It shouldn’t be news that strikeouts have increased at a pretty alarming pace over the last decade. From the end of the last strike through 2007, the league-wide strikeout rate was pretty steady, averaging 16.7%. That is, roughly one in every six plate appearances ended in a strikeout. Over the last decade, the average has reached nearly 20%, including a high of 21.6% this year. Now, more than one in every five plate appearances ends in a strikeout. A strikeout is now 30% more likely than it was a little over a decade ago.

This is a problem with many possible solutions: raising the bottom of the strike zone; lowering the mound; or, my personal favorite, expanding the league. This piece isn’t prescriptive, however. The focus of this piece is to show exactly what the strikeout has replaced, and it isn’t actually all bad.

Because I started this piece by doing some research on the home-run record, we will focus here on the year 2000 as it compares to the present. That season represents what was probably the height of the PED era; it was also the season responsible for the league-wide high in home runs until this year. Because the power numbers between the two periods are similar, a comparison of the seasons creates an interesting vantage point from which to view the role of the strikeout.

Generally, we imagine that players have to sacrifice contact for power. It’s notable, then, that the power numbers of today are equivalent those of the 2000 season even though players are striking out 30% more often now than they did back then. To provide some background, here are some standard numbers from 2000 and 2017.

As the 20-point difference in wOBA illustrates, overall offensive levels were higher back in 2000. The ISO and BABIP figures are all roughly similar. When a batter hits a ball in play, that batted ball is just as likely to become a hit as it was before. When it lands fair, it’s leading to roughly the same amount of extra bases. All that’s basically the same.

In terms of differences, one finds that this year’s walk rate is a bit lower than in 2000. That has some influence on run scoring, but not at all to the same degree that the increase in strikeout rate has. In effect, 5% of potentially positive plate appearances have been turned into strikeouts. That’s significant. However, while the main complaint about strikeouts is that they lead to fewer balls in play, it isn’t accurate to suggest that every extra strikeout has actually had that effect.

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Eugenio Suarez can hit the sinker. He’s been able to do it his whole life. And, generally speaking, that means he shouldn’t be able to hit the four-seamer. Or, at least not hit it as well, I mean. That’s typically how it goes, one or the other. It has to do with swing paths and approaches, mostly.

But Suarez has pulled off a rare feat this year. He’s been hitting the four-seamer, too. And he’s improved his success against that pitch by improving something other than his swing.

With an .878 lifetime OPS against sinkers, Suarez ranks in the top quartile among the more than 600 players who’ve seen 500-plus sinkers in the PITCHf/x era. His .797 OPS against four-seamers makes him only average against that pitch, though.

Again, that’s not uncommon. Peruse the top-40 hitters against both the four-seamer and the sinker, and only seven names appear on both lists. You might have heard of Kris Bryant, Miguel Cabrera, Matt Kemp, Paul Goldschmidt, Aaron Judge, Mike Trout, and Joey Votto. They’re pretty good.

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Admit it, you’ve wondered. Not you, the former Division I baseball player or the major leaguer who’s maybe reading this. I mean you, the former pony-league baseball kid who maybe got a cup of coffee with the varsity in a nondescript high school league: you’ve wondered if, given a full season’s chance — say, 600 plate appearances — you could get a single major league hit.

Maybe you haven’t. I certainly have. And so has MSNBC anchor Chris Hayes.

It’s easy to argue that he wouldn’t. Just making contact requires sufficient bat speed to catch up to the incoming pitch speed, and the difference between a layperson’s bat speed and a professional one is stark. I’ve linked this image recently, but this time it’s for the stats on the left. Take a look at how much faster Hunter Pence can swing a bat than I can.

Pence nearly doubles my bat speed and gets to the ball three times quicker. Maybe we mere fans just couldn’t connect with the hard stuff. And that’s on the fastball. What happens when a pitcher starts throwing the bendy stuff?

Hayes wondered the same. “I was recently at a batting cage and spent about half an hour, got the speed up to 70 mph, and after enough of them I was more or less getting around, though mostly fouling pitches off, with occasional solid contact,” he wrote in an email. “BUT: no breaking balls and no pitches out of the zone. I just think any major leaguer would be able to just terrify me with a first pitch fastball and then get me to chase garbage out of the zone and that would happen for literally an entire season.”

But isn’t this a question of numbers in the end? Over 600 plate appearances, more than 2000 pitches… couldn’t you swing as hard as possible middle-in and eventually get one measly hit?

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Last week, I took a look at Statcast data from 2016 and 2017 and attempted to find contact-management skills among pitchers. The basic conclusion of that study? Pitchers might well have skills to manage contact once the ball hits the bat; if they do, however, neither xwOBA nor Statcast classifications seem to reveal it. Quality of contact didn’t hold up from year to year — i.e. last year’s results on contact aren’t likely to inform much of this year’s results on contact.

In the comments section, however, one reader wondered if in-season results might create a different result. That’s what I’d like to examine in this post. Here we go.

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While there are certain events (like strikeouts, walks, and home runs) over which a pitcher exerts more or less direct control, it seems pretty clear at this point that there are some pitchers who are better at managing contact than others. It’s also also seems clear that, if a pitcher can’t manage contact at all, he’s unlikely to reach or stay in the big leagues for any length of time.

