Using Statcast launch angle to analysis the 2015/16 KC Royals OF

It's becoming my hypothesis that you can use launch angle on balls hit to the OF to determine an outfielders relative strength.

The more i look at the data, the more convinced I'm becoming.

So i downloaded the 2015 and 2016 KC Royals statcast data to see if I could compare their major outfielders performance year to year and see a couple things.  What i've done is bucketed hits to the OF by launch angle (in 2 degree increments) and calculated a percentage of that contact resulting in a HIT or an OUT.  Simple as that.  So what i'm comparing between  years is:
1) Are the hit likelihood percentages for each angle by OF resonably projectable year to year
2) Does improvement in my Angle metric result in improvement in other defense metrics.

First lets look at Jarrod Dyson. He's one of the best outfielders in MLB. He recorded, per fangraphs, 11 DRS in 2015 and to date has 18 DRS in 2016.  His 2015 UZR/150 was 18.4 and in 2016 to date it's 28.7.  So both of the "new-traditional" type defense stats are saying, he's not only good but he's getting better in 2016 versus 2015.  What does my angular stat suggest?

The red points are for '16 Dyson while the blue is '15.  The left linear regression eqn (with the .837 R2) is 2015 while the right (R2 .7796) is 2016.  This shows dyson as a similar player year to year, but likely a bit better.   The higher angle fly-balls, it does appear that Dyson has done a better job this year of tracking down; however, it also appears that in 2015 he did a bit better catching some of the lower angled fly balls.  So it's not entirely clear, from this graph, why Dyson is per DRS and UZR having such a better defensive year.  To have something like this happen, it could indicate that maybe Dyson is starting to play deeper than before.  This would limit he likelihood of him catching the low angled line drives to the OF, but help track down more true fly balls. I'd certainly be interested to see if Dyson is actually doing that very thing this year.   

When it comes to projecting year to year, the R2 for Dyson's '15 to '16 hit likelihood % was:

0.532.  In real life this is a pretty strong correlation, so i'd say it's a reasonable estimator.

How about we look at KC OF defensive darling Alex Gordon:

Again the red points are for '16 Gordon while the blue is '15. The left linear regression eqn (with the .939R2) is 2015 while the right (R2 .8424) is 2016.   It jumps right out to you how much smoother Gordon's regressions are than Dyson's.  Maybe experience leads to that, who knows.  So the 2016 regression line (the dashed one) shows that contact to him in the OF is a bit more likely to land for a hit now in 2016 than it was in 2015.  This would suggest that Alex Gordon is having a worse year defensively in '16 than '15.  How does DRS and UZR/150 compare?  Well Alex has a DRS of 3 in 2016 and had a DRS of 7 in 2015.  So he does seem to be trending a bit lower, though not all too much.  And an UZR/150 in 2016 of  9.9 whereas that was 10.5 in 2015.  So in this case it all sort of agrees.  Gordon seems to be a step or two slower (age and injuries easily could account for that) and as a result his defense has stepped backward a bit.  Interestingly he's still doing about the same job on balls that are high likelihood hits, the more difficult plays, it's really at the end of the spectrum which is where the balls are unlikely to be hits anyways that Alex seems to be struggling.  So maybe the "skills" are still there, but the athleticism has just faded a bit and he can't run down those long fly balls anymore.  This is sort of the opposite of Dyson.  Maybe Gordon is in fact playing to shallow, cheating to ensure his reputation for robbing sure hits stays in tact while losing a bit of overall range creating a situation where some balls land that probably should have been outs.

When it comes to projecting year to year, the R2 for Gordon'15 to '16 hit likelihood % was:

0.778.  This is excellent and i think it is clearly visible from the chart just how project-able year to year this would be.

What about allstar and defensive stalwart Lorenzo Cain?

Again the red points are for '16 Cain while the blue is '15. The left linear regression eqn (with the .8876 R2) is 2015 while the right (R2 .9073) is 2016. Well this is interesting, it's just as though you shifted the line up ever so slightly.  A 2016 higher trend line would indicate that contact to the outfield around Lorenzo would be more likely than last year to result in a base hit.  This would indicate he too has backslide some from his 2015 self.  So what does UZR and DRS say?  DRS in 2016 is 11 whereas it as 18 in 2015. But UZR/150 is currently 15.4 in 2016 and it was only 14.1 in 2015.    So there is a bit of confusion as to Cain's 2016 performance, relative to '15.   Clearly he is still an excellent outfielder by all measures, but i would lean toward him trending in the negative direction in 16 and moving forward.

Given the two linear regressoins and data sets, you'd have to believe you could use this data to project very accurately the future year.  And you'd be right.  Cain's year to year R2 checks in at 0.955.

Well what about newcomer Paulo Orlando? he already seems to be living up to the newfound tradition of excellent KC Outfield defense:

Paulo Orlando is sort of the exact reverse of Cain.  His trend has basically just taken an entire step down.  This means balls are less likely to be hits now than before.  So does UZR and DRS agree with Orlando taking what appears to be a reasonable step forward?  Suprisingly no.  DRS from 15 to 16 has jumped from 8 to 12, but Orlando has played a lot more innings which more or less would explain that growth.  And his UZR/150 went from 14.0 in 2015 to 8.7 now in 2016.  So these metrics both seem to think Orlando is the same if not a little worse than '15.

Projecting using orlando's earlier year is, like Cain, excellent. an R2 of .90 between the two data sets.


Conclusions:

So for my questions:
1) Are the hit likihood percentages projectable year to year? This seems to be a resounding yes, at least in the case of KC royals.  The R2 was always greater than 0.5 with two instances of the four being over 0.9!  I'm starting to believe this really could mean something in regards to defense evaluation.
2) How does my angle measure compare to UZR/DRS?  There does seem to be some differences; however, this is basically the norm in the "new" defense evaluations.  No universal system  has been developed and there are plenty of cases where UZR and DRS themselves have disagreements.

I do think in the end this has some merit and i will be looking further into it.  I also think similar work can be down with regards to hit speed, as i already alluded to in my earlier article

 http://www.fangraphs.com/community/using-statcast-to-substitute-the-kc-outfield-for-detroits/

i think it's important to view both the angle and hit speed as two pieces and going forward that's something i'm hoping to include for these players.

Using Statcast data to substitute the KC outfield for the Detroit outfield

As I write this post the KC outfield defense is rank #1 is defensive runs saved (DRS) with 43 (per fangraphs) and is #2 in UZR at 28.6 (1st is CHC with 29.0).  KC sports one of the best, if not the best defensive outfields in the majors this season.

Detroit on the other hand has a fairly poor one.They rank last in DRS, with -44, and last in UZR at -31.8.  Though Baltimore gives them a good run for their money, Detroit is probably the worst defensive outfield in the majors so far this season.

So I wondered if we could do an analysis to show what would happen if we substituted them entirely for one another?  How would that work.  Well, one simple approach would be to just use the DRS metrics for each team and basically say that DET would go from -44 to +43, so that's a swing of +77 runs. Using the 10 runs per Win thumbrule, that'd be a pretty big swing, nearly 8 games. Detroit is a whole lot better.   But i'm not sure this method is really the best we can do. After all we have all this statcast data now. Could we use that?

I set out to try to do just that.  So my first step was to hypothesis that the likelihood of a ball hit to the outfield actually dropping for a base hit could be correlated to the launch angle provided by statcast and then that this likelihood would change depending on the team.  So to test this theory out i went to baseballsavant and grabbed all the statcast data for balls hit to the outfield for KC and for Detroit.

The KC data consisted of 1722 balls hit to the OF (when removing the few points that had NULL data for launch angle).  I took these 1722 points and bucketed them by launch angle in buckets that were 2 degrees each.  I then calculated the percentage of hits to total (hits + outs) for each bucket.  This percentage was the likelihood that a ball hit to the outfield at a certain launch angle would end up being a base hit.  This led me to my first realization, which was that anything that was basically < 8 degrees on launch angle (so including all negative angles), and made it to the OF, was a guaranteed hit.

The results of this analysis for the 1722 KC points made a lot of sense intuitively. As the launch angle increased, so did the likelihood that it was an out, so my hit percentage trend went down. Using a simple linear regression projecting the likelihood % of a hit by angle had a 92.5% R^2.  This equation was going to work nicely.

I then considered running the same drill but this time using exit velocity of the hit to see how that impacted the likelihood of a ball being a hit.  There have been at least a couple article written on this topic, and the results i got matched up with the projections I had seen in other articles on the topic.  That's to say the trend isn't linear, but more parabolic. Using a simple 2nd order polynomial trend, a very reasonable projection could again be made of a hit likelihood based on the exit velocity of a ball hit to the OF.

Using these two points of data for any ball put in play to the outfield (exit velocity and launch angle) it seems as though OF defense could be projected fairly reasonably.

I proceeded to re-run those same drills using baseballsavant's detroit outfield data. Launch angle provided another great fit, 95% R^2 and a slightly higher overall trendline than KCs (notice the higher y-intercept or "b" value).  KC's OF was almost 4% more likely to catch a ball just from the "b" value. 

Using a simple 2nd order poly trend for Detroit's exit velocity also resulted again in an 85% R^2, very similar to that of KC.  It also showed the expected parabolic action.

What I now had was a way to project the likelihood of the KC outfield or the DET outfield making a play on any ball hit to the outfield.  All i needed to know was what the angle and exit velocity was.  Lucky for us, statcast gives us all that information.

My next step was to take all the OF plays to made by Detroit and, using my new found Detroit projection system, project the number of real hits based on the hit events to the OF.  My Detroit projection system projected 1089 hits, in reality there were 986 hits. Not perfect, and something that could undergo some more tweaking, but reasonable.  My projection system was overly simplistic, i took the % likelihood from the Angle x % likelihood from the Exit Velocity.   If the multiplication was > 25% (i.e. 50% for each as the minimum threshold) then i projected a hit, else, an out.

So my Detroit projecting Detroit resulted in 1089 hits.  When i substituted the KC projection equations in, the Detroit projected hit to the OF dropped to 903.  This was a reduction of 186 expected hits!  Wow. That's some serious work the KC outfielders would've done.

The last step here was then to attempt to convert this reduction in hits to a reduction in runs.  I grabbed fangraphs year to date pitching stats by team and used that to do a simple regression on hits allowed to runs allowed.  

This showed strong correlation with a ~77% R^2.  Using the slope of this equation it shows that each hit allowed correlates to 0.7298 runs,  This means that a reduction of 186 hits would correlate to a reduction of 135.7 runs! Again, using the 10 run thumb rule, that's a nearly 14 win move. That's amazing improvement.   Now of course we are expecting drastic improvement, we're talking about replacing the worst OF defense in the league with the best!

Conclusions:

Are there some bold assumptions made here, yes. However, I do think it's a fairly reasonable approach.  It's fun to see all the different ways this new statcast data can be used.This same drill could be run on all sorts of "swap" evaluations and could be a whole lot of fun for a variety of what-if scenarios. I enjoyed attempting to answer this question using the new data and hopefully you found this entertaining as well!

Inside Edge fielding data vs UZR (ultimate zone rating) and DRS (defensive runs saved) for OF defense.

Fangraphs so generously gives us access to the "Inside Edge" fielding data., see their process per fangraphs link HERE.

What interested me is how this more "qualitative" approach to the data seems to compare to the more quantitative approaches of DRS and UZR.

Inside Edge bins plays into a variety of categories which is an assigned a percent chance of making the play. These bins are:

0% chance
1-10% chance
10-40% chance
40-60% chance
60-90% chance
90-100% chance

So I grabbed this data from Fangraphs as far back as the inside edge info was provided (2012) for all players who played >10 innings. DATASET

I then used this data to arrive at average conversion percentages for the various bins. I arrived at the following:

0% -> 0%
1-10% --> 6.191%
10-40% --> 29.078%
40-60% --> 51.822%
60-90% --> 79.694%
90-100% --> 98.866%

phew, the buckets make mathematical sense with their analytical projections. good job inside edge.

Ok, so what this "sort of" allows us to do is determine the expected number of plays a player should make versus the real plays converted and we can see if players were making an above or below average number of players in accordance with their Inside Edge analysis. Based on that approach i calculated a fielding edge (FE) "FE Score".  This shows how many extra plays above the league average expectation this individual made.  To see if this makes sense i've listed the top 20 individual seasons alongside the UZR and DRS for that player's season as well.  This list passes a quick smell test as right away you see 2014 Jason Heyward is #1 alongside other defensive wizards Alex Gordon, Billy Hamilton, Kevin Pillar and Kevin Kiermaier.

