Though it’s not entirely clear why, it nevertheless appears to be the case that the direction of a batted ball matters when you’re attempting to model the distance over which that same batted ball will travel. Perhaps it’s because of the “slice” balls exhibit off the bat. Perhaps it’s because they exhibit less slice when batted in the direction of the pull side. Perhaps the geometry of the field is somehow responsible for distorting the results. I don’t know. A physicist would be able to tell you more!

Anyway, direction matters, and so it looks like pulling the ball is good for power, even if you keep launch angle and exit velocity constant. And that’s relevant today because Michael Conforto is relevant today. With the return of Yoenis Cespedes to the Mets, the club has one outfielder too many. Both the Mets and their 29 hypothetical trade partners are probably wondering about Conforto’s future production. Which version of him is real: the one that raked in 2015 and September of 2016 or the one who hit 10% worse than league average for three-and-half-months this past season?

I already found earlier this month that Conforto’s “barreled” balls weren’t ideal — and perhaps that it was a result of having hit too many of them to center and left (i.e. the opposite) field.

But you hear coaches say that “pull power comes last,” that a player develops his ability to pull the ball later in the development process. In fact, Don Mattingly said almost that exact thing about Christian Yelich a few months ago to our August Fagerstrom.

From Fagerstrom’s post (bold is mine):

“I still think there’s room for him to grow,” Mattingly explained. “He still hasn’t really truly learned how to pull the ball. When he learns how to pull the ball, he’s going to be really scary. Because they’re not going to be able to do some of the things they do to get him out now when he finds that next angle. Once he gets that next piece in there, he’s going to be one of the best hitters in the game.”

So common wisdom suggests that pull power develops with age. Our data suggests that Conforto barreled too many balls to the opposite field. Is it possible that age will allow Conforto to barrel more balls to the pull side?

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Remember Joe Carter? If you do, you remember a 6-foot-3, 220-pound slugger with plenty of big home runs peppered into the 402 he put together over the course of his career. He won a World Series with one of them! He was also an outfielder — and, according to the evidence available to us, he was a bad one.

Carter wasn’t an anomaly, either. In the late 90s, teams were fine with putting a dude like him in the corners because he was putting up numbers at the plate that made the whole thing work. A look around baseball in 2016, however, reveals that teams are no longer doing that these days — outfielders are fundamentally different now. In fact, they’re different than they’ve been for almost the last 100 years.

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I did a presentation in Arizona this weekend for First Pitch Arizona, an event at the Arizona Fall League hosted by BaseballHQ. The presentation served as an introduction to spin rates and exit velocity and so on. I examined the new stat from our friends at Statcast — Barrels — and how Michael Conforto does well by that stat, which attempts to combine exit velocity and launch angles to credit players who make dangerous contact. On the way out, someone asked me, basically: “So if he’s good at barreling the ball, what happened last year? What went wrong on those barrels?” There’s an easy answer and a hard answer.

The easy answer is that even players who are good at barreling the ball don’t barrel it all that often. Conforto is in the top 75 when it comes to barreling, and he barreled only about 11% of his batted balls this year. The elite guys this year — Gary Sanchez, Khris Davis, Nelson Cruz, Chris Carter and Mark Trumbo — barreled the ball around 18% of the time when they put the ball in play. Even among that group, there’s another 80% of batted balls unaccounted for.

That mirrors the difference in home-run rate, sort of. The top two in homers — you might recognize Trumbo and Davis — have a 7% home-run rate, about double that of the 75th guy, Andrew McCutchen (3.5%). But in the gaps between them, you still find interesting players. Conforto, for example, would have been 84th in home-run rate had he qualified, a little worse than (but still comparable to) his barreling rate.

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“More breaking balls!” That’s how Theo Epstein characterized the postseason for Brian Kenny on the latter’s lead-in show before Game Five of the World Series. It’s a notable observation insofar as it’s a little more actual content than you typically get publicly from a high-ranking front-office exec, but it’s also a matter of public record that his team was seeing a ton of breaking balls in the World Series. Dave Cameron, for example, took an excellent look at the subject earlier this week.

What’s interesting about Epstein’s comment, however, is how he was somehow able to remain vague about his point, even as he seemed to be offering something incredibly specific. He suggests there are more breaking balls in the playoffs, sure. But it’s not clear if he’s implying that there are more breaking balls every postseason for every team, or merely that there were more this postseason for his team, or something in between.

This postseason was defined by a transformation in bullpen usage; that’s not up for discussion, really. But it seems possible that pitching mixes themselves also changed this postseason. And while it would be impossible for Andrew Miller to throw 225 innings and strike out nearly 400 batters — the unfathomable numbers you get if you prorate his postseason work to a full season out of the pen — it might be possible for starting pitchers to throw more breaking balls all season. This postseason trend (if it actually exists) could inform the regular season in a real way.

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By the time a pitcher gets to October, his body and his mind are headed in different directions. The head can’t stop racing, but the body is battered by six months’ worth of battle. That probably seems intuitive, but it’s actually relevant tonight in a very concrete way: Cleveland right-hander Corey Kluber is once again going to climb the mound on short rest, with body and mind at odds. Here’s the good news for Indians fans, though: while the results of postseason short-rest starts isn’t great, the process — which is to say, the movement and velocity recorded on pitches — suggests that adrenaline trumps all when it comes to postseason ball.

