Note: All stats in this article include games through the Mets’ April 24th, 2024 game against the Giants.

It would be an understatement to call the start of the Mets’ 2024 season uneven and unexpected, and perhaps no other aspect of their overarching team performance illustrates that better than what’s been going on with their lineup. Players generally expected to perform reasonably well, like Brandon Nimmo and Francisco Alvarez, struggled out of the gate while players like Tyrone Taylor and D.J. Stewart are among the team’s wRC+ leaders two dozen games into the season.

One of the more disappointing performances at the plate so far has been Francisco Lindor, particularly during the first eight games of the season. Consider this: his first eight games were so bad that he still has a wRC+ of just 89 after slashing .288/.347/.515 in the 16 games since bottoming out on April 6th at .032/.184/.032. Of course, a BABIP of .038 in those first eight games will make the back of anyone’s baseball card a certified disaster, but a -14 wRC+ (yes that’s a negative value) is so fascinatingly bad that it makes you wonder what the heck was going on over such a moderately prolonged stretch (38 plate appearances to be exact).

There’s nothing particularly abnormal about a slump regardless of where it occurs during the long season, though some poorly-timed ones may hurt more than others. Lindor’s numbers were just so amazingly miserable that it merits at least a cursory look to see if we can get an idea of what was going wrong and potentially how he has started to turn it around. Well, we can at least take a look at the numbers to see if anything jumps out. The small sample caveat applies here of course.

His BB% (10.5%) was higher than his career norm while his K% (15.8%) was right in line with it during the eight-game slump, and he swung less at pitches both inside (29.3%) and out of (65.6%) the strike zone. In fact, his plate discipline profile looked relatively normal enough across the board considering the small sample save one glaring difference. His career O-Contact% (contact outside of the strike zone) during his rough eight-game stretch was 58.3% compared to 70.5% for his career. Additionally, while his hard hit rate was consistent with his career numbers, his Barrel% of 3.8% was significantly lower than his career average of 7.1%. Add to that a significantly increased launch angle of 22.3 compared to his career average of 13.2, a 53.8% fly ball percentage compared to a career average of 38%, and the fact that he was hitting it up the middle more often than his career norm and we’re starting to get a clearer picture of just what was going wrong for him from an outcomes perspective.

He also saw a bit of an uptick in sliders and cutters compared to the averages across his career and, as you can see from the chart below courtesy of Brooks Baseball, he hasn’t done all that well historically against sliders in particular:

The below chart is also from Brooks Baseball and outlines his performance against the varieties of pitches he faced during his slump. I’ve included it for the sake of comparison, but as you can see there’s limited value considering he was absolutely terrible facing everything.

I also attempted to exam some zone profile information, but again the only thing we can gain from it is the fact that Lindor exacerbated his woes by chasing both high and low a bit.

What resulted appears to be a massive black hole of a slump in which Lindor was making incredibly poor contact, mostly in the air and at defenders, while getting a higher-than-average helping of his least favorite pitches.

So what changed in those sweet 16 games after the dreadful first eight? In an unhelpful word: everything. Specifically, his Barrel%, launch angle, and fly ball percentage tracked closer to his career averages while his O-Contact% crept up closer to what we’re used to seeing as well. The jump in BABIP to .288 didn’t hurt, though he had to actually put the ball in play with authority for that to make much of a difference. That -14 wRC+ turned into 144 across those 16 games, an incredible turnaround even considering the small sample sizes.

On paper these two Lindors are dramatically different players. While all players fall into slumps, the severity of the one that bogged him down to start the season is almost inexplicable outside of some underlying health or mechanics issue. Maybe he simply never got comfortable in Spring Training and it bled over with a vengeance against a brutal schedule to open the season. “Hit the ball harder and where they ain’t” isn’t exactly crack analysis, but at the end of the day it really appears to have come down to him simply working through his issues on the field in a very extreme and public way.

Let’s hope that version of Lindor has been flushed out in a season’s worth of slumps in one horrific go. It’s likely this team will sink or swim based on the strength and consistency of its offense this year, and Lindor is obviously a key factor in whatever outcome they manage by season’s end.

And hey, they wouldn’t be the Mets if they didn’t keep things interesting.

2 comments on “Francisco Lindor’s odd start to the season

  • NYM6986

    Great stats on Lindor. It is not unreasonable to say that as Lindor goes, so goes the Mets. At least in the bigger picture. Its seems that it’s hard to say which version of Lindor, Nimmo or McNeil you will see each game but at least in his miserable start, Nimmo keeps getting on base. What Lindor has not done is let his soft start convey to his play in the field. He is still the anchor of the infield and vital to this teams success. Looking for him to continue to improve at the plate.

  • Brian Joura

    Nothing was working for Lindor those first eight games.

    In his next 10 games, he started hitting fastballs but was still miserable against sliders and curves. From 4/7 – 4/17, Lindor was 0-9 versus sliders and 1-8 versus curves.

    And now he’s hitting the slider. From 4/19-4/26, he’s 6-9 versus sliders, including a double and two home runs.

    I love how we can track things like this with Statcast!

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