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Looking Back At Our Pitchers’ Spring Training Stats

Could they be as interesting as the hitters’ stats?

Oakland Athletics v Arizona Diamondbacks Photo by Christian Petersen/Getty Images

Last week I took a look at our hitters’ K% and BB% and compared them to Spring Training. Specifically, I wanted to see that if over- or underperforming their projections had any merit to changes that we would see in the season.

The results were a mixed bag of sorts, though it seemed like there might be a signal of things to come, particular for the hitters that outperformed both in K% and BB% or underperformed in both. It was an exercise that was mostly out of amusement, though it does give me a fun new hypothesis to test out next season.

Now, just to be fair to everyone, I will do the same exercise for our pitchers.

Dbacks Spring Training Pitchers K%

Player ZiPS K% K% ST Trend Current Trend
Player ZiPS K% K% ST Trend Current Trend
Brad Boxberger 31.70% 31.20% Worse Even
Archie Bradley 27.80% 24.10% Worse Worse
Andrew Chafin 24.30% 27.50% Better Better
Patrick Corbin 20.10% 31.50% Worse Better
Jorge De La Rosa 20.50% 15.30% Better Worse
Zack Godley 24.50% 22.50% Better Worse
Zack Greinke 23.40% 25.00% Worse Better
Yoshihisa Hirano 21.30% 23.70% Better Better
TJ McFarland 12.70% 13.10% Better Even
Robbie Ray 31.50% 34.40% Worse Better
Fernando Salas 22.10% 17.70% Worse Worse
Taijuan Walker 21.30% 16.10% Better Worse

Welp. Out of 12 pitchers that I analyzed, only 4 of them managed to maintain their “trend” from Spring Training over to the regular season: Archie Bradley, Andrew Chafin, Yosihisa Hirano, and Fernando Salas. Hirano is already difficult to project because he came over from Japan.

What’s even more amsuing is Patrick Corbin, who is currently sitting on a 31.5% K%, which is the 7th-best among MLB starters this season. Yet he was somehow worse than his projections in Spring Training with a measely 16.0%. Was he just hiding it or something?

We’re not off to a good start. Is BB% going to be any more telling?

Dbacks Spring Training Pitchers BB%

Player ZiPS BB% BB% ST Trend Current Trend
Player ZiPS BB% BB% ST Trend Current Trend
Brad Boxberger 12.90% 12.30% Better Better
Archie Bradley 9.10% 6.60% Worse Better
Andrew Chafin 9.80% 10.70% Worse Worse
Patrick Corbin 7.50% 6.80% Worse Better
Jorge De La Rosa 10.60% 9.90% Better Better
Zack Godley 9.50% 11.60% Even Worse
Zack Greinke 5.50% 4.90% Better Better
Yoshihisa Hirano 8.30% 8.60% Better Even
TJ McFarland 7.60% 5.90% Even Better
Robbie Ray 9.90% 12.70% Worse Worse
Fernando Salas 7.00% 7.70% Better Worse
Taijuan Walker 7.70% 8.90% Better Worse

Slightly better, this time with 5 out of the 12 pitchers matching their trend from Spring Training. What’s amusing here is that the projections seem to be really close on a lot of the pitchers - 7 of the 12 are within 1% of their projection. BB% seems like an easier thing to project than K%, as K% is usually the thing that surgers when a player breaks out.

So far, we’re not seeing as much from the pitchers as we did with the hitters. Let’s try the “bucket” approach:

Better ST K%/Better ST BB%: Jorge De La Rosa, Yoshisa Hirano, Taijuan Walker

Two disappointments (and an injury) and an hard-to-project transplant from Japan. Not a great sign.

Worse ST K%/Better ST BB%: Brad Boxberger, Zack Greinke, Fernando Salas

Greinke and Boxberger are having solid but up-and-down seasons. Salas just wasn’t very good.

Better ST K%/Worse ST BB%: Andrew Chafin

Andrew Chafin is quietly having a really solid season. His strikeouts have declined over the past three seasons, but he’s still keeping his walks reasonable and not giving up homers. But not much to see here.

Worse ST K%/Worse ST BB%: Archie Bradley, Patrick Corbin, Robbie Ray

This just doesn’t make sense anymore. Archie is having a great season once again and Patrick Corbin was just selected to the all-star game in his breakout season. Robbie Ray has shown flashes of that dominance we saw last year and is currently riding a career-high in strikeout rate, though he was VERY wild to start the season.

Well, the bucket approach didn’t help us much, at all. Two of our best pitchers looked worse in Spring Training yet here we are. I had a feeling that the pitcher performance was going to be less reliable than our hitter data and I’m still not confident in the hitter hypothesis I developed last week.

Still, I wanted to follow up on my article to see what we would find. I might do this again after the season for some more research, but I think it will require a more analytical approach.

But Spring Training just (mostly) doesn’t matter.