Like many of you, I spend hours on FanGraphs trying to take in as much information as possible. One of the more fascinating statistics to me is the category of plate discipline. This includes how often a batter will swing on a pitch inside or outside of the zone, how often a batter swings and misses, and many other variables that affect a player’s approach at the plate. While these numbers alone are a good indication on how a player acts at bat, I wanted to know how these numbers affected performance. For instance, it would make sense that a higher O-Swing% could lead to less-than-average hitting. The 2015 season had Adam Jones second in O-Swing%, swinging at 47% of pitches outside of the strike zone. Pablo Sandoval led the league in O-Swing% with a 48% rate. Jones recorded a 109 wRC+ while the Kung Fu Panda had a 75 wRC+.

By breaking down these Plate Discipline statistics for the 2015 season, I believe that we can get a good answer on which statistic leads to the best performance. For my methodology, I used the wRC+ and Plate Discipline leaderboard for the 2015 season. After breaking down each statistic, I compiled a top 10 and bottom 10 wRC+. Additionally, I grouped percentages to get the number of batters and average wRC+ for certain percentages.

O-Swing %

O-Swing% = Swings at pitches outside the zone / pitches outside the zone

Top 10 wRC+ Average: 97

Bottom 10 wRC+ Average: 132

O-Swing% gives us a pretty good indication of a player’s overall performance. It’s no surprise that patience and a good eye are part of a skill set that leads to a higher wRC+. For each 10-percent decrease of O-Swing percentage, batters see an increase of over 10 points for their wRC+. The top 10 wRC+ compared to the bottom 10 also tells a compelling story of what O-Swing tells us. In the top 10, we see a couple of above-average hitters like Starling Marte and Nolan Arenado. However, we also see five of the top 10 with a wRC+ under 100 and one hitter (Marlon Byrd) at 100. On the other side of the spectrum, there isn’t a hitter under 100 wRC+ in the bottom 10. The difference in wRC+ between the top and bottom 10 is 35, the biggest difference between all the statistics.

Let’s look at two very different extremes: Joey Votto and Pablo Sandoval. Sandoval had an O-Swing% of 48 percent while Votto had a 19 percent rate, which means that while Sandoval is swinging at almost half of the balls he faces, Votto is taking a little more than 80% of pitches out of the zone. Sandoval faced 1848 pitches (1287 strikes to 561 balls) while Votto faced 3020 pitches (1644 strikes to 1376 balls). Sandoval’s more than double strike-to-ball ratio and Votto leading the league in walks can both be explained by their O-Swing percentage.

Z-Swing %

Z-Swing%  = Swings at pitches inside the zone / pitches inside the zone

Top 10 wRC+ Average: 111

Bottom 10 wRC+ Average: 115

The first thing that I noticed when looking at the Z-Swing charts is the duplication of names from the O-Swing charts. Adam Jones, Avisail Garcia, Marlon Byrd, and Starling Marte showed up on both the O and Z Swing percentage top-10 while Ben Zobrist, Carlos Santana, and Brett Gardner appeared on both bottom-10 lists. This is a very mixed bag of players for both the top and bottom. Both have a 100 wRC+ hitter, the epitome of average. Both have seven hitters batting above 100 wRC+ meaning that both lists also have two hitters batting below 100. The top and bottom 10 averages are almost even. The one outlier that separates them is Mike Trout in the bottom 10 with a 172 wRC+. Seeing the same name on multiple lists can tell us a lot about a player. Someone like Marlon Byrd will swing at most of the pitches you send his way while Ben Zobrist will take a pitch outside of the zone about 77% of the time but will also take a strike 45% of the time as well.

O-Contact %

O-Contact% = Number of pitches on which contact was made on pitches outside the zone / Swings on pitches outside the zone

Top 10 wRC+ Average: 104

Bottom 10 wRC+ Average: 104

Similar to Z-Swing%, O-Contact doesn’t show much disparity between the top and bottom 10. In fact, they’re identical at 104 wRC+. A higher O-Contact gives a batter more balls in play, but doesn’t always lead to success. My initial thought was that swinging at a pitch way out of the zone can lead to weak contact, and usually an out. The fact the top and bottom are identical shows that this isn’t always the case.  It also makes sense why the middle of the pack (60%-69%) has the greatest wRC+ (besides the small sample size of < 50%). These batters are still able to make contact with pitches outside of the zone more than half of the time, but also miss the pitch enough of the time where they don’t make bad contact.

Z-Contact %

Z-Contact%  = Number of pitches on which contact was made on pitches inside the zone / Swings on pitches inside the zone

Top 10 wRC+ Average: 110

Bottom 10 wRC+ Average: 125

Z-Contact was the most surprising statistic in terms on its effect on wRC+, until you look at the names in the bottom 10. One would expect that hitters that hit more pitches in the zone would be the better performers. However, the bottom 10 is filled with power hitters, leading to the main difference in wRC+. Davis and Cruz were number one and two in terms of home-run leaders in 2015. In fact, besides Michael Taylor, the bottom 10 is all in the top 50 for home runs in the MLB. The list makes sense as players like Chris Davis are trying to “Crush” the ball out of the park and swing harder than someone in the top 10 like Martin Prado.

SwStrike %

SwStr% = Swings and misses / Total pitches

Top 10 wRC+ Average: 110

Bottom 10 wRC+ Average: 105

Not surprisingly, the top 10 for SwStrike looks a combination of both the O-Contact and Z-Contact bottom 10. Obviously if your contact is low, you’re going to have more swings and misses. The main factor that stood out to me looking at the top and bottom 10 is the deviation of wRC+. The top 10 is all over the place, having players like Kris Bryant with a 136 wRC+, Michael Taylor with 69, and every level of player in between. The bottom 10 has less variation, providing a more consistent group of hitters.

Totals

As evidenced by the chart, the main statistic in regards to plate discipline to show a great change in performance that compares the bottom to the top level is O-Swing percentage. Z-Contact seems to also be relevant when evaluating and predicting a player’s performance.

The Rays always seem to be at the forefront of sabermetric innovation. They employ an army of Ivy League baseball analysts in the front office, they fully embrace the shift, and they employ pitch-framing superstars. The Rays like to stay on top of the ball. For the Rays, sabermetric advancement is a means of survival. And for the Rays, in the powerhouse AL East, it is the only way to survive.

Over the past seven years, it seems the Rays have been on to something. Looking at FanGraphs team offensive data from 2009 to 2016, there is a clear pattern with the Rays. They are third in fly ball% at 37.5%. The team with the highest FB% during that time span is the Oakland Athletics. The A’s pursuit of fly-ball-happy hitters was pretty well documented. In a great article over at Deadspin from 2013, Andrew Koo (who now works for the Tigers) shows us the advantages of hitting fly balls. First, Koo highlights how fly ball rates have decreased in the league since 2009. With an increasing trend towards ground ball pitchers, Billy Beane made a clear effort to acquire fly ball hitters. Why? Because as Koo shows us, fly ball hitters are significantly better against ground ball pitchers compared to other batters.  Tom Tango, who is mentioned in the Koo article,  found that this platoon advantage is very minimal, and is really only realized and meaningful when the “advantage is multiplied through several hitters. This is exactly what the A’s and Rays have done over the past seven years. Both teams have stockpiled fly ball hitters.

