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Fan Engagement, Team Performance

Good Intent: How Command+ Answers What Couldn’t Be Answered With Traditional Metrics

 

In this installment of our series on advanced baseball metrics, we examine what command+ tells us about the brilliance of former big-leaguer Masahiro Tanaka and the emergence of Lucas Giolito. 

By: Analyst Staff

Elite pitchers usually have two things in common: great stuff and the ability to command that great stuff.

With better technology and understanding, the baseball community has gotten much better at determining what makes pitches great. However, the ability to measure command has not evolved in the same way.

Good control is generally defined by a pitcher’s ability to throw strikes, something many websites evaluate through simple metrics like zone percentage and walk rate. But command has more to do with a pitcher’s ability to locate – whether it be in the zone or not.

To calculate command+ in MLB, every pitch is analyzed to determine actual intent. It starts with a look at four key variables – count, pitch-type, the pitcher’s trends and the catcher’s mitt location and body position during his setup. Twenty other key variables are also factored in, including things like the hitter, game situation and the runners on base.

New Chicago Cubs starting pitcher Zach Davies led the majors in command+ in 2020. (AP Photo/Tony Gutierrez)

From there, the intent of a pitch is narrowed to one of 13 zones, which corresponds with a concept. For example, a pitch that is supposed to be located on the outside corner of the plate is known as “black or better” because the intent is to paint the corner or be just off the plate. The data allows analysts to make a distinction between pitchers who are throwing balls because they are struggling with command and those who are purposefully missing the plate in an effort to get big-league hitters out.

“(Command+) answers a question that you would never be able to answer with traditional metrics,” veteran baseball analytics writer Eno Sarris said. “It requires an ability to code what’s happening in every game and turn basically a bunch of research behind the game to tell you, “Did that pitcher do exactly what he wanted to with that ball?” That’s an extremely difficult question to answer.

“It’s something that most analysts have stepped away from because they can say, ‘I can’t be in the pitcher’s head.’ They took a question they thought nobody could answer and tried a different approach with it, and really tried to get into the pitcher’s head and try to give him credit for shaping a curveball. It might be a ball, but it might be the shape that he wanted and in the general location he wanted – which I think is the true definition of command.”

Let’s look at some examples. Here are two sliders from former New York Yankees righty Masahiro Tanaka that end up in the same location, low and inside and out of the strike zone. But these are two different situations:

In the first video, Tanaka, who has chosen to resume his career back in Japan, has a 1-1 count on Yolmer Sanchez, a relatively low-power hitter at the bottom of the Chicago White Sox lineup. The pitch is a slider, so it moves in toward a left-handed hitter. Generally, this would not be used as a chase-pitch off the outside edge because it would start out of the zone.

Given that information, the game situation, and the position of the catcher, Tanaka misses on a pitch that is supposed to be thrown on the outside part of the plate and Sanchez singles to right field.

This breakdown also illustrates why the catcher’s mitt is not a good indicator of intent on its own. This pitch is intended to be a strike, yet the catcher sets up with his mitt below the batter’s knees for some reason (anticipating a block, just out of habit, etc.).

Now, let’s look at the second video:

This time, Tanaka has a 2-2 count on Chicago’s Yonder Alonso with a runner on second and two outs. Tanaka has a pitch to work with, so he can afford to throw the slider for a ball in hopes of getting a swing-and-miss strikeout. The catcher sets up inside for a common back foot slider location, and Tanaka hits the spot, unlike in the previous video, nearly getting Alonso to chase.

This is the beauty of looking at intent rather than results. From the data, we’re able to find that, for the most part, Tanaka throws his slider in two common places against left-handed batters – low and outside, and low and inside.

Both sliders shown in the videos ended up in that low and inside zone and seemingly fit in with Tanaka’s pitching trends. However, one can be distinguished as a missed location and the other as a hit location.

“Things like command+ have come from an internal curiosity,” Stats Perform AI Data Analyst Kyle Cunningham-Rhoads said. “We’re essentially answering the scouting question about which pitchers have the best command.”

To find that answer, the data compiled is compared with the results of the pitches to extrapolate the command of every big league pitcher, sortable by pitch-type, with the league average set at 100.

Looking at the table below, you can see that Tanaka’s command+ rating for all his pitches was among the best in the majors among those who threw at least 800 pitches in 2020:

2020 Command+ LeaderBOARD
RankPitcherTeamCommand+
1Zach DaviesPadres121
2Trevor WilliamsPirates119
3Aaron NolaPhillies119
4Masahiro TanakaYankees119
5Zac GallenD-backs116
6Kyle HendricksCubs116
7Zach EflinPhillies115
8Tyler MahleReds114
9Hyun-jin RyuBlue Jays114
10Alec MillsCubs114

With command+, teams can also track how a pitcher’s command is improving or trending in the wrong direction for each pitch in his arsenal.

Chicago White Sox right-hander Lucas Giolito is a prime example. He went from being one of the worst pitchers in the big leagues in 2018 to 14-9 with a 3.41 ERA and 228 strikeouts in 2019. As shown below, much of Giolito’s improvement can be attributed to his improved command.

Lucas Giolito, 2018-19 Command+
Pitch Type2018 Command+2019 Command+
Fastball9192
Curveball8180
Slider9097
Changeup93102
Total Command+9096

Giolito commanded his slider and changeup particularly well in 2019, improving 7% and 9%, respectively, relative to the league average.

His emergence led to a sixth-place finish in the AL Cy Young Award voting.

 

Data modeling provided by Lucas Haupt.