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The Best and Worst 60 Game Stretches for Recent Cardinal Hitters

A lot of things, good and bad, can happen to a hitter in a 60 game sample

Divisional Series - Atlanta Braves v St Louis Cardinals - Game Four Photo by Jamie Squire/Getty Images

We’re sort of, kind of, officially in Spring/Summer Training, or whatever it’s called. As you’ve heard countless times from a sportswriting universe starved for stories, baseball is about to get real weird with it. Other folks have covered the designated hitter, players who might benefit most from the shortened season, Tyler covered how Cardinal teams have done over 60 game stretches, and other minutaie. Today, I want to cover just how much chicanery can happen to a hitter in a 60 game stretch. This being a Cardinals site, we’ll focus exclusively on Cardinal hitters and see how they’ve done at their best and worst in any 60 game stretch in 2018 and 2019.

All of this info comes from FanGraphs. We can get 60 game stretches by going to the graph section for an individual player, selecting the stats we want, modifying the rolling average to 60 games, and exporting the data. For our sample, I’m choosing any Cardinal hitter with the team for 2020- sorry, Marcell Ozuna and Jose Martinez. I’ll also exclude hitters who only had minimal games played in those seasons- in the 70-75 games range or less. That means it’s fairly pointless to include Tyler O’Neill, Austin Dean, Lane Thomas, Dylan Carlson (obviously), Brad Miller, and Matt Wieters. O’Neill even played in exactly 60 games last season, so his peak and valley last year are the exact same. I’ll also note that I’m not rolling 2018 into 2019. You won’t see the last 23 games of Kolten Wong’s 2018 and his first 37 games of 2019 combined.

We’ve shaved our group down at this point to 2018 and 2019 for Yadier Molina, Dexter Fowler, Harrison Bader, Paul DeJong, Paul Goldschmidt, Kolten Wong, Matt Carpenter, and Tommy Edman (2019 only). I wish there were more but the Cardinals are entering the season with lots of players short on track records. One last note. For my data, I’m using any stretch of 50 to 60 games. Not every player will play all 60 games, but 50 out of 60 would certainly count as regular playing time.

We’ll start with the big gun- wRC+. It’s big enough that I turned it into a fancy dumbbell plot with each hitter’s maximum and minimum wRC+

If 2018 was a 60 game sample, depending on when it started and ended, Matt Carpenter could have been either a generic 105 wRC+ hitter or a nuclear MVP candidate at 216. Paul Goldschmidt in 2019 could have looked like a total collapse, or exactly what he always was in Arizona. Yadi’s best in 2018 looked like vintage, MVP candidate Yadi in his peak and the valley was... actually, not that bad- just barely below his 2019 peak. That’s kind of disconcerting for his 2019, but could also just mean he was very consistent.

Kolten Wong, particularly in 2019, is the poster boy for the loud variance of 60 game samples. The gap between his max and min in 2018 and 2019 is 74 in the former and 95 in the latter. Paul DeJong’s 2018 was fairly steady but 2019 saw the good (147 wRC+ peak), and the bad/ugly (67).

A lot of dumb stuff, both good and bad, can happen in 60 game samples. In case you’re not convinced, let’s take a look at the same group and their OBP and SLG max and min in 2018-2019. I’ve been incredibly busy at work lately so you don’t get another dumbbell plot (sorry!), but this table will suffice:

Cardinals, 60 Game OBP/SLG Max and Min, 2018-2019

Player/Yr MaxOBP MinOBP MaxSLG MinSLG
Player/Yr MaxOBP MinOBP MaxSLG MinSLG
Fowler 2018 0.292 0.249 0.309 0.269
Bader 2018 0.369 0.301 0.477 0.375
Carpenter 2018 0.444 0.327 0.754 0.409
DeJong 2018 0.341 0.280 0.447 0.360
Goldschmidt 2018 0.442 0.319 0.653 0.380
Molina 2018 0.359 0.306 0.505 0.391
Wong 2018 0.377 0.273 0.473 0.282
Fowler 2019 0.382 0.286 0.479 0.376
Bader 2019 0.363 0.284 0.455 0.261
Carpenter 2019 0.350 0.312 0.406 0.347
DeJong 2019 0.399 0.266 0.535 0.335
Goldschmidt 2019 0.365 0.299 0.564 0.327
Molina 2019 0.326 0.276 0.425 0.325
Edman 2019 0.373 0.288 0.515 0.406
Wong 2019 0.433 0.276 0.524 0.301

Wong had stretches of a .433 OBP and a .535 SLG last season. Fowler last year had a .382 OBP stretch and a .479 SLG stretch. Probably most impressive, at least to me, is that Edman’s worst 60 game stretch still had a .406 SLG. Not that .406 is amazing, but rather that’s a very solid floor to a season. The overall point remains the same- a lot of weird stuff can happen in a small sample like this.

Now, those data points are not necessarily at the same time. DeJong had a max SLG of .535 in a 60 game stretch last year and a .399 OBP in a stretch, but they don’t necessarily overlap. However, if we look at max and min OPS during any 60 game stretches, we see that Wong did indeed have a .956 OPS stretch last season, but also had a .592 stretch. DeJong had a .934 peak and .618 valley. Bader’s max was a solid .817- a player with his glove doing that all season would be an All-Star- but his valley was .548. Goldschmidt goes .927/.652. Look at all of these peaks and valleys and think about how they’d alter your perception of their seasons.

The last piece of this puzzle is batting average. It’s fun to think of all of this wild variance in short bursts and dream of a random Cardinal putting up a .400 batting average in a “full” 60 game season. Alas, the highest anyone had in the last two seasons was Wong at .365 last year, followed by Carpenter (.350 in 2018), with Goldschmidt (.349 in 2018) right behind. Their valleys in that season were .213, .215, and .201 respectively.

In summation, when you watch this season and see crazy stats materialize, try not to draw too many conclusions from it about any one player. I’ll let the Stranger have the final word about all of what can happen in 60 games: