When I wrote about Mike Soroka this week, I mentioned that he’s one of the best players in baseball at getting popups. Nearly 20% of the fly balls opponents have hit against him have ended up in an infielder’s glove, one of the best rates in baseball. It’s clear that this is a valuable skill for the Braves — a fifth of Soroka’s fly balls are automatic outs. But there’s a follow-up question there that’s just begging to be asked. Does Soroka have any control over this? Do pitchers in general have any control over how many popups they produce?

This is the kind of question where it’s important to know exactly what you’re asking. FanGraphs has a handy column in our batted ball stats, IFFB%, that looks like it cleanly answers what you’re looking for. Be careful, though! IFFB% refers to the percentage of fly balls that don’t leave the infield, not the percentage of overall balls in play. Let’s use Soroka as an illustration of this, because his extremely high groundball rate will make the example clear. Take a look at Soroka’s batted ball rates this year:

Soroka allows 19.7% fly balls, of which 17.6% are infield fly balls. In other words, roughly 3.5% of balls put in play against Soroka this year have been popups. For me, that helps contextualize what we’re talking about. Lucas Giolito has the highest rate of popups per batted ball in the major leagues this year among qualified starters, a juicy 7.4% (in a lovely bit of symmetry, teammate and other half of the Adam Eaton trade package Reynaldo Lopez is second). Eduardo Rodriguez is last among qualified starters at 0.5%. There’s a spread in how many popups players allow, but it’s not enormous.
Read the rest of this entry »

You’ve surely heard the sentiment: that pitcher is boom-or-bust. When he’s dialed in, he’s unhittable, but sometimes he just doesn’t “have it.” It’s a non-falsifiable claim, of course. It’s nearly impossible to say what constitutes having it or not, and harder still to know if it’s predictive. For the most part, your talent level is your talent level. Great pitcher? You’ll have fewer blowup games. Bad pitcher? Random chance is going to give you your fair share of crooked numbers.

This unprovable fact, however, set me onto an interesting train of thought. What if run clustering isn’t a purely random process? What if some pitchers, not through any innate streakiness but merely by virtue of the outcomes they allow, give up runs in interesting patterns? Take a groundball-heavy pitcher, for example. When a run scores against him, it’s almost certainly due to a series of groundball singles and walks. If one run scores, there’s often another runner in scoring position right away. The state of the world upon giving up one run, for this Zack Britton-wannabe pitcher, is such that he’s immediately threatened with more runs.

Contrast that to a different type of pitcher, a Nick Anderson-style strikeouts and dingers fly ball pitcher. When our punch-outs and fly balls pitcher gives up a run, it’s often on a solo shot. When that’s the case, one run is in, but the resulting situation isn’t threatening anymore. The bases are empty, the damage done in a single instant. Wouldn’t it be reasonable to wonder whether the two allow runs in different bunches?

Still, those are a lot of words with no real evidence behind them. Who’s to say which of those pitchers allow more big innings? Who’s to say if they’re even equally good pitchers? The guy who allows a lot of home runs sounds like he might allow a lot of big innings, just by virtue of being someone who allows a lot of home runs. We need to be more precise to say anything with conviction. Read the rest of this entry »

The height of fashion in baseball analysis three years ago was finding a reliever who could pitch multiple innings. Some people called it the Andrew Miller role, though Miller was never a perfect example of it — aside from the memorable 2016 playoffs, Miller was more of a setup man who occasionally threw the seventh in his tenure on the Indians. Chris Devenski and Chad Green were trendy examples in 2017, and Mets swingmen Seth Lugo and Robert Gsellman both performed admirably in long relief in 2018.

Whichever example you turn to, the value of having a reliever who can perform over multiple innings of work is clear to see. As starters throw fewer innings across baseball, having relievers who can handle larger workloads is increasingly important. A two-inning reliever might have been a luxury in 2009, when a seven-man bullpen would cover two or three innings a night, but 2019 bullpens go eight deep and pick up nearly four innings a game. Using relievers to cover more innings naturally results in weaker relievers getting into games, so getting extra frames out of good relievers has never been more valuable.

