It’s hard, sometimes, to believe that Atlanta Braves pitcher Julio Teheran is only 26. After being signed out of Colombia in 2007, Teheran got his first sniff of the majors as a 20(!) year-old four years later, then ranked as the second-best pitching prospect in the league. As a mid-rotation starter in 2013, Teheran more than justified that ranking, putting up a 3.69 FIP, 22 K%, 2.5 WAR season for a 98-win Braves team that would ultimately fall to the Dodgers in the NLDS.

That Braves team was still an exceptional one; the next few Braves teams (winning 79, 67, and 68 games) less so. For that reason, when Teheran has been mentioned recently, it’s often been in reference to his status as a potential trade chip. It’s no secret that the Braves are in full-fledged rebuilding mode, and a good, young pitcher with over three years left of reasonably-priced team control ($6.3M this year, followed by $8M, $11M, and $12M) could fetch an enticing package of prospects to add to their growing collection.

There’s just one problem – Teheran’s currently in the middle of the worst year of his career, and, even worse, he’s the not-so-proud owner of some of the least favorable pitching statistics in the majors. His 5.67 FIP, far higher than his 3.69 figure last season, is seventh-worst among qualified starters, and his -0.3 WAR ranks fifth from the bottom. As you might assume from the preceding figures, Teheran’s rate statistics have been similarly ugly. In fact, as the following chart illustrates, the sum of Teheran’s decline in K% and increase in BB% from 2016 to 2017 (9.5%) is the fourth-highest among all pitchers who qualified in both years.

Overall, Teheran’s K% has fallen from 22% to 16.3%, his BB% has ballooned from 5.4% to 9.2%, and while his fly-ball rate isn’t significantly higher (although it is the fifteenth-highest in the majors), his HR/FB rate is up nearly five percentage points. In some circumstances, such an increase in HR/FB% might lead one to believe that, to an extent, the pitcher in question has simply been unlucky. But Teheran’s HR/FB rate, at a shade over 15%, isn’t unreasonably high; it’s in approximately the 63rd percentile in the league. And it’d be hard to chalk up such a dramatic shift in both strikeout and walk percentages solely to random misfortune.

There doesn’t appear to be a significant difference in any of Teheran’s pitches this year, either in velocity or movement, that would explain his sudden loss of effectiveness. Additionally, none of his pitches’ spin rates have declined this year (although his slider’s spin rate has actually increased by over 200 RPM). There has, however, been an interesting development this season in regard to Teheran’s mechanics. Look at the dramatic change in his horizontal release point:

It’s evident that Teheran consciously changed his delivery during the offseason, at least with respect to his horizontal release point (his vertical release point didn’t change nearly as dramatically). And this isn’t the first time he’s switched up his mechanics; when we expand the x-axis even farther, we can see just how much Teheran has tinkered with his horizontal release throughout his career.

We can see that, compared to today, Teheran had a similar horizontal release point between August 2015 and May 2016. His results during that time span were excellent – a 2.86 ERA (although his FIP was a full run higher), a 21.4 K%, and a 7.4 BB%. But Teheran’s abrupt midseason change in horizontal release point last season didn’t seem to negatively impact his performance afterwards. From June to October 2016, his FIP and BB% were both lower, and his K% was slightly higher, than they were before he altered his delivery.

This naturally raises the question: if Teheran was so successful during the second half of 2016, why did he change his delivery so radically over the offseason? It’s probably premature to say that Teheran’s change in delivery is necessarily the cause of his struggles this year, but there could, at least theoretically, be some secondary consequence of his new mechanics that’d explain his lackluster performance. A potential clue might lie in Teheran’s swinging strike rate, which has declined from around 10.5% – where it’s consistently been throughout his career – to 8.4% this season, despite him throwing a similar percentage of his pitches for strikes in 2017 as in years prior. To me, this could suggest that something in Teheran’s delivery is leading batters to more easily pick up on his pitches’ trajectory. It’s also possible that the mechanical change has affected his control. Although Teheran’s thrown about five percent more fastballs this year, these pitches have been far more spread out across the strike zone in 2017, as the following graph illustrates (see here for 2016):

I’m not particularly privy to the Braves’ everyday clubhouse conversations, but it’d be hard to believe that an adjustment this large didn’t come from Atlanta’s coaching staff. I can think of a few possible explanations behind the change: (1) the belief that Teheran’s old delivery would increase injury risk, (2) the belief that Teheran’s velocity, movement, or command would improve with an altered delivery; or (3) a combination of the two. We can’t know for sure – and we can’t definitively confirm a link between Teheran’s new mechanics and his depressed performance – but I’d say this is a situation worth keeping an eye on, especially as the trading deadline approaches. It’ll be interesting to see if Teheran and the Braves coaching staff continue to tinker with the young right-hander’s delivery, especially if he continues to struggle so much over the coming weeks.

To begin the 2017 season, Mike Leake was one of the most cautiously optimistic targets for a breakout season. His low velocity and K-rate had a lot of people worried about how sustainable the success was. But, for a while, he led the league with a 2.03 ERA (5/23). He ended April with 33.1 IP and 5 ER total, good for a 1.35 ERA. While his success came in the face of Jason Vargas stealing all of the low-velocity, soft contact-inducing, ERA-leading thunder, he generated plenty of buzz as a welcome surprise in the Cardinals rotation after a shaky April and beginning of May by resident pitching-staff wizard, Carlos Martinez.

Part of this was certainly soft contact combined with luck to create a stellar (but unsustainable) LOB% of 86.5% of baserunners (warning: that article contains an extended metaphor comparing him to “leek soup”). But even in the midst of a brilliant start of the season, many analysts warned about the impending reversion to normalcy, referring to previous stunts of brilliance at the beginning of the season. Since the beginning of June, he has surrendered 7 ER in 11 IP, for a 5.40 ERA. While this is not a disaster when compared to other pitchers who have flamed out (cough, cough, Kevin Gausman), for those who were hoping this was a turn of the page in the story of a 29-year-old soft thrower with roughly a 4.00 career ERA — what happened?

Speeding Up or Slowing Down?

