Archive for Research

Is the Baseball Dead?

The first month of the season was marked by cold weather throughout much of the country. It seemed to have an adverse affect on offense, with power numbers particularly affected. MLB players put up an isolated-power figure of .156 this March and April, which was the lowest mark since April of 2016. Rob Arthur, who has performed extensive research on the juiced ball, noticed the ball wasn’t traveling quite as far in early April even after accounting for weather — this despite a barrage of homers in the spring. Alex Chamberlain conducted some research of his own and determined hard-hit balls and barrels weren’t doing as much damage as in previous seasons, and he wondered if baseballs had been de-juiced. It’s an interesting question that deserves further research.

Chamberlain speculated that MLB had taken the juice out of the ball, potentially through the use of humidors. He found that hitters had to hit the ball harder to get it out of the park. He also observed that, when controlling for exit velocity and launch angle, batted balls weren’t quite doing the same damage as in years past. He concluded that, since we are now well past the cold-weather days of April, the change in batted balls this season is meaningful.

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What a Smaller Strike Zone Can Do for Pace of Play

Last week, I discussed the consequences of an expanded strike zone on the game, finding that it leads to more strikeouts and fewer balls in play. While some have suggested that a larger zone — by inviting more swings from batters — might actually result in an uptick in batted balls, the observed results don’t support that hypothesis. Whatever gains a larger zone creates in terms of swing rate, they’re negated by an increase both in whiff rate and called strikes, leading to more strikeouts overall.

What that post addressed was what would happen if the strike zone got bigger. This post attempts to answer a similar question — namely, what would happen if the strike zone got smaller?

In order to test the effects of a shrinking strike zone, it’s necessary first to identify an actual instance in which the strike zone has gotten smaller. Fortunately, such an instance exists, thanks again to the research of Jon Roegele, who produced this visual in his piece on the strike zone last year.

That’s the 2007 strike zone on the left and 2017 zone on the right. As you can see, the outside edge to lefties used to be called a lot more frequently than it is now. The bottom of the zone has gotten larger for both lefties and righties (a point addressed in my last post), and the result has been a smaller strike zone for lefties than their right-handed counterparts.

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A Bigger Strike Zone Is a Bad Idea

There are a lot of strikeouts in today’s game. The most ever, in fact. If the season were to end today, the league’s 22.4% strikeout rate would represent an all-time high, eclipsing the record set in 2017. That record from 2017 surpassed the one set in 2016, which itself surpassed the one set in 2015, which surpassed the one set in 2014. Ever since 2008, actually, baseball has produced a new strikeout record, and there doesn’t seem to be an obvious end in sight.

With all those strikeouts come a lot of opinions on how to reduce strikeouts. The latest set of proposals come from Tom Veducci at Sports Illustrated. Verducci correctly places blame/credit for the strikeouts with the pitchers, where it belongs, and he suggests a few solutions: lowering the mound, limiting the number of pitchers on an active roster, and introducing a pitch clock.

I find it curious that Verducci omits any mention of the strike zone itself. I have previously proposed raising the bottom of the strike zone to put more balls in play, but there are others — including at least one MLB manager — who believe that a larger strike zone might increase the number of balls in play.

The possibility of this effect is one I’ve heard mentioned on broadcasts before, so it isn’t without precedent. The theory goes like this: an expanded strike zone will force batters to exercise less patience and, as a result, swing at more pitches. More swings, and perhaps more emphasis on contact, means more balls in play.

Fortuitously, this is a theory we can test, because the strike zone actually hasn’t remained static in recent years. In fact, thanks to great research by Jon Roegele, we know exactly where the strike zone has gotten bigger. The very bottom of the strike zone has increased considerably over the last decade, and although it got slightly smaller the last couple seasons, the trend has reversed itself this year. Even if there wasn’t an increase this year, the strike zone would still be substantially larger at the bottom of the zone than it was a decade ago.

