In my previous piece, I examined strikeout tendencies, particularly where hitters frequently would strikeout looking. The conclusion was a basin-shaped accumulation at the bottom of the strike zone. This was the densest concentration of looking strikeouts. I intended to take this data and manufacture a measure of each batter’s conformity to this trend. After assembling the data and computing the density of the area of each looking strikeout in 2019 (averaged for each batter), the results don’t suggest the erudition I desired or anticipated.
That measure is a single value assigned to each batter representing the average density (based on all MLB’s looking strikeouts in 2019) of the locations of their own looking strikeouts. I’m deeming that value strikeout “level” or commonality. If the origin of this number isn’t transparent, contemplate an analogy: This number is equivalent to the average population density of all the cities where all your family members live (if your family members were looking strikeouts). Now, seemingly, statistically informed this number was compared to various existing measures of plate discipline including strikeouts. Even after echoing the analysis for all looking strikes, no correlation could be derived.
In essence, the locations of batters’ looking strikeouts (and looking strikes) relative to their colleagues’ doesn’t contribute any insight into the frequency they struck out, the number of pitches they saw per plate appearance, the share of their strikeouts that were called, or even (relative to other batters) the location of the strikes they watched (versus swung at).
Ultimately, the question becomes does the measure of a batter’s conformity express something entirely unaccounted for in other measures, or is it just meaningless? Based on circular clouds of data and correlation coefficients screaming zero, too many to showcase here, my belief is the latter, assuredly when leveraging it to understand player performance.
To evoke some value from this seemingly meaningless metric it might be stimulating to take a look at some of these values regardless and see where several players end up on the spectrum. Naturally, the densities are normally distributed. It’s important to recognize while the highest values represent the most concentrated data, this chart displays density. The most common density, the mean, is different and hence, in the aggregate, more common than the single densest area (the most concentrated data).
Some of baseball’s most strikeout prone players don’t offer exceptional values. Domingo Santana and Rougned Odor, two players who despite a 30 point rift in their wRC+ lay within 2% of each other’s greater than 30% strikeout rate. Santana and Odor’s looking strikeout levels were 0.253 and 0.218 respectively. At the other end of the spectrum, baseball’s two sub 10% strikeout rate players, Hanser Alberto and David Fletcher achieved 0.281 and 0.288. Not equal, but their values remain well within the extended mean.
Getting more specific, the two players who struck out on a called strike most relative to all their strikeouts (accumulating at least 150 plate appearances as a non-pitcher) were Trent Grisham and Greg Garcia. The two players are the only players to meet the criteria and strikeout looking more than swinging. Their levels aren’t all that interesting either; Grisham a 0.253 and Garcia a 0.279. Turning the tables is a bit trickier. Didi Gregorius limited his called strikeouts to just 1.9% of his total, however that accounts for just one lone strikeout. Players who produced very few called strikeouts relative to their swinging strikeouts usually only did so once or twice.
As for leaders and trailers in ‘uniqueness’ (applying the aforementioned criteria), we get Eduardo Nunez (0.154) and Victor Reyes (0.174) at the top, most unique. Out here, they’re around more than one and a half standard deviations from the mean. Any more individual and the data is populated with pitchers and September call-ups or at least their equivalents. The leaders, those who typically strikeout looking in baseball’s most habitual places (excluding Didi Gregorious and his sole looking strikeout) are Matt Duffy and Jose Martinez, yielding strikeout levels of 0.347 and 0.343 respectively.
Some of baseball’s most engaging players, fan favorites, offer several levels. Notably, Mike Trout and Giancarlo Stanton. Trout’s level was 0.229, making him a little more distinctive than the average player (beyond the whole being Mike Trout thing). Giancarlo Stanton’s six looking strikeouts were all in a moderately quotidian place giving him a 0.304 level. Some pertinent cases in today’s game, Cody Bellinger and Alex Bregman. Bellinger possesses a truly unique ability to work and remain effective throughout the entire strike zone while Bregman’s stellar strikeout rate sits beside an equally impressive walk rate. For all their idiosyncrasies, they’re right at the mean when it comes to looking strikeout level, Bellinger posting a 0.249 level and Bregman a 0.25, sequentially.
One noticeable trend is (at batters) pitchers’ called strikeouts. Though appearing in both tails, they were much more frequent at lower levels. The average level of pitchers’ looking strikeouts, this being perhaps the most or only significant piece of information here, is eight-hundredths away from the hitters’ average, about one standard deviation more unique. This is perhaps due to their adversaries, fellow pitchers, not employing their comprehensive strategic arsenal. If the batter does at all influence where he’s collecting his looking strikeouts, then Sandy Alcantara (0.169) and Joey Lucchesi (0.197) are pitchers striking out in style, with the lowest levels among pitchers who collected ten looking strikeouts.
In the end, understanding where a player strikes out looking isn’t really at all estimable for obtaining acumen into his performance or abilities. There exists a diverse array of strikeout levels throughout nearly every subset of baseball players. Superstars, pitchers, and those known to don the golden sombrero. Looking strikeout (and looking strike) level’s value will remain tethered to trivia. For some, identifying who strikes out looking in the most nonrecurrent way may be valuable, credit to you. Otherwise, the meaningless metric is merely a microcosm for our own, diverse, unpredictable world where subsets and demographics do not define us.
All data sourced from baseball-reference.com, fangraphs.com and baseballsavant.mlb.com.