The Rays have done something else too. They have stockpiled fly ball hitters that also have a knack for pulling the ball. Over the past seven years, they lead the league in Pull% at 42.8%. Looking at this year’s team, the strategy seems to be in full effect once again. Of all the Rays hitters with at least 100 PA this year, only three players (Miller, Forsythe, and Dickerson) are below the league average in Pull%. Now, it could be pure coincidence that the Rays pull the ball so much. But I think we all know this is no coincidence at all. They seem to be preaching the pull-happy approach.

When looking at offensive data on pulled balls vs. data on other batted ball directions, the strategy makes sense. Looking at league data from 2009 to 2015, the average wRC+ on balls hit to the pull side is about 157, compared to 112 on balls hit up the middle. Isolated power on balls hit to the pull side is over 100 points greater than on balls hit up the middle or to the opposite field. There is an offensive advantage to pulling the ball, when the ball is put in play. Given the clear advantage to hitting the ball to the pull side, one might ask why wouldn’t every team stockpile dead pull hitters?

One answer: conventional wisdom says dead pull hitters don’t have the right approach. From the time I started playing baseball, I have been told to hit the ball to all fields. And I don’t disagree with this philosophy. Staying back and being able to drive the ball to all fields definitely makes for a very productive hitter. But it also results in dead pull hitters being undervalued.

Another knock on pull hitters is that when they hit ground balls, they roll over the ball and commit easy outs.  Looking at the soft hit percentage vs ground ball percentage on balls that are pulled for all 30 teams from 2009-2016, I found this to be a valid concern about pull hitters. The data shows a positive correlation between ground balls and soft hit percentage. 

The Rays, however, have the fourth-lowest GB% on pulled balls. During that same time span, the Rays have the sixth-lowest Soft% on ground balls. They aren’t hitting weak ground balls. The Rays have made a concerted effort to pull the ball and they have avoided the weak contact that comes with pulling the ball on the ground.

Conclusion

The Rays have found and pounced on a market inefficiency. They have optimized their offense by targeting and developing players that consistently pull the ball in the air and avoid weak contact on the ground. Since these players aren’t the conventional hit-to-all-fields type of player, they can get these players for cheap. Simply put, the Rays have have capitalized on the offensive advantage of pulling the ball.

Food For Thought

Something to think about further is the trend of Pull% in the MLB from 2002-2016. It is down 5%. Intuitively, this makes sense, as velocity is way up over that time span. With velocity up, it is harder to pull the ball. This trend reminded me of a trend mentioned earlier in the article. As noted by Koo and Tango, ground balls are up around the MLB. As Tango found, fly ball hitters have an advantage against ground ball pitchers, and it is beneficial to utilize that advantage. What if there is a similar platoon advantage regarding pull hitters vs. power pitchers? In line with Tango’s logic, what if dead pull hitters have a platoon advantage against power pitchers? What if the Rays have figured out this advantage and have been exploiting it for years? The platoon advantage makes sense. Dead pull hitters, by nature, go up to the plate looking to pull the ball. Which means they are early on almost everything. As a result, they wouldn’t have as much trouble catching up to gas. This is definitely something to think about, and something I will be certainly researching in the coming weeks.

There are good systems, there are poor systems, then there’s 50 pounds of effluence, and then there’s the Marlins. Add another 50 pounds, and you’ve finally reached the Angels.

– Baseball Prospectus, 2016

Disclaimer: The side effects of reading through the entire Angels Top 30 may include drowsiness and an upset stomach.

– Baseball America Prospect Handbook, 2016

I’ve been doing these rankings for eight years now, and this is by far the worst system I’ve ever seen.

– Keith Law, 2016

The practice of farming is prohibited. All right or claim of a major league club to a player shall cease when such player becomes a member of a minor league club, and no arrangement between clubs for the loan or return of a player shall be binding between the parties to it or recognized by other clubs.

– National Agreement, Article VI, Section 4 (1903)

Sometimes the most important things are the things that aren’t there. Those words from the 1903 National Agreement, the peace treaty ending the brief but intense war between the National and American Leagues, were omitted from the revised agreement in 1921. And into that omission rushed Branch Rickey, who did not invent the practice of “farming” minor league players, but who perfected it with a ruthless efficiency that real farmers would only achieve much later with he generous application of pesticides. Rickey purchased not players, but teams, and in some cases entire leagues.

The 1903 farming ban codified, albeit temporarily, the American League’s declaration of independence from the National League, first issued in 1901. The farming ban was Ban Johnson’s announcement to the world that no one was going to treat his league’s players as farmhands. The ban also helped secure the loyalty of the Players’ Protective Association, an incipient union opposed to the practice (see pdf p.2), and was one factor encouraging star players to jump to the new league.

Major league owners routinely eluded the farming ban, however, and by 1920, baseball’s next crisis year, the ban was on the ropes. Wracked by gambling scandals, poor wartime attendance, and the ghastly death of Ray Chapman, organized baseball forged a new National Agreement in 1921. The new agreement omitted the farming ban, perhaps because the AL, having by that time firmly achieved major league status, lost interest in the cause of player liberty. Although Commissioner Landis despised the concept of farm systems, he was largely unable to prevent their development.

Landis failed because the economic logic of farm systems is unassailable: By owning most (though certainly not all) aspects of the production process, major league teams could greatly reduce the transaction costs inherent in developing major league-caliber players. Farm systems also limit the competition among teams for minor league player’s services. After the draft, the player is essentially under team ownership for several years, unable to work for any other team without the owning franchise’s consent.

Every major league team eventually developed a farm system, though (as Bill James has noted) laggards like the Cubs and Pirates paid a heavy price, suffering through years of mediocrity beginning in the 1940s. It is now impossible to imagine a major league team without a farm system. Or at least it was until this year. The Los Angeles Angels of Anaheim today stand on the threshold of an alternate future, a future in which Judge Landis won. Alone among MLB franchises, the Angels today entirely fail to benefit from the major league owners’ long twilight struggle to reduce minor league players to peonage.

I want players. Lots and lots of players.

– Billy Eppler, 2016

The Angels’ recently minted general manager, Billy Eppler, will lead the team through the next phase of its dystopian journey. To be fair, it’s not exactly true that the Angels have no farm system at all — they have minor league affiliates in thrall to the major league club, just like other major league clubs do. And those affiliates may even win a few games (so far, just a few). But the system is bereft of impact talent at any level. A handful of these guys will turn out much better than now perceived, but the vast majority won’t. The next pennant winning Angels lineup and rotation is invisible without experimental pharmacological assistance.

One way to get “lots and lots of players,” or at least a relatively large haul of good players, would be to trade Mike Trout. The idea has been debated on these pages and elsewhere, and I don’t propose to rehash the details here. One thing Eppler might want to consider, however, if he contemplates such a drastic move is that nothing of the kind has ever happened in baseball history. Nothing even close.