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Don’t Blame Hitters for All the Strikeouts

There is considerable teeth-gnashing going on around the game due to a lack of action on the field. Those criticisms are not unfounded. All things being equal, the game is better with more and not less action. A walk might be nearly as good as a hit when it comes to scoring runs, but it is considerably less exciting. A strikeout does have some excitement of its own, but on a large field that ranges out to 400 feet in most parks, concentrating much of the action to the first 60 feet has some drawbacks when it comes to demanding and retaining the attention of fans.

In any given confrontation, both the pitcher and batter exert considerable influence over the outcome of an at-bat. Because of that, it might seem reasonable to place equal blame on the hitters and pitchers for the increase in strikeouts. In an era defined by greater velocity and more frequent shifts, one argument goes, batters are failing to adjust. If they would just take the ball the other way, they might strike out less, get more hits, etc.

That might be true. It is also possible, however, that changing their approaches might lead hitters to produce less valuable outcomes or, worse, abandon the very strengths that allowed them to become major leaguers in the first place. That isn’t fair to hitters. What I’d like to posit here is a much simpler explanation for the rise in strikeouts — namely, that pitchers are too good.

Fastball velocity has increased at a steady rate, some of that due to the rise of relief innings around the league and some of it probably to dramatic improvements in training and development. That’s not really the point of this post, though. The point of this post is to discuss one particular cause of the increase in strikeouts that likely has little to do with launch angle or players trying to hit home runs, but rather the talent level of the pitchers and a change in philosophy.

Below is a scatter plot of MLB strikeout percentage and average fastball velocity.

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Andrelton Simmons Is Avoiding Strikeouts Like Tony Gwynn

Andrelton Simmons draws comparisons to Ozzie Smith for his defensive prowess. Both players are recognized as once-in-a-generation all-time greats at their positions, though Simmons has yet rival Smith’s Hall of Fame career.

Apart from the defensive skills, similarities have emerged between Smith and Simmons offensively, as well. Consider that, through the 2016 season, Simmons had taken roughly 2,500 plate appearances and put up a weak 85 wRC+. Compare that to Smith’s first seven seasons, through 1983, when he put up an even worse 74 wRC+ in more than 3,500 plate appearances.

Smith eventually turned his career around offensively, however, putting up a 103 wRC+ from 1984 through 1992 while producing 37 runs by means of the stolen base, a total which might even understate his total offensive value. Smith was bad on offense for quite some time, then he improved and was a good offensive player for a decent portion of his career. It’s possible we are seeing the same type of transformation from Simmons. The Angels shortstop put a 103 wRC+ last season at 27 years old; thus far this season, he’s doing considerably better, with a 143 wRC+ on the strength of his .331/.402/.466 batting line. Most remarkable about Simmons’ hitting numbers are the strikeouts — or lack thereof, rather — as Simmons has struck out in just 10 of his 200 plate appearances.

In 1998, Tony Gwynn stepped up to bat 505 times and struck out on just 18 occasions. The league-average strikeout rate of 17% at that point was nearly five times Gwynn’s 3.6% mark. Preston Wilson made his debut that season and struck out more times than Gwynn despite receiving only 60 plate appearances. Gwynn’s 3.6% strikeout rate isn’t the greatest of all-time. Joe Sewell struck out in under 1% of his plate appearances five times, while 68 players between 1919 and 1951 had qualified seasons with rates lower than 2%. There were 413 seasons during that time where a player’s strikeout rate was lower than Gwynn’s in that 1998 campaign. Gwynn himself even had four seasons with a lower strikeout rate than 1998, but when considering the overall context of strikeouts in the game, Gwynn’s 1998 season is probably the best of all-time. If Andrelton Simmons can keep this up, his season is going to be better.

