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.

Almost one year ago, I took my initial stab at sabermetrics writing about how the Twins’ fabled philosophy of “pitch to contact” was being stifled by the club’s own inability to field the ball. If you are putting that much faith in your defense, it would make sense that you would have the defensive ability to back up your philosophy. For a while, this was true for the Twins. I am not going to rehash what I already wrote in August of 2015, but if I haven’t summarized myself adequately enough yet, I’ll attempt to do so again: the Twins fostered a philosophy in pitch to contact that relied on their defense, yet from 2010-2015 their defense slowly deteriorated, as did their pitching and overall record. My thought was that if the Twins were able to improve on this sub-par defense, they would be able to bail out their pitching, rather than continue to hamper it. I relied a lot of the idea of fielding-independent pitching, so if you are unaware with that concept, read about it here.

Fast forward to 22 months later, and the Twins have some new captains running the ship. These guys value math, and have started to take a more analytical look at the Twins. The most noticeable difference so far in the Twins’ somewhat surprising season (although as of this posting the team has fallen back to earth somewhat) is their improved defense. To this date, the Twins have the fourth-best defense according to Defensive WAR. Last year, they were the second-worst defense. This idea has already been written about, showing that my prediction nearly two years ago was correct. The whole idea that, on average, a good defense can bail out pitching still holds, and I ran a regression to prove it. On average, a one-unit increase in your FIP-ERA difference increases your defensive rating by 49 points. This is quite the turnaround, showing how valuable a defense can be, and this number, in combination with batting and pitching WAR, can be quantified to show its overall impact on a club’s record. I’ll spare the calculation, but one can see how this improved defense has helped lead the Twins to their surprising start.

Unfortunately, the Twins’ pitching (besides two great starts from Ervin Santana and Jose Berrios) has been awful, so any defensive gains this season have been erased by having the second-worst ERA and FIP in baseball, despite the 13^th-best FIP-ERA metric. To this point in the season, the Twins have the same ERA as they did last year, but their FIP-ERA difference was a horrendous -0.52. They have a positive FIP-ERA difference this year at 0.12, showing that their pitching has actually gotten worse from last year to this current season. In some ways, their defense has kept the team above .500. Turns out my prediction was right: improve the defense, and the team will be noticeably better. If the Twins’ pitching would have stayed at the same point as last season, (4.57 FIP), in combination with their FIP-ERA metric, the Twins would be in the top-20 for pitching this season. Unfortunately, the regression of the pitching staff (independent of the defense) has kept the Twins from fully benefiting from their improved defense.

Before I wrap this up, a quick side-note on the Cubs this year. Last season, the Cubs had far and away the best defense in baseball, the best FIP-ERA in baseball, and the best ERA in baseball. This year, as any baseball fan would recognize, the Cubs have been struggling, especially with their pitching. Coincidentally, the Cubs’ pitching this year has dropped to 14^th by ERA, along with their defense, which is also ranked 14^th. Their FIP-ERA metric is at 13^th in baseball, so their regression in defense may be partly to blame for their pitching struggles.

To sum, from 2010-2015 the Twins’ defense deteriorated, leading their pitching staff to do the same based on their pitch-to-contact philosophy. I wrote a year ago that the Twins needed to improve their defense if they wanted to continue this philosophy. They improved their defense, which has fueled a surprising start for the club, and has kept the team from bottoming out with their horrendous pitching staff.

Appendix

Linear Regression and Plot

Editors Note: Analysis in this article was conducted using Baseball Info Solutions Hard Hit batted ball data.

To be clear, this did not begin as an example of investigative journalism. While I do occasionally enjoy media pieces such as Spotlight and S-Town, my curiosity in this topic all began with the incredible amount of attention given to a seemingly mediocre player named Nick Castellanos. To give some examples, below are three popular FanGraphs/RotoGraphs articles written about Castellanos:

• Nick Castellanos: The Greek God of Hard Contact (Rylan Edwards – March 30, 2017)
• Turning Nick Castellanos Into Nolan Arenado (Jim Melichar – March 4, 2017)
• The Wait for Nick Castellanos Will Soon Be Over (Eno Sarris – November 4, 2015)

In theory, the hype surrounding Nick Castellanos makes sense. High hard-hit rate, few ground balls, sustainable HR/FB%, and a decent home ballpark. If only he could get those strikeouts down and avoid bad luck, he could turn into Kris Bryant or Nolan Arenado. The analytics community, who have been waiting for the Castellanos breakout for five years, is more divided than ever on the Tigers third baseman. Some continue to beat the drum while others are abandoning ship, arguing that the breakthrough will never happen.