Trout had a 9.4 bWAR last year; no player with that high a WAR has ever been traded in the following season. Connie Mack infamously sold Eddie Collins and his 9.1 bWAR to the White Sox after the 1914 season. The woeful Boston Braves traded Rogers Hornsby (8.8 bWAR) to the Cubs after the 1928 season for a clown car of substandard players and $200,000 in a classic salary dump.

Mike Piazza was traded twice in one year after his 8.7 bWAR in 1997. First, the Dodgers shipped him to the Marlins in exchange for a pile of good but expensive players; in this odd case the salary-dumping team received a superstar, although it also unloaded a superstar in Gary Sheffield. The Marlins then Marlined it up real good just one week after Piazza put on the teal, sending him to the Mets for Geoff Goetz, Preston Wilson, and Ed Yarnall. Centuries from now the Marlins will be viewed as we view the giant Moai of Easter Island: with a mixture of awe at the achievement and amazement that the people responsible failed to put their limited resources to better use.

And that’s about it for the top 200 player-seasons. So Eppler would be piloting the S.S. Anaheim into uncharted seas if he traded Trout; there is no comparable trade out there by which one could even vaguely assess his value.  That doesn’t mean Eppler shouldn’t try, but he shouldn’t try too hard. Trout is still just 24, and it is conceivable that the next pennant winning Angels lineup could still have him in it. No other GM in baseball history has seen fit to trade a player of Trout’s caliber; Eppler should be wary of being the first.

There is another way, pioneered by a team just a few hours north on the 5. In 2002 the San Francisco Baseball Giants made it to the World Series with a team that GM Brian Sabean had built around Barry Bonds. Bonds, for you youngsters out there, was the Oughties’ Mike Trout, though I suspect that both men would bristle at the comparison. Drug-fueled or not, Bonds dominated the game like few ever have, yet Sabean labored mightily to get Bonds into the World Series. Ultimately, Sabean achieved this not by tending crops in the blazing fields from dawn to dusk, interrupted only by a cholesterol-laced dinner at noon. Your 2002 Giants had exactly one (1) player with a bWAR over 1.o who had come up through the Giants farm system. That was Russ Ortiz, a pitcher many may remember as a failure because the red crystal in his palm began glowing right after his age 30 season, but up to that point he was a reliable innings eater with roughly a league average ERA.

So here’s the point:

Giants total 2002 bWAR: 50.6

Giants 2002 bWAR from home-grown players:  5.3

Yeesh. Tony Torcato. Damon Minor. Trey Lunsford. Yep, they’re in the 5.3, and they’ll be gleefully wielding flaming pitchforks in Scouting Hell. The news wasn’t all awful — Joe Nathan is in that 5.3, as is the aforementioned Ortiz. But it’s safe to say that the 2002 Giants are a team that Judge Landis might have liked. Well, you know, except the PED part.

So how did Sabean do it? If you haven’t guessed the answer, you probably should consider taking some of those self-paced training courses you’ve been blowing off. He signed him a passel o’ free agents (including Bonds himself, of course, as well as Reggie Sanders (3.5 bWAR in 2002) and Benito Santiago (2.6)). And he traded. Oh, did he trade. Jeff Kent was the most critical acquisition, amassing a 7.0 bWAR in 2002, which, as the alert reader will quickly grasp, exceeded the entire Giants farm produce by a wide margin. Here are the other significant guys Sabean dealt for:

David Bell (3.2)

Kirk Rueter (3.0)

Robb Nen (2.5)

Jason Schmidt (2.3)

Tsuyoshi Shinjo (1.9)

Kenny Lofton (1.7)

Tim Worrell (1.5)

That’s 15.9 bWAR for those of you keeping score at home, and adding in Kent brings the total to 22.9, or just under half of the Giants’ 2002 total. The best players traded away for those guys, by far, were Matt Williams (cumulative 12.5 bWAR after being traded for Kent) and Bill Mueller (11.8 cumulative bWAR after being traded for Worrell). Given that Williams brought Jeff Kent, the only clear mistake in hindsight was Mueller, an outstanding but aging and fragile player who put together some memorable late career seasons after being traded for Tim Worrell.  That trade may not have worked as Sabean would have hoped, but it was defensible at the time.

So the Chapter 7 condition of the Angels’ farm system doesn’t necessarily prevent Eppler from remaking his roster. But it does severely constrain his efforts; the players Sabean traded away for the most part didn’t pan out, but he was able to convince other baseball executives that they would, executives who get paid good coin to see through exactly this kind of B.S. (those are Sabean’s initials — it’s probably a coincidence). Eppler doesn’t even have enough talent on the farm to fake it.

But the current Angels major league roster has some useful bits in addition to Trout. Kole Calhoun, Andrelton Simmons, and Garret Richards (albeit currently with a UCL subject to manufacturer recall) aren’t exactly a “core,” but they’re not a bad franchise starter kit. Nick Tropeano and Andrew Heaney (albeit currently with a UCL subject to manufacturer recall) offer some hope that young Angels fans might see a quality start before they have their first legal beer. And Josh Hamilton’s $26 million of dead weight exits the ledger after this year. The Angels will be paying Albert Pujols until humans colonize the Alpha Centauri system, but other than that, their contracts aren’t awful.

So one plan might include trading some (though certainly not all) of the above-named players, especially Calhoun, who is developing into an advanced hitter at a somewhat advanced age. It will also include signing free agents in bunches, more than Sabean did. Harder to do now than in the past, given that teams seem to be locking up their top-tier young players with greater frequency, but this is why scouts get paid (or should get paid) the big dollars. Some franchise (do I smell fish?) will undervalue its own talent, and Eppler must be there to pick up the pieces.

Or he can trade Trout.

I’m glad I’m not Billy Eppler.

It seems that 2016 will be the year that Statcast begins to permeate Fantasy Baseball analysis. Recently there has been a wealth of articles exploring the possibilities of using these kinds of data. These pieces have provided relevant insights on how to improve our understanding of well-hit balls and launch angles. Also, they’ve facilitated access to information on exit velocity leaders and surgers, as well as provided thoughtful analyses to the possible workings behind some early-season breakouts.

However, there is still a lot we don’t know about Statcast data. For instance, we are uncertain of how consistent these skills are over time, both across seasons or within seasons. Also we don’t know what constitutes a relevant sample size or when rates are likely to stabilize. All in all, this makes using 2016 Statcast data to predict rest of season performance a potentially brash and faulty proposition. Having said that, we can’t help but to try; so here’s our attempt at using early-season 2016 Statcast data to partially predict future performance.

One of the early gospels of Statcast data analysis posits that the “sweet spot” for hitting homers comes from a combination of a launch angle in the range of 25 – 30 degrees and a 95+ MPH exit velocity. If this is indeed the ideal combination for hitting home runs, one could argue that players that have a higher share of fly balls that meet these criteria should perform better in other more traditional metrics such as HR/FB%.