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How I Use xwOBA

If you’ve spent any time observing some of the nerdier battles over baseball statistics in the last decade or two, you’re probably familiar with the arguments made for and against certain metrics. Beginning with the relatively simple matter of batting average versus on-base percentage, these debates tend generally to take the same shape. And generally, one recurring blind spot of such debates is that they tend to dwell on what certain statistics don’t do instead of best identifying what they do do.*

*Author’s note: /Nailed It

The last few years has seen the release, by MLB Advanced Media (MLBAM), of a flurry of new data and statistics, generally referred to as “Statcast data.” We’ve also seen advances in the measurement of catcher-framing by the people at Baseball Prospectus, who have also continued making improvements in the evaluation of pitchers in the form of Deserved Run Average (DRA). When new data and metrics emerge, there is inevitably a period of uncertainty that follows. What does this stat mean? What’s the best way to use this data set? Equally inevitable is the misapplication of new statistics. That aspect of potential statistical innovation is not really new.

Today, what is new is xwOBA — and, in part due to the wide proliferation of Statcast data by means of telecasts and MLB itself, more fans are finding and using stats like xwOBA than might have been in previous generations. As with other new metrics, we are still attempting to identify how xwOBA might best be used.

One such study into the potential utility of xwOBA was recently published by Jonathan Judge at Baseball Prospectus. The study is a good one, with Judge focusing on xwOBA against pitchers. While not ultimately his point, Judge does, along the way, object to the “x” in xwOBA, as he feels that “expected” implies predictive power. While I have always interpreted the “expected” to mean “what might have been expected to happen given neutral park and defense” — that is, without assuming a predictive measure — it does appear that reasonable people can disagree on that interpretation.

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FIP vs. xwOBA for Assessing Pitcher Performance

At a basic level, nearly every piece at FanGraphs represents an attempt to answer a question. What is the value of an opt-out in a contract? Why do the Brewers continue to fare so poorly in the projected standings? How do people behave in the eighth inning of a spring-training game? Those were the questions asked, either explicitly or implicitly, by Jeff Sullivan, Jay Jaffe, and Meg Rowley just yesterday.

This piece also begins with question — probably one that has occurred to a number of readers. It concerns how we evaluate pitchers and how best to evaluate pitchers. I’ll present the question momentarily. First, a bit of background.

Fielding Independent Pitching, or FIP, is a well-known tool for estimating ERA. FIP attempts to isolate a pitcher’s contribution to run-prevention. It also serves as a better predictor of future ERA than ERA itself. The formula for FIP is elegant, including just three variables: strikeouts, walks, and homers. It does not include balls in play. That said, one would be mistaken for assuming that FIP excludes any kind of measurement for what happens when the bat hits the ball. Let this be a gentle reminder that home runs both (a) are a type of batted ball and (b) represent a major component of FIP. There is, in other words, some consideration of contact quality in FIP.

Expected wOBA, or xwOBA, is a newer metric, the product of Statcast data. xwOBA is calculated with run-value estimates derived from exit velocity and launch angle. Basically, xwOBA calculates the average run value of every batted ball for a hitter (or allowed by a pitcher), adds in the defense-independent numbers, and arrives as a wOBA-like figure. The advantage of xwOBA is that it removes the variance of batted-ball results and uses a “Platonic” value instead.

The introduction of Statcast’s batted-ball data is exciting and seems like it might help to better isolate a pitcher’s contributions. But does it? This is where I was compelled to ask my own, relatively simple question — namely, is xwOBA better for assessing pitcher performance than the more traditional FIP? What I found, however, is that the answer isn’t so simple.

The differences between FIP and xwOBA, as well as the similarities, deserve some exploration.

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Players Don’t Become Terrible at 30

One of the oft-mentioned reasons for the slow free-agent market this winter is that teams are thinking on the same wavelength when it comes to evaluating players. One of the tenets of this theory is that free agents are bad bets because of the aging process. As players age, especially after 30, they get worse on the field, and teams don’t want to get stuck with those decline years.

There is a whole lot of reason in that explanation for the offseason’s lack of activity. There’s also a little bit of faulty logic regarding the aging process, particularly when it comes to this year’s free-agent class and the two biggest names out there, Eric Hosmer and J.D. Martinez.

