Analysis: The impatient projection system

USA TODAY Sports

The Mariners haven't changed much but their young hitters will.

As the dust from Hot Stove Apocalypse begins to settle, the Mariners emerge from the bomb shelter one by one. No casualties. No additions. Just the harsh reality of a future that bears a strong resemblance to the past.

However, assuming the 2014 Mariners are the Mariners of 2013 ignores a projected starting lineup that includes three position players age 24 or younger and four more entering their prime years. There is just so much youth, and young players tend to improve. Young players also tend to struggle and trying to distinguish a player who is adjusting from a player who lacks the skills necessary to succeed at baseball’s highest level is challenging and often impossible.

But ignore the impossible for a moment. Forget the small samples made even smaller by crazy variance in rookie performance and to hell with waiting around all summer for counting stats to trickle in and stabilize. I am tired of not knowing who these young Mariners are. The data we have is good enough. Swing and contact rates stabilize in the vicinity of 50-100 plate appearances and batted ball data isn't far behind. We can assemble these bones to create a skeleton, and continue building outward, generating indicators of future performance and potential using launch speed, trajectory, backspin, apex, and distance. We can even make our own power metric with a cool name like Z-POW or something. This should be fun and educational – or not at all. I really have no idea what we might find.

The raw numbers will come from FanGraphs, ESPN’s Home Run Tracker and Baseball Heat Maps and converted to Z-scores for comparative purposes. Feel free to skip ahead if you are familiar with Z-Scores. If not, have no fear. Z-scores are simple to understand. First, a pair of examples followed by a definition:

Rating Spd zSpd Dist zDist
Great 107.6 .98 420.2 .98
Good 105.5 .50 408.6 .50
Average 103.3 -.01 396.7 .00
Poor 101.2 -.50 384.5 -.50
Bad 99.1 -.98 373.0 -.98
Rating Traj zTraj Apex zApex
High 32.1 .98 107.3 .99
Med-high 30.0 .50 97.6 .50
Medium 27.9 .00 87.5 .00
Med-low 25.8 -.50 77.5 -.50
Low 23.8 -.98 67.5 -.99

A Z-score is a statistical measurement of a score's relationship to the mean, which is 0. A Z-score can be positive or negative, indicating whether it is above or below the mean and by how many standard deviations. Z-scores also allow us to convert statistics from different data sets into scores that can be accurately compared to each other.

So in the above examples, we see that Z-score conversions allow us to determine with ease whether a specific statistic is above average or below average. Better yet, they can be compared or even combined if necessary. For example, using the available data we can create something that resembles a backspin rating without turning this into a physics study. By subtracting the Z-score for apex (maximum height of homerun) from the Z-score for trajectory (vertical angle the ball leaves the bat), we get a number that tells us who is getting more height relative to trajectory. In other words, if two baseballs are hit with the same launch speed and trajectory, but one ball travels higher and farther, it is probably a result of more backspin. Here is a non-Mariner example:

Name zDist zSpd zTraj zApex zSpin
Edwin Encarnacion .12 .52 -.03 .06 .09
Evan Gattis .48 .54 -.03 .20 .23

Fellow mashers Encarnacion and Gattis were nearly identical in terms of average launch speed (105.6 vs 105.7) and trajectory angle (27.8), but Gattis enjoyed an extra 2.6 feet of height and 8.8 feet of distance. You get the idea. Z-Scores are cool.

So, the Mariners. Perhaps the best way to do this is reveal the entire list and then go player by player, making comparisons to comparable players along the way to see what might be possible, or impossible, in 2014:

