In his seven-plus seasons as a major-leaguer, Elvis Andrus has never been considered an offensive dynamo. And for good reason! Over nearly 5,000 plate appearances, Andrus owns an 83 wRC+ and measly .079 ISO. However, even a defensive-minded shortstop can change the game with one swing of the bat. While not an overly impressive blast, it exposes something different in his approach at the plate. Early in his career, Rangers fans and followers held out hope that Andrus could develop into a 15-20 homer a year guy. While that may feel like a lost cause, Andrus has recently displayed some newfound power. Last season, Andrus smacked a career-high seven home runs and tied his career-high with 43 extra-base hits. So far this season, he is on track for a career-high ISO and running a near league-average offensive line. Andrus’ Speed Score sits right at his career average, hence it does not appear he has bulked up significantly and traded in speed for power. Rather, he has altered his approach at the plate.

This current approach began last season, and to this point has continued over into his 2016 campaign. From his rookie season in 2009 to 2014, Andrus ran a 57.4 GB% and a 21.3 FB%. This past season and a third, those metrics have shifted to 46.5% and 31.1%, respectively. In context, Andrus has gone from the 2^nd percentile in FB% to the 30^th percentile. While no one will ever confuse him for Chris Carter, Andrus’ new batted-ball profile closely resembles that of in-state slugger George Springer. Perhaps even more indicative, Andrus has raised his Pull% from 33.9% over 2009-2014 to 43.6% since 2015; this represents a shift from the 12^th percentile to the 81^st percentile, placing him just ahead of renowned slugger Anthony Rizzo. Seeing as 27 of his 29 career home runs have landed to the left of center field, this seems a logical shift for a man in search of dingers.

Plate-discipline measures further reveal Andrus’ altered approach. Andrus has raised his O-Swing% from 21.8 to 25.8 in addition to raising his Z-Swing% from 53.3 to 61.2 over our familiar timeframes. In avoiding Simpson’s Paradox, these changes have increased his overall Swing% from 38.5 to 42.8. While still not a free swinger by any regards, Andrus’ new approach remarkably resembles fellow A.L. West shortstop Marcus Semien, albeit with superior contact rates. Known for providing impressive power from the six spot on the diamond, one could well view Semien as the ceiling of Andrus’ power dreams. Meanwhile, Andrus has held his contact rates largely steady, dispelling the notion that he has traded contact for power. Interestingly, his Zone% has steadily dropped since his rookie season but has held near 51% each of the past three full seasons. So far in 2016, that number has dropped further to 49%, so perhaps opposing pitchers have finally altered their approach in response. However, too little time has passed to determine whether this is by choice or simply small-sample variation. Indeed, Andrus will need to prove that these adjustments make him a “power” hitter before pitchers treat him differently.

That ultimately remains the question. Andrus has ostensibly made adjustments to improve his power, but do they truly make him a better overall hitter? To this point in the season, Andrus ranks 158^th in average exit velocity on fly balls and 147^th in average fly-ball distance among the 167 batters with 25 or more fly balls hit. Andrus pulling more fly-ball outs to left field doesn’t enhance his offensive output. However, if more of these balls turn into gap shots and home runs, Andrus could uncover another level to his game. With Jurickson Profar returning from the baseball grave in remarkable fashion and Rougned Odor forever cementing his place in Rangers lore, Andrus may be feeling the pressure to live up to his now ill-regarded contract extension. After three below-80-wRC+ seasons, something needed to change for Andrus at the plate. Whether this new approach works for the better remains to be seen, but right now Andrus remains a key cog on a surprising postseason contender.

On December 8, 2010, the Boston Red Sox agreed to terms with Carl Crawford, inking the outfielder to a seven-year, 142-million-dollar deal, the largest ever signed by a position player that had never hit more than 20 home runs in a single season.  Although the majority of the population felt that the Red Sox had overpaid for his services, most considered it only a slight reach, and when factoring in Boston’s position on the win curve, their decision to splurge on a premium player could be justified.  Crawford was an established elite defensive outfielder coming off the best season of his career at the plate; an increase in power prior to the 2009 season had boosted Crawford to new heights just in time for his pay day, and in the final two years of his extension with the Rays, he posted WARs of 5.9 and 7.7, respectively.  In the immediate aftermath of his signing with Boston, FanGraphs’ own Dave Cameron declared him to be a true-talent 5-win player, and at the time, it was not difficult to imagine a scenario in which the 29 year-old Crawford continued to perform at peak levels before gradually declining in the final years of the contract.  If we assume that Crawford was in fact a 5-win player, then using the $/WAR figure accepted in the winter of 2010 (5 million dollars/win), 5% inflation, and a standard aging curve, the projection for Crawford’s contract would have looked something like this, with his 6-million-dollar signing bonus excluded from the analysis:

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Two things are striking when looking at this table.  First, on an unrelated note, league-wide inflation as a result of TV deals and increased revenue streams has far exceeded the expectations of 2010, actually surpassing 10% in order to reach the accepted value of 8-9 million dollars per win today in 2016.  Although the methodology did prove to be incorrect, I do still believe the results obtained here to be worthy of inspection, as they offer insight into teams’ valuations of Crawford as a player available in the free-agent market.  Second, the divergence between industry consensus and the arithmetic presented here is worth noting; most insiders felt that Boston had spent too much, while the data presented here suggests that the contract actually provided a bit of upside.  This disparity could perhaps be explained by a skepticism of defensive metrics in 2010, along with doubts about Crawford’s ability to age well, as a large portion of his value on the bases and in the outfield was tied up in his legs.  In order to account for this discrepancy, perhaps it is better to use a “worst-case scenario,” to subject Crawford’s performance to a more punitive aging curve over the life of the contract.  Instead of docking Crawford 0.5 WAR for his age-31 through -35 seasons, instead, he will lose 0.75 wins each year.  This steeper decline is forecast below:

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It appears that this table is a more accurate representation of front offices’ opinions about Carl Crawford, as shown by the deficit in the bottom right corner.  Using the more aggressive aging curve, the contract offered by the Red Sox does appear to be a slight overpay, and if they conformed to the opinion that the outfielder would decline more swiftly than other players of similar age, then they agreed to a contract in which there was no upside.  However, if Crawford’s performance fell anywhere between the standard aging projection and the “worst-case scenario,” as it was likely to, it seemed that both sides would be satisfied with the outcome.

As we all know now, this “worst-case scenario” projected in 2010 was a far cry from reality.  After suffering through a tumultuous year and a half in Boston and undergoing Tommy John surgery to repair a partially torn UCL, Crawford was unceremoniously dumped by the Red Sox and shipped to the Dodgers on August 25, 2012 as part of the infamous Nick Punto trade.  It appears that Crawford has finally hit rock bottom, with Los Angeles designating him for assignment on Sunday.  Crawford will almost certainly clear waivers, and assuming he asks to be released rather than assigned to the club’s AAA affiliate in Oklahoma City, the Dodgers will eat the remainder of his contract and essentially pay Crawford nearly 35 million dollars to disappear.  Rather than projecting future performance, let’s instead take a look back at Crawford’s production since signing with Boston:

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Although up-to-date $/WAR figures could have been used, I stuck with the estimates of 2010, in order to further emphasize how poorly this pact has been when compared to the organization’s expectations when they chose to sign Crawford.  Elbow injury notwithstanding, it is difficult to imagine how this contract could have soured so quickly.  Crawford has already cost his employers 85 million dollars more than his production would have warranted, and even if he latches on somewhere and plays out the remainder of the deal, it’s very likely that figure ends up more than 100 million dollars in the red.  So, how did this happen?  How did Carl Crawford, he of the 7.7 WAR in 2010, second in all of baseball, flop so badly, producing only 5.3 WAR since signing with the Red Sox?

Well, the most obvious answer is the boring one: Carl Crawford got old.  Fast.  From 2008-2010, Crawford’s final three seasons in Tampa Bay, he was actually the best defensive player in the MLB, posting a UZR/150 of 20.6 in left field, two runs better than his nearest competitor on the leaderboard.  A bit of regression and decline were certainly expected, as it is incredibly difficult to sustain this level of performance, but nobody could have expected the utter evaporation of his defensive value upon arriving in Boston.  Crawford posted a negative UZR during his time patrolling the Green Monster; some criticize the Red Sox for wasting his defensive abilities in what is considered to be the smallest left field in all of baseball, suggesting that he should have been moved to Fenway’s right field in order to better leverage his extraordinary range.  However, even before his elbow injury, Crawford was known for having a weak throwing arm, and with a partially torn UCL, it would have been nearly impossible for him to play anywhere other than left.

Even so, his damaged elbow fails to explain the mysterious loss of range that sent him tumbling down the UZR leaderboards, and instead of providing value as an elite defensive player, Crawford instead resembled an average corner outfielder during his time in Boston.  After being dealt to Los Angeles, Crawford’s defensive numbers did improve slightly, perhaps indicating that he never felt comfortable playing in front of the 37-foot wall, but by the time he arrived in Chavez Ravine, Crawford had already lost a step or two, placing a ceiling on his future defensive contributions.

This loss of speed was evident on the base paths as well, with Crawford never again imposing his will upon opposing batteries like he did during his time with the Rays.  From the time of his promotion to Tampa Bay in 2002 until the end of 2010, Crawford had stolen 409 bases in 499 attempts, for a success rate of nearly 82% and the second-highest stolen base total in all of baseball during that timeframe.  However, after signing with Boston, it seems as if Crawford became more timid as a runner, never attempting more than 30 steals in a single season.  Since 2011, Crawford owns a 79% success rate, quite similar to his career average, yet he’s running far less frequently, stealing only 71 bases in 90 attempts.  Whether due to a loss of speed or a lack of aggression, or perhaps a combination of the two, Crawford never regained his form as a base-stealer, resulting in the loss of a huge chunk of his base-running value.