The first flaw in this argument is based on a misunderstanding of how clubs are compensating players. All teams — and especially the “smart” ones — know and understand that the final year or years of a free-agent contract are unlikely to be valuable in terms of strict wins-per-dollar calculus. It’s generally accepted that those “out” years are going to be mostly dead weight. Players are typically signed to deals for which the total guarantee is equally distributed over the course of a deal. The team isn’t paying an equal amount every year expecting metronomic production over the life of a contract. They expect to receive a surplus of value in the early years and a deficit in latter years. The hope is that the early years compensate for the latter ones.

Teams could, in theory, compensate players a greater amount at the beginning of a contract than at the end, but most clubs choose not to do this because, by spreading the payments out, they get to keep more money in the present, which is more valuable to them. If a team doesn’t want to add, say, a seventh year at $25 million to Eric Hosmer’s offer, it isn’t because they believe he isn’t going to be worth $25 million in that seventh year. It’s because they believe he won’t be worth extra $25 million over the first six years. The value in the seventh year is going to be close to zero in terms of expectations. That’s not the main point I’m trying to make in this post, but it does deserve a mention.

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Manny Margot and the Stickiness of a Launch-Angle Breakout

Manny Margot had a breakout within a breakout last year. After accounting for his offensive and defensive contributions, the Padres’ rookie center fielder was worth roughly two wins in slightly less than a full season’s worth of plate appearances. Even for a player who was highly touted as a prospect, producing league-average work at 22 years old represents, in itself, a kind of breakout.

Hidden within that strong end-of-year line was a drastic change in the second half, though. Margot started hitting the ball in the air. That’s a change that has powered many other breakouts. But before we book the skinny center fielder for all of the homers next year, we have to ask: what’s happened with launch-angle surgers in the past?

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Neuroscience Can Project On-Base Percentages Now

I have an early, hazy memory of Benito Santiago explaining to a reporter the approach that had led to his game-winning hit moments earlier. “I see the ball, I hit it hard,” said Santiago in his deep accent. From which game, in what year, I can’t remember. Also, it isn’t really important: it’s a line we’ve heard before. Nevertheless, it contains multitudes.

We know, for example, that major-league hitters have to see well to hit well. Recent research at Duke University has once again made explicit the link between eye sight, motor control, and baseball outcomes. This time, though, they’ve split out some of the skills involved, and it turns out that Santiago’s deceptively simple description involves nuanced levels of neuromotor activity, each predictive of different aspects of a hitter’s abilities. Will our developing knowledge about those different skills help us better sort young athletes, or better develop them? That part’s to be determined.

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Statcast’s Outs Above Average and UZR

Given the relative novelty of Statcast data, it remains unclear for the moment just how useful the information produced by it can and will be. As with any new metric or collection of metrics, it’s necessary to establish baselines for success. How good is an average exit velocity of 90 mph? What does a 10-degree launch angle mean for a hitter? How does sprint speed translate to stolen bases or defensive ability?

In an effort to begin answering such questions, the Statcast team has rolled out a few different metrics over the past few years that attempt to translate some of the raw material into more familiar terms. Hit probability uses launch angle and exit velocity to determine the likelihood that a batted ball will drop safely. Another metric, xwOBA, takes that idea a step further, using batted-ball data to estimate what a player should be hitting.

Another example is Outs Above Average. In the case of OAA, the Statcast team has accounted for all the balls that are hit into the outfield, determined how often catches are made based on a fielder’s distance from the ball, and then distilled those numbers down to find what an average outfielder would do. The final result: a single number above or below average.

At Reddit, mysterious user 903124 has published research showing that the year-to-year reliability for Outs Above Average has been considerably higher than the Range component for UZR. The user was kind enough (or foolish enough) to create a Twitter account reproduce some graphs of his results, which are shown below. There is a subsequent tweet in the thread that shows left field.



For those who can’t see the charts and would prefer not to open up a new window, what you’d see here is that, for the group selected, the r-squared is much higher for Outs Above Average than for the Range component for UZR. If Statcast could produce something that is much more reliable and much more accurate than the Range component of UZR, that would be a pretty significant breakthrough and win for Statcast, potentially improving the way WAR is calculated and providing a better measure of a player’s talent and results on the field.