Name wRC+ zHR% zParks zDist zSpd zTraj zApex zSpin zPow
Mike Zunino 73 -.05 -.16 .58 .54 -.33 -.08 .24 .23
Jesus Montero 62 .00 -.71 .73 .32 -.88 -.35 .53 .17
Brad Miller 103 -.19 .08 -.07 .09 .07 .10 .03 -.01
Justin Smoak 109 .78 -.10 -.47 -.36 .37 .20 -.17 -.07
Kyle Seager 113 .33 -.11 -.35 -.25 .38 .22 -.17 -.11
Nick Franklin 90 .15 -.13 -.15 -.46 .17 .05 -.12 -.14
Michael Saunders 98 -.01 -.05 -.40 -.33 -.04 -.15 -.11 -.18
Dustin Ackley 84 -1.05 -.99 -.73 -.28 -.56 -.83 -.27 -.66
Abraham Almonte 96 -.07 -.81 -1.14 -1.44 .51 -.12 -.63 -.82

Z-POW! There it is, as promised, in all its glory. Z-POW is simply the Z-Score average of homerun rate (zHR%), number of parks the ball would have cleared the fence (zParks), distance (zDist), launch speed (zSpd) and spin (zSpin). Now, onto the good stuff.

MIKE ZUNINO

What Zunino lacks in sample size, he counters with promise. The overall picture from 2013 (.214/.290/.329) was not pretty, but his raw power is legit and a few positive signs begin to materialize upon closer inspection:

Mike Zunino Dist # Start End
257.6 10 6/12/13 6/30/13
285.3 10 7/1/13 7/25/13
Broken Hamate x x x x
282.1 14 9/2/13 9/30/13

This is Zunino’s average fly ball distance, which includes homeruns. With only 400 minor league plate appearances under his belt, Zunino looked over-matched and overwhelmed in June, posting an average fly ball distance comparable to Brendan Ryan. It appears the light bulb went on in July, but the reality is Zunino was making steady progress almost daily, culminating with a .324/.442/.471 triple-slash in the 11 games leading up to the date of his broken hamate bone. Zunino healed just in time to fizzle out with the rest of the team in September, but he was getting stronger just as was doing before his injury. Note the steady climb in average distance both before and after the injury:

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via www.baseballheatmaps.com Phe4hao8lhiec3jfuqasoejta6572287distwm_medium

via www.baseballheatmaps.com

Finding a reliable set of comps is difficult due to his small sample size and rapid growth rate, but here is what we might expect from Zunino in 2014:

Name wRC+ zHR% zParks zDist zSpd zTraj zApex zSpin zPow
John Buck 83 .46 .67 .24 .50 -.12 .11 .24 .42
Jay Bruce 117 .99 .18 .36 .38 -.33 -.18 .16 .41
Xavier Paul 105 .20 .58 .39 .27 -.15 -.02 .13 .32
Mike Zunino 73 -.05 -.16 .58 .54 -.33 -.08 .24 .23
Curtis Granderson 97 .18 .47 .22 -.01 .62 .69 .07 .19
Adam Rosales 62 .28 .79 .06 .07 .34 .46 .12 .26
Will Middlebrooks 83 1.04 -.24 -.28 -.06 .10 -.12 -.22 .05

That is a solid list for a 23-year old catcher with plus defense as a wRC of 95-100 appears within reach in 2014. Zunino’s low contact rate shows up here, but if he makes progress against breaking balls and shrinks a few holes, the list of comps improves in a hurry.

JUSTIN SMOAK

The Smoak story has been told and retold, but for anyone late to the party:

Justin Smoak Dist wRC+ Start End
Lefty 293.5 134 4/1/13 9/30/13
Righty 262.1 54 4/1/13 9/30/13

Those splits represent a career high and low from each side of the plate but Smoak has always hit the ball farther from the left side. For the comp list, let’s assume Smoak will be platooned in 2014 and use only his strong side numbers:

Name wRC+ zHR% zParks zDist zSpd zTraj zApex zSpin zPow
Jason Giambi 85 1.01 .27 .13 .07 -.20 -.24 -.05 .29
Chris Young 82 .33 .50 .17 .28 .16 .18 .03 .26
Alex Gordon 103 .10 .28 .28 .14 -.14 -.12 .02 .16
Justin Smoak 134 1.56 -.12 -.38 -.32 .39 .29 -.10 .13
Brett Lawrie 94 -.12 -.10 -.09 .27 -.32 -.39 -.07 -.02
David Freese 106 -.56 -.03 .23 -.14 .20 .50 .31 -.04
Lyle Overbay 86 .09 -.12 -.24 -.45 .16 .08 -.08 -.16

Smoak has the highest HR rate in the group despite the 2nd lowest mph and distance. One explanation for that might his high trajectory, but the uppercut swing Smoak uses to create a steep launch angle also costs him spin. It appears Smoak is getting all he can out of his current swing, which raises concern that he might regress in 2014, and beyond.

