Are the Astros More Vulnerable to Power Pitchers?

The Houston Astros just finished a three-game series at home against the Cleveland Indians, and a few things presented themselves in respect to our discussions during this past offseason. The discussions in question pertained to two subjects: the quiet strength of the Cleveland pitching staff, and the strikeout propensity of the Houston lineup.

It was hard to know exactly where the line between the two started and ended. We can say this about the Cleveland rotation: it looked good. Corey Kluber was Corey Kluber. Carlos Carrasco looked like he did at the end of 2014, looking unhittable with his high-90’s fastball and great changeup. Finally, Trevor Bauer put the icing on the cake in the third game, showcasing his combination of wildness and raw stuff to exit with a no-hitter intact after 6 innings. Cleveland fans are obviously encouraged by what they saw in the front end of their rotation this series. It’s not a surprise two of them just signed lengthy contract extensions.

On the other side, the results were clear in another way for the Houston offense:

• .208 OBP
• .048 ISO
• 37.5 K%

Those stats were informed in large part by performances like this, from Evan Gattis:

And swings like this, on a pitch that bounced in front of the plate:

Gattis_Strikeout

The Astros scored a total of three runs in three games during this series, and they actually managed to win one of the games, which in retrospect seems like a great result given the overall circumstances. That win was due almost entirely to Dallas Keuchel out-dueling Kluber by a hair in the season opener. We knew this Houston offense was probably going to strikeout a lot. We knew it was going to rely a lot on home runs for its run scoring. And, in the first three games of the season, we saw its downside: striking out a lot but not hitting any homers.

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That made me wonder: are strikeout-prone teams more susceptible than less strikeout-prone teams to being victimized by aces or pitchers who strike out an above average number of batters?

It’s no secret that the 2015 Houston Astros are a team-wide manifestation of an in vogue offensive approach that trades contact for power. We’ve usually seen that approach on display with a few players on select teams, but Houston has now arguably made it an organizational offensive strategy. It’s important to understand how the Astros might perform when facing the front end of a rotation like Cleveland’s.

To look at the possible relationship between team strikeout rates and success against aces, I’ve joined our FanGraphs team rate statistics with Baseball Reference’s very useful batting splits for every team year from 2010-2014. This gives us 150 data points to work with – five years for each team.

For each season, Baseball Reference provides team-hitting stats against different types of pitchers: Power, Average, and Finesse. Power pitchers are considered to be in the top third of the league in strikeouts plus walks, Finesse pitchers in the bottom third, and Average right in the middle. The tiers are based on data from three years before to three years after the season in question (including the season the split is referring to).

We’re just going to be looking at power pitchers today. Here’s the relationship between K% and sOPS+ (which refers to the OPS+ of a split):

Overall_K%_OPS+_vs_Power_Pitchers_2010-14

The low p-value indicates there is some relationship here, but there’s very little predictive value to be drawn from this with the minuscule R2. There’s a ton of variability, as we often find in baseball data. An important thing to remember is that team strikeout numbers above 23% are very rare (the Astros are projected for a 24% K rate this year), and only surfaced in 2010. We’re kind of in uncharted territory. If we want to try to find comparison teams, those few dots on the lower right are where we start, which unsurprisingly are the 2014 Cubs (24.2 K%) and 2013 Astros (25.5%).

The hopeful comparison would be last year’s Astros team (the orange dot right on the trend line), which struck out just under 24% of the time and managed a slightly-below league average 92 sOPS+ against power pitchers. Given the fact that the Astros should improve overall this year over last year, there’s reason to hope they can beat that sOPS+ mark. Another hopeful trend is that they were actually above average last year against pitchers in the lower third of the league in strikeout plus walks (finesse pitchers):

Astros_sOPS+_vs_Pitcher_Type_2013-14

The bottom line is that the Astros aren’t going to strike out almost 40% of the time for the rest of the season. These were just the first three games, after all, which is why writing about trends during this time of year is difficult to do. Every team has awful stretches of three games in which they don’t score runs, but the Astros’ stretches might look a little more ugly, and be a little more eye catching than usual: that’s the price of admission for building a team with poor contact skills and high power upside. There will be incredible highs for this Astros team, but there will also be bottom-of-a-crater lows. We’ve just seen a three-game series of the latter.

Are this year’s Astros more susceptible to struggling against an opposing team’s ace than a team that strikes out less? Perhaps. It’s hard to know for certain with this little data on ultra-high strikeout teams. One thing is for sure: the Astros will take their cuts this year, and it’ll be a fun ride when it’s going well. However, they might have a problem when they run into a rotation with the likes of Kluber, Carrasco, and Bauer. Any team might say that; the hard part is knowing where the line between great pitching and strikeout susceptibility begins and ends.





Owen Watson writes for FanGraphs and The Hardball Times. Follow him on Twitter @ohwatson.

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Twoniner
10 years ago

I would use tOPS+ in place of sOPS+. tOPS+ gives you relative data to the team’s overall strength. sOPS+ just tells you how they did compared to the league. So you are pretty much just going to show the best teams performing the best, and it doesn’t account for park factors.

I believe Tango showed in the book there wasn’t much correlation, but I wouldn’t mind seeing updated numbers w/ the increase in K% since then.

a eskpert
10 years ago
Reply to  Twoniner

This right here.