This season, Castellanos is not the only Detroit Tigers player who has received love from the analytics community:

• Alex Avila: The Tigers Have Found Another Slugger (Dave Cameron – May 22, 2017)
• Miguel Cabrera: How to Beat Statcast’s Hitting Metric (Craig Edwards – May 16, 2017)

The claims brought up by all of these writers have one thing in common: high or increased hard-hit rate. As presented in Matthew Ludwig’s article The Value of Hitting the Ball Hard, hard-hit rate and wRC+ have a positive correlation. In general, a player who hits the ball harder would be expected to have more favorable results when they make contact.

This brings us to the question, is it possible for so many Detroit Tigers players to be underperforming their batted-ball profiles? In order to gauge exactly how much harder the Tigers are hitting the ball than their opponents this year, I took a look at the hard-hit rate for the Tigers as a team. The point that is colored “Tiger orange” represents the Detroit Tigers.

It isn’t even close; the 2017 Detroit Tigers are currently the best team at making hard contact and the worst team at preventing hard contact. Thinking qualitatively, are the Tigers hitters really that much better at making hard contact than the hitters on the Astros, Nationals, or Diamondbacks? Are the pitchers really that much worse at preventing hard contact than the pitching on the Padres, Orioles, or Reds? If so, the results are not proving it. The Tigers currently rank ninth in runs scored and 20th in runs against. Park factors and other variables do apply, so it may be possible that the hitters are getting unluckier and the pitchers are getting luckier than the batted-ball data shows. Assuming that players’ abilities are transferable across stadiums, we should small differences in hard-hit rate for Tigers hitters and pitchers when looking at home/away splits.

Quadrant I (x,y) represents the teams that have a higher hard-hit rate for both hitters and pitchers on the road than at home. Quadrant III (-x,-y) represents the teams that have a higher hard-hit rate for both hitters and pitchers at home than on the road. The Detroit Tigers (orange point) rank as the team with the largest negative difference for both hitters and pitchers. One thing to note about the data is that 22 out of the 30 points lie within either quadrant I or quadrant III. This could give some validity to the assumption that hard-hit rate is not consistently measured from park to park. There could be a variety of reasons for this (humidity, air density, etc.). For more on this, I would point to Andrew Perpetua’s article Home And Road Exit Velocity. If there was truly something unique about Detroit causing these balls to be measured harder, this trend would be seen over a wider time period. Let’s look at where the Tigers ranked for the years 2012-2016.

See that orange circle almost directly in the middle of the chart? That is the Detroit Tigers. The only point that has a closer distance to the direct center is the Atlanta Braves, who now play in an entirely different city and stadium.

So what about all other stadiums? If hard-hit rate is being artificially increased at Comerica Park, it is likely that there are slight adjustments at all ballparks. Based on 2017 data, the difference for each stadium (hitters or pitchers) is listed below:

Looking at an individual-player level (min. 50 AB home and away, min. 20 IP home and away), let’s see how many Tigers batters appear on the top 20 away-home hard-hit-rate difference leaderboard for hitters and pitchers. Detroit Tigers players are highlighted in orange.

I can see four possible scenarios to explain why Detroit Tigers players may be experiencing this phenomenon:

1. Tigers hitters and pitchers have actually experienced large splits between home/away hard-hit rate this year (with no other variables changing)
2. Something about Comerica Park is causing increased error in the variables used for the quality of contact algorithm
3. Changes are being made to the ball or environment at Comerica Park, making it act differently
4. Small sample size bias is skewing the data

Unfortunately, this is about as far as I can take this piece. Something is going on in Detroit this year that is skewing the hard-hit-rate calculations. However, the whys and hows beyond the data are not clearly evident. Until then, I will continue to monitor this unintended project of investigative journalism from the sidelines.

The utility player has made low-profile appearances on rosters throughout baseball history, but only recently fans, media, and ownership have come to appreciate the full value of their versatility. After the Cubs had so much success with utility players Ben Zobrist and Javier Baez in their title run last year, many teams are choosing to develop young talent into utility players instead of having them specialize in one position. While there are many Hall of Famers who played multiple positions over the course of their careers, most of them switched positions not because they were equally good at multiple positions,  but because they were good hitters who became defensive liabilities at their previous position. My hope is that that will change within the next 20 to 25 years as some of baseball’s top talents are groomed for the new super-utility role.

Before we marvel at these young and exciting players of today and tomorrow, let us take a moment to reflect on the super-utility men of yesteryear.