That’s the theory, anyway. In practice, the role isn’t easy to fill. If you’re looking for someone to throw a few innings of relief, they have to be a decent pitcher. There’s not really much point in filling bulk innings with replacement-level stuff — you could just use the back of the bullpen for that. There’s just one problem with that: a good pitcher who can throw multiple innings mostly describes a starter, and getting rid of a good starter to create a good reliever doesn’t make that much sense. Blake Snell, for example, would probably make a great reliever, but that would be a waste of his talent. Read the rest of this entry »

Earlier this month, I noted that hitters are chasing fewer pitches and seeking out fastballs in the zone. It’s one thing batters can do to fight back against the rising pitching talent and increased strikeouts. It seemed to me that every time I looked into a hitter potentially breaking out this season, I saw the same pattern: fewer swings on pitches outside the zone and a rising wRC+.

• It was true for George Springer, who took over the AL WAR lead.
• Hunter Dozier seemed to benefit greatly from better discipline.
• Jason Heyward’s mini-resurgence seemed due to better plate recognition.
• Paul DeJong took a step forward by mashing balls in the strike zone and avoiding those outside of it.

There comes a point when writing about the same thing over and over again becomes presumptuous if we can’t quite be sure that the benefits will last. To that end, I first went through plate discipline numbers from this season to determine if chasing fewer pitches seemed to help batters like I think it should. First, I looked at all hitters with at least 300 plate appearances in 2018 who were also qualified for the batting title as of May 13 of this year. While we can presume that taking pitches outside the strike zone is a skill, and one that stabilizes pretty quickly based on previous research, here’s how the numbers from last season and this one match up as of Tuesday’s data. Read the rest of this entry »

Last week, I investigated the changing performance of starters relative to relievers. There’s nothing too crazy about that — FanGraphs is a baseball analysis website, after all, and the starter/reliever divide is a rich topic for analysis. I have to confess, though, that the reception of the article was pretty exciting for me. You see, I got into baseball statistics when a friend recommended The Book to me, and there was Tom Tango, writing about my piece.

Aside from making me feel validated, Tango went over a few methodological improvements I could make to strip a little more noise out of the data. That, in essence, is what all of this analysis is doing — removing noise piece by piece, hoping to find the sweet, sweet signal underneath it all. In my initial article, I covered three topics: pitchers the first time through the order, starters vs. relievers but only using good pitchers, and swingmen. Today, I’d like to look at each of the three with a slightly different aim.

First, let’s talk about performance the first time through the order. Focusing on this consistent set of data (first time through the order, batters 1-7) for both starters and relievers lets us strip out distributional effects from starter workload changes. Merely looking at these splits, however, left out one key factor: home vs. away performance. Mitchel Lichtman has found that home field advantage isn’t a constant — it’s highest in the first inning. Road batters have a pronounced disadvantage relative to home batters in the first inning, which fades away somewhat afterwards. Credit it to having to hit cold, or go the other way and say that road starters are off their game in the first inning, but it’s worth exploring home and away splits to see if there’s anything there. Read the rest of this entry »

If you read about baseball on the internet these days, it’s tough to miss pieces on the changing relative skill levels of relievers and starting pitchers. As Sam Miller pointed out on Effectively Wild, relievers have a higher ERA this year than starters. Not only that, but the strikeout rate advantage relievers have traditionally had over starters is plummeting. Look at almost any statistic, and the historical edge relievers have had over those in the rotation has diminished.

At the same time, relievers are setting volume records left and right. For five straight years, relievers have set a new record for largest share of pitches thrown. In 2012, Rockies relievers struck out more batters than Rockies starters for the first time in baseball history, and you could convince yourself that it was a Coors field oddity. In the next six years, however, four more teams did it. From a bulk perspective, relievers are pitching more and more innings, carrying ever more of baseball’s pitching workload.

Clearly, these two effects are correlated. You’ve undoubtedly heard of the times-through-the-order penalty, the concept that starters fare worse each time through the batting order. In tandem with the innings spike by relievers, the number of pitches starters throw their third time through the order is plummeting. It’s not rocket science — the third time through the order is the time when starters are weakest, and those weak points are disappearing. Of course starters’ stats look better!

