Last week, I took a quick look at plate-discipline statistics for hitters, and tried to determine an overall grade of just how disciplined certain hitters are. Unfortunately, as some folks pointed out in the comments section of that article, my methodology was flawed. I'm currently reworking some of the data behind the scenes, and hopefully I'll revisit that post at some point with more accurate and telling results. Due to the changes in my research, I will take a different route to analyze pitchers' plate-discipline stats in this article.
First, I'll share a bit of what I had been working on before I changed course. Just as I did for hitters, I looked at each plate-discipline statistic (O-Contact%, Z-Swing%, etc. Again, here is FanGraphs' glossary of the terms you need to know). I find these percentages to be highly difficult to interpret without context or being made relative to league averages. The plan of attack to solve this was to take all 81 qualified pitchers from 2013, determine the means, standard deviations, and ultimately the Z-Scores for each stat so that it is easy to measure how an individual's percentage ranks related to that of his peers.
My next step was to total the Z-Scores, and reach a conclusive metric that collectively shows how an individual's plate discipline ranked from league average, as an aggregate of all nine stats. As I mentioned earlier, some commenters pointed out the redundancy involved in doing this, as well as general inaccuracies. In any case, here are some results:
|"Name"||O-Swing% zsc||Z-Swing% zsc||Swing% zsc||O-Contact% zsc||Z-Contact% zsc||Contact% zsc||Zone% zsc||F-Strike% zsc||SwStr% zsc||Sum of Z Scores|
As you can see, Matt Harvey ranks at the top, followed by Cole Hamels and a pair of Cy Young winners. However, the Sum of Scores don't really correlate strongly with any other metrics. For example, the Sum of Scores had an R^2 value of .35 with xFIP; SwStr% alone correlates more strongly with xFIP. There's no need to put much stock in this yet. I'll be sure to update if I make any progress in the future. In any case, the real information in the chart lies in the individual Z Scores, as they are now much easier to interpret relative to the average qualified pitcher. I'll leave you to gloss over the entire spreadsheet of scores here.
Now, on to some things that may hold a little more weight. You may have noticed, on that FanGraphs glossary page I linked earlier, that there was a note regarding swinging strikes percentage, and not to confuse them with whiff rate. This hasn't been an issue for me personally, as I tend to stick to FanGraphs for data collection and they don't carry whiff rate. Whiff rate is simply the number of swings-and-misses on swings, whereas swinging strike percentage is swings-and-misses on all pitches. I've never used whiff rate, so naturally I am curious as to its value.
Predictably, I am not the first to take a more in-depth look at whiff rates, and Blake Murphy wrote this here at BtBS a while back. In my study, I took all pitchers from 2013 with at least 50 Innings Pitched and tested their correlations with actual strikeout percentages. Results show that whiff rate correlated with strikeout percentage at an R^2 coefficient of .68, while swinging strike percentage had an R^2 of .64. On the other hand, swinging strike percent correlated a tiny bit better with xFIP than whiff rate. With the 88 qualified pitchers from 2012, correlations are almost identical to those above. Whiff rate had a R^2 of .69 with strikeout rate, while swinging strike percentage correlated at .65.
In jumping back to the 2013 data of those with at least 50 IP, I thought I'd use whiff rate to determine those who may be due for a rise or fall in terms of K%, by simply subtracting K% from whiff rate. Here is a chart of the top five, and another of the bottom five (by biggest whiff rate - strikeout rate):
|Rank||Name||K%||Whiff Rate||Whiff - K%|
I suppose this provides some hope for Nationals fans as Taylor Jordan might have a bit more swing-and-miss in his game than you'd think by just looking at K/9. Also, Scott Rice had a higher whiff rate than Craig Kimbrel, so that's always fun. Here is the same idea, only with qualified starters from this past year:
|Name||K%||Whiff Rate||Whiff - K%|
|1||Jorge de la Rosa||15.70%||20.00%||4.30%|
Jerome Williams is a guy that could see a nice bump in K% next year, and could provide some value for the Astros. The Rockies could really use a good year from de la Rosa, especially now that Jhoulys Chacin might be hurting.
I refuse on principle to acknowledge anything that diminishes my opinion of Jose Fernandez, so we won't talk about the bottom of that list. In all seriousness, there is clearly more to a strikeout than whiff rates, but it would be silly to dismiss this data especially since it correlates with strikeout rate better than swinging strike percentage. Here is the full spreadsheet for the two tables above.
I'll be sure to keep an eye on whiff rate a bit more going forward. Also, I'll keep working on the plate discipline stuff, so you can look forward to seeing a bit more of that in the future.
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All statistics courtesy of FanGraphs
Bryan Robinson is a Contributor at Beyond the Box Score. You can follow him on Twitter at @ProProjections.