Following this line of thought we dug up all the batted balls under the “sweet spot” criteria, and divided them by all balls hit at a launch angle of 25 degrees or higher (which MLB determines as fly balls) to come up with a Sweet Spot%. In an attempt to identify potential HR/FB% surgers, we compare Sweet Spot% and HR/FB% z-scores (to normalize each rate) for all qualified hitters with at least 25 fly balls and highlight the biggest gaps.  Here are the Top five gaps considering the games up to May 28^th:

Calhoun seems like a good candidate for a power uptick. He has the third-highest Sweet Spot% of 2016, and he has sustained similar Hard% and FB% to the previous two seasons. Yet somehow he has managed to cut his HR/FB% to less than half of what he put together in either 2014 or 2015.  More so, he has had some bad luck with balls hit in the “sweet spot”; his batting average in these kinds of balls is .500, whereas the league average is around .680. He is not killing fly balls in general, with an average exit velocity of 84.6 MPH, but if he keeps consistently hitting balls in the “sweet spot” range he should improve in the power department. Look out for a potential turnaround in the coming weeks and a return to 2015 HR/FB% levels.

Piscotty holds second place in the Sweet Spot% rankings. However, his FB% is very similar to what he did in 2015 whilst his Hard% is down from 38.5% to 32.5%. Lastly, he plays half of his games in Busch Stadium, which has a history of suppressing home runs. I would be cautious of expecting a major home-run surge, but in any case Piscotty is likely to at least sustain his performance in the power department, which would be welcome news to owners that got him at bargain prices.

Carpenter is another dweller of Busch Stadium, however his outlook might be a bit different. He is the absolute leader in Sweet Spot%. He is posting the highest Hard% and FB% marks of his career. Carpenter is also crushing his fly balls in general, with an average Exit Velocity of 93.7 MPH. Just as a point of reference Miguel Cabrera, Josh Donaldson and Giancarlo Stanton fail to reach an average of 93 MPH on their own fly balls. Lastly, he has had some tough luck with balls hit in the “sweet spot”, posting a batting average of just .420. Carpenter is already putting up the highest HR/FB% of his career, and he is a 30-year-old veteran of slap-hitting fame, but the power looks legit and perhaps there is more to come.

Denard Span and Yonder Alonso show up in this list not because of their Sweet Spot% prowess but rather due to their putrid HR/FB%. They barely crack the Top 50 in Sweet Spot%. They play half their games in two of the bottom three parks for HR Park Factor. Span is putting up his lowest FB% and Hard% rates since 2013, when he ended up with a HR/FB% of 3.4%. Meanwhile, Yonder’s rates most closely resemble those of 2012, when he had a HR/FB of 6.2%. Whilst their batting average of “sweet spot” batted balls is just .500, there is nothing to look here. In any case, their power situation looks to improve from bad to mediocre.

If you are interested in the perusing the Top 50 gaps between HR/FB% and Sweet Spot%, please find them below:

Note: This analysis is also featured in our emerging blog www.theimperfectgame.com

One would do well to recall that the last feature article written about Erick Aybar appeared in NotGraphs (#KeepNotGraphs), where he was pictured as the inept, rebel fleet commander Admiral Ackbar from the good section of Star Wars. Before, that there were articles that described him as, “Erick Aybar: Not as Bad as You Might Think,” and “Erick Aybar, Perennial Sleeper,” and “Erick Aybar: 2012 Sleeper.” Since then, Aybar hasn’t had an actual FanGraphs piece done on him. It looks as though people are still sleeping on him (but for good reason this time).

One of the most interesting parts of the novel 1984 is the concept of “Newspeak,” where the government twists and eliminates the meaning of certain words to serve its own purposes. In the novel, Winston, the protagonist, is educated by one his colleagues at the Ministry of Truth, Syme. He tells Winston, “A word contains its opposite in itself. Take ‘good,’ for instance. If you have a word like ‘good,’ what need is there for a word like ‘bad’? ‘Ungood’ will do just as well – better, because it’s an exact opposite, which the other is not.” In today’s society, particularly in the world of baseball, there is a great need for descriptors such as “ungood” so that people don’t feel bad.

There are numerous expletive-laden phrases that would aptly describe Erick Aybar’s season up to this point, but perhaps it’s best to just say he’s doubleungood. That’s the clearest way of saying that Aybar has been incredibly awful this season. This isn’t just about offense or just about defense. He has been mind-numbingly, historically bad offensively and pretty subpar defensively.

It’s lucky for Aybar that the Braves aren’t exactly their c. 1998 selves because he can hide relatively easily on this roster. The Braves have three of the league’s ten worst players by wRC+ (min. 100 plate appearances), so it’s not like he’s exceptional. Moreover, it doesn’t look like the Braves are terribly interested in winning, anyway, so at least he isn’t holding back a team with championship aspirations (you’re being glared at, Russell Martin).

This season, through 43 games (many of them started) and 161 plate appearances, he has amassed an unimpressive -1.7 WAR, worst in the league. Also absolute worst in the league is his wRC+, which is 11! That’s insane. It’s 89% worse than average! Even 90-year-old A.J. Pierzynski has a 39 wRC+. Consider this: Erick Aybar is running a .184/.222/.211 line. How can a major-league baseball player be this bad?

Well, it’s not terribly helpful to have a .223 BABIP, a number 78 points off of his career average (and basically league average) .301 BABIP. Just for fun, let’s say he has a .301 BABIP this season. That would add approximately nine hits to his total of 27 thus far, giving him a much more respectable .245 batting average. Now let’s say he maintains his ratio of hits to extra-base hits and see what that does to his slugging percentage (he ends up with one more double). This gets him to a much better .245/.279/.279 line. But that’s still probably not good enough to be a major-league player.

As you can probably guess, Aybar’s plate discipline and power numbers suck quite a bit. His four doubles and 23 singles have given him a .027 ISO, which is the worst in the league by 16 points. He has a K-BB% of 14.3%, a number that’s meritorious as a pitcher (hint: Aybar isn’t a pitcher). His O-Swing% increased by five percentage points this year and his contact rate on pitches outside the strike zone decreased by five percentage points, leading to more strikeouts and worse contact when he actually hits it. At least he’s only a slightly below-average baserunner.

Unfortunately, his defensive numbers have been subpar this year also, but at least he’s not the worst player in the league in this category. Instead, he’s eighth-worst, with a raw UZR of -4.9 and a UZR/150 of -22.9. He isn’t committing too many errors, but his range is a definite factor. Aybar hasn’t completed a single play in the remote to unlikely range per Inside Edge. He’s also seen a marked drop in even chance fielding opportunities (down 6.7%) and likely opportunities (down 3%).