First, Leake’s sinker velocity has changed in slightly different ways than one might imagine. Below is the chart of his sinker velocity with June in red and the rest of the season in blue:

The most noticeable change is the slight uptick in sinkers for the 92-93 mph and 89-90 mph range, with less of the 90-92 mph variety. For most pitchers, this would correspond to an increase in swings and misses, but for Leake, a pitcher who relies on command and finesse, this has a minimal impact on overall performance. Also, it should be noted that at a certain point, an increase in velocity has higher returns (e.g. a jump from 92 to 95 mph as exhibited by Brewers breakout-ace Jimmy Nelson), but as MLB hitters are used to seeing slightly faster sinkers than Leake’s with less movement, this increase in velocity has small (perhaps even negative) returns on his performance. When I looked at the chart for contact rates broken down by velocity quantile, this phenomena was ever present, although not as prominent for his sinker, but his cutter.

The cutter quantiles were based on splitting the distribution into thirds and were defined as follows: “Slow” (v < 89 mph), “Medium” (89 mph < v < 90 mph), & “Fast” (v > 90 mph). As shown in the above table, the way to miss bats with this cutter is to keep it below 90 mph, and Leake seems to be moving in the opposite direction. The histogram below charts changes in cutter velocity, red being the distribution in June. While he decreased the amount of cutters directly at 90 mph, the number close to 91-92 mph (danger zone) increased, along with the low-velocity 87-88 mph cutter. Also, we can’t rule out the possibility of an injury with a much wider variation in velocity (although there are more reliable metrics for judging injury risk, like variation in spin rate).

With the changeup, we see the same story. The changeup quantiles were: “Slow” (v < 85 mph), “Medium” (85 mph < v < 86.5 mph), & “Fast” (v > 86.5 mph). Again, the way he misses bats with this is to keep the velocity under 85 mph. This histogram below categorizing the change in changeups shows that this may be the culprit.

Many more changeups are being thrown in the 87-88 mph range, which is really dangerous for a pitcher like Leake whose fastball does not get much faster. A major goal of throwing changeups, especially early in the count, is to disrupt the hitter’s timing. Little research has been done on the optimal separation in fastball and changeup velocity, but generally a 3-4 mph difference is insufficient. It is worth noting, however, that the Statcast pitch tracker system is far from perfect and some of these could very well be slow cutters.

Here are some pretty telling gifs (from the same game) demonstrating the two types of changeups. The first is a particularly nasty changeup on the outside corner to strike out Yasmani Grandal. He is not only totally off balance, but uses none of his legs and pokes, trying to stay alive. This change in velocity is exactly what we should be looking for when getting the feel for changeups.

Now, here’s the high-velocity, flat changeup that has been getting him into trouble.

It lacks vertical movement and just sort of slides through the top of the zone. Utley has zero problem keeping his weight back and engaging his hips to launch it over the right-center field fence, which leads me to my next point.

Leake-ing Over the Plate

Next, we can note the situational pitching Leake has had to do in June, relative to other months. Below is the bar graph of the change in frequency of counts he has faced in June:

Most of the count distributions are roughly the same, but he’s pitching in a lot more 3-1 and 3-2 counts. Leake has never been one to walk many hitters, which may explain the increased exit-velocity numbers. When Leake falls behind in the count (and loses command of his off-speed pitches) he often times has no choice but to spin a cutter over the middle of the plate. Previous to this last start (6/14) Leake pitched in significantly fewer 3-0 counts, while the amount of 2-0 counts he was in stayed pretty much constant. This could be a sign that he lost confidence to shoot for the corner on 2-0 and would be more likely to catch the middle of the plate. The alternative of a 3-0 count (or subsequent walk) might be the lesser of two evils.

Also, the deeper into the count hitters get against Leake, the more comfortable they are against his variety of offerings. Leake thrives off of keeping hitters off balance and surprising them with variations in movement. The more time hitters have to track these pitches, the less effective they will be at throwing off their timing.

As we can see from the locational charts from this season before June, Leake’s moneymaker is very bottom of the zone:

Compare this with the zone chart from June and you can see Leake’s concerted effort to throw more strikes has resulted in many more pitches middle-in at the expense of the bottom half that he dominated at the beginning of the season:

Establishing the inside fastball is a great tool for pitchers with high velocity, but with Leake’s pitch mix, it can be dangerous to leave a sinker middle-in if right-handed hitters have the ability to catch their hands up.

Final Thoughts

Overall, I would caution against reading into Leake’s start of the season as an indication of a fundamental change in stuff. Part of it was most certainly batted-ball luck. Even guys who pride themselves as being soft-contact-inducing studs generally cannot sustain a 0.234 BABIP. Whatever adjustments he made at the beginning of the year have faded. However, look for an adjustment in the coming months to move back toward the bottom half of the zone, especially when behind in the count. I would not be deterred by a slight uptick in BB/9 rate if I saw it accompanied by a decrease in exit velocity. If he can find the sweet spot between leveling out the velocity in his pitches a little more to keep hitters off balance and allow for the most movement possible, we could see another go-around of Peak-Leake.

Clayton Kershaw is the best pitcher of his generation. He is a six-time All-Star and a three-time Cy Young winner. The Los Angeles Dodgers ace won’t turn 30 until next season, but he has already accumulated over 2,000 strikeouts and 135 wins. So, when we see Kershaw falter a little bit for a short period of time, it is justified that the struggles are written off as nothing. That’s what was done earlier this year, but, 14 starts into 2017, he has a problem that isn’t going away. And it’s time to really investigate the issue.

Kershaw has given up at least one home run in his last four starts, and is just three long balls away from tying his career-high 16 home runs allowed in 2012. Those 16 came in 33 starts. Let’s compare his HR/9 and HR/FB for each season:

Both would easily be career highs, and aside from his rookie year in 2008, his current HR/9 of 1.21 would nearly double the next worst.

It’s not like this issue has destroyed him or trickled down into the rest of his game — he is still running a 2.23 ERA. His 23.8% K-BB% isn’t quite what it’s been the last few seasons, but it is still better than his career average. Kershaw has actually still been great, but he is held to a different standard than any other pitcher in the league. He just hasn’t been Kershaw great. So what’s behind the home runs?

Well, we are dealing with Kershaw here, so the first thing to investigate is whether he has had a little bad luck. Maybe a few balls that normally shouldn’t clear the fence did…

But that’s not the case, and that explanation is actually a lot further off than one might expect. Kershaw’s allowed home runs have been hammered. The average exit velocity on them is 105.5 mph, which ranks in the 12th percentile for pitchers who have allowed at least five home runs. Not a single one has been hit below 100 mph, and only two of the home runs had a home-run probability lower than 50%. One of those two is a home run 37% of the time, but it’s usually not an out, either. Similar balls in play to that home run have an .800 average. The other one under 50% is a home run 49% of the time. So, clearly he’s not suffering from bad luck, and it’s actually a little troubling how little luck has gone into the homers.