JESUS MONTERO

Confirmed use of pharmaceutical enhancements obstructs credibility of the one and only plus tool Montero has in baseball, and perhaps life, but it never hurts to look:

Jesus Montero Dist # Start End
yuck 263.1 23 6/12/13 6/30/13

OK, sometimes it hurts to look. Not even his moonshot in Houston masks the fact that Montero had trouble squaring up the baseball last season. For reasons already mentioned, Montero is pointless to comp, but a list of potential suitors appears to include Garrett Jones, Juan Uribe, Kyle Blanks and Clete Thomas.

BRAD MILLER

Sifting through Miller’s game logs, two things immediately jump out: the multi-hit games – 30 in only 72 full games – and the reminder that when he hit one homerun, there was a 67% chance he would hit another. Multi-hit games may be a junk statistic but Miller’s pace was better than Matt Carpenter, who led the majors with 63 multi-hit games. Miller only averaged 275.9 feet per fly ball but he also hit some authoritative homeruns. For example, five of Miller’s blasts were launched with higher velocity than Nick Franklin’s hardest hit dinger. As for his comps:

Name wRC+ zHR% zParks zDist zSpd zTraj zApex zSpin zPow
Eric Hosmer 119 -.13 .46 .88 .46 -.11 .15 .25 .38
Brad Miller 103 -.19 .08 -.07 .09 .07 .10 .03 -.01
Matt Dominguez 89 .49 .02 -.20 -.24 .51 .36 -.15 -.01
Mike Moustakas 77 -.23 .63 -.22 -.08 .09 -.11 -.21 -.02
Brandon Belt 139 .20 .03 -.07 -.40 .43 .41 -.02 -.05
Allen Craig 135 -.23 -.36 .01 .07 -.25 -.12 .13 -.08
Manny Machado 101 -.46 -.08 -.14 .01 -.08 -.10 -.02 -.14

Wow. Look at all that young talent. You might assume an age parameter was involved, but that is not the case. Miller’s comp list was created like all the others – starting with swing and contact rates. Perhaps it’s just a coincidence, or maybe these batters share an approach that is typical for young and talented hitters. Either way, Miller might be closer to stardom than we thought. His contact rate on pitches in the zone (89.2%) is already near-elite and an improvement to his O-Swing% would thrust him into the next tier, which includes a wide array of baseball’s premier hitters, none of whom play shortstop. One of those premier hitters is the next Mariner on our list.

KYLE SEAGER

This is where we are reminded of the defensive shifts Seager faced late in the season:

Kyle Seager BB% K% AVG OBP SLG BABIP wRC+ Dist LD% GB% FB% IFFB% HR/FB
Apr-Jul 8.5% 15.9% .298 .361 .492 .324 136 277.2 23.1% 36.4% 40.6% 8.2% 12.0%
Aug-Sept 12.3% 20.9% .183 .294 .292 .214 67 288.6 15.7% 29.4% 54.9% 18.0% 6.0%

BABIP highlights the run of bad luck, but Seager changed his approach during the final two months and the results of his experiment were not positive. In terms of monthly highs, August and September featured the two highest BB% and FB% of his career, which would have been great had everything else not gone down the toilet. I hate to speculate about a player’s mental state, but Seager may have been pressing. Yet, even with those two sub-Seager months, his comparables are strong:

Name wRC+ zHR% zParks zDist zSpd zTraj zApex zSpin zPow
Carlos Beltran 132 .74 .17 -.16 .01 .10 -.04 -.14 .12
David Wright 155 .66 -.40 .04 -.31 .05 .12 .08 .01
Buster Posey 133 -.05 -.03 -.14 -.13 .27 .19 -.08 -.09
Kyle Seager 113 .33 -.11 -.35 -.25 .38 .22 -.17 -.11
Billy Butler 116 -.22 -.12 .10 -.38 .45 .52 .07 -.11
Luis Valbuena 95 .36 -.19 -.39 -.37 .71 .45 -.27 -.17
Michael Young 102 -.78 -.32 -.30 -.21 -.35 -.53 -.18 -.36

If you find it hard to envision Seager unleashing a David Wright or Buster Posey season in the near future, just remember the 136 wRC+ he carried through the first four months of 2013. If he can put those final two months behind him, the 26-year old Seager is poised for a breakout in 2014.

NICK FRANKLIN

For many Mariners fans, the lasting image of Franklin is probably that of a hitter confounded by advanced breaking balls and pitch sequencing. And he most certainly was and probably still is. However, Franklin may have turned the corner late in the season. While he never recovered his power or punished many breaking balls, Franklin lowered his K% and nearly doubled his BB% in September and closed out the final 12 games of 2013 with a .310/.396/.381 line. Some additional silver lining includes a 10.2% walk rate and team-leading 24.3% line drive rate, not to mention a decent set of comps:

Name wRC+ zHR% zParks zDist zSpd zTraj zApex zSpin zPow
Kelly Johnson 101 .76 .07 .14 .14 -.19 -.02 .17 .25
Wil Myers 131 .49 -.03 .01 -.06 .17 .20 .03 .09
Chase Headley 113 -.26 .00 -.30 .11 .05 -.11 -.16 -.12
Nick Franklin 90 .15 -.13 -.15 -.46 .17 .05 -.12 -.14
Lyle Overbay 86 .09 -.12 -.24 -.45 .16 .08 -.08 -.16
Jhonny Peralta 123 -.15 -.17 -.14 -.27 -.05 -.19 -.13 -.17
John Mayberry 86 .07 -.52 -.50 -.52 .16 -.07 -.22 -.34

We haven’t seen enough of Franklin to know what he might become, although Kelly Johnson is someone he has been compared to before. Johnson is notoriously streaky and strikes out a lot, and because of that, he has played with four different teams over the past five seasons. Johnson also ranks among the top 15 second basemen since 2007. Compared to Johnson, Franklin amassed a superior minor league resume while advancing through the upper levels at a younger age than Johnson. Again, anything regarding Franklin’s future is speculation at this point, but Kelly Johnson appears to be closer to the floor than the ceiling and that is a plus. Franklin may never be a star, but a five-year run as one of the top 10-15 second basemen in the game would make him a valuable asset.

MICHAEL SAUNDERS

Saunders injured his shoulder on April 10, struggled for two months, and then returned to pre-injury form:

Michael Saunders Dist wRC+ Start End
289.9 108 4/1/12 4/9/13
Shoulder Injury x x x x
278.5 59 4/29/13 6/30/13
290.3 124 7/1/13 9/30/13

Clearly, the injury had a major impact on batted ball distance but the tender shoulder may have forced Saunders to be less aggressive at the plate as well. From 2010-1012, Saunders carried a league average swing rate against pitches outside the zone. Last season, Saunders lowered that rate more than any other player in baseball, finishing with the 10th lowest O-Swing% among batters with 450 plate appearances. Basically, Saunders morphed into Rickie Weeks:

Player O-Sw% Z-Sw% Sw% O-Con% Z-Con% Con% Zone% F-Str% SwStr%
Weeks 22.60% 62.00% 41.20% 47.90% 84.90% 74.20% 47.20% 61.40% 10.50%
Saunders 23.20% 68.10% 43.90% 53.70% 84.40% 75.60% 46.10% 57.90% 10.40%