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Right-hander Josh Tomlin starts for Cleveland tonight in Game Three of the World Series. While he does a lot well, he also has a weakness — namely, that he gives up more homers than the average pitcher. It’s possible that, among the explanations you’ll hear regarding that weakness, most will relate either to how it’s because Tomlin lives in the zone or never gives in or something along those lines. He certainly doesn’t walk people, so there would seem to be some logic to that argument.

It’s also tempting to point to the relationship between his walk rate and his home-run rate because of the extremes he’s reached in both departments. Record-setting extremes, actually. This year, Tomlin gave up 16 more homers than he did walks. In over 5200 qualified starting-pitcher seasons since World War II, nobody has ever produced a greater discrepancy in that department. Only four times — Carlos Silva in 2005, Brian Anderson in 1998, Brad Radke in 2005, and then Tomlin this year — has that difference run into double digits.

Still. The walk rate is nice. And it’s probably not why he gives up homers.

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It may be impossible to believe after the last two games — after all the front-door sinkers thrown by Corey Kluber that turned the Cubs’ bats into mush and after a similar experience last night facilitated by his apprentice Trevor Bauer — but the front-door sinker is not a hot new trend in baseball.

First, to review: the front-door sinker is thrown from a pitcher of one hand to a hitter of the opposite one. The intention? Essentially, to fake the batter into not swinging. It’s a sinker thrown at the hip that then moves into the strike zone. Here’s an example from August Fagerstrom’s piece on Kluber this week:

Seems like a rad pitch. In the era of the swinging strike, it’s a pitch that’s designed to elicit a take. It relies on command in an era when we wonder if pitchers even have any command. After all, as I noted in my for last year’s Hardball Times Annual, the average pitcher misses the catcher’s target by more than 11 inches on a 3-0 count.

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I’ve got a vote for American League Manager of the Year this season and I’m terrified. My first vote as a member of the Baseball Writer’s Association, and it’s the impossible one.

Maybe impossible is too tough a word. I’m sure I’ll figure something out in time to submit a vote. But evaluating the productivity of a manager just seems so difficult. We’ve seen efforts that use the difference between projected and actual wins, or between “true talent” estimations for the team and their actual outcomes. But those attribute all sorts of random chance to the manager’s machinations.

I’d like to instead identify measurable moments where a manager exerts a direct influence on his team, assign those values or ranks, and see where each current manager sits. So what are those measurable moments?

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My favorite part of my job is when players ask me questions. It’s difficult enough to come up with questions on a daily basis, so it’s great to get a free piece — and it’s even better when the question came from someone who plays the game every day. Once you make it to the Show, it’s all about staying in the Show, and that means making the most of your athletic talents. Strategy is often the key component to these questions.

When Athletics infielder Jed Lowrie came bounding across the Oakland clubhouse to me with his question earlier this year, he’d already decided to act on what he had perceived as an issue with his new/old home park. In the spring, he’d connected with his hitting coach, Darren Bush, in order to work on going the other way since he was leaving Houston’s friendly confines for Oakland’s cold. Because fly balls die in Oakland, and opposite-field fly balls are, by nature, less damaging than their pull counterparts, part of that new “oppo” approach was a heavier ground-ball profile. Mission accomplished.

But the reason behind Oakland’s fickle fly-ball play was still on his mind. “I think it’s Mount Davis,” he said back then. His theory was that the wall-like 10,000-seat expansion in center field — constructed in 1996 and nicknamed Mt. Davis in scorn after the Raiders’ late owner Al Davis — was responsible for suppressing fly ball distance in the Coliseum.

Answering his question turned out to be fairly difficult.

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It’s been over a year now since Sean Dolinar and I published our article(s) on reliability and uncertainty in baseball stats. When we wrote that, we had the intention of running reliability numbers for even more statistics, including pitching statistics, of which we had included none.

That didn’t happen. So a little while ago, when I was practicing honing my Python skills by rewriting our code in, well, Python (it was originally in R), I figured, “Hey, why not go back and do this for a bunch more stats?” That did happen. Sean was/is swamped making the site infinitely better, though, so I was on my own rewriting the code.

In case you need a refresher, never read our original article, and/or don’t want to now, here’s a quick description of reliability and uncertainty: reliability is a coefficient between 0 and 1 that gives a sense of the consistency of a statistic. A higher reliability means that there’s less uncertainty in the measurement. Reliability will go up with a larger sample size, so the reliability for strikeout rate after 100 plate appearances is going to be much lower than the reliability for strikeout rate at 600. Reliability also changes depending on which stat is being measured. Since strikeout rate is obviously a more talent-based stat than hit-by-pitch rate (well, maybe not for everybody), the reliability is going to be higher for strikeouts given two identical samples. You can think of it like strikeouts “stabilize” quicker than hit-by-pitches.

Reliability can be used to regress a player’s stats to the mean and then to create error bars around that, giving a confidence interval of the player’s true talent. To continue with the strikeout example, I’ll add another point — namely that, the more plate appearances a player has recorded, the closer the estimate of his true talent will be to the strikeout rate he’s running at the time. In fact, strikeout rate is so reliable that, after a full season’s worth of plate appearances, a player’s strikeout rate will probably be almost exactly reflective of his true talent. The same cannot be said for many other stats, like line drive rate, which is mostly random; the reliability for LD% never gets very high, even after a full season’s worth of batted balls.

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