Adam Jones
This first breakdown compares Adam Jones' True Average on breaking balls down & away versus his True Average on those same pitches this season. Keep in mind that the typical Small Sample Size (SSS) warning applies here, but it's interesting nonetheless. For a description of True Average check out Baseball Prospectus' glossary here.
Adam Jones TAv Career - Normalized for RHH |
Adam Jones TAv 2012 - Normalized for RHH |
The interesting point here is that, over his career, Jones has performed well below average on breaking balls down & away compared to other MLB right-handed batters. However, so far this season, Jones' performance has been above league average (.260) in all 4 quadrants of the low and away portion of the zone. This is certainly interesting, and could be a reason for Jones' success thus far this season.
Chris Davis
Here we're going to look at how pitchers have been pitching to Chris Davis so far this season, something that I think shows how well pitchers adjust to hitters over the course of a season. The first image will show, compared to other left-handed hitters how often Davis sees "hard pitches" (fastballs) in a certain zone. The second image shows Davis' True Average over the various zones against "hard pitches".
Chris Davis Frequency 2012 - Normalized for LHH & "Hard Pitches" |
Chris Davis TAv 2012 - Normalized for LHH & "Hard Pitches" |
Nick Markakis
The last player we'll analyze today is another long-time Oriole, Nick Markakis. The interesting thing about Nick's data is that it seems nobody knows where to pitch Nick. The lowest % in terms of pitch frequency is 85.63% which is quite high. The second image shows how Nick has performed against pitches in the various zones, and highlights the lack of a hole in the zone for the most part.
Nick Markakis Frequency Career - Normalized for LHH |
Nick Markakis TAv Career - Normalized for RHH |
This color scheme shows just how good Nick has been at covering all zones across the plate. Of the 25 zones in the breakdown, only 4 of them show TAv values that deviate significantly from the league average figure.
Takeaways
All in all this tool is very cool. If you haven't already, you should play around with it here and see if you can find any interesting data. I hope to do more of this in the future, and I really think the applications for this data are truly endless. Let me know any interesting points you notice from the graphs above, or feel free to link to new graphs in the comment section.
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