Ranks Season Name Team Innings FE Score Total UZR DRS 1 2014 Jason Heyward ATL 1317.0 16.96 24.1 26 2 2014 Jacoby Ellsbury NYY 1237.0 13.79 0.5 -3 3 2014 Alex Gordon KCR 1372.2 12.38 25 26 4 2012 Michael Bourn ATL 1340.1 11.45 23.3 23 5 2014 Nick Markakis BAL 1314.1 11.00 6.2 1 6 2016 Billy Hamilton CIN 815.2 10.99 11.6 11 7 2015 Kevin Pillar TOR 1382.0 10.74 15.2 22 8 2012 Ben Revere MIN 1061.1 10.24 14.9 10 9 2014 Billy Hamilton CIN 1199.1 10.18 20.1 14 10 2015 Billy Hamilton CIN 975.2 9.97 14.5 8 11 2013 Denard Span WSN 1300.2 9.62 10.2 3 12 2013 Brandon Barnes HOU 1034.2 9.35 5.9 5 13 2016 Kevin Pillar TOR 967.2 9.30 21.1 17 14 2015 Ben Revere - - - 1241.1 8.93 -4.4 -1 15 2015 Kevin Kiermaier TBR 1188.2 8.75 30 42 16 2013 Andrew McCutchen PIT 1378.0 8.72 6.9 5 17 2013 Gerardo Parra ARI 1355.1 8.56 31.1 37 18 2014 Brett Gardner NYY 1252.1 8.31 2.4 4 19 2014 Kevin Kiermaier TBR 824.2 8.00 17.7 14 20 2014 Sam Fuld - - - 863.2 7.72 14.6 3

So now lets do a little bit of what we set out to do and see if UZR and DRS have anything majorly different.  Well you see right away, 2014 Jacoby Ellsbury appears to have some significant beef.  All of the top 3 come from 2014 and look remarkably similar in innings and FE Score, but UZR and DRS show Ellsbury as an outlier.  A deeper look at '14 jacoby doesn't really give any indication why or how his score is so low. It appears the only big difference is that of the 3 aforementioned players, Ellsbury is the only one who actually played the more difficult CF position and he's then docked for that because the CF position has a stronger "average" than the corner slots occupied by Heyward and Gordon. 

Now lets try to look for players the FE Score system says aren't that great, but DRS says are:

Season	Name	Team	Innings	FE Score Total	UZR	DRS
2016	Colby Rasmus	HOU	757.0	-0.16	12.9	17
2014	Leonys Martin	TEX	1247.1	-0.24	11.3	16
2015	Rusney Castillo	BOS	614.1	-0.77	10.4	15
2015	Leonys Martin	TEX	673.1	-0.96	8.5	15
2016	Starling Marte	PIT	916.0	-1.80	-0.5	13
2016	Adam Duvall	CIN	886.0	-1.09	6.2	12
2016	Paulo Orlando	KCR	764.1	-1.59	1.2	12
2016	Lorenzo Cain	KCR	768.1	-0.20	8.9	11
2015	Eddie Rosario	MIN	1035.2	-1.56	7.4	11
2012	Ben Zobrist	TBR	541.1	-0.46	10.3	10
2014	Yoenis Cespedes	- - -	1125.2	-5.58	8.4	10
2014	Marcell Ozuna	MIA	1308.2	-0.41	3.3	9
2012	Giancarlo Stanton	MIA	1034.1	-3.52	9.1	9
2016	Mallex Smith	ATL	414.0	-0.50	2.8	8
2014	A.J. Pollock	ARI	585.1	-0.62	7.1	8
2015	Christian Yelich	MIA	1069.1	-0.63	-3.7	8
2015	Justin Upton	SDP	1260.1	-2.30	2	8
2015	Paulo Orlando	KCR	604.1	-3.05	6.1	8
2016	Randal Grichuk	STL	627.0	-4.04	-3	8

These are the top 20 DRS seasons with a negative FE score.  A negative FE score means that their "fielding edge" was actually negative plays, so from the list 2016 starling marte has already misplayed 1.8 plays this season; however, per DRS marte has 13 DRS.  He's an interesting case here becuase UZR and DRS clearly have a stark disagreement on his performance as well.  There are several quite outlandish cases though, notably 2014 Yoenis Cespedes who clocks in at highly positive UZR and DRS numbers but a -5.58 in FE!! What is going on here?  This shows one of the FE score's flaws, or maybe somethign that UZR and DRS overvalue and that's "Arm".  Cespedes has huge score for his ARM in both DRS and UZR rating, and that's not taken into account for the FE calculation.  Looking at the inside edge fielding data it shows that, per the buckets, cespedes was pretty bad. Converting 0 (zero) plays within the 0%, 1-10%, and 10-40% buckets.  Nada. He converted 25% of the 40-60% bucket (league average 51.8%) and 69% of the 60-90% bucket (league average 79.6%).  So yes, he performed poorly, but got a great ARM score (i presume from throwing out a lot of runners that year).  One has to wonder, when looking at these numbers, if missing those easier plays setup Cespedes to have great opportunities to throw out runners or just more opportunities, which in turn helped up his ARM score.  That'd be an interesting analysis.  That same trend holds true for Leonys Martin, who occupies 2 of the top 4 spots on the list. As he has incredibly high ARM scores, but terrible performance on achievable plays, per the inside edge analysis of 2015, Leonys only made 1 play all year that was below the 60-90% likelihood (that single play feel inside the 10-40% bucket).

Conclusions:

I think this data and approach using the inside edge data to calculate a Fielding Edge (FE) score does is offer an alternative bit of insight into defense; given the somewhat sporadic nature of the data.  In fact i'd argue it's more important, and  yet easier to understand than UZR and DRS.  Those systems go out of their way to try to over complicate and account for variables that in reality are just not in reality, meaningless.  When i saw this data it shows that over this period of time 2012-mid august 2016, 91748 OF plays have occurred of which 19.1% had a 0% chance of being converted and 70.5% were virtual sure things (90-100%).  This leaves 10.3% of plays as ones where you really have to take advantage of your OF skill level and of that 10.3%, 7+% of that is worse than a coin-flip 50/50 shot at converting.  We're talking about so few outs over the course of the season that it's unlikely impact the game in the significant way many saber analysts (or jason heyward fans.. i'm looking at you theo epstein.. talk about terrible deals) would love to think.

Now this doesn't address the fact that yes, part of what these great outfielders, heyward, the kevins, do is get to more balls than other guys. I get it and it's an important piece to understand that as well, but that's closer to a zero sum game where the venn diagrams of overlapping outfielders probably give more credit to guys than credit is truly due.

i'm going to look more into this data and maybe highlight specific areas i think are odd going forward as this just seems like a fruitful area.  My whole list of players and their scores is shown below.

