Are World Baseball Classic Players Actually Underperforming in 2026?

Denis Poroy and Kevin Sousa-Imagn Images

Approaching the end of a 2026 season that didn’t match his stratospheric standards, Paul Skenes attributed some of his problems this year with velocity to his participation in the World Baseball Classic.

Usually, that time of year, you’re kind of ramping up and it’s a little bit slow. You can kind of get onto the slope and find your body. One live [batting practice], you’re topping at 97 [mph], and then the next you’re 98, 99. And that wasn’t the case this year. Looking back, I don’t think that really helped.

This notion from Skenes did not come out of nowhere. A wide assortment of people has addressed this question on some level. Our very own Michael Baumann touched on it in 2023, though he was looking more at teams as a whole than players.

I’m a natural skeptic when it comes to claims of causation, which tend to be fueled by anecdote. From the supposed sophomore slump to the suspected swing-ruining impact of the Home Run Derby, there’s a lot of loosey-goosey if-then statements going around. But as these things go, the theory that WBC participation in a given year negatively affects player performance in the corresponding campaign has a lot of plausibility. The WBC is a very different environment than typical spring training games, and it comes at a time when players are normally focused on getting ready for the regular season. It doesn’t sound crazy to think these changes in preparation have some kind of deleterious effect on a player. However, we should test these things.

To do this, I collected a sample of all the players who have registered either 200 plate appearances or 40 innings pitched in the majors this season, and then separated them into two buckets: those who played in the 2026 WBC and those who didn’t. From there, I examined how their actual performance compares to their final ZiPS projections entering the season.

As of Thursday morning, 81 of the 357 position players who’ve recorded at least 200 plate appearances this season participated in the WBC. These players run the gamut from Pete Crow-Armstrong, who has exceeded his ZiPS-projected wRC+ by 45 points, to Jarren Duran, who has underperfomed his projection by 47 points.

Largest wRC+ Overperformers, WBC Participants (min. 200 PA)
Player 2026 wRC+ ZiPS wRC+ Diff
Pete Crow-Armstrong 157.8 112.7 45.1
Curtis Mead 132.5 94.6 37.9
Randy Arozarena 151.0 116.1 34.9
Mickey Gasper 134.9 102.6 32.3
Willson Contreras 152.1 123.4 28.7
Liam Hicks 123.8 96.3 27.4
Dominic Canzone 133.0 107.8 25.2
Javier Sanoja 114.5 89.7 24.8
Brice Turang 125.8 103.6 22.2
Cole Carrigg 101.9 81.0 20.9
Nolan Arenado 114.4 95.6 18.9
Junior Caminero 142.3 124.3 18.0
Otto Lopez 114.2 97.7 16.5
Oneil Cruz 131.4 115.3 16.2
Travis Bazzana 110.5 95.3 15.3
Sam Antonacci 118.6 107.3 11.3
Alex Bregman 124.1 113.4 10.7
Bryce Harper 135.1 125.3 9.8
Nick Gonzales 109.2 100.4 8.8
Jackson Chourio 124.1 115.5 8.6

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Largest wRC+ Underperformers, WBC Participants (min. 200 PA)
Player 2026 wRC+ ZiPS wRC+ Diff
Jarren Duran 69.4 116.6 -47.2
Vladimir Guerrero Jr. 97.1 139.9 -42.9
Ezequiel Tovar 53.7 95.0 -41.3
Aaron Judge 140.7 179.1 -38.4
Cal Raleigh 94.9 131.4 -36.4
Edouard Julien 66.2 100.9 -34.7
Ronald Acuña Jr. 124.1 157.6 -33.5
Austin Wells 73.8 103.6 -29.8
Roman Anthony 96.3 125.8 -29.5
Gunnar Henderson 102.4 131.9 -29.5
Ketel Marte 102.0 131.1 -29.1
Mark Vientos 80.5 109.0 -28.6
Salvador Perez 73.7 101.9 -28.2
Josh Naylor 98.1 123.9 -25.7
Julio Rodríguez 105.2 129.4 -24.3
Owen Caissie 88.8 111.5 -22.8
Tyler O’Neill 94.1 116.8 -22.7
Eugenio Suárez 98.9 118.5 -19.6
Shohei Ohtani 141.9 160.9 -19.0
Spencer Horwitz 100.6 118.7 -18.1

The average WBC hitter underperformed his wRC+ projection by 3.8 points, with a median right around the same number (3.9). This is a smaller underperformance than it sounds, because if you look at the control group, the players who didn’t play in the WBC underperformed their wRC+ projections by an average of 2.4 points, with a median of 2.9 points. If you also use minor league translations to more accurately capture underperformers who were demoted to the minors, the average underperformance for the WBC participants drops to 4.7 points of wRC+, and the non-WBC player underperformance declines by a similar margin, to 4.0 points. Comparing these results to those of the 2023 WBC participants gives us a similar statistical conclusion: The negative impact of playing in the WBC, if it’s real at all, appears to be exceedingly small.