Strangely, while the home runs have been crushed, Kershaw isn’t giving up more hard contact overall. His hard-contact rate is nearly identical to last season’s, and he is actually sporting a career high in soft-contact rate. Hitters are turning on specific pitches, not hitting him harder overall.

The specific pitch they’re turning on is, surprisingly, his fastball. From 2011 (when Kershaw won his first Cy Young) to 2016, Kershaw’s fastball had a whopping 148.6 run value. That easily ranked first, and the next closest in that time frame was his teammate, Kenley Jansen, at 97.8. His fastball simply dominated guys. And while pitch values are not the most perfect metric to use, there is something to be said that his fastball ranks only 20th in run value in 2017. Yes, 20th out of 85 is far from poor, but remember who we are talking about here.

In that 2011-2016 time frame, Kershaw gave up 44 home runs on his fastball. 14 of those came on pitches that landed arm side of the plate and in the middle third. That was seven more than any other zone. That trend hasn’t changed this season, as half of his eight home runs allowed on fastballs have come in that zone. Obviously some of that is due to the frequency that he throws his fastballs there, but hitters still like to club his fastball there more than any other areas.

So, that zone, along with the middle of the plate (like with any pitcher), are the danger zones for Kershaw’s fastball. Well, look at Kershaw’s fastball location from 2011-2016. Kershaw likes to elevate his fastball on the outer third, so making the occasional mistake and bringing it too low is understandable. But, now, look at Kershaw’s fastball location this season. Yikes. Kershaw is throwing his fastball most often right in the middle of his weak zones.

The pitch is good enough that, even with the poor location this season, it’s still a great pitch. The average exit velocity on his fastball is 85.0 mph in 2017, compared to 84.8 mph in 2015-2016. Guys aren’t consistently hitting it any harder than they usually do. The issue is Kershaw is making more mistakes. In 2011-2016, hitters had a barrel (balls in play with at least .500 average, 1.500 slugging) rate of .11% on his fastball. In 2017, that number has skyrocketed to .94%. Kershaw is leaving it in the sweet spot of the zone too often.

The fly-ball rate on the pitch is also way up to 35.2% this season, which is much greater than recent years. We all know about the launch-angle obsession and how guys are trying to lift the ball out of the park more. If you hit the ball higher, it’s more likely to sail over the wall. Well, that is exactly what’s happening to Kershaw. The overall effectiveness of trying to raise one’s launch angle is yet to be determined, but it clearly leads to more home runs. It’s no surprise that if Kershaw is allowing more balls in the air, he’s allowing more home runs.

Kershaw seems to have lost some command on his fastball, and hitters are starting to tee off on it a little more than usual. If anyone could recover from this, it would be Kershaw. Obviously, with the way he is still pitching, the home runs are not a death sentence. But with the way these balls have been crushed, the issue is worrisome and it hasn’t been shrinking as the sample size increases.

Recently, for my job, I got to mess around with Statcast data for fly balls. I have a good job. As part of the task I was working on, I attempted to calculate the maximum heights and travel distances of fly balls using my extensive ninth-grade physics knowledge. Now, I was excellent at ninth-grade physics, especially kinematics, but my estimates, compared to the official Statcast numbers, were terrible. Figuring the discrepancies must be due to air resistance, I did my best to remember AP physics (with the help of NASA) and adjusted my calculations for drag. The results improved, but were still way off. There are many additional factors that affect the flight of a fly ball such as wind, air temperature and altitude, but I think the biggest factor causing the inaccuracy of my estimates is batted-ball spin. (If you disagree, let me know in the comments.) Exit velocity and launch angle get all the attention when discussing batted-ball metrics, but the data I was looking at suggested that batted-ball spin merits attention too. Are there batters who are consistently better at spinning the ball than others, and if so, is this a valuable skill?

We already know that balls hit with top-spin sink faster than normal while balls hit with back-spin stay in the air longer. It’s unclear, though, whether it’s better for the batter to hit the ball with more or less spin, and whether top-spin or back-spin is more beneficial. Back-spin would seem to be better if you are a home-run hitter while top-spin might be more beneficial if you are a line-drive hitter.

As far as I know, Statcast doesn’t measure batted-ball spin, and if it does, it’s not available on Baseball Savant. So to act as a proxy for spin, I calculated the estimated travel distance (adjusted for air resistance) from its launch angle and exit velocity for every line drive, fly ball and pop up hit in 2016 and subtracted this number from the distance estimated by Statcast. The bigger the deviation between these two numbers, the faster the ball was spinning, theoretically. Balls with positive deviations (actual distance > estimated distance) must have been hit with back-spin and balls with negative deviations (actual distance < estimated distance) must have been hit with top-spin.

The following table shows the 20 hitters (min. 50 fly balls hit) who gained the most distance on average in 2016 due to back-spin:

With a few exceptions, these are not home-run hitters. This group of 20 players averaged 8.25 home runs in 2016. The players who are getting the most added distance on their fly balls are not the ones who need it most. (Note: four players on this list and three of the top four players played their home games at Coors Field. Did you forget that Daniel Descalso played for the Rockies last year? Me too.)

What about the other end of the spectrum? The following are the 20 players who lost the most distance on average in 2016 due to top-spin:

Kris Bryant, Miguel Sano, Ryan Schimpf: this list is full of extreme fly-ball hitters with an average of 24 home runs last year. The scatter plot below with a correlation of -0.58 shows the relationship between batting spin and fly-ball percentage for all players in 2016.

And this isn’t just a one-year phenomenon. I was relieved to find out that the correlation between 2016 average distance deviations and 2015 average distance deviations is 0.75. Players who hit balls with a lot of spin in 2015 overwhelmingly did so again in 2016. Again, the plot below shows the strong relationship.

Mechanically, this is not such a surprising result. Players with a more dramatic uppercut swing (like a tennis swing) will impart more top spin onto the ball while the opposite should be true for players with a more level swing.

It remains to be seen whether this knowledge is useful in any way or if it falls more into the “interesting but mostly irrelevant” category of FanGraphs articles. There is essentially no relationship between a player’s average distance deviation and his wRC+ (correlation = -0.13), so we cannot say that spinning the ball more or in either direction leads to better results. And I imagine it is difficult to alter one’s swing to decrease top-spin while still trying to hit fly balls. At best, maybe this is a cautionary tale for players who want to be more hip and trendy and hit more fly balls like James McCann (FB% = 0.41), but don’t have the raw power to absorb a loss of 28 feet per fly ball (HR = 12, wRC+ = 66).

