soonest opportunity.

The Mets vow that they can’t possibly perform as poorly with runners in scoring position as they did last year, when their .225/.305/.372 slash line in those situations gave them the worst batting average, tied them with the Phillies for the worst on-base percentage, and ranked them third-to-last in slugging percentage. In the context of the Mets’ worries and woes, let’s put it this way: It’s far less likely the Mets will be brought down by their lack of clutch hitting than by pitching injuries.

“It was good towards the end of both 2015 and 2016,” Mets hitting coach Kevin Long said Sunday of his team’s batting with runners in scoring position. “But before that, it was awful. I’ve got my fingers crossed that we’ve kind of turned the corner with that.”

You take spring-training team data with a grain of salt, understanding that minor-leaguers receive a healthy amount of the playing time. Yet after the Mets’ 7-5 loss to the Marlins, they sported a respectable .276 batting average in those situations, with 63 hits in 228 at-bats, ranking them in the middle of the baseball pack (thanks, Elias Sports Bureau). As Long said, “It’s one of those stats that you just hope is going to be close to our regular average. If it is, or if it’s a little bit above, then we’re in good shape. If it’s not, there’s really not a whole lot you can do about it.”

In this contest, the Mets went 3-for-16 overall in their prime scoring opportunities, and missed on their first eight attempts before the Marlins leapt far ahead, 7-0, with a six-run sixth. Yet if you scrutinized the individual at-bats, you’d appreciate why Long called it “really kind of a luck stat.” In the fourth inning, with the bases loaded and two outs, Curtis Granderson hit a ball on the screws that former Met Matt den Dekker tracked down in center field. In the fifth, with Mets on first and third with one out, Lucas Duda drilled a hard grounder right at Dee Gordon, who turned an inning-ending double play.

“I think it’s kind of an unfair stat to evaluate,” Long said. “I just don’t think it’s one you can hone in on. Most of our rounds of [batting practice] I would say are situational-hitting rounds. Having said that, it’s work done every day.”

The Mets appear pleased with the work they’ve done this spring. Their overall team batting average is .269, and their 132 runs put them in the industry’s upper half.

“We’ve actually been swinging the bats very, very well,” Terry Collins said. “Today was one of those days, but we’re going to give those main guys a day [Monday]. We have the off day Tuesday. And then starting Wednesday, it’s crunch time. We’ve got … basically eight games left and they’re playing six of them.”

Matt Harvey, working to alleviate concerns about his tough spring, won’t have much offensive support joining him Monday in far-away Lakeland against the Tigers. The Mets’ offensive production should be healthy enough. The health of their pitching remains unresolved, although the early non-Harvey signs are encouraging. Jacob deGrom enjoyed another solid outing Sunday as he lasted 5 ¹/3 innings.

The Mets’ clubhouse Sunday didn’t carry a regular-season vibe. All of the regulars had departed by the final out, the usual drill. They’ll get after it again with runners in scoring position, believing their process to be sound.

“I remember a few years ago [2014], they said the St. Louis Cardinals had the answer to all of that,” Long said. “And then they were the worst team in baseball the next year.”

Not quite the worst, but terrible. The Mets are due some good times on this particular statistical roller coaster.