Ranks	Season	Name	Team	Innings	FE Score Total	UZR	DRS
1	2014	Jason Heyward	ATL	1317.0	16.96	24.1	26
2	2014	Jacoby Ellsbury	NYY	1237.0	13.79	0.5	-3
3	2014	Alex Gordon	KCR	1372.2	12.38	25	26
4	2012	Michael Bourn	ATL	1340.1	11.45	23.3	23
5	2014	Nick Markakis	BAL	1314.1	11.00	6.2	1
6	2016	Billy Hamilton	CIN	815.2	10.99	11.6	11
7	2015	Kevin Pillar	TOR	1382.0	10.74	15.2	22
8	2012	Ben Revere	MIN	1061.1	10.24	14.9	10
9	2014	Billy Hamilton	CIN	1199.1	10.18	20.1	14
10	2015	Billy Hamilton	CIN	975.2	9.97	14.5	8
11	2013	Denard Span	WSN	1300.2	9.62	10.2	3
12	2013	Brandon Barnes	HOU	1034.2	9.35	5.9	5
13	2016	Kevin Pillar	TOR	967.2	9.30	21.1	17
14	2015	Ben Revere	- - -	1241.1	8.93	-4.4	-1
15	2015	Kevin Kiermaier	TBR	1188.2	8.75	30	42
16	2013	Andrew McCutchen	PIT	1378.0	8.72	6.9	5
17	2013	Gerardo Parra	ARI	1355.1	8.56	31.1	37
18	2014	Brett Gardner	NYY	1252.1	8.31	2.4	4
19	2014	Kevin Kiermaier	TBR	824.2	8.00	17.7	14
20	2014	Sam Fuld	- - -	863.2	7.72	14.6	3
21	2012	Mike Trout	LAA	1225.2	7.71	13.3	19
22	2016	Mookie Betts	BOS	1018.1	7.65	11.8	16
23	2014	Ben Revere	PHI	1199.0	7.61	-6.4	-16
24	2013	Josh Reddick	OAK	966.1	7.50	16.4	13
25	2016	Adam Eaton	CHW	1042.0	7.50	22.2	21
26	2012	Ichiro Suzuki	- - -	1346.1	7.49	13.1	5
27	2012	Michael Brantley	CLE	1237.0	7.48	-0.7	0
28	2015	George Springer	HOU	885.1	7.48	3.3	6
29	2014	Khris Davis	MIL	1156.1	7.47	3.1	4
30	2016	Jason Heyward	CHC	916.2	7.40	17.2	16
31	2014	Desmond Jennings	TBR	1033.1	7.23	4.9	4
32	2013	Carlos Gomez	MIL	1242.0	7.23	24.4	32
33	2016	Ender Inciarte	ATL	786.0	7.15	11.2	13
34	2013	Mike Trout	LAA	1308.2	7.07	4.4	-11
35	2012	Alex Gordon	KCR	1424.1	7.05	14.6	24
36	2013	Carlos Gonzalez	COL	857.0	7.04	7.1	11
37	2013	Will Venable	SDP	1072.1	6.92	-2.3	1
38	2012	Denard Span	MIN	1073.1	6.78	7.7	19
39	2012	Ryan Braun	MIL	1318.0	6.73	4.7	6
40	2012	Cameron Maybin	SDP	1210.1	6.70	4	7
41	2013	Chris Denorfia	SDP	1024.1	6.69	16.3	18
42	2015	Alex Gordon	KCR	864.2	6.65	6.9	7
43	2015	Jason Heyward	STL	1268.1	6.64	22.6	24
44	2014	Mike Trout	LAA	1314.0	6.52	-9.8	-12
45	2015	Jake Marisnick	HOU	923.0	6.44	9.3	13
46	2013	Alex Gordon	KCR	1364.1	6.43	8.6	17
47	2016	Ben Revere	WSN	640.0	6.32	2.6	1
48	2013	Gregor Blanco	SFG	1022.2	6.31	11.8	13
49	2014	Adam Eaton	CHW	1043.2	6.27	-3.3	11
50	2014	Ichiro Suzuki	NYY	886.2	6.24	-0.9	1
51	2013	Jay Bruce	CIN	1438.2	6.23	10.2	16
52	2013	Nick Markakis	BAL	1381.0	6.19	-6.6	-7
53	2014	Christian Yelich	MIA	1258.2	6.18	9.9	11
54	2016	Giancarlo Stanton	MIA	856.1	6.08	-1.5	3
55	2014	Brock Holt	BOS	382.1	5.97	3.5	9
56	2015	Anthony Gose	DET	1120.0	5.94	-10.4	-12
57	2013	Jason Heyward	ATL	861.2	5.94	12.5	14
58	2014	Lorenzo Cain	KCR	1111.2	5.92	17.6	22
59	2015	Kole Calhoun	LAA	1383.2	5.92	13.8	6
60	2014	Jackie Bradley Jr.	BOS	1012.0	5.91	13.8	15
61	2014	Juan Lagares	NYM	945.0	5.87	18.6	26
62	2014	George Springer	HOU	679.0	5.85	-4.7	-2
63	2014	Gerardo Parra	- - -	1161.0	5.80	0.1	0
64	2015	Michael Brantley	CLE	1034.2	5.76	-3.3	-2
65	2016	George Springer	HOU	992.0	5.75	7.9	15
66	2013	A.J. Pollock	ARI	965.2	5.75	17.2	12
67	2013	Ichiro Suzuki	NYY	1133.1	5.75	11.1	10
68	2012	Roger Bernadina	WSN	503.2	5.60	1.9	-1
69	2014	Andrew McCutchen	PIT	1286.0	5.55	-10.8	-13
70	2014	Brandon Barnes	COL	516.0	5.51	0.1	4
71	2015	Ender Inciarte	ARI	1063.1	5.44	14.5	29
72	2015	Billy Burns	OAK	1066.0	5.32	-5.2	4
73	2015	Justin Maxwell	SFG	554.1	5.29	7.1	5
74	2013	Brett Gardner	NYY	1166.1	5.28	-0.5	5
75	2012	Shane Victorino	- - -	1351.1	5.27	4.9	7
76	2012	Jarrod Dyson	KCR	699.0	5.10	2.4	4
77	2015	Michael Bourn	- - -	1043.2	5.07	0.1	6
78	2012	Jason Heyward	ATL	1355.2	5.03	22.8	17
79	2015	Mike Trout	LAA	1362.2	5.03	0.2	5
80	2016	Joc Pederson	LAD	773.2	5.02	-1.5	4
81	2014	Hunter Pence	SFG	1426.0	5.00	3.9	-1
82	2014	Yasiel Puig	LAD	1233.0	4.99	-2.3	-1
83	2015	Lorenzo Cain	KCR	1192.1	4.98	14.1	18
84	2015	Chris Coghlan	CHC	898.2	4.98	9.5	0
85	2013	Sam Fuld	TBR	512.1	4.94	0	2
86	2014	Denard Span	WSN	1302.2	4.90	-4.7	-2
87	2013	Coco Crisp	OAK	919.0	4.86	0.1	3
88	2012	Jose Bautista	TOR	775.2	4.85	1	6
89	2013	J.B. Shuck	LAA	807.2	4.84	-4.6	-2
90	2013	Dexter Fowler	COL	921.1	4.77	-1.9	-4
91	2014	Carlos Gomez	MIL	1269.2	4.76	5.8	0
92	2014	Charlie Blackmon	COL	1201.1	4.73	-1.8	2
93	2013	Shane Victorino	BOS	1021.1	4.73	24	23
94	2014	Collin Cowgill	LAA	682.1	4.73	8.1	7
95	2013	Cody Ross	ARI	712.0	4.69	12.6	19
96	2012	Gregor Blanco	SFG	878.1	4.65	10.7	7
97	2014	Will Venable	SDP	955.2	4.62	5.5	10
98	2014	Giancarlo Stanton	MIA	1262.1	4.62	1.6	6
99	2014	Eric Young	NYM	580.1	4.58	8.8	5
100	2012	Ryan Sweeney	BOS	467.1	4.57	4	5
101	2014	Peter Bourjos	STL	649.1	4.54	8.9	7
102	2014	Marlon Byrd	PHI	1337.1	4.51	3.8	9
103	2015	Jackie Bradley Jr.	BOS	608.1	4.50	10.1	8
104	2015	Bryce Harper	WSN	1304.0	4.46	-2.4	9
105	2013	Robbie Grossman	HOU	555.2	4.46	-8.4	-3
106	2012	Tyler Colvin	COL	723.1	4.45	-2.2	2
107	2012	Gorkys Hernandez	- - -	344.0	4.40	-0.3	-2
108	2014	Wil Myers	TBR	676.1	4.39	1.3	-8
109	2015	Juan Lagares	NYM	1003.2	4.38	3.5	2
110	2012	Coco Crisp	OAK	972.2	4.37	-2.1	0
111	2013	Jon Jay	STL	1285.2	4.35	-7.3	-10
112	2013	Marlon Byrd	- - -	1200.0	4.34	2.4	8
113	2013	Jonny Gomes	BOS	656.0	4.28	-2.7	0
114	2014	Josh Reddick	OAK	882.1	4.23	4.8	10
115	2012	Nate McLouth	- - -	584.1	4.20	-2	-1
116	2013	Colby Rasmus	TOR	1002.2	4.20	11.2	12
117	2014	Nate McLouth	WSN	318.0	4.19	-1.3	-2
118	2015	Nick Markakis	ATL	1330.1	4.16	-3.7	-6
119	2014	Craig Gentry	OAK	560.0	4.16	6.7	9
120	2014	Kole Calhoun	LAA	1036.1	4.14	5.7	1
121	2013	Craig Gentry	TEX	647.2	4.10	14.3	11
122	2015	Michael Conforto	NYM	389.2	4.09	7.5	9
123	2014	David Lough	BAL	500.1	4.08	11.1	10
124	2012	Marlon Byrd	- - -	362.0	4.08	-0.2	2
125	2014	Kevin Pillar	TOR	281.2	4.07	3.2	3
126	2016	Jake Marisnick	HOU	504.1	4.07	2	16
127	2012	Matt Kemp	LAD	911.0	4.06	-9	-10
128	2016	Travis Jankowski	SDP	504.0	4.06	11.6	7
129	2013	Michael Brantley	CLE	1297.1	4.04	-4.1	4
130	2012	David Murphy	TEX	1025.0	4.01	7.8	5
131	2014	Allen Craig	- - -	690.2	3.97	0.6	3
132	2012	Lorenzo Cain	KCR	493.0	3.97	7.3	5
133	2012	Travis Snider	- - -	348.1	3.96	0	2
134	2012	Nori Aoki	MIL	1092.0	3.95	-0.9	3
135	2015	Mookie Betts	BOS	1254.0	3.94	0	10
136	2014	Anthony Gose	TOR	656.1	3.94	9.2	2
137	2012	Jon Jay	STL	993.1	3.93	3.7	1
138	2016	Kole Calhoun	LAA	1026.1	3.93	4	1
139	2012	Peter Bourjos	LAA	501.2	3.93	16.3	9
140	2014	Carlos Gonzalez	COL	525.2	3.91	-3.5	-5
141	2012	Vernon Wells	LAA	589.0	3.88	0.9	-1
142	2015	Josh Reddick	OAK	1184.1	3.78	-1.7	1
143	2012	Drew Stubbs	CIN	1107.1	3.74	7.2	1
144	2016	Carlos Gonzalez	COL	927.1	3.74	1.8	4
145	2015	Michael Taylor	WSN	1100.2	3.71	12.4	5
146	2015	Andre Ethier	LAD	919.2	3.69	1.3	2
147	2014	Nate Schierholtz	- - -	755.1	3.68	5.5	10
148	2016	Khris Davis	OAK	572.2	3.64	0	2
149	2015	Brandon Barnes	COL	638.0	3.64	-1.5	-5
150	2012	Austin Jackson	DET	1184.0	3.63	3.5	6
151	2014	Jim Adduci	TEX	206.1	3.62	6.9	5
152	2015	Yoenis Cespedes	- - -	1334.2	3.57	15.6	11
153	2013	Michael Bourn	CLE	1098.1	3.57	-0.5	2
154	2014	Daniel Robertson	TEX	396.2	3.51	1.2	-1
155	2013	Jacoby Ellsbury	BOS	1188.1	3.48	10	13
156	2013	Endy Chavez	SEA	572.2	3.47	-7.4	-5
157	2014	L.J. Hoes	HOU	328.1	3.46	-0.9	7
158	2013	Sean Rodriguez	TBR	287.0	3.46	3.8	2
159	2014	Jarrod Dyson	KCR	691.1	3.46	18	13
160	2012	Gerardo Parra	ARI	841.2	3.43	7.6	9
161	2015	Andrew McCutchen	PIT	1374.2	3.40	-4.5	-8
162	2012	Jacoby Ellsbury	BOS	611.1	3.40	3	2
163	2015	Joc Pederson	LAD	1223.0	3.40	-3.9	-3
164	2013	Matt Tuiasosopo	DET	365.2	3.38	1.6	-3
165	2014	Melky Cabrera	TOR	1173.2	3.36	-5.8	-5
166	2013	Nori Aoki	MIL	1297.1	3.35	3.2	10
167	2016	Byron Buxton	MIN	508.1	3.34	2.8	5
168	2014	Dustin Ackley	SEA	1130.0	3.33	7.6	8
169	2012	Juan Pierre	PHI	799.2	3.33	0	3
170	2014	Curtis Granderson	NYM	1328.1	3.32	-11	-5
171	2013	Yasiel Puig	LAD	838.2	3.32	3.3	8