Let me know what you think in the comments.

I was planning on writing about Justin Smoak, but Jeff Sullivan stole my thunder and for some reason people like reading articles written by professional baseball analysts more than articles from college undergraduates (but I guess it’s still worth a read). So, I moved on to the next guy on my list.

First of all, if anyone is going to benefit from their environment in a lineup, it’s Adam Duvall. The Reds have turned out to be one of the most productive lineups in baseball (as a Cardinals fan, it hurts to write that). It starts with the best base-stealer in the MLB followed by the player about to overtake Mike Trout as the best of the 2017 season in terms of WAR, followed by one of the best hitters in baseball, followed by Duvall. He’s protected by a surging Eugenio Suarez, a breakout Scott Schebler (who many in baseball refer to affectionately as “this year’s Adam Duvall”), speedy Jose Peraza, and recently-discovered greatest player of all time, Scooter Gennett. Great American Ball Park has the best right-handed home-run factor in baseball. Overall, Adam Duvall has it good in Cincy.

We’ll start with the most obvious factor in what makes Adam Duvall such a force in the Reds lineup: the elite power. Duvall’s .530 slugging percentage and .258 isolated slugging are good for 26^th (right behind Kris Bryant) and 28^th (behind Paul Goldschmidt and ahead of George Springer) in the majors, respectively. By all accounts, he is one of the top 30 pure power hitters in the league. This much has not changed. What makes him interesting as a hitter is not a major change of swing plane or pitch selection like Alonso or Lowrie. He has always been near the top in FB/GB rate (20^th this season with a 1.22 ratio).

The obvious “yes…but” to all of this is his plate discipline. Yeah…fair point. In 2017, he has a weak 24% K rate, and an even worse 6% walk rate, making a 0.26 BB/K ratio (ouch). We can hope for a Justin Smoak-esque transformation in the future where he starts making contact with two strikes without sacrificing any power, but in the meantime, what we should look for is what happens with the balls he does put in play.

Batted Ball Data

When I examined the batted-ball data, it doesn’t look like there’s a major change.

There are very slight adjustments, some that might fall within the range of statistical noise, but interesting nonetheless. It looks like there’s a slight decrease in the number of fly balls, increasing his GB% by 1 and LD% by 2. It also looks like he’s becoming slightly less of a dead-pull hitter and hitting the ball more to center and opposite field. All of this resulted in a slight uptick in his HR/FB rate. This decrease in fly balls is confirmed by the difference in the two years’ launch-angle charts:

2017 Launch Angle Chart

2016 Launch Angle Chart

It seems clear that this year, in terms of launch angle, there’s a much larger difference between his home runs and fly balls. Last year, the majority of his hard-hit balls were square at 20 degrees. This could explain some of the jump in HR/FB rate.

Platoon Splits

One of the things that jumps out in Duvall’s stats from this year to last is the major transformation in results in his platoon splits.

What is the reason for this sudden transformation against left-handed pitching? Is it just luck?

It looks like there’s a combination of things at play. First, his BABIP in 2016 was right around league average for both right- and left-handed pitchers. His BABIP against righties basically followed the league average while against lefties it rose to almost .050 points higher than the average. It could be luck…or something has really changed for the rising power hitter.

He Goes Down Swinging…Hard

Here’s one of the coolest changes in Duvall’s performance the last few years.

The 2016 data seems like what you would expect from a power hitter. Weak contact with two strikes, watch out when you fall behind in the count to him, and full-count with first base open, it might be worth walking him. However, the 2017 data shows a major difference. He’s averaging 92 mph exit velocity on 0-2?? He’s not getting cheated on any count. This explains some of the change in BABIP over the past two years. Instead of choking up and trying to make contact after falling behind in the count, he’s more consistently driving the ball. This comes with appreciable increases in exit velocity when ahead in the count 1-0 and 2-0.

Pitch Breakdown

My next thought was: maybe this is the result of differences in his approach to certain pitches. This is where stuff gets interesting. I looked at the pitch breakdown for the past two years against Duvall and found major differences between years. More than half of the pitches he’s seen this year are fastballs, 138 of them two-seamers (pitchers around the league have decided low and outside sinkers are the only way to get him out). In those 138 pitches, he has a .481 average and is slugging .852…That’s not a typo. Around half of the time his at-bat ends with a two-seam, he gets a hit. Here’s the breakdown of his results against two-seams by year.

He’s always hit them pretty hard when he makes contact (.570 SLG vs .234 AVG in 2016), but the biggest difference is apparent in the last column: he stopped whiffing on the two-seamer. Most of the change in slugging percentage can be explained by the massive .250 point increase in average against what used to be one of the most effective pitches against him. Because his underlying K rates haven’t changed that much, we can assume that it’s not just that he’s putting the sinker in play more, but that he’s driving it.

So we know he can hit the sinker now; what about other pitches? Below are his results on changeups.

He’s whiffing slightly less and still getting on base more often than not, driving the ball a significant amount. While we can expect some of the spike in BABIP to be a result of batted-ball luck (and thus regress in the coming months), some of that change has come from an increase in exit velocity and above-average performance against the pitch that most lefties attempt to put him away with. The lesson here is if I were a DFS player and I saw the Reds facing…I don’t know…a Jason Vargas-type pitcher, it might be worth coughing up the money to buy one of the more-overlooked assets in the Reds lineup.

Note: This article was originally published at The Unbalanced, with minor alterations

One of the best early stories of this season was that of Milwaukee Brewers first baseman Eric Thames. Thames, a former prospect who never developed into anything more than a journeyman (he was once traded for Steve Delabar, which is a rite of passage for all middling players bouncing around the league), decided to take his talents to the NC Dinos of the Korea Baseball Organization. The legend of Eric Thames begins there. He hit .345 in the Pacific, with 145 home runs in three years. After three years of doing his best Barry Bonds impression, he sought to return to Major League Baseball as a conquering hero this year. Based on what he did in April, that return went exactly as he intended.