Melvin Mora

Melvin Mora debuted as a Met in 1999 and immediately was used all over the field, playing six positions in 66 games that season. Over the course of his career, he had six seasons where he played at least three different positions in the field. In total, Mora appeared in 908 games at 3B, 194 at SS, 174 in LF, 158 in CF, 48 at 2B, 29 in RF, 27 at 1B. Only pitcher and catcher eluded him. He had a career combined +3.1 DWAR, never having a season below -.8 DWAR. In addition to being a huge asset in the field, Mora was a 105 OPS+ hitter over 6,158 career plate appearances.

Juan Uribe

While Juan Uribe’s six-foot, 245 lb physique may have looked out of place on a baseball field, he was a true gem of a fielder, accumulating +15 career DWAR across five different positions. Over the course of his entire career, he appeared in 917 games at SS, 644 at 3B, 228 at 2B, 4 at 1B, and 1 in CF. His value as a fielder is what kept him around for so long; even though he hit 20+ home runs on four separate occasions, he was a career 87 OPS+ hitter.

Placido Polanco

If you are a hardcore baseball fan, you may know that Polanco is one of two players to win a Gold Glove at multiple positions (two at 2B and one at 3B). However, I think very few people realize that he ranks first all-time in fielding percentage at BOTH of those positions! In addition, if he had only played 214 more innings at SS (equivalent to just under 24 games), he would have ranked 6th all-time in fielding percentage there as well! In addition to playing in 1,027 games at 2B, 751 at 3B, and 122 at SS, he appeared in 5 games in LF and 1 at 1B and finished his career with +18.1 DWAR, good for 65th all-time. In addition to being a superb fielder, Polanco was an accomplished contact hitter as well, batting over .300 five times and .297 for his career.

Gil McDougald

A central part of the 1950s New York Yankees, McDougald could be one of the most overlooked players of all time in terms of Hall of Fame consideration. He never received higher than 1.7% of the vote despite being a part of five World Series championship teams and averaging +4 WAR per season over his 10-year career. A large part of that value came from his play in the field, where he played in 599 games at 2B, 508 at 3B, and 284 at SS. Over the course of his career, he accumulated +14 DWAR, never having a DWAR under +.4 and having at least +1 DWAR in 8 of his 10 seasons. In addition to his elite defense, McDougald was a career 111  OPS+ hitter.

Craig Biggio

The first and only Hall of Famer on this list, Biggio almost didn’t make my cut because he only had two seasons where he appeared in at least seven games at more than one position. Despite not displaying much fielding diversity within seasons, though, Biggio accumulated 1,989 games at 2B, 428 games at C, 255 games in CF, 109 games in LF, and 2 games in RF over his career. At the time,  he was regarded as an above-average fielder, earning four Gold Gloves at 2B. His -3.9 DWAR is somewhat misleading because he played for so long after his defensive prime due to being a Hall of Fame hitter. Over his 20-year career, Biggio earned Silver Sluggers at both catcher and second base, and had a career OPS+ of 112.

Pete Rose

Like Biggio, Pete Rose didn’t display spectacular fielding diversity within seasons, but over the course of his career the Hit King appeared in at least 73 games at every position in the field except pitcher, catcher, and shortstop. To be exact, he appeared in 939 games at 1B, 673 in LF, 634 at 3B, 628 at 2B, 589 in RF, and 73 in CF. That’s a lot of games. While his hitting accomplishments are well documented, few people realize that Pete Rose actually won two Gold Gloves during his career as well. Whether he deserved them or not is another story (-14 career DWAR) though to his credit, he had a modest -0.1 DWAR during his first 12 seasons while playing 2B and OF. Despite not being the finest fielder of the bunch, and though he is not a Hall of Famer like Biggio, Pete Rose, aka Charlie Hustle, is the quintessential super-utility player, championing the gamer-ship that all utility players must have to earn the title “super.”

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.

As statistics have become more advanced and public, we’ve gained myriad ways to understand baseball more in depth. We don’t just know that Aaron Judge smacks the crap out of the ball; we know that he can hit it out of the park at more than 120 miles per hour. We don’t just know that Yu Darvish’s pitches can dive all over the zone, but that they have an average spin rate of more than 2500 revolutions per minute.

While those stats represent single facets of a player’s game, there’s one that incorporates everything they do to give a sense of their overall value: Wins Above Replacement, or WAR. Depending where you find your stats — there’s fWAR from FanGraphs or bWAR from Baseball Reference — there will be subtle differences in how it’s calculated. But the point is the same: to tell you who the best and worst players are compared to anyone who could replace them.

