BB% and GB%: Standard deviations and performance

A high ground ball rate has helped Francisco Liriano's resurgence. - Jared Wickerham

Controlling for the other variables, which is more important for performance, walks or ground balls?

In the present installment of my standard deviation starting pitcher series, I will be examining the relationship between BB% and GB% and how those two variables affect performance. The methodology is basically the same as before; since batted balls are included, the years in this analysis are 2002-2013. Only starting pitchers who had at least 170 batters faced for a stable BB% and 70 balls in play (GB+FB+LD) for a stable GB% are included. I have again chosen RA9-WAR as the performance metric for each group. The table below shows the results.

-2 -1 0-1 0+1 1 2 RA9-WAR
BB% -2 -0.7 0.5 2.3 3.1 5.7 7.1 3.2
-1 1.0 1.8 2.7 2.9 3.4 4.8 2.6
0-1 0.8 1.6 1.5 1.8 1.9 3.3 1.7
0+1 0.7 1.0 0.8 1.0 1.6 0.1 1.0
1 -0.5 -0.1 0.2 0.5 0.6 1.4 0.3
2 -0.3 -0.2 -0.2 0.2 0.6 0.1 0.0
RA9-WAR 0.5 0.9 1.1 1.4 1.6 2.3

Across the top of the table are the GB% standard deviation groups, and going down the table are the BB% standard deviation groups. -2 means at least two standard deviations below the middle, -1 means at least one standard deviation below the middle, 0-1 means between 0 and 1 standard deviations below the middle, etc. The RA9-WAR values shown in the far right column are the median RA9-WAR values for each BB% group regardless of GB%. The RA9-WAR values shown in the bottom row are the median RA9-WAR values for each GB% group regardless of BB%. For example, the median RA9-WAR for all pitchers who were at least 2 standard deviations below the middle BB% is 3.2.

Essentially, lower walks and more ground balls are good. These things are known. Because BB% and GB% are in reverse polarity* (i.e., lower BB% is good while lower GB% is bad), we can again divide the table into 4 quadrants like we did with the K%/BB% analysis. Comparing the two quadrants of interest, the top left and bottom right, it appears as though the low-walk, low-grounder group performs better than the high-walk, high-grounder group.

Looking at a specific example, we can use the group in which Edinson Volquez found himself in 2013. His BB% was in the +1 group, and his GB% was in the 0+1 group, which can be abbreviated (1,0+1). The median RA9-WAR value of this group was 0.5. Not particularly good, but it was slightly better than the overall +1 BB% group median value of 0.3. It was, however, much worse than the overall 0+1 GB% group median value of 1.4. The inverse of this group in the other quadrant is group (0-1,-1), whose median RA9-WAR value was 1.6. This particular group did better than the overall -1 GB% group, whose median RA9-WAR value was 0.9 and performed about the same as the overall 0-1 BB% group, whose median RA9-WAR value was 1.7.

There is one main exception in the table. Group (0+1,2) had a median RA9-WAR value of 0.1, which is completely outside the general trend. There were 18 pitchers in this sample, which is still relatively small but not so small as to dismiss it entirely. Many pitchers in this group performed far more poorly than their peripherals as shown by the huge difference between the median RA9-WAR value of 0.1 and the median fWAR value of 1.5. This group's RA9-WAR performance was heavily skewed downward, as 8 of the 18 pitchers had negative RA9-WAR values but only 2 of the 18 pitchers had negative fWAR values. I suspect that home run rates were partially responsible for this outlier due to the decent median xFIP- value of 97.

It would appear that when looking at performance, walks are more important than grounders. Performance with a low walk rate is not strongly dinged with a lower ground ball rate. On the other hand, having a high ground ball rate can help overcome the poor performance in general of high walk pitchers. The Pittsburgh Pirates, with Francisco Liriano, Jeff Locke, and Edinson Volquez, are employing this strategy to maximize value out of de-valued assets.

*The solution to all problems in the reboot of Doctor Who. Reverse the polarity of...anything.

To wrap up this series, the final step is to put K%, BB%, and GB% together to see how performance is affected. After that is completed, I will post a reference table of the standard deviations.


All statistics courtesy of FanGraphs.

Kevin Ruprecht is a contributor for Beyond the Box Score. He also writes at Royal Stats for Everyone. You can follow him on Twitter at @KevinRuprecht.

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