Thames became the talk of baseball by that point, and universally praised by the online community. FanGraphs ran four articles and a podcast about him in one week, Baseball Prospectus declared that pitchers are as careful with him as they are Bryce Harper, and even our own Quinn Allen profiled the role his confidence plays in his game. April was a great comeback for Thames, but he has not been as hot since the calendar turned to May:

Everything that made Thames’ April so special dried up to his previous journeyman levels in May. His batting average dropped from “Barry Bonds” to “Mario Mendoza.” He only hit four home runs, three of which came in May. His on-base plus slugging (OPS), which measures how well a hitter can reach base, hit for average, and hit for power, was so low that it rivaled his .727 mark in the majors before leaving for Korea. Additionally, his Batting Average on Balls in Play (BABIP), which measures the role defense and luck plays in a batter’s success, went as south as one can go. This suggests that Thames was the recipient of luck in April, or that something went horribly wrong in May; for Thames, it was the latter.

In May, Thames dealt with a hamstring issue and a bout of strep throat. The hamstring is probably the injury to focus on, because it affected the physical approach Thames took at the plate. I believe that Thames, whom I consider something of an equal to Edwin Encarnacion, is not the player we saw in May and that he will return to his mashing ways after fully recovering from injury.

Normally, I would never bother writing an article in support of a struggling player by citing his injuries, but Thames is a special case because our data sample on him is so small. The idea that a journeyman in the MLB can come back from South Korea and hit like he did in April has drawn many skeptics. Reportedly, Thames has been drug tested five times already this season, and it’s easy to compare his May production to his early career production before going overseas. I want to point out some of the consequences Thames’ hamstring injury has had on his batted ball rates, and then point to the positives:

As you can see, Thames suffered drops in line-drive rate, pull-percentage, and hard-hit percentage; all of these are tell tale signs of a hamstring injury. Fellow writer Quinn Allen, who played college ball at Douglas College, talked to me about the direct causes and effects between the hamstring injury and those rate changes:

“A hamstring injury in Thames’ left leg, the loading leg, can inhibit his ability to pull the ball with power because he generates a lot of his power from the lower half — it’s the back leg in his stance, after all.”

He continues:

“Even though Thames has a very simple swing with minimal movement, not being able to fully use his lower half has affected his ability to turn on pitches for a high exit velocity on a consistent basis.”

Indeed, Thames has struggled to hit fastballs with the hamstring injury. In April, Thames posted a 90.8 MPH Average Exit Velocity (aEV) on fastballs, six of which accounted for his 11 home runs. Since May, that number has decreased all the way down to 86.2 MPH. While we can draw a direct line between Thames’ injury struggles and his struggles at the plate, there are more reasons to be optimistic that he will be back in form soon. There are some positives in Thames’ batted ball rates that I found very interesting:

Despite being limited by his hamstring troubles, Thames avoided rolling pitches over and hitting more ground-balls; in fact, it seems that he made a conscious effort to avoid just that. While decreasing his ground-ball rate, he posted a big uptick in fly-ball rate, all while continuing to avoid pop-ups. Additionally, his soft contact rate only increased minimally; this means that the drop in hard contact we saw earlier was distributed to his medium contact rate. In other words, Thames’ results may have been less productive, but he was never quite weak. There are more encouraging signs that Thames is maintaining the same solid approach that is conducive to generating power:

Thames may be getting less juice on his fly-balls, but he is certainly still hitting the snot out of his line drives. As Quinn alluded to, once the hamstring is fully healed, Thames will be able to transfer the power he is putting into his line-drives back to his fly-balls. David Cameron of FanGraphs noted in April that Thames produced a stellar 97.2 MPH FB/LD aEV. By combining the two batted ball types together, Cameron was able to point out that Thames hammers both fly-balls and line-drives. Even though he isn’t hammering his fly-balls with the hamstring injury, maintaining the damage on line-drives indicates that he will return to hitting fly-balls with authority.

We noted earlier that Thames is hitting fewer line-drives since May; conventional wisdom would conclude that he would probably have had better success while injured by not trying to hit as many soft fly-balls and instead concentrating on hard line-drives. This is an approach that Red Sox shortstop Xander Bogaerts took to deal with the cold weather in April:

“I mean in April it’s not easy to hit home runs,” Bogaerts said to WEEI. “You’re playing in Boston. I know the wall is right there but it’s pretty hard to hit in the cold in general. We’ll hit some home runs, especially when it starts warming up. Looking forward to a lot of home runs from a lot of guys.”

He continues:

“I mean the cold is good and bad for me,” he said. “The good part is that it helps me do a little bit less. My effort level goes down because it’s kind of cold. But when it warms up I start swinging a bit bigger. You feel stronger because of the sun and whatever. The cold is good because I just try to do more contact, don’t want to get jammed or off the end for my hands to feel pretty bad.”

Thames, as we can see in our chart above, is not taking that line-drive approach. His Average Launch Angle (aLA) has only increased (as has his fly-ball rate), which was par for the course for him, but not a player with a bad hamstring. While it’s easy to criticize Thames for not adjusting accordingly, it’s probable that keeping consistency is better for him in the long run. When the hamstring heals and the power returns, Thames will not have to adjust back to his April tendencies, because his swing plane is already where it needs to be. To me, that is a good sign that he will be back with a vengeance soon.

Bartolo Colon has not been good. There is no way to spin things to say that he has been good. Conversely, it is pretty easy to spin things to say he is bad. After another bad outing on Monday, his ERA is 7.78 in 59 innings of work. Masahiro Tanaka and Bronson Arroyo are second- and third-worst among qualified starters, at 6.34 and 6.24 respectively.

However, if you look at other statistics, they are not so bad. By FanGraphs’ measure of WAR, he is a tick above replacement level. His K% and BB% have both trended in the wrong direction by a couple points when compared to recent three-year stint with the Mets. His HR rate is up, though some of that may be attributable to what might be a very homer-friendly home park. Colon has also suffered from some bad batted-ball luck, with a BABIP of .353, only .004 points lower than his 2007 season that ended his tenure with the Angels and made many question if he was finished.

However, above all else, what is hurting Colon is probably his strand rate. As of right now, his LOB% is 48.5%. This is terrible. This is pretty much without precedent. And here is a table to show exactly how unprecedented this is:

When you see charts like this and statistical points like this, one thing that should always pop into your mind is that the 2017 figure represents about one-third of a season. Regression to the mean should make Colon’s LOB% go up over the course of the next year. Unfortunately for Colon, he is on the wrong side of 40 and often times when older players struggle, whether fair or not, it spells the end of the road. However, there is evidence that in cases like this, pitchers do not get the opportunity to play their ways out of struggles, regardless of age.

What I wanted to do here was look up pitchers who had similar LOB% to Colon through a comparable amount of the season, and to see what happened to those players. To me, that would have been ideal. However, I get an error message when I try to do that on the leaderboards, so I’ll have to present some less ideal numbers and invite anyone else who has access to look into this further.