There aren’t a whole lot of good reasons for this. He isn’t injured (although he did have to get a chicken bone removed from his throat) and he doesn’t look injured. I can’t find a way to press the videos onto the article, but his swing looks a lot different from last year, at least from the right-hand side of the plate. I’m not a swing expert, but it looks like he isn’t using his hips to turn on the ball like he has in years past, which would explain the lack of power. Additionally, Aybar looks off-balance this year as compared to last year, when he was much better. Another thing to consider is that it seems like his swing has less lift than before, resulting in more ground balls and less power. On the other hand, maybe Aybar is just getting old. He’s 33 and hasn’t missed a lot of time in his career.

On the other hand, he actually was a very good player for a long time, a sleeper even. From 2008 through 2014, he was worth 20.1 WAR, combining passable offense for a middle infielder with good baserunning and decent defense. In fact, he was 57th* in WAR during that time period, better than more highly esteemed names like Carlos Beltran, Nelson Cruz, and David Ortiz. He was a very good player for a very long time, making more money than most people ever dream of. And that’s cause for positivity.

It stands to reason that Aybar will regress back to the mean. No one can sustain those numbers for a full season, if only because they would definitely get benched. There’s a reason why sample size and past performance matters and Mr. Aybar embodies it. If we expected him to keep playing at this level with the same amount of playing time, then he’d end up with the worst season in baseball history with a little over -6 WAR (not that six fewer wins would make that big of a difference to the Braves). But that isn’t going to happen. He’s projected to finish around zero, which would make him an average player the rest of the way. Based on his past performance, I fully expect that to happen and I want it to happen. It’s terribly sad when one of the game’s great, unknown players spirals into oblivion. Nonetheless, what he’s doing right now is insane and not for the right reasons.  Just as Admiral Ackbar managed to right the rebel fleet, Aybar can do the same with his performance.

*Fun fact: Mike Trout is 19th on that list. Remember, WAR totals from 2008 through 2014.

All statistics current through 5/26/2016

This is the final part of a six-article series on xHR%, a metric devised rather unoriginally by myself. If you feel so inclined, you can look at the other parts here: P.1, P.2, P.3, P.4, P.5.

It’s always nice when things mostly work out. More often than not, when someone devotes countless hours to some pet project, whether it’s a scrapbook of some variety or an amateur statistical endeavor, it doesn’t work out terribly well. From there, one often ends up spending nearly as many hours fixing the project as they did on putting it together in the first place. The experience is incredibly frustrating, and it’s something we’ve all gone through at one time or another.

Luckily, my “quest” went much better than that of Juan Ponce de León.  While I didn’t find the fountain of youth, I did find a formula that works moderately well, even though I can only back it up with one year of data at this point. The only thing Señor Ponce de León has to brag about is being arguably the second most important explorer in colonial history. Somehow those things don’t compare particularly well.

Nonetheless, things do look quite good for xHR% v2. I culled data from a variety of sources, but mainly from FanGraphs and ESPN’s selectively responsive HitTracker. I used FanGraphs for FB%, HR, AB, and strikeout numbers (in order to find BIP, I subtracted strikeouts from at-bats). On the other hand, HitTracker was used just for home run distance numbers and launch angle data. I studied all players with at least 1200 plate appearances between 2012 and 2014 in order to ensure some level of stability for the first sample taken.

And so, without further ado, take a few seconds to look at some relatively interesting graphs (I forgot to title the first one, but it’s xHR vs HR).

Here, it’s fairly easy to discern that there’s a strong relationship between expected home runs and home runs. It doesn’t take John Nash to figure that out. What is fairly interesting, however, is that the average residual is quite high (close to 2.5), indicating that the average player in the sample hit approximately +/-2.5 home runs than he should have. That difference comes from a number of factors which the formula attempts to account for. They include home ballpark, prior performance vs. current performance, and weather. One of the issues, and this was bound to be a problem because of the sample size, is that there aren’t enough data points for players who hit 40+ home runs, so it’s hard to say how accurate the formula actually is as a player approaches that skill level.

This is a slightly zoomed-in version of expected home run percentage vs home run percentage. Clearly, there’s a much stronger relationship between HR% and xHR%, due in large part to the size of the digits and because the formula was written to come out with a percentage, not a solid number. But I won’t waste too much time on xHR% because, quite frankly, it’s far less interesting and understandable than actual home run numbers.

For the interested and worldly reader, here are the equations for each:

xHR: y=.0019x²+.9502x+.1437

xHR%: y=1.0911x²+.9249x+.0007

If either of these equations gets used at all, I expect it will be xHR because home run numbers are far more accessible than home run percentage numbers. Frankly, I regret writing the formula for xHR% for that very reason. This is supposed to be a layman’s formula, so its end result should be something understandable to the average baseball fan. It should be self-evident and easy to comprehend.

Thank you for following along as the formula developed over time. Obviously, it isn’t done yet and it requires some changes, but it’s close enough to where it needs to be. It’s very similar to getting to the door of the room where the Holy Grail is, shrugging, and turning around with the intention of coming back in a few weeks (although in this case it must be noted that the Holy Grail isn’t the real one, but a plastic one covered in lead paint). Expect a return under a different name and a better data set.

You’ll notice that I didn’t include very much statistical analysis at all. I figured that was rather boring to write about, but you can feel free to contact me for the information if you would like a nice nap.

Last year, I suggested that Wilson Ramos might want to try hitting the ball in the air more.

It turns out, there is a Washington National who appears to have made an effort to put the ball in the air more, but that is not Wilson Ramos. It is their soon-to-be-erstwhile shortstop, Danny Espinosa.

Last year, Espinosa rode a hot start to a .240/.311/.409 line at the end of the season, good enough for a 94 wRC+. It was his first offensive season since 2012 that you would accept from a starting middle infielder, and you’d be excused for seeing it as a sign that he might be back to his 3-win form of 2011 and 2012.

This year, however, Espinosa is scuffling to a .201/.307/.288 line that has been inflated by five intentional walks. Overall his wRC+ is down to 58.

One might look at his 23% strikeout rate and note that, while poor, it is still better than his 27.5% career mark or 25.8% 2015 rate. (His plate discipline numbers are indeed better this year than last.) One might notice a .250 BABIP compared to his .296 career number and expect improvement there. Also noticeable is a 7.0% HR/FB rate when his career mark is 12.9%. So perhaps we could expect something more like his 86 career wRC+ going forward? Or at least his Steamer projection of 79? (That is, if Trea Turner weren’t highly likely to be called up shortly.)

Possibly, but there is something else about Espinosa’s numbers that create pause: he has become a fly ball hitter. Entering this season, Espinosa had never posted a full-season GB/FB ratio lower than 1.12, but this year he has hit 37 grounders and 43 flies for a 0.86 rate.

If you hit a lot of fly balls, your BABIP is going to suffer. If those flies don’t turn into home runs, it’s a double whammy, and Espinosa is certainly getting whammed pretty good by that combination.

This is the danger of fly balls. And they could become even more dangerous if you try to hit them.

I can’t read any player’s mind, so perhaps Espinosa just happens to be hitting the ball in the air more. But ground ball and fly ball rates stabilize pretty quickly, and how you hit the ball is one of the more controllable aspects of hitting (it’s where the ball goes that’s the rub).