WAR is the type of stat that enables us to react in real time, and with relatively sound reason, to newly-signed contracts. It’s how we can say Kevin Kiermaier’s deal is probably a notable win for the Rays and why Ryan Howard’s last extension was premature at best.

The reality we shape as observers and fans often looks at these contracts under a microscope, and only under a microscope. When a guy strikes out looking to end a rally, or gives up the hit that sparks one, that’s when we notice. And, fair or not, those moments craft the narratives we often carry throughout the life of a player’s contract.

Zooming out is helpful, though. In certain context, there might not be such a thing as a bad contract.

Owners have been raking in the money for a long, long time. They’ve pretty much always taken home more than the players and in recent years that difference has only grown. When you consider that there are only ever as many owners as there are teams, and that the players’ share is split hundreds more times, the disparity becomes emphasized.

If we want additional perspective, we can look at how the percent of overall revenue accounted for by player salaries has decreased almost annually like clockwork.

Revenue data goes beyond that which fans and analysts use to justify a point of view on a player’s worth to their team. Those trains of thought spur additional conversation about how a given contract can influence the team’s composition and ability to compete for championships. And these points may well hold water. But they probably don’t provide much influence on the business perspective.

No matter how good or bad a contract is, a team is likely still profitable and operating within a relatively certain margin of error that isn’t dramatically different than if they didn’t have that deal on the books.

That’s not to say owners don’t care about a bad contract. It’s just that, at an operational level, they have to concern themselves with the bottom line first and foremost because it’s what allows them to persist. Sure, the big deals that go sour are disappointing to them, but they’re not damning.

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.

…the New York — not the mashing Yankees, but the Mets. Unfortunately I had a hardware crash so I currently can’t pull reports from Statcast and thus I now take ground-ball rate as a measure for elevation instead of launch angle. I prefer grounder rate over fly-ball rate because that tells you the “off the ground rate” (100 – gb%). Since liners are also very good I think they should be included.

The Mets have faced a lot of heat from sabermetric fans and sometimes for good reason, like their lowish OBP, neglecting defense and handling injuries.

But there is one thing they have done for a couple years now and that is elevate the ball.

In 2015 they had the third-lowest grounder rate in the majors at 41.9%, only trailing the Astros and Yankees. That means 58.1% of their balls were off the ground.

In 2016, after losing the poster boy of the fly-ball revolution, Daniel Murphy, they improved their grounder rate to a clearly league-leading 39.5% (almost 2 points on the second-place Rays). That improved their off-the-ground rate to over 60%.

In 2017, despite a lot of injuries, the Mets have even improved their GB rate to 38.2%, but they’ve been exceeded by the A’s.

Overall, the Mets clearly lead the Statcast era with a 40.3 GB%, almost 2 points ahead of the second-place Tigers.

The elevation also leads to power output, as they are 7th in ISO (only NL team ahead of them is the Rockies) and 6th in HR (top NL team, even ahead of the Rockies). Granted, they are only 21st in OBP, and negative in defense, so they are not without flaw, but there is no doubt they were built to elevate and mash, and that is by design.

Now did the Mets teach that or acquire elevation?

Looking at some long-time Mets:

Curtis Granderson

2013(Yankees): 33.8%, 2014: 34.2%, 2015: 30.8% , 2016: 36.4%, 2017: 31.3%

Granderson was a FB hitter when the Mets got him.

Daniel Murphy

We all know about him. 50% grounders in 2012 and improved that to 42% in 2013 and then more.

Lucas Duda

Always was a FB hitter with sub-40% grounder rates since the minors.

Yoenis Cespedes

Was a FB hitter when they got him (upper 30s grounder rate) but became a more extreme FB hitter in NY. This year he is running an insane sub-30% grounder rate.

Travis d’Arnaud

He started out in the mid-40s and then had some ups and downs with a very bad 50% rate last year, but this year he is down to 39%. We will have to wait to see whether that is sustainable.

Michael Conforto 

Sightly improved his grounder rate over his career from low-40s to now high-30s.

And then there is Jay Bruce who was acquired as a fly-ball hitter and became an extreme fly-ball hitter.

It seems like elevation was mostly acquired, but there are or were players who learned to lift more with the Mets. I assume it is at least encouraged by the Mets that hitters hit everything in the air.