Consider: since the conclusion of World War II, about 750 pitchers have recorded at least 1,000 innings; of those 750 or so, all but nine of them have conceded a batting average on balls in play (BABIP) of .310 or less. Even that group of nine is pretty concentrated, the middle two-thirds separated by .029 BABIP. The difference between the guy ranked 125 out of 751 and the guy ranked 625 out of 751 is just three hits out of 100 balls in play. Those three hits can add up over a long period of time, of course, but it still represents a rather small difference even between players with lengthy careers. For that reason, attempting to discern batted-ball skills among pitchers with just a few seasons of data is difficult. Thanks to the emergence of Statcast, however, we have some better tools than just plain BABIP to evaluate a pitcher’s ability to manage contact. Let’s take a look at what the more granular batted-ball data reveals.

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The defining characteristic of that period in baseball now known as the PED Era isn’t particularly hard to identify: it was power. Home-run totals increased across the game. The long-standing single-season home-run record was broken multiple times in a few years. And, of course, drug testing ultimately revealed that many players were using steroids and other PEDs specifically to aid their physical strength.

Attempting to find a similarly distinctive trend for the decade-plus since testing began isn’t as easy. For a while, the rise of the strikeout seemed to be a candidate. A combination of increased velocity, better relievers, and a bigger strike zone has caused strikeout rates to increase dramatically in recent seasons.

Over the last couple years, though, we’ve also seen another big rise in homers — a product, it seems, both of a fly-ball revolution and potentially juiced ball. We’ve also witnessed the aforementioned growth of the strike zone begin to stagnate, perhaps even to reverse.

The combination of the strikeouts with the homers over the last few years has led to its own sort of trend: an emergence of hitters who record a lot of strikeouts, walks, and homers — each of the three true outcomes, in other words — without actually hitting the ball in play all that often.

The players responsible for this development are the sort who swing and miss frequently while refusing to offer at pitches on which they’re unable to do damage. To get a sense of who I mean, here’s a list of the top-10 players this season by percentage of plays ending in one of the three true outcomes.

That’s a pretty representative collection of the sort of hitter I’m talking about. Not only are these guys refusing to hit balls in play, they’re being rewarded for it: all but two have recorded distinctly above-average batting lines.

And this group of 10 is representative of a larger trend across the league. Consider how TTO% has changed in the 20-plus years since the strike.

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During this series of articles that have comprised my FanGraphs Residency, I have updated my analysis of the free-agent market that I last researched over three years ago. The vast majority of my new findings have suggested that teams have gotten smarter about spending in line with true player talent, all the while spending roughly the same share of league revenue as they were spending before.

Perhaps my biggest finding is that the OPP Premium has declined. Teams used to receive significantly less WAR for signing other team’s players as they did for re-signing their own players, and this seemed largely related to private information that teams knew about their own players. As teams have become more aware of this phenomenon, the evidence suggests that they have become more careful and have driven up the price of their own players while being more reluctant to sign players on other teams.

This is especially true for pitchers, who used to have the largest OPP Premium. Hitters appear to have actually increased their OPP Premium, which is probably more related to a handful of expensive players who did not pan out rather than teams collectively getting sloppier about signing hitters.
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In my previous articles in this series, I have looked at trends in free-agent spending over time, and specifically I have reviewed more recent data to see if market inefficiencies that I discovered in earlier work have disappeared over time. In this piece, I will review the findings on pitchers in my 2013 Hardball Times Annual article. In that piece, I discovered that teams tended to overvalue old-school statistics that did not translate to actual value. This included wins for starting pitchers and saves for relief pitchers. I also noticed that free-agent pitchers with strong peripheral statistics (e.g. those with good FIPs, usually) were often undercompensated, suggesting teams did not all realize the importance of peripheral statistics in projecting future performance. Much of this seems to have been corrected by the market over the years, although a handful of players have created some noise.
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Talk to pitchers on the record, and the links they’re willing to draw between an increase in blisters and what looks like a tighter baseball are minimal. That makes sense — and it’s doesn’t seem to be concern for politics or press relations that’s holding them back. There are so many confounding factors that it’s the probably the right way to approach the situation.

Talk to a few pitchers off the record, though, and another link emerges, one that might provide some insight into the relationship between seams and blisters.

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Over at Baseball Savant, another Statcast leaderboard has been rolled out. This one relates to speed. They are calling it Sprint Speed, and the definition is as follows:

Sprint Speed is Statcast’s foot speed metric, defined as “feet per second in a player’s fastest one-second window.” The Major League average on a “max effort” play is 27 ft/sec, and the max effort range is roughly from 23 ft/sec (poor) to 30 ft/sec (elite). A player must have at least 10 max effort runs to qualify for this leaderboard.

While Sprint Speed has been used for a while, we didn’t have leaderboards until now. Mike Petriello over at MLB.com has a full article on the rollout which I would recommend. Among the highlights: Sprint Speed correlates well from year to year; it doesn’t require a large sample to become reflective of true talent (Petriello compares speed to fastball velocity); and it might be useful when attempting to identify injuries that could be slowing players down.

So, we know that the metric can tell us who is fast and who is not. That’s helpful. I wondered if it might also be able tell us anything about any other statistics.

Before trying to predict the future or look at past years, I thought it might be useful to compare speed to the stats we have and see how they compare. While the leaderboard over at Statcast features nearly 350 names (every player who’s produced 10 or more max-speed data points), those sample sizes might be a bit too small when looking at other statistics. As a result, I narrowed the sample for this study down to the 166 players who were qualified at the end of Monday’s games.

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