Espinosa has had above-average power, so why not try to convert that into extra home runs by hitting more flies?

Another way to look at hitting grounders vs. hitting flies is the target launch angle. So another way to interpret “hit more fly balls” is “hit the ball at a higher angle.” Espinosa is hitting the ball at too high an angle, and it follows that if you intend to hit more fly balls, they may well on average end up launching at a higher angle than in the past.

Monday night was the clearest example yet of this problem: Espinosa hit fly balls at 56, 59, and 61 degrees in his three plate appearances, and all three were easy outs to left field. As for the exit velocity, his contact in the air spent much of this season around 95-96 mph, which is good, but that hasn’t done any good without the right launch angle, and now he’s also down to 94.5 mph on the season when he hits the ball in the air, with Monday’s 86, 89, and 92 velocities contributing to that decline.

This turned into an analysis of why Espinosa has been struggling even more than the most pessimistic might have imagined. Perhaps there is a general lesson as well, however, beyond the well-established fact that fly balls without home runs are nigh useless.

Some players might want to pick one approach and stick with it to improve as much as possible. This is especially true if that hitter isn’t a great one, because they might not get the results they are hoping for by changing things up. Although you could argue the potential rewards for a below-average hitter are worth the risk and it just hasn’t worked out for Espinosa, one might counter that the likelihood of the change working for a less-talented hitter is quite low. (And the risk in this particular case was even higher with the hot prospect on his tail, limiting the time he had available to work things out.)

Take Ramos, a better hitter than Espinosa over the course of their careers, but not a spectacular one either. He hasn’t changed a thing in ground/fly ball terms: his 2016 GB/FB ratio is basically identical to his 2015 ratio, but his BABIP has gone from .256 to .370 and he is hitting .333/.385/.512. That won’t continue, but his ROS projected wRC+ has improved to the 90’s, when his actual wRC+ in 2015 was just 63.

Consistency in approach can produce better results with time. If you want to change things up, beware the risks. You may end up with the worst of both worlds.

You could also end up succeeding, as Leonys Martin has.

Since dominating the Dominican Summer League as a 17-year-old shortstop, Xander Bogaerts has been considered one of the elite young talents in the game, heralded for his on-base ability, and specifically his power.  After being promoted to start the 2011 season in Greenville, the Aruban native continued to rake, proving his skills at every rung of the organizational ladder.  At each full-season minor league level, Bogaerts never ran a wOBA below .366, and his lowest ISO was a very respectable .169.  It seemed as if he were destined to inherit the throne left vacant in Boston since Nomar Garciaparra departed in 2004; fans drooled over his future as the Red Sox’s franchise cornerstone, anchoring the heart of the Boston lineup while playing a premium defensive position.

On August 19, 2013, with Stephen Drew mired in a slump and the Sox struggling, Bogaerts was promoted from Pawtucket and joined the team in San Francisco, thus beginning his tenure in Boston.  Bogaerts appeared in 18 games down the stretch, hitting only 1 home run and watching his K% balloon to 26%.  However, his struggles were mostly ignored as the team wrapped up the division, and all concerns were quieted by the maturity he demonstrated after being inserted into the Sox’ starting lineup on baseball’s biggest stage, as evidenced by his .386 wOBA during the postseason run culminating with a title.  At the tender age of 20, Xander Bogaerts was a World Series champion, appearing poised for a Rookie of the Year campaign in 2014.

Unfortunately, Bogaerts failed to meet expectations in 2014, posting his worst season as a professional by far.  After a hot start, he collapsed in the second half.  He continued to strike out in nearly 25% of his plate appearances, his 6.6 BB% was a career worst at the time, and he finished with a disappointing 82 wRC+.  Bogaerts’s struggles were driven by his inability to hit right-handed pitching, as he posted a measly .105 ISO against righties coupled with a 71 wRC+.  The following image should help to explain the decline:

After getting ahead in the count, righties attacked Bogaerts down and away, leading him to chase breaking balls and expand the strike zone.  In fact, on a per-pitch basis, the rookie shortstop was the fifth-worst hitter in baseball against the slider.  With his confidence shattered after a poor performance at the plate along with Boston’s decision to sign Stephen Drew midseason, outsiders questioned whether Bogaerts could recover from his prolonged slump, while some predicted that he would be the next big prospect to bust.

After admitting that 2014 was probably the “toughest season [he] ever had,” Bogaerts entered 2015 once again as Boston’s starting shortstop, hoping to recapture the stroke that propelled him to the big leagues so rapidly.  Although he collected a Silver Slugger and seemingly accomplished his goal, Bogaerts exhibited a vastly different approach, one in stark contrast with his minor-league track record.  While he retained his high on-base ability, rather than selectively punishing mistakes, Bogaerts became a more restless slap hitter, sacrificing power in exchange for contact.  He boosted his Swing% by almost four points, offering at nearly half of the pitches he seen, but his ISO fell to a career worst .101.  This change can be attributed to his increased willingness to use the entire field; Bogaerts boosted his Oppo% by 13 points but showed nearly no power when going to right field as evidenced by a Hard% of only 14.5.  He also become an above average hitter on a per-pitch basis when challenged with sliders, improving upon perhaps what was his biggest weakness.

This more aggressive approach resulted in a significant drop in Bogaerts’s K%, coupled with a smaller decline in his BB%.  He finished the year with a much-improved 109 wRC+, certainly playable when coupled with league-average defense at shortstop, yet he left much to be desired in the minds of talent evaluators around baseball.  Rather than demonstrating the power he had exhibited throughout his minor-league career, Bogaerts instead resembled a weak middle infielder.  Once destined for stardom, Bogaerts had been relegated to an average shortstop, definitely a valuable piece on a contending team, but not the player many had projected him to be.

Now over 40 games into the regular season, despite capturing success in 2015, rather than settling, it appears that Bogaerts has once again evolved.  A quick glance at his numbers may suggest his improved offensive performance can be chalked up to luck, as evidenced by his high BABIP, but a deeper look at his underlying peripherals indicates that Bogaerts may have once again altered his approach at the plate.  First, he is proving that the decrease in K% is legitimate; Bogaerts is once again running a strikeout rate below 16%, nearly five points better than league average.  This year, it also appears that he has developed better command of the strike zone, as the has cut down his swing rate while boosting his BB%, both to nearly league-average levels.  More important than these, however, may be the reemergence of Bogaerts’s power.  Through 40 games, Bogaerts is running an ISO of .157, a level that he never once reached during his miserable 2015 season.

Unlike other unsustainable power surges, it seems as if Bogaerts’s may be viable.  His HR/FB has risen by nearly six percentage points, yet it still falls below the league average.  Statcast also seems to confirm our findings, as Bogaerts’s average exit velocity has risen by three miles per hour since the end of last season, although this data is still relatively new and cannot be considered a perfectly reliable indicator of future performance.  The majority of Bogaerts’s damage this season has come to the pull side, as his wRC+ has jumped by almost 100 points, and it seems as if he is making a concentrated effort to elevate more of the balls that he hits to left, as his FB% to the pull side has increased by nearly four points.  His bloated wRC+ will almost certainly fall, as a 44.4% HR/FB ratio to left field is absolutely ridiculous, but Bogaerts’s new offensive approach suits him well.