Given the changing roles of starters and relievers, it’s probably not right to look at unmodified splits to figure out whether starters are actually getting better relative to relievers. Even if the talent level of every pitcher remained exactly the same, cutting out a chunk of third-time-through plate appearances from starters’ cumulative totals will change their statistics. To actually see whether relievers are getting better relative to starters, we’ll need to do something a little fancier. Read the rest of this entry »

On May 17, 2018, Paul DeJong stepped to the plate in a tense situation. The Cardinals were down 4-0 in the eighth, but were rallying — two on, nobody out. On a 2-2 pitch, DeJong saw a pitch inside, and he didn’t exactly get out of the way:

After a replay review, DeJong went to first base. Then, he went to the doctor. The diagnosis: a broken hand. DeJong sat out nearly two months, and when he came back, his power lagged. At the time of his injury, he’d slugged his way to a 125 wRC+ and .213 ISO. The balance of the year, he compiled a 90 wRC+ and a .182 ISO, and the first month back was particularly dire: 59 wRC+ and a Hamiltonian .090 ISO.

Clearly, getting hit by that pitch wasn’t worth it. DeJong is one of the best players in baseball this year, and he was off to a solid start last year before getting hit. If it weren’t for that power-sapping injury, we might be talking about him as a consistent star rather than an out-of-nowhere surprise. At the time, though, it surely made sense to take one for the team. Reaching base there was huge — it increased the Cardinals’ chances of winning the game by almost 10%.

In a full season, a league-average baseball player (think Kevin Pillar or DJ LeMahieu’s 2018) is worth around two wins above replacement. That’s over 600 plate appearances — each trip to the plate adds infinitesimal value. DeJong had a chance to get 1/20th of that value in a single plate appearance, and he didn’t even have to do anything. As the saying goes, “We got ice.” Accepting a hit by pitch to get on base is a time-honored tradition. But is it worth it?

While this question seems pretty straightforward, it’s a thornier problem than it first appears. For example, if a career minor-leaguer, who is only up for the day, is at the plate, it almost doesn’t matter how likely it is that he’ll be injured; it probably makes sense to lean into one. If Mike Trout is at the plate, on the other hand, he should probably be exceedingly cautious. I don’t have all the answers. I do, however, have a theoretical model that should help you know how to feel about any given player taking one for the team.

To start, we’ll need an idea of the likelihood of injury. Anecdotes are great and all, but to judge the likelihood of injury we’ll need more. The DeJong example above is great, but he’s been hit by 18 pitches in his career. Cherry-picking one or two is no way to study this. Luckily, The American Journal of Sports Medicine published an excellent study on HBP injuries last year, and we can use their data.

Between 2011 and 2015, the study counts 361 HBP’s that caused injury in MLB, averaging 11.7 days missed per injury. That gives us a rough baseline for days missed per injury, averaging over the bruised ribs that might result in a precautionary day of rest and the broken hands that linger. Add in the total number of HBP’s from 2011-2015 (7838), and we can work out how likely an injury is to occur each time a batter is hit.

Armed with this data, let’s take our first naive pass at estimating the net benefit of letting yourself get hit. For this example, we’ll use Trout. Trout’s projected 2019 wOBA is .432, while being hit by a pitch clocks in at .720. Through the magic of wOBA, we can work out the run value of that single event — in this case, about a quarter of a run. In other words, every time Trout gets hit by a pitch, that plate appearance is worth .25 runs more to the Angels than a random Trout plate appearance. Not bad!

Next, let’s turn to the dark side. In the study data, about 5% of HBP’s resulted in injury. The average time missed per injury was roughly 11.7 days. In all, getting hit by a pitch costs around half a day lost due to injury, though most HBP’s have no lasting ill effects. For ease of calculation, we’ll assume Trout gets replaced by a replacement-level player and gets 4.5 plate appearances a day, basically his career average.

Sticking with projections, Trout is worth about 8.4 WAR per 600 PA. Do the math, and a half-day absence costs Trout just under a twentieth of a win above replacement. By substituting in this year’s run value for a win, we get that Trout’s absence costs the Angels a third of a run. Whoops! Given that the initial event was worth about a quarter of a run, every time Trout gets hit, the Angels lose expected value.

Well, we’ve established one extreme. Mike Trout shouldn’t lean into a pitch — his continued health is too valuable. Let’s run this again for a 100 wRC+, league-average WAR player. Joe Average has a .316 wOBA, so getting hit by a pitch is more valuable to him — he picks up a full third of a run by hanging an elbow out there. At the same time, Joe’s team doesn’t miss his absence nearly as much — he costs them a tiny fraction of a win through his expected absence. That said, that still works out to .12 runs. Joe Average should lean in, but he doesn’t benefit his team all that much by doing so.