172	2012	Eric Young	COL	244.2	3.31	3.3	4
173	2016	Curtis Granderson	NYM	909.1	3.23	-6.8	-3
174	2013	Laynce Nix	PHI	179.0	3.23	1.3	3
175	2012	Andre Ethier	LAD	1265.1	3.22	-1.9	0
176	2014	Aaron Hicks	MIN	528.0	3.20	-3.9	-3
177	2014	Chris Denorfia	- - -	691.0	3.20	5.8	2
178	2015	Yasiel Puig	LAD	638.0	3.20	2	2
179	2013	Collin Cowgill	- - -	366.2	3.18	1.3	2
180	2013	Chris Heisey	CIN	455.0	3.17	8.5	7
181	2013	Daniel Nava	BOS	971.0	3.17	-10.8	-3
182	2012	Nick Swisher	NYY	907.2	3.15	3.2	2
183	2016	Albert Almora	CHC	177.2	3.11	5.3	4
184	2012	Trayvon Robinson	SEA	367.1	3.10	3.5	2
185	2013	Justin Maxwell	- - -	567.0	3.10	-1.1	-5
186	2013	Ryan Sweeney	CHC	428.2	3.09	2.8	-4
187	2016	Alex Gordon	KCR	764.2	3.07	3.3	4
188	2016	Desmond Jennings	TBR	485.2	3.07	-4	6
189	2013	Carl Crawford	LAD	835.2	3.06	8.6	0
190	2012	Craig Gentry	TEX	654.0	3.00	14.2	15
191	2012	Brandon Barnes	HOU	227.1	2.97	5.3	4
192	2013	Alejandro De Aza	CHW	1315.1	2.94	-2.5	-17
193	2015	Adam Jones	BAL	1168.2	2.94	7.1	4
194	2013	Lorenzo Cain	KCR	948.0	2.91	20	23
195	2015	Gregory Polanco	PIT	1280.1	2.90	6.8	12
196	2013	Aaron Hicks	MIN	701.1	2.89	-6.9	2
197	2014	Michael Saunders	SEA	556.2	2.88	3.6	5
198	2013	Ben Revere	PHI	708.0	2.88	-2.3	-3
199	2016	Yasiel Puig	LAD	618.2	2.88	0.2	6
200	2015	Carlos Gomez	- - -	959.2	2.87	5	6
201	2014	Dexter Fowler	HOU	959.0	2.87	-21.8	-20
202	2015	Trayce Thompson	CHW	295.1	2.86	2.5	3
203	2012	Andres Torres	NYM	904.2	2.85	2.1	4
204	2013	Juan Perez	SFG	218.0	2.85	13.7	10
205	2012	Quintin Berry	DET	644.0	2.83	-1.9	-4
206	2014	Michael Bourn	CLE	925.2	2.83	-9.4	-5
207	2016	Joey Rickard	BAL	593.0	2.82	-9.8	-7
208	2015	Shane Robinson	MIN	458.0	2.78	2.7	3
209	2015	Starling Marte	PIT	1289.1	2.78	8.8	24
210	2013	Hunter Pence	SFG	1431.1	2.77	5.5	-8
211	2014	Moises Sierra	- - -	418.1	2.76	0.9	2
212	2013	Clete Thomas	MIN	727.1	2.73	6.1	3
213	2014	Daniel Nava	BOS	774.2	2.72	11.9	17
214	2013	Eric Young	- - -	1083.1	2.71	-1.9	-7
215	2012	Andy Dirks	DET	605.1	2.70	-5.3	1
216	2013	Logan Schafer	MIL	663.0	2.68	3.6	9
217	2014	Robbie Grossman	HOU	865.0	2.64	3.4	6
218	2015	Khris Davis	MIL	871.1	2.64	-6	-6
219	2012	David DeJesus	CHC	1125.1	2.62	-4.5	-6
220	2015	Brett Gardner	NYY	1264.2	2.61	-2.7	1
221	2014	Jordan Danks	CHW	306.2	2.60	0.7	-3
222	2013	Khris Davis	MIL	265.0	2.60	-3.1	-2
223	2012	Endy Chavez	BAL	365.0	2.58	0.2	1
224	2016	Peter Bourjos	PHI	745.2	2.56	1.4	0
225	2015	Coco Crisp	OAK	253.1	2.55	1.9	1
226	2012	Shin-Soo Choo	CLE	1331.2	2.53	-16.7	-10
227	2016	Christian Yelich	MIA	966.1	2.52	0.1	5
228	2015	Randal Grichuk	STL	719.2	2.48	2.9	7
229	2014	Josh Hamilton	LAA	668.2	2.48	-0.3	-1
230	2013	Marcell Ozuna	MIA	628.2	2.44	9.6	4
231	2012	Chris Heisey	CIN	738.0	2.44	2.5	-3
232	2012	Brett Jackson	CHC	313.1	2.44	0.9	-1
233	2016	Charlie Blackmon	COL	911.1	2.43	-1.9	4
234	2015	Jarrod Dyson	KCR	560.2	2.43	8.1	11
235	2014	Adam Jones	BAL	1368.1	2.41	8.3	3
236	2015	Daniel Robertson	LAA	177.0	2.41	2.5	5
237	2012	Melky Cabrera	SFG	979.2	2.39	-0.8	1
238	2012	Martin Prado	ATL	985.2	2.39	11	11
239	2013	Seth Smith	OAK	447.1	2.38	2.2	0
240	2012	Desmond Jennings	TBR	1100.2	2.38	10.5	10
241	2012	Chris Coghlan	MIA	221.2	2.36	-3.3	-3
242	2014	Matt Joyce	TBR	729.0	2.36	0.1	1
243	2013	Jordan Schafer	ATL	493.2	2.35	1.3	2
244	2013	David Murphy	TEX	988.1	2.35	11	5
245	2014	Starling Marte	PIT	1105.0	2.32	0.1	5
246	2014	Ender Inciarte	ARI	909.0	2.30	19.2	20
247	2013	David Lough	KCR	708.0	2.29	14.5	14
248	2013	Kole Calhoun	LAA	420.2	2.26	-3.3	-6
249	2016	Kevin Kiermaier	TBR	563.2	2.24	7.8	16
250	2015	Stephen Piscotty	STL	480.2	2.22	-2.5	-4
251	2012	Brennan Boesch	DET	909.2	2.21	-11.8	-6
252	2015	David DeJesus	- - -	486.2	2.21	1.5	3
253	2012	Reed Johnson	- - -	506.1	2.20	-2.7	-3
254	2014	Jake Marisnick	- - -	534.0	2.20	8.4	15
255	2013	Jayson Werth	WSN	1072.0	2.19	-3.3	0
256	2015	Jason Bourgeois	CIN	370.0	2.19	-6.1	-7
257	2015	David Lough	BAL	376.2	2.18	-0.5	7
258	2016	Juan Lagares	NYM	324.1	2.18	4.9	7
259	2016	Michael Bourn	ARI	609.1	2.18	-1.9	1
260	2013	Alex Presley	- - -	378.1	2.16	-4.7	-4
261	2015	Aaron Altherr	PHI	323.1	2.16	7.3	5
262	2013	Franklin Gutierrez	SEA	305.1	2.15	-2.4	-7
263	2016	Franklin Gutierrez	SEA	388.2	2.15	-0.7	-4
264	2013	Rajai Davis	TOR	722.1	2.14	-2.2	4
265	2015	Sam Fuld	OAK	705.2	2.14	6.5	9
266	2013	Shin-Soo Choo	CIN	1361.0	2.14	-15.5	-18
267	2015	Jacoby Ellsbury	NYY	948.0	2.12	-3.2	1
268	2016	Kirk Nieuwenhuis	MIL	672.2	2.11	0.6	1
269	2014	James Jones	SEA	698.1	2.08	-12.6	-11
270	2013	Roger Bernadina	- - -	507.1	2.08	2.4	3
271	2016	Jeremy Hazelbaker	STL	343.0	2.08	-3.1	0
272	2013	Alfonso Soriano	- - -	1163.1	2.05	7	3
273	2014	Michael Brantley	CLE	1304.1	2.05	-5.3	-1
274	2016	Stephen Piscotty	STL	953.0	2.04	4.9	6
275	2015	Matt Joyce	LAA	469.2	2.04	-3.5	-3
276	2012	Corey Hart	MIL	408.0	2.04	-0.4	-1
277	2013	Derrick Robinson	CIN	395.1	2.00	3	5
278	2014	Chris Heisey	CIN	544.0	1.99	12	8
279	2012	Michael Saunders	SEA	1188.1	1.99	-8.2	-10
280	2012	Sam Fuld	TBR	232.0	1.98	0.7	5
281	2013	Jordan Danks	CHW	407.1	1.96	-2.9	1
282	2015	Kirk Nieuwenhuis	- - -	278.1	1.94	1	6
283	2014	Jon Jay	STL	987.1	1.92	3.1	6
284	2016	Jake Smolinski	OAK	429.1	1.92	0.4	-5
285	2012	Justin Maxwell	HOU	693.0	1.92	4.5	6
286	2012	Jason Repko	BOS	32.0	1.92	0.4	2
287	2013	Cole Gillespie	- - -	132.1	1.91	3	2
288	2015	Gerardo Parra	- - -	1164.0	1.91	-18.1	-10
289	2012	Darin Mastroianni	MIN	397.1	1.90	9.9	5
290	2013	Desmond Jennings	TBR	1188.2	1.90	-5.8	-6
291	2012	Justin Ruggiano	MIA	662.1	1.90	0.2	0
292	2016	Mike Trout	LAA	965.1	1.90	0.6	3
293	2014	David Peralta	ARI	726.1	1.89	-0.2	3
294	2014	Rajai Davis	DET	1058.0	1.88	-8	-10
295	2013	John Mayberry	PHI	811.1	1.88	-7.7	-13
296	2012	Andrew McCutchen	PIT	1364.0	1.88	-8.8	-6
297	2012	Dexter Fowler	COL	1026.0	1.87	-13.6	-12
298	2012	Jordan Schafer	HOU	692.2	1.86	-3.9	-5
299	2014	Josh Harrison	PIT	362.1	1.84	1.6	4
300	2014	Carl Crawford	LAD	736.0	1.83	3.6	1
301	2012	Garrett Jones	PIT	467.0	1.81	-2.4	-4
302	2016	Sean Rodriguez	PIT	135.0	1.81	1.8	2
303	2015	Abraham Almonte	- - -	531.0	1.80	0.9	2
304	2014	Scott Van Slyke	LAD	393.1	1.80	3.9	4
305	2016	Max Kepler	MIN	630.2	1.78	-1.2	3
306	2016	Adam Jones	BAL	986.0	1.77	-7.9	-10
307	2013	Justin Ruggiano	MIA	945.0	1.77	-3.3	-5
308	2015	J.B. Shuck	CHW	297.0	1.76	-4.9	2
309	2014	Gregor Blanco	SFG	890.2	1.73	2.7	0
310	2014	Jose Tabata	PIT	307.0	1.73	-3.7	2
311	2014	Emilio Bonifacio	- - -	538.0	1.71	5.9	4
312	2013	Shane Robinson	STL	360.1	1.71	4	8
313	2015	Dustin Ackley	- - -	518.1	1.70	-4.1	-8
314	2013	Carlos Beltran	STL	1138.1	1.68	-15.3	-7
315	2012	Nyjer Morgan	MIL	587.1	1.68	4.4	4
316	2012	Matt Diaz	ATL	182.1	1.67	-4	-4
317	2016	Brandon Barnes	COL	227.1	1.67	5.3	7
318	2013	Domonic Brown	PHI	1138.2	1.66	-10	-4
319	2014	Jose Bautista	TOR	1134.2	1.66	2.6	-1
320	2016	Melvin Upton Jr.	- - -	929.1	1.66	1.4	12
321	2014	Michael Cuddyer	COL	279.1	1.65	-1.4	-1
322	2013	Christian Yelich	MIA	544.1	1.65	-2.5	1
323	2013	Leonys Martin	TEX	1127.2	1.64	9.4	14
324	2015	Brandon Guyer	TBR	724.1	1.62	3.5	1
325	2016	Ezequiel Carrera	TOR	468.0	1.60	4.1	4
326	2012	Franklin Gutierrez	SEA	322.2	1.58	-8.8	-5
327	2015	Mikie Mahtook	TBR	225.2	1.58	4.1	-1
328	2016	Aaron Hicks	NYY	687.2	1.57	4.1	5
329	2012	Brent Lillibridge	- - -	139.1	1.55	0.9	1
330	2013	Josh Hamilton	LAA	931.1	1.55	-0.6	-6
331	2014	Randal Grichuk	STL	218.1	1.53	5.4	4
332	2013	Curtis Granderson	NYY	382.2	1.53	6.5	3
333	2013	Chris Coghlan	MIA	326.0	1.53	-5.7	-4
334	2016	Jackie Bradley Jr.	BOS	1019.1	1.52	-0.6	7
335	2015	Lonnie Chisenhall	CLE	354.1	1.52	9.3	11
336	2013	Chris Parmelee	MIN	526.0	1.49	-2.2	4
337	2014	Alex Presley	HOU	572.0	1.49	-0.5	1
338	2012	Jordan Danks	CHW	183.0	1.48	4	2
339	2015	Todd Cunningham	ATL	184.0	1.48	3.4	6
340	2015	Brock Holt	BOS	253.2	1.48	2.1	4