That approach hasn't worked well for Weeks the last two years, but during his age 27-29 seasons Weeks posted an average wRC+ of 126. In other words, pretty much what Saunders did after regaining full strength of his shoulder. Saunders will be entering his age 27-29 seasons beginning in 2014 and if he continues down this path of patience, history suggests Saunders could be in for a productive run. Let’s see what the comp machine kicks out:

Name wRC+ zHR% zParks zDist zSpd zTraj zApex zSpin zPow
Sean Rodriguez 101 -.20 .27 .28 .83 -.90 -.60 .30 .29
Rickie Weeks 86 -.07 .14 .23 .12 -.23 -.14 .09 .10
Dexter Fowler 106 -.03 -.49 .27 -.26 .00 .02 .02 -.10
Chase Headley 113 -.26 .00 -.30 .11 .05 -.11 -.16 -.12
Michael Saunders 98 -.01 -.05 -.40 -.33 -.04 -.15 -.11 -.18
Christian Yelich 116 -.71 .05 -.18 -.11 -.32 -.27 .05 -.18
John Mayberry 86 .07 -.52 -.50 -.52 .16 -.07 -.22 -.34

No surprises here as we see Weeks along with Condor’s reverse twin, Dexter Fowler. The similarities to Franklin should not be surprising due to their mutual combination of patience and low contact rates, but the average wRC+ from this group is mildly discouraging. It will be interesting to see if a healthy Saunders can graduate from these comps in 2014.

DUSTIN ACKLEY

When Ackley returned from AAA, he posted the highest average fly ball distance of his career:

Dustin Ackley Dist wRC+ Start End
266.6 75 4/1/12 9/30/12
257.1 44 4/1/13 5/26/13
Sent to AAA x x x x
275.5 112 6/28/13 9/30/13

I really have no idea what to write about here, because of the four regulars entering their prime years – Ackley, Seager, Saunders and Smoak – Ackley is by far the player we know least about. The strange thing is he might also be the most projectable:

Name wRC+ zHR% zParks zDist zSpd zTraj zApex zSpin zPow
Nate McLouth 100 -.38 -.20 -.27 -.29 .00 -.06 -.06 -.24
Ben Zobrist 115 -.55 -.27 -.74 -.28 -.13 -.38 -.26 -.42
David DeJesus 102 -.50 -.37 -.62 -.55 .35 .23 -.11 -.43
Coco Crisp 117 .72 -.19 -1.15 -.98 .49 -.10 -.60 -.44
Dustin Ackley 84 -1.05 -.99 -.73 -.28 -.56 -.83 -.27 -.66
Elvis Andrus 78 -1.26 -.10 -.97 -.77 .26 -.33 -.59 -.74
Jimmy Rollins 84 -1.07 -1.07 -.65 -.93 .20 -.34 -.54 -.85

Low upside. Low downside. The Zobrist comp is encouraging as that is the type of player everybody hopes Ackley becomes, but any upside for Ackley going forward appears to be mostly BABIP dependent. That is typical for line drive/groundball hitter with limited power, but for Ackley to elevate himself from the bottom half of this list, that is exactly what will be required.

ABRAHAM ALMONTE

There are no comps for Almonte because no other hitter matches his swing and contact profile. This is probably a result of an 82-game sample size, or perhaps Almonte is a just unique talent. The latter would make him something of an honorary Seahawk and anti-Willie Bloomquist folk hero, so let’s run with that storyline. He already hits the ball further than Bloomquist (who doesn’t?) and Steamer sees Almonte as a championship-caliber 4th outfielder (1.5 WAR). That role is available to Almonte in 2014 unless the Mariners acquire three starting outfielders and retain Saunders this winter. The odds of that happening are slim to none, so feel free to get attached in a Mark McLemore sort of way.

CONCLUSION

As if this needs more words, so real quick:

Zunino has enough bat to deserve the starting job, Smoak appears maxed out while Montero lacks credibility and perhaps talent. Miller could be great soon, Seager even sooner and Franklin might be infuriatingly less great, but who knows. Finally, Saunders has a case of Rickie Weeks syndrome, Ackley has BABIP-itis and Almonte is the Bloomquist antidote. Z-POW!

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