To find a player who should really consider stocking up on body armor and going full Brandon Guyer, we need to get into the fringes of a major league roster. A perfectly average player is a valuable commodity, after all. How about a utility infielder, though? Consider Hernan Perez, the do-everything Brewer who played every position except catcher last year, but hit quite poorly while doing so.

Perez has a .288 career wOBA, so let’s use that in our equation. He projects to be worth about 1 WAR in a full season of games, but he doesn’t play every game. In fact, he has averaged about two-thirds the plate appearances of a regular, so we can ignore one-third of the plate appearances he misses as times when the team already wasn’t planning on using him. Perez’s lean grants him .36 runs over his normal output, a significant upgrade. He then misses fewer at-bats, and his value is easier to replace — in all, his absence costs the team only .03 runs. We’re slicing things thin here, but if Hernan Perez has a chance to get hit, it looks like he should take it.

These examples lack context, though. Trout might pick up .25 context-neutral runs every time he’s hit, but plate appearances don’t come without context. If the Angels are up 10, those runs are meaningless. If they’re in a tie game, they’re incredibly valuable. Let’s redo the analysis, but this time consider how many expected wins being hit adds, rather than how many runs.

To start, consider an extreme situation. It’s the bottom of the ninth, and the Angels are locked in a tie game. The bases are loaded, with two outs, when Trout steps to the plate. Get on base, and the game ends. Make an out, and we’re headed to extras. This is the situation where getting hit is most valuable — if you get hit, you literally win the game.

In a normal plate appearance, Trout is already a great player to have at the plate in this situation. His OBP projection for the balance of the year is .446. Thus, you can think of the chances of the Angels winning the game as .446*1 (he gets on base, they win) plus .554*.5 (he makes an out, the game goes to extra innings and the Angels are 50% to win). This makes the Angels 72.3% likely to win the game at the moment Trout steps into the box. Getting hit increases the chances of a win to, well, 100% — a 27.7% pickup.

In the Trout section above, we worked out that Trout’s expected absence costs the Angels about a twentieth of a win. It looks like it might make sense for any hitter, even Mike Trout, to accept a HBP in the highest-possible-leverage situation. We’ve defined the boundaries — in a normal plate appearance, you need to be a below-average backup for accepting a base to make sense. In the most dramatic possible situation, everyone should do it. What about the spaces in between, though?

Well, this section is going to veer into bad math, but given the speculative nature of this article, I think I’m okay with that. Rather than work out the exact win probability change for each outcome, as we did for the Trout example, let’s just use leverage index. In essence, leverage index measures how important a plate appearance is in terms of swinging the outcome of the game. Average is 1.0, so a plate appearance with a leverage index of 2.0 means that the result of this plate appearance will, on average, change win expectancy twice as much as a random at-bat.

Now, leverage index isn’t perfect. In some situations (like my hypothetical above), a home run is the same as a walk. In others, say second and third with two outs when your team is down by two runs, hits are incredibly valuable and free passes much less so. Still, it gives us a template. Let’s revisit Joe Average using LI.

Joe steps up to the plate to start the bottom of the ninth inning, down 2-0 (LI 1.97). Rather than compute the exact change in win probabilities for each outcome, let’s just multiply his run value by the leverage index. From above, being hit is worth .34 runs. Multiply that by the leverage of the situation, and it’s the equivalent of .68 runs in a context-neutral situation. Since his absence costs his team about .12 runs, the calculus is clear — in high leverage spots, Joe Average should accept a hit by pitch if he wants to help his team win.

Let’s rewrite this as a formula. If you want to know whether it makes sense for any player to take one for the team, you can roughly use this:

(.720- wOBA) / 1.194 * LI – 10.026 * PA/Game * .54 * WAR/PA

A quick breakdown: .720 minus the player’s wOBA gives the extra wOBA accrued by being hit, and dividing it by 1.194 (wOBA scale) puts it into run terms, where it can be multiplied by the leverage of the situation. At 10.026 runs a win and .54 days of expected absence per hit-by-pitch, you can work out the expected run cost of an injury by plugging in the hitter’s playing time and skill level.

There’s still one thing left to cover. Should Paul DeJong have been trying to get hit? Let’s plug it into the formula and find out. When DeJong got hit, the Leverage Index was exactly 2.0. ZiPS projected his 2018 wOBA as .320 before the season (2.1 WAR/600 PA), so we’ve got all the values we need. DeJong earned .67 context-neutral runs by being hit, and his expected absence cost the team a mere .09 context-neutral runs. It was worth it, ex ante, to get hit there.