341	2012	Carlos Gomez	MIL	911.1	1.48	4.8	2
342	2013	Juan Lagares	NYM	904.0	1.47	24.4	28
343	2013	David DeJesus	- - -	852.2	1.46	3.7	-3
344	2014	Steve Pearce	BAL	271.0	1.46	6.3	9
345	2015	Sean Rodriguez	PIT	158.1	1.44	0.2	1
346	2012	Scott Podsednik	BOS	436.0	1.44	0.3	0
347	2012	Jimmy Paredes	HOU	119.0	1.43	-0.7	0
348	2016	Brett Eibner	- - -	191.0	1.43	5	6
349	2012	Skip Schumaker	STL	135.2	1.43	-1.3	1
350	2015	Byron Buxton	MIN	327.0	1.42	-2.3	4
351	2012	Xavier Avery	BAL	217.0	1.41	-1.4	-2
352	2013	Xavier Paul	CIN	385.0	1.41	-3.5	-11
353	2012	Mike Baxter	NYM	406.1	1.40	1	-4
354	2013	Nelson Cruz	TEX	906.1	1.37	-4.3	-3
355	2014	Dalton Pompey	TOR	90.0	1.37	0.9	-1
356	2013	Juan Pierre	MIA	564.1	1.35	-1.1	3
357	2014	Chris Coghlan	CHC	829.1	1.33	-1	-12
358	2016	David Lough	PHI	166.0	1.33	-1.4	0
359	2016	Jace Peterson	ATL	98.0	1.33	-2.8	-1
360	2014	Alfredo Marte	ARI	206.1	1.32	-1	1
361	2013	Reed Johnson	ATL	210.0	1.31	0.6	0
362	2014	Matt Szczur	CHC	138.2	1.31	-0.9	-3
363	2014	David DeJesus	TBR	109.0	1.31	-3.1	0
364	2016	Bryce Brentz	BOS	143.0	1.30	-1	-2
365	2012	Darnell McDonald	- - -	226.2	1.30	1.5	3
366	2013	Freddy Galvis	PHI	79.2	1.30	1.7	1
367	2013	Zoilo Almonte	NYY	239.0	1.30	4.2	1
368	2013	Jose Tabata	PIT	615.1	1.29	-1.3	0
369	2014	J.B. Shuck	- - -	226.2	1.29	5.8	5
370	2016	Gregory Polanco	PIT	816.2	1.29	7.2	3
371	2016	Matt Joyce	PIT	283.2	1.29	-8.1	-3
372	2014	Cody Ross	ARI	404.0	1.28	-9.7	-6
373	2016	Daniel Descalso	COL	42.0	1.27	1	1
374	2014	Alexi Amarista	SDP	144.1	1.27	1.9	3
375	2016	Kris Bryant	CHC	385.1	1.27	5.6	5
376	2012	Nick Markakis	BAL	926.0	1.26	-8.6	-7
377	2016	Chris Coghlan	- - -	223.2	1.26	-0.1	1
378	2015	Ryan Braun	MIL	1121.0	1.25	-6	-1
379	2015	Cole Gillespie	MIA	315.0	1.24	-7.7	-2
380	2012	DeWayne Wise	- - -	534.0	1.24	1.3	-2
381	2016	Michael Conforto	NYM	568.2	1.24	2.5	1
382	2012	Jose Constanza	ATL	182.0	1.23	3.5	6
383	2015	A.J. Pollock	ARI	1303.2	1.22	6.5	14
384	2012	Jason Donald	CLE	47.0	1.22	1	2
385	2014	Corey Hart	SEA	54.2	1.22	-2	-1
386	2016	Nick Markakis	ATL	1000.1	1.21	1.4	5
387	2012	Elian Herrera	LAD	207.1	1.21	0.6	3
388	2012	Chris Dickerson	NYY	59.1	1.21	0.2	-1
389	2012	Xavier Nady	- - -	319.1	1.21	-2.7	1
390	2015	Travis Jankowski	SDP	234.0	1.20	0.1	1
391	2013	Austin Jackson	DET	1145.2	1.20	-3.8	4
392	2013	Starling Marte	PIT	1108.0	1.19	10.1	20
393	2012	Andruw Jones	NYY	452.2	1.17	2.8	0
394	2013	Vernon Wells	NYY	780.0	1.15	0.3	0
395	2015	Juan Perez	SFG	70.1	1.15	2.1	2
396	2015	Travis Snider	- - -	480.1	1.15	1.9	6
397	2013	Kevin Pillar	TOR	251.0	1.15	3.2	4
398	2014	Endy Chavez	SEA	452.1	1.14	-3.1	-3
399	2013	Jarrod Dyson	KCR	571.2	1.14	10.4	6
400	2012	Bryce Harper	WSN	1188.0	1.14	9.5	14
401	2013	Mark Trumbo	LAA	201.1	1.13	-0.4	-1
402	2016	Cody Asche	PHI	400.2	1.13	-0.6	-3
403	2013	Don Kelly	DET	444.2	1.13	-3.4	-6
404	2015	Logan Schafer	MIL	268.0	1.10	-3.9	-6
405	2013	Melky Cabrera	TOR	620.2	1.09	-7.3	-4
406	2016	Mac Williamson	SFG	231.2	1.09	4	3
407	2012	Dave Sappelt	CHC	150.1	1.08	5	2
408	2015	Kristopher Negron	CIN	69.0	1.08	1.2	2
409	2015	Matt den Dekker	WSN	216.0	1.07	-1.1	2
410	2015	Dexter Fowler	CHC	1324.1	1.07	-1.7	-12
411	2014	Nori Aoki	KCR	958.1	1.06	5.9	-7
412	2013	Jaff Decker	SDP	62.1	1.06	0.3	-1
413	2014	Kiké Hernandez	- - -	225.0	1.05	2.7	4
414	2014	Tyler Holt	CLE	189.1	1.05	3.4	3
415	2013	Rick Ankiel	- - -	308.0	1.03	-4.6	-4
416	2014	Ryan Sweeney	CHC	426.2	1.03	0.5	-1
417	2012	Justin Christian	SFG	90.0	1.03	1.6	2
418	2013	Bryce Harper	WSN	993.2	1.02	2.6	4
419	2016	Rob Refsnyder	NYY	98.2	1.02	1.9	2
420	2014	David Murphy	CLE	1002.0	1.02	-11.2	-13
421	2015	Steve Pearce	BAL	361.2	1.01	-1.8	-3
422	2013	Jose Constanza	ATL	52.0	1.00	1.6	2
423	2013	Chris Herrmann	MIN	150.0	0.99	-1.2	-4
424	2013	Trevor Crowe	HOU	390.0	0.97	2.3	1
425	2014	Jake Smolinski	TEX	172.0	0.97	-0.4	1
426	2013	Martin Prado	ARI	233.1	0.96	1.4	-2
427	2014	Logan Morrison	SEA	70.2	0.96	2.6	2
428	2014	Willie Bloomquist	SEA	24.0	0.96	0.7	0
429	2013	Skip Schumaker	LAD	412.0	0.96	-3.6	-5
430	2012	Curtis Granderson	NYY	1364.1	0.96	-18.1	-7
431	2015	Derek Dietrich	MIA	354.2	0.95	-7.7	-8
432	2015	Curtis Granderson	NYM	1291.2	0.94	5.9	11
433	2012	Chris Parmelee	MIN	141.0	0.92	0.1	-2
434	2012	Jonny Gomes	OAK	281.2	0.91	-1.2	-3
435	2013	Brennan Boesch	NYY	103.1	0.91	-3.2	-1
436	2015	Allen Craig	BOS	103.0	0.90	-1.1	-1
437	2014	Justin Maxwell	KCR	108.0	0.90	-6.9	-7
438	2012	Chris Young	ARI	725.0	0.90	10	6
439	2012	Matt Joyce	TBR	957.1	0.89	-4.6	4
440	2014	Angel Pagan	SFG	775.1	0.87	-5.7	-5
441	2012	Alexi Amarista	SDP	142.2	0.86	1.7	0
442	2012	Jerry Hairston	LAD	109.0	0.86	5.6	5
443	2016	Shane Robinson	LAA	232.2	0.86	6.8	6
444	2015	Michael Cuddyer	NYM	606.2	0.86	-5.4	-3
445	2013	Tony Campana	ARI	78.1	0.86	-1.8	-1
446	2015	Peter Bourjos	STL	476.2	0.85	-3.4	-4
447	2015	David Murphy	- - -	476.1	0.84	-2.9	-4
448	2013	Peter Bourjos	LAA	415.0	0.84	-0.3	-1
449	2015	Odubel Herrera	PHI	1065.0	0.83	9.9	10
450	2015	Giancarlo Stanton	MIA	625.2	0.82	8.6	9
451	2012	Corey Brown	WSN	37.1	0.82	1.3	2
452	2016	Jarrod Dyson	KCR	523.2	0.81	11.6	13
454	2012	Francisco Peguero	SFG	36.0	0.81	4.6	6
453	2014	Zach Walters	- - -	51.2	0.81	-1.4	-1
455	2015	Aaron Hicks	MIN	849.0	0.81	1.5	1
456	2013	Jordany Valdespin	NYM	154.1	0.80	-3.2	-5
457	2015	Ramon Flores	NYY	81.0	0.79	3.6	2
458	2015	Jon Jay	STL	496.2	0.78	7.7	3
459	2014	Domonic Brown	PHI	1041.1	0.78	-9.4	-7
460	2016	Jurickson Profar	TEX	56.0	0.78	0.9	2
461	2013	Donald Lutz	CIN	84.2	0.78	1.1	1
462	2015	Jose Bautista	TOR	1038.2	0.77	-9.9	-3
463	2016	Alexi Amarista	SDP	38.0	0.77	0.5	1
464	2014	Chris Young	- - -	739.2	0.77	-4.7	1
465	2014	J.D. Martinez	DET	931.2	0.76	-1.6	0
466	2012	Josh Reddick	OAK	1279.1	0.76	17.9	15
467	2016	Darin Mastroianni	MIN	29.0	0.74	0	1
468	2016	Darin Ruf	PHI	44.0	0.74	-1.2	1
469	2012	Adam Eaton	ARI	186.0	0.74	0	1
470	2013	Matt Kemp	LAD	576.1	0.73	-16.2	-5
471	2016	Kiké Hernandez	LAD	236.2	0.73	4.1	4
472	2013	Torii Hunter	DET	1236.1	0.73	-4.1	-10
473	2013	Nick Swisher	CLE	199.0	0.72	-1	1
474	2016	Blake Swihart	BOS	113.2	0.72	1.4	1
475	2013	Ryan Braun	MIL	503.0	0.72	0.2	3
476	2013	Ben Zobrist	TBR	244.1	0.72	-2.7	-1
477	2014	Nick Swisher	CLE	44.0	0.72	-2.4	-1
478	2015	Delmon Young	BAL	333.2	0.72	-2.2	3
479	2013	Nate Schierholtz	CHC	1041.0	0.71	0.2	1
480	2012	Scott Cousins	MIA	161.0	0.69	0.5	-1
481	2012	Bryan LaHair	CHC	248.0	0.69	-5.2	-6
482	2013	Casper Wells	- - -	198.0	0.69	2.4	4
483	2012	Anthony Gose	TOR	438.0	0.68	1.4	3
484	2012	Ryan Ludwick	CIN	929.1	0.67	-4.1	-3
485	2016	Michael Brantley	CLE	89.1	0.67	1.4	1
486	2012	Carl Crawford	BOS	245.2	0.67	-1.8	1
487	2015	Marlon Byrd	- - -	1124.1	0.67	-2	1
488	2015	Shane Peterson	MIL	392.2	0.66	-1.7	4
489	2014	Roger Bernadina	- - -	131.0	0.64	-0.4	2
490	2016	Brandon Drury	ARI	485.2	0.64	-9	-6
491	2014	Kirk Nieuwenhuis	NYM	217.1	0.63	1	3
492	2014	Chris Dickerson	CLE	235.1	0.62	-1.7	1
493	2016	Guillermo Heredia	SEA	65.1	0.62	0.9	1
494	2013	Engel Beltre	TEX	95.0	0.62	1.9	1
495	2012	Tony Gwynn	LAD	578.0	0.61	2.4	0
496	2013	Scott Van Slyke	LAD	291.2	0.60	1.5	2
497	2012	Travis Buck	HOU	146.0	0.60	3.8	2
499	2015	Cliff Pennington	- - -	45.0	0.60	1.2	3
498	2013	Eury Perez	WSN	24.0	0.60	1.1	1
500	2012	Steve Lombardozzi	WSN	252.1	0.59	1.5	1
501	2014	Cole Gillespie	- - -	183.0	0.58	-1.6	-1
502	2014	Logan Schafer	MIL	285.2	0.58	3.4	3
503	2012	Don Kelly	DET	267.1	0.58	-2.6	-1
504	2015	John Mayberry	NYM	193.0	0.58	1.2	1
505	2013	Jackie Bradley Jr.	BOS	242.0	0.58	-2	-3
506	2014	Ryan Doumit	ATL	126.0	0.58	0.6	-1
507	2016	Brett Gardner	NYY	905.0	0.57	1.2	3
508	2013	Abraham Almonte	SEA	167.2	0.57	-2.4	-2
509	2015	Ryan LaMarre	CIN	61.0	0.56	0.9	0
511	2012	Jerry Sands	LAD	41.0	0.56	1	1
510	2013	Jurickson Profar	TEX	34.0	0.56	-2.5	-2
512	2015	Collin Cowgill	LAA	200.0	0.56	6.2	6