Of course, we’ve only analyzed position players so far. It’s certainly a possibility that a huge change in routine affects pitchers differently than hitters. Our study includes the 382 pitchers who’ve pitched at least 40 innings this season, 59 of whom participated in the WBC. I’m also going to look at year-over-year fastball velocity change, to directly test what Skenes was talking about. I’m using ERA- instead of ERA+ because the weirdness of extreme values of ERA+ tends to distort things.

Largest ERA- Overperformers, WBC Participants (min. 40 IP)
Player 2026 ERA- ZiPS ERA- Diff
Cal Quantrill 70.5 129.1 -58.7
Gordon Graceffo 67.0 103.8 -36.7
Garrett Whitlock 40.3 76.3 -35.9
Kevin Kelly 59.4 93.5 -34.1
Brennan Bernardino 61.2 94.6 -33.4
Michael Petersen 72.6 103.9 -31.2
Eduardo Rodriguez 68.6 98.8 -30.1
Rico Garcia 76.2 106.1 -30.0
Mason Miller 29.7 57.3 -27.6
Antonio Senzatela 92.7 120.2 -27.5
Abner Uribe 48.4 73.6 -25.2
Huascar Brazobán 74.5 99.6 -25.1
Michael Wacha 78.3 101.1 -22.8
Keider Montero 83.5 105.9 -22.4
Ryan Yarbrough 92.7 111.5 -18.9
Enmanuel De Jesus 91.7 110.5 -18.8
Greg Weissert 78.3 97.0 -18.7
Kenley Jansen 78.4 97.2 -18.7
Michael Soroka 78.7 96.2 -17.5
Yoshinobu Yamamoto 60.6 78.1 -17.5

Largest ERA- Underperformers, WBC Participants (min. 40 IP)
Player 2026 ERA- ZiPS ERA- Diff
Michael Lorenzen 155.2 106.8 48.4
Ron Marinaccio 148.4 105.3 43.0
Andrés Muñoz 109.6 73.6 36.0
Garrett Cleavinger 114.9 81.8 33.2
Dennis Santana 112.6 80.8 31.9
Logan Webb 105.8 75.9 29.9
Jameson Taillon 137.8 111.0 26.8
Paul Skenes 90.5 66.9 23.6
Luinder Avila 129.8 108.9 20.8
Griffin Jax 86.9 67.2 19.7
Victor Vodnik 111.9 92.2 19.7
Dean Kremer 121.2 103.0 18.2
Seth Lugo 121.3 103.5 17.9
Yusei Kikuchi 118.6 103.7 14.9
Camilo Doval 102.5 88.0 14.5
Juan Mejia 109.4 96.8 12.5
Jose Quintana 114.4 102.1 12.3
Aaron Nola 104.9 94.5 10.5
Eduard Bazardo 99.7 90.3 9.4
Brayan Bello 105.2 95.8 9.4

As a group, the WBC pitchers outperformed their preseason projections by about 4 points of ERA- (-4.2 points vs. projection). The non-WBC pitchers outperformed by a similar margin, at -3.8 points of ERA- vs. the preseason projections. As before, the conclusion doesn’t change if you look at 2026 minor league translations or repeat the exercise with the 2023 WBC pitchers.

For velocity, I gathered a sample of all pitchers who threw 10 innings in both 2025 and 2026, and I specifically looked at the velocity of the fastest pitch type in their repertoire. The average WBC pitcher improved his velocity by 0.03 mph from 2025 to 2026. The average non-WBC pitcher saw his velocity go up by 0.04 mph.

So, what does this mean? At least from the data we have, there’s little reason to believe that playing in the World Baseball Classic has a negative effect on a player’s regular-season performance, as a general rule*. This is a good thing for baseball, as the WBC is a great showcase of the game to an international audience, and I hope that it continues to spread baseball to countries not known traditionally for being into the sport.

Note there’s an asterisk in that last paragraph, and it’s an important one. This is an examination of the effect on a macro level. Humans are complex animals, and it’s very possible that there are some players who may see a negative effect from replacing their low-key spring training with an international tournament. For that reason, players should think long and hard about how their participating might affect their regular-season preparation. Still, this study should provide some encouragement for players who want to compete in the WBC, and some reassurance for teams and fans who would otherwise be concerned.





Dan Szymborski is a senior writer for FanGraphs and the developer of the ZiPS projection system. He was a writer for ESPN.com from 2010-2018, a regular guest on a number of radio shows and podcasts, and a voting BBWAA member. He also maintains a terrible Twitter account at @DSzymborski.

23 Comments
Oldest
Newest Most Voted
willybeanesMember since 2020
10 days ago

I think the table is confusing Kevin Kelly the Rays pitcher with Kevin Kelly the pitcher in the Mexican League that pitched for Netherlands

Eminor3rdMember since 2019
10 days ago

Good study. Good job, Dan

srosnerMember since 2025
10 days ago

Your findings confirm my suspicions. Therefore this must be a great article.

SEAfahrerMember since 2019
10 days ago

Dan are you hosting a chat this week?