Now, all of this said, this model isn’t the last word on the subject. It’s extremely approximate, for one. It doesn’t cover any reduced effectiveness that doesn’t involve missing games, a notoriously difficult problem to study. Lastly, it treats getting hit as a binary act that doesn’t interact with the rest of the game. Anthony Rizzo needs to get hit to be Anthony Rizzo — he’s made a career out of standing with two-thirds of his body hanging over the plate to hit outside pitches. Accepting a hit by pitch might sometimes be optional and independent of the rest of the game, but sometimes you can’t disentangle it.

Still, having a rough guess of the benefits and costs of a free trip to first base beats having no idea. Should you get hit by a pitch? Maybe! It depends who you are, and it depends on the game state. The next time you hear an announcer say “We got ice,” know that it’s not that simple. It might be a baseball truism, but without knowing the context, you can never say for sure. There are situations where Mike Trout should get hit by a pitch, and situations where a below-average player should shy away from contact. Nothing in baseball is ever black and white.

Note: The initial version of this article incorrectly included instance of hit by pitch in both the major and minor leagues; is has been updated to correctly reflect the likelihood of injury due to being hit by a pitch.

Take a look at a 2019 WAR leaderboard and you’ll see some familiar names at the top. Cody Bellinger is having a whale of a season. Christian Yelich is hitting like Barry Bonds and is somehow second in the majors in baserunning runs as well. Mike Trout — well, you know Mike Trout. Look a little closer though, and you might notice something strange. There are four shortstops in the top 10 for WAR this year, and they’re not the usual suspects. Paul DeJong, Elvis Andrus, Jorge Polanco, and Javier Báez are all having great seasons so far, and if you had them as the four best shortstops in baseball this year, you’re a better prognosticator than I am.

Cast your eyes a little further down the board and you might see an interesting trend. Marcus Semien is 11th in WAR. Tim Anderson, Trevor Story, Xander Bogaerts, and Adalberto Mondesi are in the top 25, and Fernando Tatis Jr. isn’t far behind. Perennial stalwarts Andrelton Simmons, Corey Seager, and Carlos Correa are off to good starts. Shortstop, in fact, has produced more WAR than any other position this year.

Now, to some extent, that’s a referendum on how important shortstop is defensively. Only catcher has a higher positional adjustment than shortstop, and as a result only catchers have been worth more defensive runs this year. However, dismissing the prevalence of shortstops atop the WAR leaderboard as a defense-based illusion sells this current crop short. We could very well be looking at the best-hitting shortstop season of all time.

Let’s start at the very top with wRC+. This year’s shortstop class has produced a 107 wRC+ so far. That isn’t the actual best in baseball history, but it’s second only to 1874, and hoo boy are stats from 1874 weird. In that season, shortstops walked .9% of the time, struck out 1.2% of the time, and delivered a batting line of .305/.311/.372 in only 660 games. Let’s be reasonable here and throw out everything before the turn of the century. Cut those out, and the leaderboard looks like this:

2019 shortstops are on top, and it isn’t particularly close. Strip out everything pre-integration, and the recent rise of slugging shortstops jumps out even more:

Ask most baseball fans for the best shortstop-hitting season in history, and they’ll point to 2002. This was indeed a year of great shortstop hitters — Alex Rodriguez hit .300/.392/.623 on his way to a 10-WAR season, and Derek Jeter, Nomar Garciaparra, and Miguel Tejada all had sterling years. That’s all well and good — it was a top 10 season on the above leaderboard, after all — but 2002 also had 585 plate appearances of Neifi Perez’s .236/.260/.303 line, as well as a shockingly low-offense season from Rockies shortstop Juan Uribe, who hit .240/.286/.341 while playing half of his games at Coors.

