Last week over at Pinstripe Alley, I investigated DJ LeMahieu’s latest scorching streak. Naturally, he obtained injured as quickly as I completed writing, however I went by means of with the piece nonetheless as a result of I felt like I used to be onto one thing. Specifically, I seen that LeMahieu’s struggles this 12 months got here when pitchers had been difficult him extra; because of this, he was swinging extra, however proportionally, extra of these swings occurred to return on balls than when pitchers had been being stingy with their strikes.
When making an attempt to contextualize LeMahieu’s scorching stretch, I seen one other hitter who’s been on hearth these days due to some improved self-discipline: Ha-Seong Kim. Over the previous 30 days, he’s tied for the main league lead in WAR with Freddie Freeman at 2.1. Some of that manufacturing has come from his sometimes wonderful protection, however Kim has been no slouch with the bat both; in that span, he’s posted a 189 wRC+, eighth-highest amongst 167 qualifiers. Perhaps most notably, he’s additionally tied (with Lars Nootbaar and Alex Bregman) for the second-best BB-Okay price, behind solely Marcus Semien.
Prior to that 30-day stretch, Kim’s swing price was already a career-low, and his BB-Okay price close to a career-best. But his swing price has dropped even additional within the final 30 days, rating second-lowest at 34.2% to Nootbaar’s 34.1%, and his BB-Okay price has gone from unfavorable to constructive; now it’s undoubtedly a career-best. Nootbaar has adopted an identical trajectory: his swing price was already a career-low and has sunk even additional, and his BB-Okay price is now approaching a career-best due to his personal torrid month.
One query this raises: are hitters extra productive after they swing much less? Eno Sarris of The Athletic discovered that usually, sure, they’re. But why? Being affected person and letting the ball journey can truly lower a hitter’s residence run likelihood; making contact out in entrance of the plate supplies the perfect probability at a dinger.
Some hitters with elite eyes, like Juan Soto, can seemingly determine to swing at fewer balls with out having to attend for pitches to journey extra. This not solely permits them to keep up their typical level of contact after they do swing, however it additionally results in extra high-ball counts and thus walks. But what about “bad ball” hitters? Is it value it for them to take extra walks on pitches they will drive? And what about hitters with poor eyes; if they will’t merely begin taking solely balls, aren’t they sure to face extra referred to as strikes as properly?
Let’s sort out that final query first by asking one other: does swinging much less result in higher swing selections in mixture? One of the extra tried-and-true measures of plate self-discipline because the creation of PITCHf/x has been Z-Swing% minus O-Swing%, or a hitter’s swing price on pitches contained in the zone minus their swing price on pitches exterior of the zone. By this measure, LeMahieu improved throughout his scorching, less-swingy stretch, however Kim truly obtained worse. Sure sufficient, the outcomes 12 months over 12 months (for hitters with not less than 300 plate appearances in every season) supply a equally blended bag:
On the season, Kim’s Z-O% has truly been worse than final 12 months’s. Meanwhile, LeMahieu has truly swung greater than final 12 months on the entire, however he’s made higher swing selections by means of this lens. Nootbaar’s Z-O% has worsened about as a lot as Kim’s though his swing price hasn’t dropped as a lot. Our examples run the gamut of prospects, and there’s nearly no correlation right here.
Yet lately, there was an explosion of measures dedicated to evaluating swing selections. An enormous problem with Z-O% is that it considers all balls — from a pitch over the catcher’s head to 1 simply above the zone — the identical, in addition to all strikes, from a dart on the nook to a meatball proper over the center of the plate. Baseball Savant rolled out some measures in an effort to fight this, as a substitute divvying up pitch areas into 4 completely different buckets: coronary heart, shadow, chase, and waste.
My colleague Ben Clemens has experimented with melding these buckets right into a single swing-decision measure. It’s extra useful to conceptualize plate self-discipline this manner than Z-O%. The common run worth of a swing is barely constructive, and the common run worth of a take is barely (considerably) unfavorable, on meatballs, or “heart” pitches. That’s not solely intuitive, but additionally consistent with Eno’s reporting that hitters would sometimes profit from swinging much less.
As good as the center/shadow/chase/waste system is for conceptualization, it’s not essentially the most sturdy framework in follow. Even although it makes use of extra classes than Z-O%, it’s nonetheless categorical, which implies we’ll at all times be sacrificing some nuance. Additionally, it depends on contextualized run values — that’s, run values that change relying on base-out conditions. For instance, the worth of a ball in an 0–0 rely might be decrease with the bases empty and two down than with the bases juiced and no outs. In essence, it bakes in leverage and situational hitting, which I’m not searching for to do right here.
