Generally speaking, a decent proxy for a batter’s understanding of the strike zone is his O-Swing% — that is, the percentage of pitches outside of the zone at which he offers. The lower that figure, the less often a player is offering at pitches outside of the zone. The less often a player is offering at pitches outside of the zone, the more likely he is both to draw walks and (one assumes) swing at better pitches inside the zone.
As to the first point, that is borne out by the numbers: O-Swing% and walk rate correlate rather tightly. Consider the following graph, for example, which includes the O-Swing%s (from the PITCHf/x zone) and walk rates for all 143 qualified batters from 2012. (Note: average O-Swing% among this population is 28.9%. Standard deviation is 5.7%.)
As for the second point, however — that O-Swing% necessarily indicates a better idea of the strike zone — it recently occurred to the author (who isn’t very sharp) that perhaps these are not the same thing. Anyone who ever saw Mark Bellhorn bat, for example, will know that it’s sometimes possible for a player not only to refrain from swinging outside of the zone, but also to avoid swinging altogether. There is a difference, however, between selectivity — which we’ll define, for the sake of this post, as “ability to discern between balls and strikes” — and a refusal to swing the bat. The former, we reason, is a good thing; the latter, less so.
In fact, this appears to be a justified concern. As this second graph indicates (of those same 143 qualifiers from 2012), batters who swing less outside of the zone are also, frequently, swinging less inside of it. (Note: Z-Swing% represents pitches offered at within the zone.)
If one were to really “measure” something like selectivity, the better plan — instead of looking just at O-Swing% — might be to look at the separation between a batter’s O-Swing% and Z-Swing%. Each batter does, of course, have his own particular preferences so far as hitting is concerned. Perhaps there are pitches outside the strike zone that are, in their way, more hittable than those inside it. Conversely, there are areas within the zone to which a pitcher might throw and still induce weak contact. In lieu of a more granular approach, however, that somehow accounts for each batter’s preferences (an effort of which the present author is incapable), it seems fair to suggest that a batter who demonstrates the greatest difference between his O-Swing and Z-Swing tendencies would be the league’s Most Selective Hitter.
To that end, what I’ve done is calculated, for each of 2012′s qualified batters, z-scores (standard deviations from the mean) both for O-Swing% and Z-Swing%. In both cases, a positive z-score is better — which is to say, a positive z-score for O-Swing% means a batter chases fewer pitches outside the zone than the mean. I’ve then averaged those z-scores together for an overall selectivity measure (noted below as Sel). Sel is the average standard deviations from the mean for a batter by O-Swing% and Z-Swing% combined. Furthermore, just for reference, I’ve made a rough index version of Sel, as well (presented as Sel+). I’ve placed Sel+ on more or less the same scale (and with the same range) as wRC+ for this particular group.
Here are the top-10 qualified batters by this methodology:
And here are the bottom 10:
|Dayan Viciedo||White Sox||543||38.9%||63.7%||-1.75||0.10||-0.83||70|
|Alexei Ramirez||White Sox||621||40.8%||66.5%||-2.09||0.57||-0.76||74|
|Shane Victorino||- – -||666||31.3%||56.7%||-0.42||-1.09||-0.75||74|
Yonder Alonso — by this method, at least — was 2012′s most selective hitter; Martin Prado, its least. And, indeed, the presence of Prado among the laggards suggests that this way of measuring selectivity will run at odds with a more established idea of what selectivity is — and continues to suggest that, perhaps, this method has its own flaws. The reason for Prado’s low Selectivity rating has everything to do with his incredibly low Z-Swing%: while the average qualified batter offered at ca. 63% of pitches in the PITCHf/x zone (with a standard deviation of ca 6%), Prado swung at fewer than 49%. His approach obviously worked for him: Prado posted a 116 wRC+ in 690 plate appearances with almost identical walk and strikeout rates (8.4% and 10.0%, respectively). Relative to his O-Swing%, however, which was closer to league average, the Z-Swing% was quite low.