Last edited 10 days ago by SEAfahrer
gydemeMember since 2020
10 days ago

as suspected, but always best backed up with data

LaBellaVitaMember since 2018🏆 MVP
10 days ago

It would be nice if you provided the standard deviation values of the 4 groups so that we can approximate some simple p-values.

francis xavier pfefferMember since 2024
10 days ago

If it weren’t for that dastardly WBC, PCA would have gone 70-70

resist1922Member since 2024
10 days ago

He still could, have faith.

Sonny LMember since 2017
9 days ago
Reply to  resist1922

Depending on the wind direction this weekend Teddy Ballgame’s red seat could be in play

Doug LampertMember since 2016
9 days ago
Reply to  Sonny L

Unlikely, discussions I’ve seen of the red seat say that the added boxes atop the stands probably block too much of the tailwind for that to happen again.

Even Ted Williams needed a lot of help from the wind to hit one that far.

NATS FanMember since 2018
10 days ago

deleted by me

Last edited 10 days ago by NATS Fan
compucles
9 days ago

I think the effect of the Home Run Derby also has a lot of plausibility. There’s plenty of logic behind it as well as plenty of examples, including again this year. Home Run Derby Champion Jordan Walker hit 22 HRs in 357 ABs (.062 HR/AB) with a .532 SLG before the Derby but only 6 HRs in 240 ABs (.025 HR/AB) with a .371 SLG after the Derby.

Runner-up Schwarber also has significantly uneven splits this year with .091 HR/AB and a .560 SLG in the first half and 0.060 HR/AB and .423 SLG in the second half.

While some of the noise is due to players who have a better first half being more likely to participate in the Derby in the first place, it would be nice if someone also did a larger case study on this alleged phenomenon, including taking into account how far each player lasted in the Home Run Derby.

Last edited 9 days ago by compucles
crew87Member since 2016
9 days ago

Would be very intrigued to see the same numbers broken out by Team USA vs other participants. The vibes were rancid on the team (e.g., hurr durr we don’t shake hands). Of course, it didn’t seem to affect PCA, and we’re narrowing down to even smaller sample sizes so it might not even be feasible.

Jorge FabregasMember since 2016
9 days ago

Another question would be whether it increases the chance of injury, but that might be captured in the performance data, not just a count of missed time.

Jorge FabregasMember since 2016
9 days ago
Reply to  Jorge Fabregas

Like Kyle Teel isn’t in this data because he didn’t reach 200 PAs. Maybe he would’ve gotten the same injury in spring training, we can’t say. Or if he hadn’t gotten the WBC injury if he would’ve gotten his other injuries.

BTW, looks like preseason ZIPS had him on the nose (102 wRC+).

Last edited 9 days ago by Jorge Fabregas
dl80Member since 2020
8 days ago
Reply to  Jorge Fabregas

I would really love to see a study of injury rates for WBC participants vs non.

avogadrothemoleMember since 2020
9 days ago

Have there been studies on injury rates in WBC vs non groups? I recall that being a big topic of just-so stories a few cycles ago.

KinanikMember since 2016
9 days ago

Your last paragraph is the key, and often overlooked in attempts to find out “does X make players do Y” (this is also a big problem in other fields that try to determine causality—antidepressant studies, etc). “Paul Skenes had a bad year because of the WBC” is perfectly compatible with “WBC participation does not predict a bad year.” Maybe PCA doesn’t have his breakout without the WBC, with the infinite wisdom he got from Mark DeRosa. Until we can have Skenes both pitch and not pitch in the WBC and compare both Skenesses, we’re stuck with these studies.

A deeper understanding could involve looking at underperformers and seeing if there are any physical/psychological predictors… but this is assuming information not accessible to us.

One piece I did wonder about, though: innings pitched/injury probability. We know Edwin Diaz pitched fewer innings after the last WBC… but did players get hurt more often because they didn’t have their typical ramping up? If not, does that mean that whatever teams do during Spring Training doesn’t prevent injury?

eastmanMember since 2022
9 days ago
Reply to  Kinanik

Hah! We wrote a lot of the same things at just about the same time 🙂

eastmanMember since 2022
9 days ago

I think it’s cool that you wrote that last paragraph about the individual context. I was enjoying the analysis and just considering the final caveat you raised just as you got to it. It’s totally plausible for the effect to be real at an individual level.

It might be interesting to look at cross-WBC correlation for players who have played in multiple tournaments. If a player underperformed their projection the years after WBC1 and 2, how likely is it that they will underperform after WBC3, compared to players who didn’t play, or compared to a standardized aging curve for example.

airforce21oneMember since 2026
8 days ago

Possibly dumb question: if you set the bar at 200 plate appearances, aren’t you cutting out players that may have been performing so poorly that they got benched or sent down?

dl80Member since 2020
8 days ago
Reply to  airforce21one

Or injured

andgilbertMember since 2020
7 days ago

I’d love to see some sorry of weighted average where playing time is factored in so it’s not just on a rate basis, getting at injury time implications. Like a net war impact cumulative across position players and pitchers