Going back to 2002, using a minimum of 50 innings pitched, Colon still has the very worst LOB%, just ahead of a guy you might have heard of, Roy Halladay, who clocked a 49.4% rate in what was a truly dreadful 2000 campaign. Looking through the bottom 50 LOB% list, you will find a couple interesting trends. First, a lot of these players played for terrible teams. The early-2000 Tigers and mid-2000 Devil Rays have a few entries. Colon joins Williams Perez’ extremely forgettable 2016 season as the recent Braves on this list. Second, aside from Derek Lowe in 2004, none of these pitchers came close to pitching a full season. Lowe, who checks in at #26 on this list, had 10 more starts and 45 more innings than the second-highest total.

What this list does not account for, however, is that there could be pitchers like Colon that do very poorly in the LOB% department early in the season, but then turn things around due to better luck and thus do not end up on this list. In order to do this, I wanted to look at players that were similar to Colon’s 2017 season. Colon sports a 123 FIP-, which is worse than league average by a decent amount, but not close to his 184 ERA-.

Looking at the next 10 worst LOB% ranked players, you see that they were not having good seasons. Here are the players:

And here is how they compare to Colon’s 2017 (numbers as starting pitcher only):

Finally, a quick rundown of what happened to each of these players during their unfortunate seasons:

Boof Bonser: Bonser was demoted after May 31^st to the bullpen, and finished the year there. Bonser was victimized by a horribly unlucky May, where his LOB% was 33.3%. Despite a lack of actual good pitching, the Twins did give Bonser a chance to improve his luck despite him being only 26. He had surgery in the offseason and barely played in the majors after that.

Dallas Braden: Braden actually did a pretty good job of keeping runners from scoring in his 2007 rookie season when he was coming out of the bullpen, but he was awful as a starter. Still, it seems as though the going-nowhere A’s did not hold Braden back as he finished the year as a starter. Braden was fairly successful until injuries cut his career short, most notably pitching a perfect game in 2010. It’s possible that Braden, 23 at the time, was helped by the A’s decision to let him continue in his starting role at the major-league level.

Charlie Morton: After starting with a 9.35 ERA, Morton was disabled, sent to sports psychiatrist, and demoted to the minor leagues on May 27^th. He was able to return on August 29^th, and had a decent rest of the season. Morton, who was 26 that year, has bounced around as a fringe starter ever since.

Jose Lima: Lima was a bad pitcher in 2000 and 2001 and somehow managed over 50 innings as a starter in 2002 to make this list. He struggled to a 7.77 ERA and famously responded to his release by Detroit by claiming he was “the worst pitcher on Earth.” Twenty-nine at the time, he managed to start 74 more games in the majors after that.

Brian Duensing: Duensing was 29 in 2012 and he makes this list because he managed to make just enough spot starts, despite the fact he was mostly a bullpen guy. For what it’s worth, Duensing’s 11 starts in 2012 were his last, though he still pitches in the majors. The fact that he went into the season thought of as a bullpen guy means you cannot make much out of his trajectory.

Taylor Buchholz: In his 24-year-old rookie season, Buchholz was not bad by peripheral stats when he was demoted to AAA on July 29^th. The Astros, with nothing to play for, had given up on him and traded him to the Rockies, where he has two adequate years mostly pitching in relief. While it would be a stretch to say that he could have been wildly successful had he been given a chance, even a team with a new, forward-thinking GM was unwilling to look past the painful on-field results.

Justin Germano: At 29, Germano got a shot to end the year with the Cubs, and performed okay based on peripheral stats. But Germano was a journeyman player who recorded 23 of his career 48 starts in 2007. He was demoted and released, but honestly it would be the toughest sell job to say that he had any real potential.

Charlie Furbush: Furbush was a mediocre reliever in his age-25 rookie season when he was traded to Seattle in the Doug Fister trade, and for some reason the Mariners let him finish the season as a starter. He wasn’t good, but he was also very unlucky in the stranding-runners department. The Mariners held onto him, but put him back in the bullpen, where he was okay.

Yohan Flande: Flande was a 28-year-old rookie in 2014 that only made two starts after mid-August thanks to his struggles. He has barely been heard from since.

Josh Fogg: Fogg was an old man compared to the rest of this list (except of course for Colon) at the age of 33. I can’t find any indication that Fogg was demoted due to his struggles, and he finished the season in the rotation. The Reds were not playing for anything. After the 2008 season, he barely played.

Conclusion: Players with poor LOB% generally are not pitching very well, and generally are not given a chance to recover. It is likely that extremely poor strand rates are correlated with pitching poorly. Colon’s stint with the Braves and his time in baseball may be coming to an end, and he has likely been the victim of some historically bad luck. But the bad luck can only explain so much. Most of the pitchers who have pitched like Colon in the past were young guys who ended up converting to relievers or guys that were on their way out of the game. Only Braden and Morton remained starters for a significant amount of time afterwards, and Morton has been below average. They were also both almost 20 years younger than Colon is now. In other words, considering all of the bad numbers Colon has, even when taking into consideration his bad luck, there is probably not a good case to be made for giving a fat guy a chance. And he probably won’t get one.

Marco Estrada has a .302 BABIP. If you don’t know, Estrada has been one of the best pitchers at limiting batting average on balls in play. Of the 41 qualified pitchers who have at least 750 innings pitched throughout their career, Estrada has the sixth-worst BABIP difference this season relative to his career.

Despite this increase, Estrada has managed a 3.86 ERA. It’s not great but it ranks 43^rd among qualified pitchers (90) this season. Marco’s 3.59 FIP ranks 25^th, one of the more intriguing developments of this season. From 2015-2016, Estrada had the second-largest difference between his FIP and ERA, behind only Dan Haren, who did not pitch in 2016.

One of the game’s better contact managers, Marco Estrada looks to be adapting. The Blue Jays ace has the best strikeout-to-walk ratio of his career thus far. Estrada has the thirteenth-best strikeout percentage this season, sandwiched between Cardinals ace Carlos Martinez and Nationals pitcher Stephen Strasburg. There are 45 pitchers who qualified for the leaderboards for the past two seasons, only six of which had a greater K/9 increase. Driving this increase looks to be the change.