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What Statcast Says About the National League Cy Young

Over in the American League, there’s a clear two-horse race between Chris Sale and Corey Kluber for the Cy Young Award. Both are head and shoulders above the rest of the league and both have very strong cases for the honor, depending on what metrics you prefer.

Over in the National League, that isn’t quite the case. Max Scherzer is the clear front-runner at this point, with a host of other pitchers behind him all trying to make an argument why they might have had better seasons. Clayton Kershaw has a lower ERA. Zack Greinke pitches in a much tougher park. Teammate Stephen Strasburg has a lower FIP.

Those are just the stats that measure outcomes, though. Let’s see what Statcast has to say about the sort of contact the other candidates are allowing to see if anybody has a real case against Scherzer.

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How 2017 Compares to the Steroid Era: Part II

Yesterday, I looked at how one of the last seasons of the steroid era (2002) compares to the present one in terms of home runs, total offense, and overall value by position. To summarize the findings of that post briefly: while corner outfielders account for less production now than they did in 2002, infielders and catchers are now responsible for more of it. Moreover, players at the top of the home-run leaderboards now are accounting for a lower percentage of total league-wide homers than in the steroid era. There’s a more even distribution of homers, in other words.

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How 2017 Compares to the Steroid Era: Part I

Infielders account for a greater percentage of homers now than in 2017. (Photo: Ryan Claussen)

The 2017 season has seen offensive levels rise to a height unmatched in major-league baseball for quite some time. Overall this year, teams are averaging 4.65 runs per game, the highest mark since 2007 — though not quite the five runs per game teams averaged in 1999 and 2000. Most of the offensive increase can be traced to a juiced ball. There’s also been a lot of talk about the role of a fly-ball revolution of some sort or another in the establishment of a new league-wide seasonal home-run record.

An increase in PED use has now been raised as an issue, as well. MLB has administered both PED testing and PED-related suspensions since 2004; both have existed in the minors since 2001. Even with those measures in place, however, power continues to be associated with steroid use, and unfounded rumors have hounded the authors of every breakout season over the last decade. With the rise of power in recent years, the whole league is under suspicion. But how similar is this version of the league to the one now known as the “steroid era”? Let’s take a look at what the latter actually looked like and how it compares to now.

Our split tools are very expansive going back to 2002. This is convenient because 2002 was the last season that lacked PED testing of any kind. It might not have been quite the height of that period now regarded as the “steroid era” — that was probably 1999 and 2000 — but the league looked quite different before testing and suspensions were permitted.

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What Strikeouts Have Taken from Baseball

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.

Comparing 2000 and 2017
2000 62083 190261 5693 9.6 % 16.5 % .167 .300 .270 .345 .437 .341
2017 54957 173900 5753 8.5 % 21.6 % .172 .300 .255 .325 .427 .321

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 Both Fastballs

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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Would Chris Hayes Get a Hit in a Full Season of Play?

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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Is Contact Management Consistent In-Season?

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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What Statcast Reveals About Contact Management as a Pitcher Skill

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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Young Players Are Leading the Rise in Three True Outcomes

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.

Three True Outcome Leaders in 2017
Name Team PA HR BB SO TTO% wRC+
Joey Gallo Rangers 364 31 45 138 58.8% 125
Aaron Judge Yankees 467 35 81 146 56.1% 174
Miguel Sano Twins 429 25 48 150 52.0% 128
Eric Thames Brewers 417 25 60 122 49.6% 124
Khris Davis Athletics 469 30 53 149 49.5% 126
Trevor Story Rockies 364 15 34 131 49.5% 67
Mike Napoli Rangers 373 22 32 126 48.3% 82
Steven Souza Jr. Rays 446 24 57 128 46.9% 139
Mark Reynolds Rockies 437 23 52 128 46.5% 111
Cody Bellinger Dodgers 385 32 42 103 46.0% 141

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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