Pitcher Struggles Explained with Breaking Ball Zone Rate

Baseball’s supposed to be a simple game and it is in theory. But the deeper a person digs, the more complex it gets. ERA estimators like FIP, xFIP, kwERA, and SIERA came along to help explain the limits of ERA. The main issue with each metric is how to deal with batted ball data. More specifically, they fail at it. I tried to answer the batted data question with pERA but it only explained some of the differences. Even with all those attempts to fill in the missing data, some differences haven’t been explained. Today, I am going to fill in on missing gap while examining a pitcher’s breaking ball zone rate.

Today’s study will be sponsored by Michael Pineda and Robbie Ray. Each pitcher has posted good strikeout and walk numbers which historically has pointed to good ERA’s. Instead, they get hit around and their ERA’s are quite a bit higher than their estimators. Here are the career stats for the pair.

Ray & Pineda’s Career Stats
Michael Pineda 9.2 2.1 1.1 0.300 43.0% 11.9% 3.99 3.42 3.28 3.17 3.31
Robbie Ray 9.7 3.6 1.0 0.339 43.6% 11.8% 4.65 3.80 3.79 3.75 3.85

Both have ERA’s which are over a half run higher than their estimators. The labels of good or bad luck can get placed on these pitchers who don’t have their ERA and estimators out of wack. These differences are not explainable using any known metric and I finally figured out why they stuggle after watching them pitch. They can’t throw their breaking balls for strikes.

This past season, Both of them threw their breaking balls (includes changeups) in the strike zone 33% of the time which puts them near the league’s laggards. (full list back to 2010 with min 5 starts, 90% of games were starts).

Note: For fastballs, I included four-seamers, two-seamers, cutters, and sinkers. Grouping the pitches this way will lead to some false positives like with Jon Lester. Lester has three distinct fastballs, cutter, sinker, and 2-seamer, which he can throw for strikes. A person is going to have to look at a player’s Pitchf/x page to get a full understanding if the pitcher is predictable once behind.

Lowest Breaking Ball Zone% Among 2016 Starters
Name Breaking Ball Zone%
Kevin Gausman 24.5%
Jon Lester 26.8%
J.A. Happ 29.9%
James Shields 30.4%
Aaron Blair 31.5%
Archie Bradley 31.6%
Ervin Santana 31.8%
Anthony DeSclafani 32.5%
Robbie Ray 32.6%
Dallas Keuchel 32.6%
Michael Pineda 32.8%
Zack Greinke 33.0%
Adam Conley 33.3%
Tim Lincecum 33.4%
Gio Gonzalez 33.6%
Mike Leake 33.8%
Cesar Vargas 34.2%
Jesse Hahn 34.2%
Andrew Cashner 34.3%
Drew Smyly 34.4%


The next step to see if these pitchers allow hard contact once behind. This information can be found on the pitcher’s split page at Baseball-Reference.com. Once there, look at the pitcher’s tOPS+ for their First Pitch, Batter Ahead, and Pitcher Ahead. tOPS+ compare’s the pitcher’s results to the rest of the league for that single split with 100 being league average. For a pitcher, a value under 100 is good and over 100 not so good. This stat is ideal because pitchers are expected to perform better once ahead in the count. tOPS+ take the analysis a step further and compare values in the single split.

2016 tOPS+ Based on Count
Name First Pitch Behind Ahead
Pineda 224 195 23
Ray 220 173 25

On the first pitch or if behind in the count, these two are about 50% worse than the league average pitcher. Hitters know to wait on the fastball in the zone. Once they got ahead, they became lights out as hitters are forces to chase the breaking pitches.

Once breaking ball zone rate and its effects are broken down, it can be easy to see why these two struggle. A low breaking ball zone rate is not an issue with many pitchers. For this reason, I wouldn’t recommend using this information when doing a first look on a pitcher. Or even a second look. It is instead the idea broken out when nothing else can explain a pitcher’s batted ball struggles. The pitcher may fall into the few who struggle with this aspect of their game.

Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.

Newest Most Voted
Inline Feedbacks
View all comments
7 years ago

Nice work! In the aggregate we understand that pitchers suffer good or bad luck, but it’s useful to know if there are other factors at work for specific pitchers.