513	2012	Kole Calhoun	LAA	52.0	0.56	1.1	1
514	2016	Ryan Rua	TEX	399.0	0.56	1.3	3
515	2012	Steve Pearce	- - -	270.2	0.56	-2.4	3
516	2012	Torii Hunter	LAA	1112.2	0.55	11.2	12
517	2012	Che-Hsuan Lin	BOS	40.0	0.54	-1	0
518	2015	Darrell Ceciliani	NYM	129.1	0.54	4.2	6
519	2015	Desmond Jennings	TBR	225.0	0.54	0.1	2
520	2015	Kyle Blanks	TEX	25.0	0.53	2.2	1
521	2013	Andy Dirks	DET	950.1	0.53	10.4	8
522	2014	Jason Bourgeois	CIN	65.0	0.52	1.2	3
524	2015	Michael Reed	MIL	11.0	0.52	1.6	1
523	2016	Mitch Haniger	ARI	26.0	0.52		0
525	2016	Dustin Ackley	NYY	54.1	0.51	0.8	2
526	2016	David Dahl	COL	187.1	0.51	-1	-2
527	2014	Xavier Nady	SDP	59.0	0.51	-0.8	0
528	2014	Alejandro De Aza	- - -	1156.1	0.51	7.6	0
529	2016	Craig Gentry	LAA	93.0	0.50	1.3	2
530	2012	Lew Ford	BAL	105.0	0.50	2	2
531	2015	Joey Gallo	TEX	125.2	0.50	2.8	2
532	2015	Stefen Romero	SEA	58.1	0.49	-0.3	-1
533	2016	Kolten Wong	STL	92.0	0.49	0.1	-1
534	2016	Chase d'Arnaud	ATL	88.0	0.49	-0.3	0
535	2013	Carlos Quentin	SDP	556.0	0.49	-1.7	-5
536	2013	Elliot Johnson	- - -	49.2	0.49	-0.3	-1
537	2013	Andre Ethier	LAD	1141.0	0.49	-1	0
538	2015	Shawn O'Malley	SEA	114.0	0.48	-2.7	0
539	2015	Seth Smith	SEA	797.2	0.48	6.8	1
540	2015	Kyle Parker	COL	209.1	0.48	-0.3	-3
541	2013	Justin Upton	ATL	1259.0	0.48	-9.6	-8
542	2012	Alex Rios	CHW	1369.0	0.48	1.5	7
543	2012	Juan Rivera	LAD	301.0	0.47	-2.4	-1
544	2015	Ichiro Suzuki	MIA	823.0	0.46	7.8	6
545	2016	Matt den Dekker	WSN	73.1	0.46	1	3
546	2013	Wilkin Ramirez	MIN	171.2	0.46	0.8	0
547	2015	Melky Cabrera	CHW	1324.2	0.46	-7.4	-2
548	2013	Adam Jones	BAL	1394.0	0.45	-6.8	-1
549	2013	Matt Joyce	TBR	803.2	0.45	-0.6	-3
550	2016	Gregor Blanco	SFG	522.1	0.44	-4	-7
551	2013	Charlie Blackmon	COL	523.1	0.44	-5.4	-6
552	2013	Brandon Moss	OAK	237.2	0.44	-3.1	-3
553	2015	Alexi Amarista	SDP	56.0	0.44	-1.6	-2
554	2013	Dave Sappelt	CHC	134.0	0.43	-1.7	0
555	2014	Shane Victorino	BOS	263.2	0.43	-0.8	1
556	2013	Blake Tekotte	CHW	92.1	0.43	0.5	1
557	2016	Nori Aoki	SEA	708.1	0.42	-2.5	0
558	2012	Mitch Maier	KCR	154.0	0.42	-1.8	-5
559	2014	Darin Ruf	PHI	104.1	0.42	0	0
560	2014	Grant Green	LAA	126.0	0.42	-2.2	-1
561	2015	Daniel Nava	- - -	264.0	0.41	2.5	2
562	2015	Ben Paulsen	COL	103.2	0.41	0.6	3
563	2015	Ryan Flaherty	BAL	46.0	0.40	0	-1
564	2016	Rafael Ortega	LAA	286.2	0.40	-1.6	0
565	2015	Scott Schebler	LAD	68.0	0.40	2.6	2
566	2015	Tommy Pham	STL	328.1	0.39	0.8	3
567	2016	Kelly Johnson	- - -	77.0	0.38	-0.1	1
568	2015	James Jones	SEA	98.1	0.38	-6	-5
569	2015	Marwin Gonzalez	HOU	97.1	0.37	0.5	2
570	2015	Josh Hamilton	TEX	345.0	0.37	-0.5	0
571	2016	Corey Dickerson	TBR	333.2	0.36	3.6	-1
572	2012	Adron Chambers	STL	115.0	0.36	3.5	4
573	2015	Michael Martinez	CLE	71.0	0.36	0.5	0
574	2016	Tyler Goeddel	PHI	448.0	0.35	-3.7	-1
575	2012	David Lough	KCR	127.2	0.35	2.2	0
576	2012	Matt McBride	COL	79.0	0.34	-2.1	-2
577	2012	Chris Denorfia	SDP	735.0	0.34	-5.5	5
578	2014	Darin Mastroianni	- - -	94.1	0.34	2.1	2
579	2013	Jason Bay	SEA	481.1	0.34	-4.7	-1
580	2016	Brandon Nimmo	NYM	123.2	0.34	0.4	1
581	2012	Jeff Baker	- - -	185.0	0.34	-0.4	0
583	2014	Andrew Lambo	PIT	43.0	0.33	1.4	1
582	2015	Michael Saunders	TOR	75.1	0.33	1.2	0
584	2013	Mike Carp	BOS	259.2	0.33	-3.3	-3
585	2014	Ryan Ludwick	CIN	751.2	0.32	-4.8	-5
586	2014	Ben Zobrist	TBR	358.1	0.32	9.4	5
587	2016	Jose Bautista	TOR	637.2	0.32	-4.7	-9
588	2013	Melky Mesa	NYY	28.0	0.32	1.7	0
590	2014	Travis Ishikawa	SFG	29.0	0.31	1.4	1
589	2013	Matt Carson	CLE	50.0	0.31	0.8	0
591	2016	Scott Van Slyke	LAD	171.1	0.30	1.9	1
592	2015	Darin Ruf	PHI	153.1	0.30	0.9	-1
593	2012	Eric Hinske	ATL	63.2	0.29	-5.8	-3
594	2015	Chris Heisey	LAD	163.1	0.29	0.7	2
595	2016	Abraham Almonte	CLE	191.2	0.29	3.3	5
596	2015	Mike Aviles	CLE	256.2	0.29	1.5	-1
597	2013	Ben Francisco	NYY	32.2	0.28	0.2	1
598	2014	Antoan Richardson	NYY	42.0	0.28	1	1
599	2016	Cedric Hunter	PHI	81.1	0.27	-1.3	-2
600	2016	Andrew Romine	DET	116.0	0.27	-1.2	-2
601	2015	Tyler Moore	WSN	123.2	0.27	-1.4	-2
602	2015	Scott Van Slyke	LAD	426.0	0.27	6.3	11
603	2015	Shane Victorino	- - -	450.1	0.27	1.4	2
605	2014	Gary Brown	SFG	21.0	0.27	1.6	0
604	2013	Adron Chambers	STL	43.0	0.27	-0.8	-1
606	2015	Rajai Davis	DET	635.2	0.27	4.3	3
607	2013	L.J. Hoes	- - -	387.1	0.27	-6	-6
608	2014	Chris Carter	HOU	57.2	0.27	-0.8	-2
609	2016	Alex Presley	- - -	231.2	0.26	-3.6	-3
610	2012	Avisail Garcia	DET	121.1	0.26	-0.5	-1
611	2013	Wil Myers	TBR	655.2	0.25	1.1	-1
612	2014	Andrew Brown	NYM	69.2	0.25	-0.6	0
613	2012	Scott Van Slyke	LAD	91.2	0.25	1.9	1
614	2016	Tony Kemp	HOU	139.0	0.25	-1.1	-2
615	2012	Brandon Snyder	TEX	37.0	0.24	-0.2	0
616	2012	Laynce Nix	PHI	154.0	0.24	2.1	0
617	2016	Josh Reddick	- - -	679.2	0.24	-2.3	2
618	2013	Nate McLouth	BAL	1150.2	0.24	4	1
619	2016	Andrew Toles	LAD	75.2	0.23	-1.4	-3
620	2014	Travis Snider	PIT	612.2	0.23	-2.4	3
621	2015	Henry Urrutia	BAL	73.0	0.23	1.1	0
622	2014	Kelly Johnson	- - -	19.0	0.23	-0.1	0
623	2014	Xavier Paul	ARI	28.1	0.23	0.3	0
624	2016	Tyler Collins	DET	232.2	0.22	-3.4	-3
625	2013	Jerry Hairston	LAD	158.1	0.22	-1.2	0
626	2012	Brian Bogusevic	HOU	808.0	0.22	5	2
627	2014	Logan Forsythe	TBR	16.0	0.21	-0.7	0
628	2015	Craig Gentry	OAK	139.0	0.21	-1.9	0
629	2013	Kirk Nieuwenhuis	NYM	198.2	0.21	3	1
630	2016	Leonys Martin	SEA	916.2	0.20	3.8	0
631	2015	Robbie Grossman	HOU	127.0	0.20	-0.1	-1
632	2016	Brandon Belt	SFG	12.0	0.20	0.7	1
633	2015	Chris Denorfia	CHC	431.0	0.20	6	-1
634	2016	Dexter Fowler	CHC	715.0	0.19	0	3
635	2012	Logan Schafer	MIL	38.2	0.19	2.4	1
636	2014	Rusney Castillo	BOS	89.0	0.19	2	2
637	2015	Efren Navarro	LAA	92.0	0.19	1.7	2
638	2015	Denard Span	WSN	523.0	0.19	-4.9	-10
639	2012	Adam Jones	BAL	1458.0	0.19	-6.5	-13
640	2016	Mark Canha	OAK	34.0	0.19	-0.8	0
641	2016	Gregorio Petit	LAA	41.0	0.17	0.3	-1
642	2016	Danny Valencia	OAK	93.1	0.17	0	-1
643	2012	Johnny Damon	CLE	396.0	0.17	0.5	2
644	2013	Michael Taylor	OAK	53.0	0.17	-1	-2
645	2016	Jacoby Ellsbury	NYY	906.1	0.17	1	9
646	2016	Brandon Moss	STL	270.0	0.16	-0.1	-1
647	2012	Brett Gardner	NYY	85.1	0.15	0.5	1
648	2013	Austin Kearns	MIA	37.0	0.15	1.7	0
649	2016	Nick Franklin	TBR	133.0	0.14	-3	-4
650	2014	Michael Taylor	CHW	64.1	0.14	-1.4	0
651	2012	Ezequiel Carrera	CLE	354.1	0.13	-3	0
652	2016	Billy Burns	- - -	615.0	0.13	3	1
653	2015	Tyler Holt	- - -	81.0	0.13	1.5	0
654	2016	Matt Szczur	CHC	254.2	0.13	1.3	3
655	2012	Vinny Rottino	- - -	97.1	0.13	3.2	1
656	2012	Russ Canzler	CLE	88.0	0.13	-1.6	-1
658	2012	Jayson Nix	NYY	76.1	0.12	0.6	0
657	2012	Thomas Neal	CLE	54.0	0.12	-2.9	-2
659	2015	Socrates Brito	ARI	52.0	0.12	1.9	4
660	2013	Billy Hamilton	CIN	45.0	0.12	0.7	1
661	2015	Matt Holliday	STL	495.1	0.12	-1.4	-4
663	2013	Michael Choice	OAK	41.0	0.11	0.4	0
664	2016	Collin Cowgill	CLE	43.0	0.11	0.1	0
662	2013	Felix Pie	PIT	57.0	0.11	-2.3	-1
665	2014	Jordany Valdespin	MIA	50.1	0.11	0.9	1
666	2014	Kevin Frandsen	WSN	141.1	0.11	-1.5	-3
667	2013	Joey Terdoslavich	ATL	101.1	0.10	-0.7	0
668	2013	Scott Hairston	- - -	284.1	0.10	-4.5	-5
669	2013	Leury Garcia	CHW	38.0	0.10	1.2	1
670	2013	Willie Bloomquist	ARI	55.1	0.10	1.1	1
671	2014	Grady Sizemore	- - -	758.1	0.10	-7.9	-2
672	2013	Garrett Jones	PIT	196.0	0.09	-2	-2
673	2016	Austin Jackson	CHW	465.0	0.09	-3.5	-5
674	2016	Jaff Decker	TBR	72.0	0.09	0.6	1
680	2014	Tyler Moore	WSN	24.2	0.09	1.1	1
681	2015	Danny Santana	MIN	28.0	0.09	0.5	1
678	2013	Brett Pill	SFG	39.0	0.09	1.3	0
679	2012	Wilson Betemit	BAL	47.0	0.09	-0.3	0
676	2014	Brad Glenn	TOR	36.0	0.09	-0.5	-1
677	2012	Matt Downs	HOU	59.2	0.09	0.7	-1
675	2016	Stefen Romero	SEA	35.0	0.09	0.2	-2
682	2015	Torii Hunter	MIN	1035.2	0.09	0.3	-8
683	2015	Ryan Rua	TEX	184.0	0.09	0.1	0
684	2013	Jeff Kobernus	WSN	57.0	0.09	-0.3	-1
685	2016	Anthony Gose	DET	238.0	0.08	2	-3
688	2013	Corey Brown	WSN	30.0	0.08	0.2	1