Estrada’s changeup is one of the best in the league. It’s not a hard change like Stephen Strasburg’s; rather the second-slowest in the league, ahead of only Jered Weaver. There are a couple of factors that make Estrada’s changeup one of the best. Foremost, it comes with an 11 MPH separation between his fastball, making it great for generating whiffs. Furthermore, his release points allow him to deceive batters. The pitch comes from a similar angle as the fastball but travels 10+ MPH slower, making it more difficult to pick up. If you’re thinking the fastball is coming, and a split-second later you realize it’s much slower, by then you’ve already swung as the ball goes right by you. Lastly, the pitch gets little drop. Estrada’s vertical movement on the changeup was 2.56 inches higher than the next right-hander, Chase Anderson. This is another problem for the hitter as the pitch barely drops relative to a major league pitcher’s average changeup.

In the end, you’ve got a pitch that might look like a fastball from the arm slot, is going quite slow, and doesn’t drop much. You can see how the batter faces a tough quandary. The fastball-changeup combo play off each other well. Deception is a key part of Estrada’s arsenal. To get even better, Estrada began to utilize his best pitch more. Using your best pitch isn’t a novel concept. We’ve seen Rich Hill and Lance McCullers Jr. have success in this mold.

Decreasing the usage of the cutter has brought better performance thus far. The cutter is inducing more swinging strikes, and less contact, as hitters have swung more often when he throws it. In 2016, Estrada threw 625 cutters leading to a .352 wOBA, the worst of his four pitches. In 2017, Estrada has thrown 93 cutters, to the tune of a .272 wOBA, currently the best of his repertoire. Why the change? The cutter has seen a massive drop in vertical movement, likely the reason for its reduced usage. While the results have been better, the process might not be. Marco has been unable to get sufficient rise on the cutter. Moreover, the increased effectiveness might simply be due to small sample size. Or perhaps throwing it less brings its own added value.

ACEstrada, as he is affectionately known as to Jays fans, has ramped up usage of his four-seam fastball as well. The pitch is still strong and it’s traveling a mile faster. It won’t keep a 31% strikeout rate but it should continue to induce lots of infield fly balls. On the downside, the average launch speed on the fastball on line drives and fly balls is up 1.5 MPH from last season, to 94.7 MPH. This would explain part of the .316 BABIP it currently sports, up 52 points compared to his career. With a first-pitch-strike rate the highest since his last season with the Brewers, and his best walk rate since 2013, Estrada’s not making it tougher than it has to be. Pitches inside the strike zone are at the highest rate of his career. Once again, it’s because of a changeup he’s commanding very well. It’s practically 50/50 whether the change will make it in the zone, up 8 percentage points relative to his career average.

Looking at Estrada’s batted-ball profile, the big one that jumps out is the decrease in popups. He’s inducing more than 50% fewer popups this season relative to last year. The main culprit: the changeup.  Given Estrada has an 18.2% popup rate on his changeup compared to the changeup generating popups at a 34% clip during his career, it’s likely this issue sorts itself out as the season progresses. With good command, Estrada is capable of finding those easy outs through strikeouts or pop-outs.

To counteract a cutter not moving like it usually does and some BABIP regression, Estrada turned to his two best pitches. The ERA should improve as the season progresses. Being a two-pitch pitcher isn’t an easy task; Estrada has the command of his two primary pitches to pull it off. The key during the rest of the season will be to hold his strikeout and walk gains while continuing to be one of the league’s better contact managers.  Combined, the Blue Jays ace might be getting better. Marco Estrada will play a key role down the stretch; whether it be with the Jays or for a contender in a contract year.

Dallas Keuchel has reemerged as an ace for the Houston Astros this season, as he has posted a 1.71 ERA thus far and is yet to lose a game. He has an absurd 67.4% ground ball rate while still maintaining an 8.21 K/9 innings. Keuchel’s performance has been impressive, but his brilliant pitch repertoire may be even more impressive. Starters in the MLB essentially need at least three pitches. However, a lot rely on two pitches, while sprinkling in a third out of necessity. Possessing confidence in three pitches can be a commodity. But not only does Keuchel have three weapons, he has four pitches that he can effectively use.

It all starts with the two-seam fastball for the bearded ace, which he is throwing almost exactly 50% of the time this year. Hitters are slashing .179/.252/.291 against the pitch, and it’s drawing a GB% of 80.8%. Watch the pitch in live action:

The pitch sinks at the last second, dropping from Joey Rickard’s knees as it crosses the plate to nearly hitting the dirt. Rickard may not be the poster child for hitting, but there isn’t much you can do with that pitch. Even if it doesn’t have the ridiculous late sink, it puts hitters in a bind. It’s perfectly located down and away, so hitters have to reach to get the ball. Maybe you can send it to the opposite field, but Keuchel’s two-seam generally comes in below 90 mph, so a hitter is gonna have to put a hard swing on that to get a solid line drive. And with they way it keeps guys off balance, hard swings usually aren’t finding that pitch.

But that is just one pitch, you say. Keuchel can’t replicate that perfection often. Well…

Keuchel rarely misses his spot with the two-seam, making it a dangerous ground ball/strikeout weapon for him. The two-seam is Keuchel’s most commonly seen fastball, but it is not his only one. He actually throws a cutter to accompany his fastball. The cutter is his least thrown pitch of the repertoire, but he still throws it 10.8% of the time. What’s rare here is the two-seam and cutter combo, as Keuchel is one of only four starters that throws the two-seam at least 25% of the time and the cutter at least 10% of the time.

His cutter is quite effective too, as hitters have a .174 average against it. Similar to the two-seam, Keuchel has great command of the pitch. He knows where he wants to throw it and, usually, he puts it right there. The cutter isn’t quite the ground-ball pitch that the two-seam is, but rather Keuchel uses it jam righties inside. The cutter has the highest infield fly-ball rate (20.0%) of his four-pitch arsenal.

Next is Keuchel’s slider, which he throws 22.2% of the time. Hitters are slashing just .125/.143/.208. His slider is incredibly effective, but it is also different than most sliders. In terms of vertical and horizontal movement, below is your average slider from a lefty:

Blake Snell’s slider breaks down and in, but now look at Keuchel’s slider:

Keuchel’s slider has a ton of horizontal movement, but has almost no downward break. It averages only half an inch of vertical movement. His command of the pitch isn’t nearly as pretty as the fastballs, but that makes sense considering it’s a breaking ball.

Last not but not least, Keuchel’s changeup, which he throws 12.7% of the time. The pitch has limited hitters to just a .233 slugging in 2017. And, like with any of his other pitches, Keuchel throws it where he wants to. Keuchel also kind of has a four-seam fastball, but the pitch is used very rarely and isn’t really part of repertoire.