Unlike his collapse in the outfield and on the base paths, Crawford’s decline at the plate cannot be explained by a loss of speed simply chalked up to age.  This dilemma is a bit more perplexing.  After posting the two best seasons of his career at the plate in Tampa Bay immediately prior to hitting free agency, Crawford’s production in the batter’s box cratered after signing with Boston in 2011, falling to levels only experienced by the outfielder during his first full season in the majors in 2003.  Since joining the Red Sox, Crawford has sported a more aggressive approach leading to fewer walks and more strikeouts, has exhibited less power than he did during his time in Tampa Bay, and his problems against left-handed pitching have only been exacerbated.  In a vacuum, none of these changes themselves would be damning, but in conjunction with one another, this trio has formed a nasty combination, only hastening Crawford’s demise.

Starting in 2006, as Crawford entered his offensive prime and started to become a force at the plate, his Zone%, the number of pitches he saw in the strike zone, began to decline as pitchers decided to carefully pitch around him rather than challenging him, falling from a high of 57% to only 43% in 2010.  During his MVP-level campaigns in 2009 and 2010, Crawford adjusted to these changes appropriately, cutting his swing rate and accepting the free passes being handed to him by opposing pitchers, adopting what could be considered somewhat of a slugger’s profile.  However, in 2011, perhaps feeling the weight of his new contract and worrying that hits rather than walks were needed to justify the nine-figure deal and appease Boston fans, Crawford gave these gains back, as his O-Swing% jumped by nearly three points.

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Surprisingly, Crawford actually controlled the outside corner of the plate, but he expanded the zone in nearly every other direction.  By chasing balls rather than selectively punishing mistakes, Crawford effectively got himself out more than ever, posting a career-high K% and his lowest BB% since 2003.  Even when Crawford did make contact, the quality was often terrible, as his Soft% rose to a nearly unfathomable 26%, contributing to a 40-point drop in his BABIP and a subsequent, almost identical, fall in batting average.  Although some of the walks have returned since his horrendous 2011, Crawford’s strikeouts remain elevated, seriously limiting his offensive production.

The lack of quality contact has also affected Crawford’s power output, because although his fly ball and line drive tendencies have been in line with his career norms, Crawford is doing far less damage.  During his time in Tampa, Crawford had an ISO of .148, peaking at .188 in 2010.  In Boston and Los Angeles however, this number has fallen to .136, and he’s never posted a single-season ISO higher than .150.

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This loss of power is most obvious at the top of the strike zone and on the outside corner, where Crawford is now capable of doing little to no damage.  Even in his wheelhouse, down and in, Crawford’s strength has eroded, leaving him as a shell of his 2010 American League MVP candidate self at the plate.

Finally, and perhaps most troubling, since leaving Tampa Bay, it seems like Crawford has forgotten how to hit left-handed pitching.  Even in his prime, the lefty struggled against southpaws, boasting only a .308 wOBA, but since signing with Boston, his production against same-handed pitching has collapsed, with his wOBA falling nearly 30 points, leaving with him with a wRC+ of 73 against lefties.  And yes, we now have an answer, his platoon split absolutely matters.  The final straw came in 2013, when he posted an ISO 0f .084 and a wRC+ of 56 in 115 plate appearances against left-handers; since then, Crawford has become a platoon outfielder, almost never allowed to face lefties and failing miserably when he does, as evidenced by his -64 wRC+ against them this year (granted, in only 12 plate appearances).

So, there you have it.  Carl Crawford, the electric baserunner, phenomenal outfielder, and prodigious hitter of less than six years ago is soon to be unemployed, assuming he clears waivers and is released.  Does he have any baseball left in him, or is this 142-million-dollar man done?  In any other year, he might have been, but given the number of contenders that will need an outfielder and the limited supply, it’s very possible that a team will give him a chance.  However, it is unclear if Crawford even wants to continue playing, given that the team acquiring him will almost certainly place him in a platoon role, while he has stated that he doesn’t believe he is a platoon player.  If he does agree to play in a limited role, where could he land?  An obvious answer is Cleveland, yet during his time in Boston, Crawford didn’t get along well with current Indians’ skipper Terry Francona.  Somewhat comically, Boston is another obvious fit, as he could be a nice platoon partner for Chris Young, but we all know how his first stint with the Red Sox went.  Other teams that could be interested in the outfielder’s services include the Orioles, Nationals, Mariners, and White Sox, although they may look to make a bigger splash before settling upon Crawford.  Whether Crawford returns to the big leagues or not, his time as an impact player almost certainly ended years ago, and that’s a shame.

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No matter their team allegiance, fans of the game of baseball have to be disappointed by the outcome of Crawford’s career, as his prime was gone far too soon.  One of few players that could truly dominate the game in every phase, through a combination of injury, age, and perhaps a lack of mental toughness, Carl Crawford’s star was extinguished almost immediately after signing with Boston.

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.