686	2012	Matt Young	DET	15.1	0.08	0.9	0
687	2013	Nick Buss	LAD	42.0	0.08	0.6	0
689	2014	Martin Prado	NYY	91.0	0.08	-2	-1
691	2014	Yorman Rodriguez	CIN	60.0	0.07	-0.1	0
690	2013	Fernando Martinez	HOU	65.0	0.07	-3.9	-4
692	2016	Adam Frazier	PIT	73.2	0.07	0.6	1
701	2015	L.J. Hoes	HOU	37.0	0.07	0.8	2
699	2016	Phil Gosselin	ARI	18.1	0.07	-0.2	1
700	2016	Rusney Castillo	BOS	20.0	0.07	0.6	1
695	2016	Clint Robinson	WSN	18.0	0.07	-0.5	0
696	2016	Will Venable	LAD	28.0	0.07	-0.2	0
697	2013	Brandon Inge	PIT	33.0	0.07	0.3	0
698	2012	Wilson Valdez	CIN	35.0	0.07	1.1	0
693	2014	Domingo Santana	HOU	43.0	0.07	-1.2	-1
694	2013	Andrew Lambo	PIT	48.0	0.07	-2.2	-1
702	2013	Steve Lombardozzi	WSN	170.0	0.07	-2.9	-4
703	2016	Ichiro Suzuki	MIA	376.2	0.06	3.6	5
704	2013	Yoenis Cespedes	OAK	934.1	0.06	6.7	-1
705	2015	Chris Parmelee	BAL	55.0	0.06	-1.6	0
706	2016	Trea Turner	WSN	66.1	0.06	0.8	0
715	2016	Kelby Tomlinson	SFG	20.0	0.06	1.7	2
713	2013	Ed Lucas	MIA	10.1	0.06	1.4	1
714	2016	Rob Segedin	LAD	11.2	0.06	1.8	1
708	2012	Hector Luna	PHI	15.0	0.06	-0.2	0
709	2014	Ben Paulsen	COL	17.0	0.06	0.5	0
710	2015	Chris Dominguez	CIN	25.0	0.06	0.2	0
711	2013	Jake Elmore	HOU	37.2	0.06	0.8	0
712	2012	Darin Ruf	PHI	46.0	0.06	0	0
707	2013	Nick Castellanos	DET	38.2	0.06	-0.5	-1
716	2013	Matt den Dekker	NYM	137.1	0.06	0.2	1
717	2014	Shane Robinson	STL	83.1	0.05	0.7	1
718	2014	Efren Navarro	LAA	202.0	0.05	2.1	2
719	2015	Corey Hart	PIT	22.0	0.05	1.4	1
720	2013	Jim Adduci	TEX	50.0	0.05	1.4	1
721	2014	Steven Souza Jr.	WSN	46.0	0.05	0.3	0
729	2014	Mitch Moreland	TEX	16.0	0.05	0	1
730	2015	Ryan Lollis	SFG	26.1	0.05	-2.2	1
731	2016	Darwin Barney	TOR	37.0	0.05	0.9	1
732	2015	Willie Bloomquist	SEA	37.0	0.05	1.1	1
723	2013	Pete Orr	PHI	12.0	0.05	-0.4	0
724	2014	Logan Watkins	CHC	14.1	0.05	0.5	0
725	2016	Kyle Waldrop	CIN	17.1	0.05	0.5	0
726	2013	Quintin Berry	BOS	21.2	0.05	0.2	0
727	2015	Matt McBride	COL	30.0	0.05	0.2	0
728	2016	Brian Goodwin	WSN	31.0	0.05	0	0
722	2016	Chris Davis	BAL	15.0	0.05		-1
735	2015	Adonis Garcia	ATL	56.0	0.04	1.1	1
734	2016	Darrell Ceciliani	TOR	73.0	0.04	-1.8	-1
733	2016	Nick Buss	LAA	52.0	0.04		-2
736	2013	Chris Dickerson	BAL	131.0	0.04	5.1	3
737	2014	Chris Dominguez	SFG	33.0	0.04	-0.5	0
738	2012	Todd Frazier	CIN	56.1	0.04	1.1	2
749	2015	Jose Ramirez	CLE	14.0	0.03	0.6	1
750	2013	Joey Butler	TEX	21.0	0.03	1.2	1
740	2015	Max Kepler	MIN	10.0	0.03	0.3	0
741	2016	Ryan Goins	TOR	12.0	0.03	-0.2	0
742	2015	Richie Shaffer	TBR	12.0	0.03	0.3	0
743	2016	Ryan Kalish	CHC	13.0	0.03	-0.1	0
744	2014	Jamie Romak	LAD	14.0	0.03	0.5	0
745	2016	Ryan LaMarre	BOS	14.0	0.03	0	0
746	2015	Daniel Dorn	ARI	23.0	0.03	0.7	0
747	2016	Benjamin Gamel	NYY	24.0	0.03	0	0
748	2016	Teoscar Hernandez	HOU	43.0	0.03		0
739	2015	Phil Gosselin	ARI	18.0	0.03	0.7	-1
751	2016	Marlon Byrd	CLE	254.2	0.03	2.8	0
752	2012	John Mayberry	PHI	828.1	0.03	-2.3	3
756	2012	Mike McCoy	TOR	48.1	0.03	1.4	1
754	2012	Adam Dunn	CHW	32.0	0.03	-1.1	-2
755	2014	Garrett Jones	MIA	60.0	0.03	-0.9	-2
753	2015	Jaff Decker	PIT	52.0	0.03	-3.2	-3
757	2016	Aaron Altherr	PHI	167.1	0.03	1.2	-1
758	2012	Josh Hamilton	TEX	1172.0	0.03	-12.5	-8
759	2012	Michael Taylor	OAK	47.0	0.02	0.5	3
772	2015	Alfredo Marte	LAA	13.0	0.02	1.1	1
765	2012	Jason Pridie	PHI	10.2	0.02	0.3	0
766	2014	Nick Franklin	SEA	11.0	0.02	0	0
767	2013	Josh Prince	MIL	13.0	0.02	0	0
768	2012	Brandon Guyer	TBR	14.0	0.02	0.1	0
769	2016	Emmanuel Burriss	PHI	17.0	0.02	-0.7	0
770	2015	Jose Pirela	NYY	18.0	0.02	-1.5	0
771	2013	Jhonny Peralta	DET	18.2	0.02	0.1	0
761	2013	Adam Dunn	CHW	17.0	0.02	0.5	-1
762	2013	Brock Peterson	STL	17.0	0.02	-1	-1
763	2015	Ryan Goins	TOR	20.0	0.02	-1.1	-1
764	2015	John Jaso	TBR	49.0	0.02	0.1	-1
760	2013	Alex Castellanos	LAD	38.1	0.02	-1.6	-2
773	2013	Darnell McDonald	CHC	100.1	0.02	1.8	0
775	2012	Aubrey Huff	SFG	32.0	0.02	-0.4	0
776	2014	Zelous Wheeler	NYY	49.0	0.02	0.1	0
774	2016	Hector Olivera	ATL	43.0	0.02	0.3	-1
777	2016	Ryan Braun	MIL	818.2	0.02	-0.9	6
780	2016	Mike Freeman	ARI	10.0	0.01	-1.2	0
781	2016	Derek Dietrich	MIA	10.0	0.01	-0.3	0
782	2016	Erik Gonzalez	CLE	10.0	0.01	0	0
783	2013	Ty Wigginton	STL	11.0	0.01	-0.5	0
784	2012	Adrian Cardenas	CHC	11.0	0.01	0	0
785	2012	Eury Perez	WSN	11.0	0.01	0.3	0
786	2014	Mark Reynolds	MIL	12.0	0.01	0.4	0
787	2014	Alex Hassan	BOS	17.0	0.01	0	0
788	2015	Gorkys Hernandez	PIT	17.0	0.01	-0.3	0
789	2016	Tony Renda	CIN	18.1	0.01		0
790	2015	Jason Pridie	OAK	19.0	0.01	-0.4	0
778	2012	Bill Hall	BAL	16.0	0.01	0	-1
779	2015	Peter O'Brien	ARI	16.0	0.01	-0.3	-1
792	2015	Tyler Ladendorf	OAK	18.0	0.01	0	0
791	2013	Josh Harrison	PIT	60.0	0.01	-2.4	-2
793	2012	Carlos Beltran	STL	1174.0	0.00	1.6	5
794	2014	Ryan Rua	TEX	151.0	0.00	3.2	-2
795	2014	Andy Parrino	OAK	10.0	0.00		0
796	2015	Jamie Romak	ARI	13.0	0.00	0.4	0
797	2015	Jason Rogers	MIL	14.1	0.00	-0.2	0
798	2013	Todd Cunningham	ATL	15.2	0.00	-0.1	0
799	2013	Elian Herrera	LAD	17.0	0.00	-0.4	0
800	2012	Joe Mather	CHC	321.2	0.00	-5.3	-7
803	2015	Logan Morrison	SEA	21.0	-0.01	0.6	0
804	2014	Michael Martinez	PIT	23.0	-0.01	-0.5	0
805	2015	Danny Espinosa	WSN	23.1	-0.01	0.3	0
806	2015	Jake Elmore	TBR	28.0	-0.01	-0.4	0
807	2016	Jake Elmore	MIL	62.2	-0.01	-1	0
802	2015	Reed Johnson	WSN	22.1	-0.01	-0.2	-1
801	2015	Evan Gattis	HOU	71.0	-0.01	-0.9	-4
808	2016	Ben Paulsen	COL	30.2	-0.01	-1	-1
810	2015	Mark Reynolds	STL	42.0	-0.01	0.8	0
809	2016	Julio Borbon	BAL	29.0	-0.01	-0.7	-1
811	2013	Michael Morse	- - -	580.1	-0.01	-11.9	-14
812	2015	Leury Garcia	CHW	22.0	-0.02	-0.9	0
813	2014	Elian Herrera	MIL	161.0	-0.03	0.8	-1
815	2015	Zach Walters	CLE	20.2	-0.03	0.5	0
816	2014	Carlos Peguero	KCR	23.0	-0.03	-0.1	0
814	2013	Carlos Peguero	SEA	18.0	-0.03	-0.7	-1
817	2014	Jordan Schafer	- - -	501.1	-0.03	0.2	-5
818	2016	Justin Ruggiano	- - -	29.0	-0.03	-1.2	1
819	2015	Eric Campbell	NYM	39.1	-0.03	0.9	1
820	2016	Hyun Soo Kim	BAL	463.0	-0.05	-6	-11
821	2012	Denis Phipps	CIN	18.0	-0.05	-0.6	-1
822	2012	Charlie Blackmon	COL	230.0	-0.05	9	5
823	2013	Kyle Blanks	SDP	421.2	-0.06	-2.6	0
824	2015	Terrance Gore	KCR	10.0	-0.06	-1	-1
825	2012	Mike Carp	SEA	169.0	-0.06	-0.9	0
826	2012	Edwin Encarnacion	TOR	17.0	-0.07	-0.9	-2
827	2016	Marwin Gonzalez	HOU	45.0	-0.07	-0.3	0
828	2014	Don Kelly	DET	182.0	-0.07	-0.2	1
829	2015	Carlos Gonzalez	COL	1230.1	-0.07	-1.7	5
830	2014	Tyler Colvin	SFG	310.0	-0.08	-0.6	-2
831	2016	Aaron Judge	NYY	45.0	-0.08		0
832	2016	Emilio Bonifacio	ATL	72.1	-0.08	-3.4	-1
833	2015	Jose Tabata	PIT	43.1	-0.08	-0.3	-2
834	2015	Kyle Schwarber	CHC	309.2	-0.09	-0.3	-3
835	2013	Michael Martinez	PHI	56.2	-0.09	-1.4	-1
836	2016	Daniel Nava	LAA	244.0	-0.09	-2.4	-7
837	2013	Travis Snider	PIT	527.0	-0.09	-0.6	0
838	2016	Ben Zobrist	CHC	196.0	-0.09	1.4	1
839	2012	Aaron Cunningham	CLE	299.0	-0.10	1.4	1
840	2014	Raul Ibanez	- - -	173.0	-0.10	1.9	-2
841	2012	Daniel Nava	BOS	631.2	-0.10	0.7	4
842	2015	David Peralta	ARI	1042.2	-0.10	-2.4	-2
843	2014	Joc Pederson	LAD	69.0	-0.11	0.9	0
844	2013	Allen Craig	STL	360.1	-0.12	-2.7	-2
845	2012	Xavier Paul	CIN	118.2	-0.12	-1.3	-2
846	2014	Bryce Harper	WSN	841.1	-0.13	-1.1	0
847	2012	Collin Cowgill	OAK	255.1	-0.13	1.2	3
848	2013	Mike Aviles	CLE	35.0	-0.13	0.4	1
849	2012	Trevor Plouffe	MIN	132.0	-0.15	0.3	0
850	2015	Kris Bryant	CHC	98.0	-0.16	0.6	1
851	2016	Colby Rasmus	HOU	757.0	-0.16	12.9	17
852	2014	Donald Lutz	CIN	43.0	-0.17	1.9	1
853	2016	David Peralta	ARI	385.0	-0.17	0.2	3
854	2014	Tyler Collins	DET	42.0	-0.17	1	1
855	2013	Cesar Hernandez	PHI	190.1	-0.17	-3.3	-3
856	2014	Stephen Vogt	OAK	118.1	-0.19	-1	-1
857	2014	Steve Tolleson	TOR	25.0	-0.19	-0.3	0
858	2016	Mike Aviles	DET	260.1	-0.19	-1.5	-5
859	2015	Corey Dickerson	COL	433.0	-0.19	-4.2	-7
860	2015	Alex Presley	HOU	34.0	-0.20	-0.4	-1
861	2012	Chris Davis	BAL	316.0	-0.20	-0.1	0
862	2013	Logan Forsythe	SDP	77.1	-0.20	-0.5	-2