As seen in the table, Bogaerts is also demonstrating more power going the other way, and although his solid contact has still not resulted in any home runs to right field, the singles of 2015 have transformed into doubles this season.  Although he still sees the same number of percentage of pitches in the strike zone, it seems as if pitchers are approaching Bogaerts with more trepidation because of his newfound power, as he is seeing fewer fastballs this season than at any point during his major-league career.

The projections are a bit skeptical, as they forecast a fall in both BABIP and ISO, but if Bogaerts is able to maintain his current level of production, or really anything near it, 2016 will be his most successful season in the major leagues, by far.  He has undergone a major transformation at the plate, yet he has essentially reverted to the hitter he was as a prospect shooting through the minor leagues.  The strikeout-prone 2014 Xander Bogaerts gave way to the slap-hitter 2015 version, which then evolved into the more selective and powerful current manifestation of the young shortstop.  Perhaps most intimidating, however, is the fact that Bogaerts remains only 23 years old, and his evolution may not be complete.  Overshadowed prior to this season by the likes of Carlos Correa, Francisco Lindor, and Addison Russell, Xander Bogaerts appears set on mashing his way back into the conversation as the best young shortstop in baseball.

Edit: Since this piece was submitted (May 23), several developments in the Martin narrative have arisen, notably some more astute analyses than mine (namely Jeff Sullivan’s great piece on Martin’s batted-ball profile & an extremely in-depth look at his swing mechanics by Jason Churchill over at ProspectInsider, do go check him out) as well as this walk-off dinger against the Oakland A’s. 

A lot has gone right for the Seattle Mariners in new GM Jerry Dipoto’s first season. At time of writing, they sit in first place in the AL West with the third-best record in the American League and the best road record in baseball. One potential factor in Seattle’s success that has, until recently, taken a backseat to Robinson Canó‘s resurgence and Dae-Ho Lee’s power-hitting heroics is the sudden onset of what could turn out to be an offensive breakthrough for outfielder Leonys Martin.

The Mariners’ acquisition of Martin and Anthony Bass in exchange for Tom Wilhelmsen, James Jones, and a PTBNL (Patrick Kivlehan) is one of several moves last offseason that seem to follow a common guiding principle: bring in players who’ve struggled in recent seasons but demonstrated real value in seasons past. This category includes the likes of Steve Cishek and Chris Iannetta, both of whom seem to have (thus far) rebounded from uninspiring 2015 campaigns.

Meanwhile, Leonys Martin is having the best season of his life. This is mostly remarkable due to the fact that his hitting isn’t, and has never really been, the source of his value. He’s never topped 89 wRC+ in any season, and his career high for home runs in a year is eight. He’s also been historically abysmal against left-handed pitching. From 2012-15, Martin slashed .233/.274/.298 with 53 wRC+ against southpaws; no outfielder in baseball posted fewer wRC+ in that same span (min. 300 PAs). His poor performance in the second half of 2015 (.190/.260/.190 with 22 wRC+ after the All-Star break) earned him a demotion in early August. That lackluster second half, coupled with the emergence of Delino Deshields Jr. as a capable replacement, made it a lot easier for the Rangers to part with him in the offseason (incidentally, DeShields was demoted in early May and Wilhelmsen has been the worst reliever in the majors this year by fWAR, so that’s something).

Going into this season, Steamer projected him for around 492 PA with a .241/.292/.350 slash line and 79 wRC+, in addition to eight homers and 22 stolen bases, putting him on course for 1.2 fWAR. While not exceptional, this likely would have been an adequate season for Jerry Dipoto given the cost, especially at Martin’s $4,150,000 salary, but Martin’s already managed to match that mark, posting 1.4 fWAR as of May 23rd, and he’s providing a great deal of that value with his bat.

Martin seems to have shook off a bit of whatever seemed to be plaguing him at the tail end of 2015. He’s slashing .252/.331/.467, which would, over a full season, leave him with a career-best OPS of .798 and 124 wRC+. He still hasn’t been able to hit lefties, but that’s what platooning is for. But by far the most eye-popping aspect of Martin’s game this year is what looks like a sudden influx of power. Martin’s mark of .215 ISO is easily the best of his career — his eight home runs have already matched his career-best single-season total — and it’s not even June yet. With no context, one could look at Martin’s line thus far and notice that he might be on pace to post a 30 HR/30 SB season, if not for the slight inconvenience called “At No Point In His Career Has Martin Demonstrated That He Might Even Touch 30/30”. And yet this is baseball, and this is 2016, the Year of the Bartolo Colón Home Run. Anything is possible.

So — what’s changed for Martin? And perhaps more importantly, where the heck did all these home runs come from?

We turn first to Martin’s batted-ball profile. For the last two-and-some seasons, Martin’s fly-ball percentage has actually increased. His 2015 mark of 33% was actually a career-best at the time, especially considering it was brought down by his abysmal second half. He’s picked it back up in 2016, with a gaudy 45% fly-ball rate. Of course, the sustainability of this figure is questionable (one might also point out Martin’s likely inflated HR/FB rate of 20.5% — opposed to a current league average of 12.1%), but at no point in his career has Martin hit fly balls with such consistency:

Other indicators of improved power add credence to this positive trend. Martin’s quality of contact also seems to have improved this year, as his hard-hit ball rate of 34.4% is vastly superior to his pre-2016 range of about 23 – 25%. It’s also true that home/road splits affect the narrative somewhat, as only one of his eight home runs occurred at Safeco Field. But I suspect that there may be more to Martin’s offensive resurgence than just hitting balls harder.

One of the feel-good narratives of this season is the positive influence that new hitting coach Edgar Martínez has introduced to the Mariners offense, which currently ranks 2nd in the AL in runs scored. Martinez was brought in to replace Howard Johnson in June 2015, hoping to fix an anemic Mariners offense that struggled early and often. To date, that new appointment has been received with praise from Seattle media and fans, but more importantly from the players themselves. Could it perhaps be the case that Edgar’s tutelage, along with Jerry Dipoto’s promise to mold the 2016 Mariners to fit his “Control the Zone” philosophy, has brought about a positive change in the way Leonys Martin approaches hitting?

Overall, Martin’s plate discipline metrics show that his approach at the plate hasn’t changed too drastically from last season. If anything, his 70.4% contact rate is his lowest since 2012. One other thing sticks out here, namely that Martin seems to be more patient on pitches out of the zone and more aggressive on pitches in the zone. Compare the percentage of pitches he swings at in 2015 (left) to 2016 (right), courtesy of BrooksBaseball.net:

There is a relatively noticeable difference here, especially on high and outside pitches. According to PITCHf/x, his O-Swing% of 27.9 is easily the lowest of his career. Likewise, his Z-Swing% of 67.0 is his highest since 2012. These are generally good indicators that Martin is seeing the ball better or, at least, cut down on his tendency to chase pitches out of the zone.

