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By Brian Joura
When we see a player’s line at the end of the year, we get to see how he did over the largest possible sample size. And that’s good, even if it can be a bit misleading. There’s no better example of that than 2022 Eduardo Escobar, who was lousy the first five months of the season and then who hit like gangbusters in the final month of the year. His overall line was that of a slightly above-average hitter. The day-to-day or week-to-week or month-to-month for Escobar was a different story.
Anyone who’s watched baseball for more than a couple of years should realize this at least to some extent. But sometimes it seems like even the die-hards don’t have a complete understanding of how much variability a player has during a full season. Let’s look at that in a few different ways. First, let’s examine the dozen Mets with the most PA here in 2023, with their OPS broken down on a monthly basis. September stats are thru 9/29:
| April | May | June | July | August | September | |
|---|---|---|---|---|---|---|
| Tommy Pham | .631 | .790 | 1.027 | .684 | NA | NA |
| Pete Alonso | .890 | .882 | .586 | .833 | .911 | .808 |
| Francisco Lindor | .762 | .685 | .816 | .923 | .818 | .848 |
| DJ Stewart | NA | NA | NA | .720 | 1.106 | .655 |
| Brandon Nimmo | .892 | .748 | .860 | .626 | .820 | 1.020 |
| Francisco Alvarez | .494 | 1.029 | .534 | .974 | .456 | .610 |
| Mark Canha | .675 | .754 | .718 | .771 | NA | NA |
| Jeff McNeil | .831 | .620 | .550 | .620 | .771 | .857 |
| Daniel Vogelbach | .792 | .582 | .651 | .791 | .890 | .733 |
| Mark Vientos | NA | .530 | .385 | .963 | .453 | .778 |
| Brett Baty | .861 | .642 | .659 | .552 | .217 | .540 |
| Starling Marte | .618 | .629 | .651 | .700 | .000 | NA |
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