Luckily, there are many steady measures of plate self-discipline on the market that depend on decontextualized run worth. A private favourite of mine is predicated on Pitcher List’s PLV, or Pitch Level Value. PLV for pitchers resembles the pitching fashions now we have on this web site, Stuff+ and PitchingBot, and it’s the place Pitcher List’s Decision Value measurement for hitters begins. PLV takes into consideration a pitch’s stuff (velocity, motion, and many others.), location (together with relative to a hitter’s height-based strike zone), and different variables comparable to pitch sort, handedness, and rely, utilizing that info to foretell whether or not a hitter will swing or not.
From there, the mannequin evolves into a call tree. On one aspect is what occurs within the occasion of a swing: a mannequin predicts whether or not there might be contact, and within the occasion of contact, whether or not the ball might be in play, and eventually, if the ball is in play, what the outcome might be. On the opposite aspect is what occurs within the occasion of a take: a mannequin predicts whether or not the pitch might be referred to as a ball, a strike, or whether or not it’ll hit the batter. Every node on the finish of the tree is a ultimate end result: whiff, foul, hard-hit liner, and many others., every with a likelihood of occurring and a corresponding decontextualized run worth within the occasion it does in actual fact happen. The sum of all of the likelihood*run-value merchandise is the anticipated run worth of the pitch.
For hitters, within the occasion of a swing, the sum of these end-node merchandise on the “take” aspect is subtracted from the sum of these merchandise on the swing aspect to lend the anticipated worth of a swing, and vice versa for a take. This results in one “Decision Value” quantity for each pitch a hitter sees. This is a much better proxy of plate self-discipline than Z-O%.
Additionally, there’s additionally a “Swing Aggression” worth borne from the preliminary mannequin that predicts whether or not a hitter will swing or not primarily based on the pitch high quality and placement. If a hitter swings extra usually than the mannequin expects them to, they’re thought of aggressive. This is a fair higher measurement than pure Swing% as a result of it takes into consideration the pitches a hitter truly sees; no must ruminate on whether or not LeMahieu was actually making higher selections solely as a result of he was seeing fewer strikes over the previous month. PLV says that, even controlling for the pitches he’s seen, LeMahieu has been making significantly better selections as of late:
For these curious, you can also make graphs like this and fiddle with the higher-level swing resolution stats right here. But Kyle Bland, PLV mastermind, was form sufficient to offer me with extra granular information, which I’ll use to check out my theories. After this long-winded clarification, let’s get again to the query I used to be asking within the first place: does swinging much less result in higher swing selections? Controlling for the sorts of pitches hitters see (i.e., utilizing the Swing Aggression metric), the reply is sure:
For a variable as nebulous as Decision Value, the flexibility of aggression to elucidate even 10% of its variance (as denoted by R-Squared) is spectacular. But there are lots of exceptions to the rule. LeMahieu’s poor selections when pitchers had been difficult him actually tanked his rating. Kim, in the meantime, simply bested Nootbaar by way of resolution enchancment though they had been neck and neck when it got here to Z-O%, however even he was beneath the place we’d count on given his lower in aggression.
The overarching cause that swinging much less results in higher selections, even for hitters who see extra referred to as strikes than extra balls because of being much less aggressive, is that swinging at strikes usually results in worse outcomes than taking, with meatballs and two-strike pitches being the exception. Now, this isn’t to say that swinging much less makes a hitter higher at discriminating between balls and strikes; in actual fact, on non–two-strike pitches, that doesn’t appear to matter as a lot as discriminating between pitches to hit and pitches to put off. Every hitter has a special subset of choices that fall beneath the “pitches to hit” umbrella, a subset that usually modifications all through the course of a season as hitters and pitchers regulate and readjust to one another.
Because of their dynamic nature, it will be laborious to incorporate particular person pitch preferences in a stat like Decision Value. Instead, they could make sense as a separate metric, one thing just like the customized good versus dangerous resolution charges that Robert Orr developed over at Baseball Prospectus. For now, I’ll give you this: Kim has graded out properly by way of his Decision Value enhancements, however he nonetheless lies beneath the match line by way of his anticipated enchancment primarily based on his drop in aggression. One potential cause: he’s nonetheless susceptible to fishing on pitches in and off the plate:
I’m unsure I’d mess with a very good factor, however it appears to me that there’s a reasonably apparent repair right here. Kim has a barely open stance, so the within pitches look fairly appetizing. But whereas his stance is open, he’s nonetheless a methods off the plate; if he crowded it a bit extra, his warmth map would shift over one sq., and he’d be swinging at much more strikes with out having to vary his stance or mechanics. Kim, who was an offensive drive within the KBO earlier than he got here stateside, has but to achieve his offensive ceiling; combining heat-map pushed insights with decision-value modeling might assist each the Padres’ second baseman and the evaluation of plate self-discipline attain new heights.
Stats are as of finish of day Sunday, August 13.
Content Source: blogs.fangraphs.com