And then there’s the matter of his batting stance.

Take a look at his stance for this home run on May 27, 2015, facing off against Scott Atchison:

Now check out his stance almost a year later, on May 22, 2016 in this at-bat against John Lamb.

An important thing to note about these stills is that I picked them mostly because of their similar camera angles. Martin’s foot position in other highlights is often obscured by the pitcher, or the pitcher is already in the middle of his wind-up, giving Martin time to square up before the pitcher’s delivery (as is slightly apparent in the at-bat against Lamb). But the vast majority of video evidence from this season is consistent with the idea that Martin has generally closed off his stance and now begins pretty much every at-bat with his feet squared to the pitcher. Now, I am aware that the batting stance is a rather fluid component of any baseball player’s oeuvre and can change for a number of reasons, not all of them being deliberately engineered to improve performance. I can’t seem to find anything about Martin having changed his stance online, aside from this ESPN piece from February of this year — but the focus of that article is on a legal issue Martin dealt with over the offseason, and the only comments offered on Martin’s approach seem to indicate that his stance hadn’t actually changed:

Martin also worked with a hitting instructor during the offseason in Miami. He altered his approach at the plate — his stance remains the same, he said — and he was pleased with the results when he faced pitchers in winter ball.

The most significant changes I’ve noticed as a result of comparing film from 2015 to film from 2016 are the aforementioned foot positioning and the fact that his hands are a little bit closer to his body this year. Generally speaking, though, it’s hard to really quantify the connection between a player’s stance and his performance. If this change in stance is deliberate, we can only really speculate as to the reasoning behind it. There are certainly good reasons to make the adjustments Martin has made. Bringing the hands closer to the body is often a nice starting point for a player who wants to make his swing a little more compact and less erratic. As for the foot positioning, there are a few benefits to batting with an open stance, especially for a left-handed hitter. One is that it enables left-handed hitters to see the ball better, especially when facing a left-handed pitcher. Another is that it eliminates the problem of the front foot stepping away from the plate on the swing, as batting from an open stance requires you to bring your front foot towards the plate in order to square up to hit the ball. It’s hard to say if Martin has previously had this issue in the past, but the fact that he’s changed from an open stance to a square stance likely indicates to me that whatever advantage he gained from an open stance may no longer be necessary. We don’t know if Martin has made these adjustments for the reasons listed above or if he has made them for any real reason at all, but he’s still made them all the same, and as it happens, they’ve been working out quite nicely for him.

That said, let’s not go overboard about a quarter-season of statistics just yet. Though Martin is posting career bests in almost any meaningful batting metric, there is still reason to believe he might still turn out to be an average or below-average hitter for the rest of the season. His on-base record is rather inflated by recent performances, he strikes out too much, and he continues to sport uninspiring numbers against left-handed pitching. All the same, his eight home runs this season aren’t going away, even if his fly-ball rate might. It’s unlikely, barring injury, that he’s not going to hit any more home runs for the rest of the year, so 2016 will most likely be a career year for him in the power department, and if his BABIP mark of .302 this year can regress back to his 2013-14 average of .326 rather than his poor 2015 mark of .270, 2016 may turn out to be a career year for him across the board. Martin’s offensive production has certainly been a pleasant surprise for the Mariners, and it would be interesting to know if altering his batting stance was a deliberate factor in producing an improved approach at the plate. If the Leonys Martin we’ve seen so far this year is anything like the Leonys Martin we’re going to see for the rest of the year, Jerry Dipoto may have stumbled upon a surprisingly high return on what was initially a low principal investment.

The Rays are known as one of the most sophisticated organizations in the MLB, mostly thanks to an advanced analytics department. They have been first adopters of some of the now prevalent advanced baseball strategies today. They perennially are winners with annually low payrolls.

The Rays sometimes blow me away with the strategies discovered and implemented by their analytics departments. One of the most fascinating strategies they implemented at the beginning of last year was getting their pitchers to throw fastballs with more rise high in the zone, causing pitchers like Drew Smyly and Matt Moore to make drastic improvements in their results. Now I believe they are having their hitters implement a new strategy.

Swinging hard.

I cannot be positive they are telling their hitters to swing harder, but there is some evidence to lead me to believe this is true.

The Rays strike out a lot. Almost all their players have strikeout rates above their ZiPS and Steamer projections and they currently have one of the highest strikeout rates in baseball. A strikeout is the worst outcome possible for a hitter, so at first glance the Rays appear to have a lot of hitters who have gotten a whole lot worse. It’s clear looking at the data this isn’t just variance. Across the board for the Rays, the contact rates of their hitters have been much worse this season than the previous, an average decline of about 5%.

There are a few possibilities that come to mind that could explain the decreased contact rates. The first one is luck. It is possible most of the Rays contact rates have decreased because of chance alone. This is certainly possible, but also unlikely. The 5% decrease in team contact rate is by far the highest margin in the league.

Because of the degree of the contact rate change, it’s unlikely that the Rays’ worse contact rates are happening purely by chance. That leaves two possibilities in my mind. One possibility is the Rays have advised some or all of their hitters to take more of an uppercut swing. A steeper or uppercut attack angle of the bat theoretically should lead to less contact, so this is a possible explanation. If this were true, we would expect the Rays to have more fly balls from their hitters. And they do. Their fly ball rate is up about 3% from last year

But the increase in fly ball rate is only the sixth highest in the league, and can mostly be accounted for by the addition of extreme fly ball hitter Steve Pearce and the loss of extreme groundball hitter John Jaso. I’m also skeptical that a team would try to drastically change all their players’ swing planes. I can’t rule out this possibility though.

That leaves us with the explanation I believe to be true: The Rays have adopted a grip it and rip it mindset. The Rays currently have the highest ISO in baseball, meaning they hit for power better than every other MLB club, a 30% improvement year to year. They also have a large increase in hard contact percentage across the board, an average of about 5% per player, by far the highest increase in the league.

Hitting for power and hitting the ball hard are not unrelated. With MLB Statcast data, we can now see their is a clear and strong relationship between hitting for the ball well and hitting the ball hard. The harder you swing, the harder the ball will be hit. That is if you make contact at all.

If contact wasn’t an issue, swinging hard would be a no-brainer. But there is a trade-off here. While a home run is the best outcome for a hitter, the strikeout is the worst. If you hit the ball in play, you can advance runners and get on base. With a strikeout, neither of those things will happen.

But is the increased power really worth increased strikeouts? The Royals would beg to differ. They won the World Series last year with historically good contact and strikeout rates. However, no one would argue that hitting was the biggest reason for the Royals success. On the contrary, it was really their bullpen and defense that carried them to a championship.

I can only imagine that the Rays have done the math and have decided: Yes, it’s worth the trade-off. Hitting the ball high and hard is good, and the Rays are doing that better than practically everyone else in the majors. Yes they are getting less contact, but the Rays do not have an abundance of talent in the batting department, so given their results I would have to say this change in approach has been a success.