This season has its fair share of laggards (Brandon Crawford is slugging .212), but it also has 16 shortstops with a batting line at or above league average. Freddy Galvis is hitting .297/.317/.485 and is the 14th-best-hitting shortstop this year. That 114 wRC+ would have been sixth-best in 2002. The depth of shortstop right now is simply stunning. Read the rest of this entry »

Over the last decade, hitters have been fighting a losing battle against incredibly talented pitchers who throw at higher velocities with even more effective offspeed and breaking pitches. Faced with the increase in talent and velocity on the pitching side, position players have done their best to adapt. The emphasis on launch angle, so as to hit balls harder and farther to get an extra base hit, is a fight against hitters’ inability to take the ball the other way or string together rallies, which are increasingly blunted by the strikeouts. Hitting an 89 mph fastball on the outer edge of the plate to the opposite field is a strategy that might work well. Unfortunately, those 89 mph fastballs aren’t as prevalent as 89 mph sliders that dart away from the outside corner and the fastballs that are routinely in the mid-90s. Hitters are continuously adapting to changes in pitching in order to be successful, and this season, they are getting better by not swinging.

Hitters tend to get some blame for their role in there being fewer balls in play, what with the proliferation of strikeouts and homers and three true outcome players who seek walks and power and have a willingness to swing and miss, but much of what hitters do is simply react to what pitchers do. The increase in strikeouts over the years isn’t due to hitters actively choosing to strike out, but to pitchers who have gotten much better at striking hitters out. When I looked at the issue last season, the rise in strikeouts was due to primarily two factors: the increase in the number of pitches at 95 mph or greater, and the increase in the use of non-fastballs to get hitters out. It’s hard to catch up to velocity, and it’s really hard to lay off breaking and offspeed pitches. This season, pitchers are still throwing hard, and as Ben Clemens demonstrated, they are throwing even fewer fastballs.

To go along with the increased use of non-fastballs is an accompanying decrease in pitches in the strike zone. The graph below shows the number of fastballs and non-fastballs in the strike zone over the past few years. Read the rest of this entry »

If you want to paint with an extremely broad brush, you can think of the last twenty years of analytical advances in baseball as waves, alternately benefiting hitters and pitchers. First came the Moneyball years, when sabermetric advances brought offense into the game. It wasn’t just that teams started playing more beefy guys who could hit for power and take a walk. They also encouraged their existing players to be more patient — that’s how you got the iconic four-hour Yankees-Red Sox games of the mid-2000s, in which both teams seemed to make a personal challenge out of who could take more pitches. This coincided with the beginning of the end of the sacrifice bunt, yet another boost to offense.

If it first seemed like every analytical advance increased offense, however, the tables quickly turned. First the Rays realized that newly offense-minded front offices were undervaluing defense. Then they turned to infield shifts. Before long, the Pirates were using data to optimize pitch selection and every team was hunting high and low for pitch framing. If the early 2000s were all about using math to find better ways to hit, 2008 to 2014 was about using data to strangle offense from every angle.

Things have started moving more quickly since then. Batters reacted by trying to lift the ball more, helped out by a livelier baseball. Pitchers tried throwing higher in the zone to counter that, and at the same time teams started working with pitchers to tailor arsenals to their innate spin rates and pitch shapes. It’s not stopping here — batters are going to work to counter pitchers’ new arsenals, and defenses are going to work to find new and better shifts.

For all this back and forth though, I think that the long game favors pitching. The reason is that, to my mind, batting is a game of picking on weaknesses. Teams don’t get their offense against the aces and the tough part of the bullpen, or in lefty-lefty matchups. They pick on tiring pitchers, righties pitching to lefties, or relievers pitching their third game in three days. It’s always been this way — offense spikes in expansion years when the pitching pool gets diluted, and the times-through-the-order penalty has always existed.

If that’s where offense has always been generated, however, then batters are in trouble. Pitching staffs across baseball are shoring up weak points like never before, and there’s not much offenses can do about it aside from just hit better. It’s still April, but it’s almost a guarantee that two pitching trends are going to reach all-time extremes this year. You’ve probably heard of the first one: starters will face batting orders for a third or fourth time less than ever before. The second one is more subtle, but it’s affecting offense just the same. So far in 2019, batters have faced opposite-handed pitching only 51% of the time, a record low.

Let’s handle the times through the order trend first. The effect isn’t novel — I learned about it from The Book, but the general concept has existed much longer than that. Ted Williams talked about it in The Science of Hitting, and it’s not some deep secret. The more looks a batter gets at a pitcher, the better he sees the pitches. It’s not clear whether pitcher fatigue adds to the penalty, but either way it’s not a small effect. In 2018, starting pitchers allowed a .304 wOBA the first time through the order and a .336 wOBA the third time through. That 32-point wOBA swing is about the same as the difference between the 2018 Yankees offense and the 2018 Royals offense. It’s a big deal, in other words. Read the rest of this entry »