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Three Astros Things: Leg Kicks, Ronel Blanco, and Pitch Modeling

Caution: Small sample size applies.

MLB: Detroit Tigers at Houston Astros Troy Taormina-USA TODAY Sports

Jeremy Peña Kept The Leg Kick Adjustment

We’re all familiar with the story of Jeremy Peña by now. The eventual ALCS and World Series MVP got his rookie season off on the right foot, hitting .281/.329/.490, which was good for a 132 wRC+ through May 31. By all appearances, the Astros found their replacement for Carlos Correa. However, from June 1 through September 10, Peña’s hitting — .233/.262/.366 — left something to be desired. While Peña’s usually strong defense provides a high floor, his inability for long stretches to get on base consistently was an issue. Opposing pitchers adjusted to him by the summer, especially as they peppered him with more breaking and offspeed pitches, with an 11.5% jump in the June 1 through September 10 period compared to Opening Day through May 31.

But on September 10 against Shohei Ohtani and the Angels, something changed. Specifically, Peña left his pronounced leg kick in the dust and adopted an approach in which his left foot hit the ground more quickly. It was an adjustment I was curious to see carry over into 2023. Thus far, through seven games, it appears that the leg kick adjustment is here to stay.

Here are Peña’s numbers against breaking and offspeed pitches — sweepers included — from April 1 through September 10, 2022: .207/.225/.346, 49 hits (880 pitches). Here are those same metrics, but from September 11, 2022 through April 6, 2023: .327/.352/.596, 17 hits (203 pitches). There is a small sample caveat to keep in mind, but the results continue to look promising.

Ronel Blanco’s Early Performance

When the Astros broke camp in 2022, Ronel Blanco was on the Opening Day roster and had a bit of momentum, allowing only three baserunners and no runs while striking out seven in five innings of work. But following an April when he allowed five runs in 6 13 innings across seven appearances, Blanco was sent to Sugar Land where he remained for the remainder of last season, posting a 3.63 ERA/4.86 FIP in 44 23 innings with the Space Cowboys. Consider this case an example of why Spring Training stats are to be taken with a grain of salt.

Wash, rinse, and...repeat? Once again, Blanco broke camp on the Opening Day roster following a strong performance in Spring Training. This time, he looked even more impressive, striking out 17 and allowing one run in 14 innings. As camp progressed, we also saw the Astros stretch out Blanco, possibly as preparation for a starting role later in the season if opportunity strikes. If anything else, he could also assume what was once Cristian Javier’s role before his ascension in the rotation, which was to provide some length out of the bullpen as a multi-innings option.

Unlike last season, however, we could see Blanco stick around longer as his first three innings this season have been solid. The age-29 hurler has yet to allow a run, much less a hit, while striking out six. His slider, in particular, has looked nasty, generating 11 eleven whiffs on 13 swings against the White Sox on April 1. The usual small sample caveat applies, but I have liked what I’ve seen from Blanco thus far.

Pitch Modeling Stats

Taking inspiration from Ben Clemens of FanGraphs — highlighted here — discussing two of the site’s newest features from the offseason, Stuff+ (courtesy of Eno Sarris) and PitchingBot (courtesy of Cameron Grove). It was a welcomed addition as both Stuff+ and PitchingBot provide another useful way of measuring various aspects of pitching as these models further isolate what only a pitcher can control and not taking into account the outcome. I immediately think back to Will Harris’ ill-fated cutter in Game 7 of the 2019 World Series, which was a decent pitch in that spot. Howie Kendrick just did a good job of making contact.

As it relates to the pitching models, I took a quick look to see how Houston’s staff looks thus far in terms of overall stuff. Yes, another small sample caveat applies again here, but it at least gives us a quick idea of how the stuff thus far grades out per the models.

Early Season Pitch Modeling Data

Name IP Stuff+ botStf
Name IP Stuff+ botStf
Ryan Pressly 3 141 57
Bryan Abreu 4 140 66
Ryne Stanek 2.2 117 66
Rafael Montero 4 110 51
Hunter Brown 4.2 108 48
Hector Neris 4.1 107 49
Cristian Javier 11 106 43
Phil Maton 3.1 102 63
Framber Valdez 12 102 50
Jose Urquidy 4 101 48
Seth Martinez 4 99 58
Luis Garcia 5 96 42
Ronel Blanco 3 92 56
FanGraphs (Stuff+, Eno Sarris; PitchingBot, Cameron Grove)

Some of the scores are frankly not much of a surprise like Bryan Abreu and Ryan Pressly. But there are instances where the two models appear to disagree as indicated by Cristian Javier’s scores. Another post delving into much greater detail about Stuff+ and PitchingBot is warranted as there is plenty of nuance of limitations and what these models do not account for. But it is a fun exercise to quickly test what our eyes are seeing and what the data indicates.