But back to why I’m writing this in the first place. If you look back at the heat maps for all of Keuchel’s pitches, it’s pretty clear that, aside for elevating his changeup on occasion, Keuchel keeps everything low. All of his pitches consistently land across one plane at the bottom of the strike zone, covering every part of the plate from left to right. When you consider his slider is what it is, Keuchel essentially doesn’t have a true breaking ball. Why this is so odd is because every one of his pitches, in terms of vertical movement, moves in a straight line and lands in the same place every time.

However, every one of his pitches is moving side to side, so Keuchel never gives you anything straight up. They are always going to be cutting or fading. But Keuchel throws all of his pitches relatively slow, so they are not easy to discern based off velocity. If you combine that with the fact that all of his pitches are landing across the same plane and not breaking, it makes it incredibly hard to recognize his pitches.

Just to make it even harder on hitters, here is Keuchel’s pitch mix by count. It’s always going to be a heavy dose of two-seam fastballs, but any of his secondary pitches can be thrown at any time.

So, Keuchel can throw you four different pitches, that all look similar, at any time he wants and exactly where he wants to throw them. That sounds like a recipe for success. Keuchel’s pitch mix may be different, but it is about as effective as anybody’s. Despite extremely limited velocity and stuff, Keuchel remains one of the top pitchers in the game because his command and ability to mix pitches is truly beautiful.

Earlier this month, Eno Sarris posted an article called “Could Ichiro Have Been a Power Hitter?,” which began with a launch angle and exit velocity analysis of Ichiro himself, and developed into a wider examination which led to the interesting proposition that “players may have their own ideal launch angles based on where their own exit velocity peaks.”  In this article, I’ll look at a larger sample of players whose fly-ball rates increased from 2015 to 2016 and see if their peak exit velocity range changed or stayed constant.  First I’ll re-examine Elvis Andrus, then I’ll look at Jake Lamb, Xander Bogaerts and Salvador Perez.

Elvis Andrus

As mentioned by Eno, Andrus’ average launch angle went from 8.1 in 2015 to 8.6 in 2016, but his fly-ball rate actually decreased.  It seems like he started the change in 2015, but was only able to translate it into results (a 112 wRC+) in 2016.  Regardless, let’s look at the data again, and see what we can find.

Instead of just qualitatively looking at the distribution and giving an approximate range of maximum exit velocity, I split the data set into launch angle buckets, and found the bucket with the highest median exit velocity.  For example, if I set the bucket size at 5 degrees and applied it to Elvis Andrus in 2015, I got a range (-2°, 3°) (I’ll omit the degree symbol from now on).  If I set the size at 10 degrees, I got a range (-2, 8).  For the rest of the article, I’ll keep it set at a range of 5 degrees.

The peak range for Andrus’ 2016 was (-3, 2).

Using the method outlined, the peak range for 2015 was (-2, 3), and for 2016 it was (-3, 2), so Andrus’ peak exit velocity range did not change much from 2015 to 2016, just as Eno pointed out, and as we can see with the two years overlaid.

Jake Lamb

Comparing 2015 and 2016, Jake Lamb raised his average exit velocity from 89.7 to 91.3 MPH, and his fly-ball rate from 32.4% to 36.7%.  His adjustments were chronicled by August Fagerstrom during his breakout (http://www.fangraphs.com/blogs/jake-lambs-revamped-swing-made-him-an-all-star-snub/).

The peak 5 degree range for Jake Lamb’s 2015 was (3, 8).

The peak 5 degree range for Lamb’s 2016 was (15, 20)!

Unlike Andrus, Jake Lamb’s peak exit velocity range increased along with his launch angle distribution!  This seems to be the kind of effective swing change that players attempting to join the fly-ball revolution strive for.  Lamb managed to revamp his swing to not only elevate the ball more, but to hit the ball harder at high launch angles, and actually increase the angle at which he hit the ball the hardest.  However, as the next two cases show, this is far from a guaranteed outcome.

Salvador Perez

Perez’s peak 2015 range: (9, 14).

Perez’s peak 2016 range: (0, 5).

From 2015 to 2016, Perez increased his fly-ball rate from 37.4% to 47.1%, and increased his average exit velocity from 87.3 to 88.8 miles per hour.  He also increased his average launch angle from 13.7° to 19.1°.  But curiously, his peak exit velocity range actually went down from (9, 14) to (0, 5)!  When I saw this, I thought I’d have to change my methods, because it didn’t make sense to me at first.  But if you look at Perez’s exit velocity vs. launch angle graphs for 2015 and 2016, these ranges actually seem to qualitatively fit.  Somehow, the Royals backstop managed to hit the ball harder and higher, but become more effective at lower launch angles.  This could be a rising tide lifts all ships situation, whereby his swing adjustments let him hit tough low pitches hard at lower angles, or it could just be a sample size issue.  By splitting the data set into buckets, the sample size gets dangerously small, and prone to strange results.  But I think the results fit the picture, and either Sal Perez needed to hit more balls for us to get reliable results, or he just had a strange batted-ball distribution.  We have a similar, more extreme situation with Xander Bogaerts next.

Xander Bogaerts

Bogaerts’ peak 2015 range: (5, 10).

Bogaerts’ peak 2016 range: (-6, -1).

Bogaerts, like the other three players here, hit the ball harder in 2016 than in 2015.  He raised his fly-ball rate and his average launch angle, and was rewarded with a 113 wRC+, a slight improvement on his 109 wRC+ from 2015.  But his peak exit velocity range for 2016 was, like Perez, lower than in 2015.  Looking at his plots, it looks like he hit his ground balls harder in 2016, while not changing the exit velocity of his line drives and fly balls as significantly.  I’m not sure what else to say about Xander, other than that he’s kind of a weird player, as already noted by Dave Cameron (http://www.fangraphs.com/blogs/xander-bogaerts-is-a-very-weird-good-player/).

Summary

The following table summarizes the findings for each player.

It seems like Andrus improved by simply hitting the ball harder and staying within his peak exit velocity range of launch angles (which fits Eno’s hypothesis), whereas Jake Lamb improved by hitting the ball harder, raising his average launch angle, and shifting his peak exit velocity range (which runs contrary to Eno’s hypothesis).  Perez and Bogaerts didn’t really improve, and their Statcast data yielded some strange results, which suggests that this method is far from foolproof, and that there may have been better choices of players to investigate.

Many thanks to Eno for the inspiration for this article, and to Baseball Savant for all of the Statcast data.