The Mets have earned their share of criticism with some things they have done, but when it comes to the fly-ball revolution, it is they who deserve credit as the leaders of the fly-ball revolution, and probably moreso than the saber-darling teams like the Cubs or A’s, who are usually cited when talking about the fly-ball revolution. I’m not saying those teams did not target air balls, as the A’s have the 5th-lowest and the Cubs have the 7th-lowest grounder rates during the 2015 to 2017 to date time frame, but the leaders have clearly been the Mets.

There is value in the fly ball. That statement isn’t something that will surprise any fan. Even someone who knows very little about baseball could piece together the logic behind it. The most valuable individual outcome is a home run. How do you hit a home run? Hit a fly ball. As Travis Sawchik found for 2016, fly balls produced a wRC+ of 139, while ground balls put up a mark of 27 wRC+.

Of course, the sabermetrically inclined will quickly point out that it’s not that simple. Judging the value of a hit based on whether it is a fly ball or a ground ball is a futile exercise. You have to consider batted ball distance, launch angle, and exit velocity. Much has been made about the recent “fly ball revolution” occurring throughout the league. And while some believe hitting more fly balls really does increase the value of a player, data suggests that the fly ball revolution is hurting as many batters as it’s helped.

It’s possible that there are benefits to hitting more fly balls, but that doesn’t seem to correlate to an increased value.

There really is no correlation between fly ball % and wRC+. So, it seems that value is added not by hitting the ball higher, but by hitting the ball harder.

Now this is a pretty clear correlation. Hit the ball harder and a better outcome is more likely. A soft liner toward the second baseman will probably be an out. But, a laser to right-center field could be a triple.

This trend is not a new development or a new discovery. As far back as 2002, when batted-ball data became available, there has always been a positive correlation between Hard% and wRC+. In fact, the average correlation (R-squared value) between these two variables over the last 15 years is .475.

Hard% also has predictive value. Take a look at the data for 2017 thus far.

Although the correlation from past years isn’t there, it doesn’t need to be. We should no more expect the data to already have an R-squared value above .4 than we would expect an MVP to have a WAR higher than 6 at this point of the season. Because there are quite a few outliers that will come back to the mean, Hard%, based on its historical data, has considerable predictive value.

Ignoring the one point above the 200 wRC+ line (Mike Trout, whose entire career is an outlier), let’s examine a couple outliers. First, the point on the far right toward the bottom. Nick Castellanos is hitting the ball harder than Aaron Judge, who just set a Statcast record for hardest home run ever hit, but only has a wRC+ of 82 — well below average. Towards the top of the chart at the 175 wRC+ mark, we see that Zack Cozart is making hard contact only 32% of the time.

It is reasonable to expect, based on this chart, that Castellanos’s numbers will start to improve and Cozart’s will regress. As it turns out, Andrew Perpetua found the same outliers by looking at exit velocity and xOBA in a RotoGraphs article last week. These statistics all point toward the same thing — Castellanos has been very unlucky and Cozart has been just the opposite. The takeaway here is that Hard% can be used as a predictor for value even over a smaller sample size.

If Hard% is such a good indicator of success, what is the actual value of hitting the ball hard? Hitting the ball hard has been a hallmark of both HR leaders and batting champions. Over the last five years, the HR champion has an average Hard% of 40.12 and the batting champion has one of 35.16%. Although the almost five-point spread is a lot, a Hard% above 35% is nothing to laugh at — it’s still in the upper half of all players.

For the last full season (2016), increasing Hard% by even just 5% added 13 points to the wRC+ value. That is pretty significant. For context, 13 wRC+ is the difference between Aaron Judge and Yonder Alonso so far this year. But has it always been this way? Not exactly. In 2002, a 5% increase in Hard% increased a player’s wRC+ by 20 points. This points toward an interesting trend.

For the last 15 years, the correlation between Hard% and wRC+ has decreased. In other words, hitting the ball hard is not as valuable as it once was. My initial thought was that players aren’t hitting as many HRs as they did in 2002. But that is simply not true. 14.2% of flies result in HRs — the highest rate ever recorded. Perhaps this trend is a result of defenses shifting. Are batters hitting the ball harder than ever, but fielders are now better positioned? The shift is certainly a powerful tool — it kept Ryan Howard out of the Hall of Fame. Still, I’m not convinced the shift is solely responsible for this eerie trend.

Hitting a ball hard is much more important than hitting it high, that is, if you can’t have it both ways. However, the value of hitting the ball hard has decreased for more than a decade. Looking at the data, is it possible that in 10 years we’ll see a sort of “v” shape, indicating a return to the value of hitting the ball hard? Maybe. But for now, this is an interesting trend with no clear indicator.