863	2016	Lorenzo Cain	KCR	768.1	-0.20	8.9	11
864	2015	Nori Aoki	SFG	729.2	-0.20	3.4	-1
865	2016	Bryce Harper	WSN	931.2	-0.21	10.4	1
866	2014	Ryan Braun	MIL	1168.0	-0.21	-6.7	-8
867	2012	Josh Harrison	PIT	85.2	-0.21	-0.4	-3
868	2013	Andres Torres	SFG	591.2	-0.21	5.1	-2
869	2015	Alejandro De Aza	- - -	738.0	-0.21	-1.1	-4
870	2015	Will Venable	- - -	793.2	-0.21	1	-5
871	2014	Ed Lucas	MIA	29.0	-0.21	1.6	2
872	2015	Mike Baxter	CHC	79.1	-0.21	0.2	1
873	2016	Adonis Garcia	ATL	29.0	-0.22	-0.5	-2
874	2015	Skip Schumaker	CIN	312.0	-0.23	-7.2	-4
875	2014	Leury Garcia	CHW	97.2	-0.23	-3.2	-1
876	2016	Ty Kelly	NYM	46.2	-0.23	-0.4	1
877	2014	Eury Perez	NYY	24.0	-0.24	-1.2	0
878	2014	Leonys Martin	TEX	1247.1	-0.24	11.3	16
879	2012	Austin Kearns	MIA	235.0	-0.24	3.5	0
880	2014	Brett Jackson	ARI	15.2	-0.25	-0.6	0
881	2013	Jake Marisnick	MIA	261.0	-0.25	2.5	7
882	2013	Avisail Garcia	- - -	551.1	-0.25	-10	-4
883	2015	Andrew Lambo	PIT	31.0	-0.26	-1.5	0
884	2012	Rich Thompson	TBR	57.0	-0.26	-0.8	-2
885	2013	Alfredo Marte	ARI	78.0	-0.26	-1.3	-2
886	2015	Travis Ishikawa	- - -	29.0	-0.27	-0.4	-1
887	2016	Eddie Rosario	MIN	567.0	-0.27	1.5	-2
888	2012	Adrian Gonzalez	BOS	127.0	-0.27	-4.3	-2
889	2015	Mac Williamson	SFG	61.1	-0.27	-0.6	0
890	2016	Jason Coats	CHW	64.0	-0.28	2.4	2
891	2015	Gregor Blanco	SFG	732.2	-0.28	-1.1	-6
892	2014	Juan Perez	SFG	280.0	-0.28	0	-2
893	2016	Scott Schebler	CIN	246.1	-0.28	-2.9	0
894	2016	Steve Pearce	BAL	21.0	-0.28	-0.8	-1
895	2012	Yamaico Navarro	PIT	57.0	-0.29	-0.5	2
896	2013	Dustin Ackley	SEA	495.0	-0.29	-7	-7
897	2014	Tony Gwynn	PHI	189.1	-0.30	-3.2	-3
898	2013	Tyler Colvin	COL	163.0	-0.30	-4.6	-2
899	2012	James Darnell	SDP	27.0	-0.30	-0.7	-1
900	2012	Fred Lewis	NYM	28.2	-0.31	-1.3	-2
901	2014	Stefen Romero	SEA	318.1	-0.31	-2.1	-3
902	2012	A.J. Pollock	ARI	180.0	-0.31	2.1	1
903	2013	Michael Saunders	SEA	998.1	-0.31	-4.2	-12
904	2014	Jorge Soler	CHC	205.0	-0.33	-0.5	1
905	2014	Alex Guerrero	LAD	14.0	-0.33	-0.3	-1
906	2016	Chris Young	BOS	308.1	-0.33	-1.9	-3
907	2013	Cameron Maybin	SDP	120.1	-0.33	-3.6	-5
908	2013	Moises Sierra	TOR	238.2	-0.34	-1.4	-1
909	2013	Emilio Bonifacio	- - -	258.1	-0.34	-1.5	-3
910	2015	Ryan Raburn	CLE	194.0	-0.34	-1.9	-5
911	2013	Francisco Peguero	SFG	66.0	-0.35	0.4	2
912	2014	Reed Johnson	MIA	236.0	-0.35	-4.4	-2
913	2015	Franklin Gutierrez	SEA	309.1	-0.36	3.5	3
914	2016	Jarrett Parker	SFG	236.0	-0.36	-1.5	-2
915	2016	Alejandro De Aza	NYM	326.1	-0.37	1.7	3
916	2012	Angel Pagan	SFG	1279.1	-0.37	0.5	-5
917	2015	Junior Lake	- - -	151.1	-0.37	-3.6	-5
918	2016	Trayce Thompson	LAD	556.0	-0.37	-7.1	0
919	2012	Leonys Martin	TEX	119.0	-0.37	-2.9	0
920	2016	Ryan Flaherty	BAL	29.0	-0.38	0.1	-1
921	2014	Eric Campbell	NYM	101.1	-0.38	1.4	1
922	2012	Steve Tolleson	BAL	50.0	-0.39	2.3	0
923	2015	Garrett Jones	NYY	164.1	-0.40	-1	-2
924	2016	Jared Hoying	TEX	64.0	-0.40	0.5	-1
925	2015	Cody Asche	PHI	522.2	-0.41	-9.4	-8
926	2016	Taylor Motter	TBR	67.2	-0.41	0.4	3
927	2013	Giancarlo Stanton	MIA	1031.1	-0.41	-7.8	-6
928	2012	Kirk Nieuwenhuis	NYM	613.2	-0.41	-2.7	-2
929	2014	Marcell Ozuna	MIA	1308.2	-0.41	3.3	9
931	2012	Brett Pill	SFG	47.0	-0.42	1.2	0
930	2013	Thomas Neal	- - -	30.0	-0.42	-0.2	-1
932	2012	Ryan Flaherty	BAL	138.2	-0.43	-2.3	0
933	2015	Eric Young	- - -	171.0	-0.43	-1.4	0
934	2012	Erik Komatsu	- - -	107.1	-0.43	-1.7	-1
935	2012	Brian Bixler	HOU	77.0	-0.44	1.5	4
936	2015	Mason Williams	NYY	53.0	-0.44	1.1	-1
937	2012	Tony Campana	CHC	381.1	-0.44	-0.1	2
938	2016	Rajai Davis	CLE	789.2	-0.44	4.3	-5
939	2012	Starling Marte	PIT	351.0	-0.44	6.3	5
940	2013	Darin Mastroianni	MIN	165.0	-0.45	-1.4	-3
941	2015	Jonathan Villar	HOU	25.2	-0.45	0.1	0
942	2012	Clete Thomas	- - -	71.0	-0.45	1.6	2
943	2013	Mike Baxter	NYM	268.2	-0.45	-2.8	3
944	2016	Daniel Robertson	SEA	53.1	-0.46	-0.1	-1
945	2012	Bryan Petersen	MIA	528.1	-0.46	-6.3	-6
946	2012	Ben Zobrist	TBR	541.1	-0.46	10.3	10
947	2013	Lyle Overbay	NYY	26.0	-0.46	-0.8	-2
948	2014	Jake Goebbert	SDP	39.2	-0.47	-0.3	0
949	2016	Jabari Blash	SDP	147.0	-0.48	-0.2	4
950	2013	Adam Eaton	ARI	526.2	-0.48	-10	-2
951	2012	Michael Martinez	PHI	51.0	-0.48	1.3	2
952	2015	Emilio Bonifacio	CHW	15.0	-0.48	0.3	0
953	2012	Drew Sutton	PIT	126.2	-0.49	-3.3	-4
954	2012	Domonic Brown	PHI	449.2	-0.49	-3.8	-5
955	2013	Anthony Gose	TOR	347.1	-0.49	-4.8	0
956	2016	Mallex Smith	ATL	414.0	-0.50	2.8	8
957	2012	Jay Bruce	CIN	1343.1	-0.50	-4.7	-1
958	2016	Marcell Ozuna	MIA	975.1	-0.50	2.6	-11
959	2014	Matt den Dekker	NYM	360.0	-0.50	0.8	4
960	2016	Dariel Alvarez	BAL	10.0	-0.51	0	0
961	2016	Carl Crawford	LAD	151.0	-0.51	-1.4	-3
962	2012	Nolan Reimold	BAL	126.0	-0.52	-2.3	-1
963	2015	Alex Guerrero	LAD	206.1	-0.52	-3.1	-3
964	2014	Oscar Taveras	STL	500.0	-0.53	-4.3	-4
965	2014	Nyjer Morgan	CLE	103.0	-0.53	-3.7	-4
966	2012	Blake Tekotte	SDP	21.0	-0.55	-0.3	0
967	2015	Brian Bogusevic	PHI	128.2	-0.55	-0.2	0
968	2015	Ryan Strausborger	TEX	128.0	-0.55	-0.7	-3
969	2014	Marc Krauss	HOU	165.0	-0.55	-0.1	1
970	2012	Seth Smith	OAK	515.0	-0.55	0.4	2
971	2015	Slade Heathcott	NYY	71.0	-0.56	0.8	0
972	2014	Jesus Guzman	HOU	41.0	-0.56	-0.2	-1
973	2012	Ryan Kalish	BOS	231.1	-0.57	-9.9	-5
974	2012	Mark DeRosa	WSN	110.2	-0.57	-3.9	-4
975	2016	Brock Holt	BOS	432.1	-0.57	-5.3	3
976	2012	Carlos Peguero	SEA	111.2	-0.58	1.9	-1
977	2016	Jose Ramirez	CLE	375.1	-0.59	-1.9	-1
978	2015	Adam Duvall	CIN	120.0	-0.60	1.7	-1
979	2016	Socrates Brito	ARI	111.1	-0.60	0.7	1
980	2014	A.J. Pollock	ARI	585.1	-0.62	7.1	8
981	2015	Drew Stubbs	- - -	291.1	-0.62	0.4	2
982	2013	Kelly Johnson	TBR	408.1	-0.62	-4	0
983	2014	Bryce Brentz	BOS	56.0	-0.63	-0.9	-1
984	2015	Christian Yelich	MIA	1069.1	-0.63	-3.7	8
985	2014	Elliot Johnson	CLE	24.0	-0.64	-1	0
986	2016	Max Muncy	OAK	88.0	-0.64	1.3	1
987	2013	Jason Kubel	- - -	514.1	-0.64	-7.6	0
988	2016	Shin-Soo Choo	TEX	334.2	-0.64	-2.1	-5
989	2016	Angel Pagan	SFG	760.1	-0.64	2.7	-2
990	2015	Jake Smolinski	- - -	435.2	-0.64	4.6	-2
991	2016	Jayson Werth	WSN	868.1	-0.65	-0.4	-5
993	2014	Jeff Francoeur	SDP	51.0	-0.65	0.1	0
992	2012	Ty Wigginton	PHI	48.0	-0.65	-2.7	-2
994	2015	Eury Perez	ATL	278.2	-0.65	-3.6	0
995	2014	Cameron Maybin	SDP	631.0	-0.65	1.1	2
996	2015	Brandon Moss	- - -	753.2	-0.66	-1	-2
997	2015	Carlos Peguero	- - -	184.1	-0.67	4.1	1
998	2013	Ezequiel Carrera	- - -	38.0	-0.67	-0.3	-1
999	2012	Alejandro De Aza	CHW	1133.1	-0.67	-1.3	-6
1000	2014	Nolan Reimold	- - -	78.0	-0.67	-1.2	0
1001	2013	Darin Ruf	PHI	367.1	-0.67	-7.6	-9
1002	2013	Jeff Baker	TEX	109.0	-0.68	-2.7	-1
1003	2016	Andrew Benintendi	BOS	114.0	-0.68	-0.4	-1
1004	2014	Mookie Betts	BOS	326.2	-0.68	0.7	5
1005	2016	Wil Myers	SDP	43.0	-0.68	0.5	0
1006	2014	Alex Rios	TEX	962.1	-0.69	-4.3	-4
1007	2015	Dariel Alvarez	BAL	81.0	-0.69	1.5	-1
1008	2013	Roger Kieschnick	SFG	189.2	-0.69	0.9	0
1009	2012	Matt Carson	MIN	143.0	-0.69	1.2	4
1010	2015	Domonic Brown	PHI	403.1	-0.69	0	1
1011	2016	Willson Contreras	CHC	164.2	-0.70	-2.2	-1
1012	2014	Mike Aviles	CLE	203.2	-0.70	-6.4	-5
1013	2014	Chris Herrmann	MIN	158.0	-0.70	-2.9	-4
1014	2015	Melvin Upton Jr.	SDP	441.1	-0.71	2.4	2
1015	2012	Ryan Raburn	DET	246.2	-0.71	0.1	0
1016	2016	Todd Cunningham	LAA	81.0	-0.72	2	2
1017	2015	Kiké Hernandez	LAD	224.1	-0.72	0.9	1
1018	2014	Seth Smith	SDP	1034.1	-0.73	-3.2	3
1019	2012	Melvin Upton Jr.	TBR	1254.2	-0.74	-2.2	-5
1020	2016	Steve Selsky	CIN	12.2	-0.74	-0.6	-1
1021	2013	Marc Krauss	HOU	178.1	-0.74	-2.1	0
1022	2015	Carl Crawford	LAD	346.2	-0.75	-2.1	-4
1023	2012	Brandon Allen	TBR	23.0	-0.75	-0.2	-1
1024	2014	Zoilo Almonte	NYY	77.2	-0.75	-0.2	-1
1025	2016	Shawn O'Malley	SEA	120.0	-0.76	1	-1
1026	2014	Michael Taylor	WSN	85.0	-0.76	1.1	-1
1028	2014	Matt McBride	COL	20.2	-0.76	1.1	2
1027	2014	Marwin Gonzalez	HOU	14.2	-0.76	-1.9	-2
1029	2014	Brennan Boesch	LAA	62.0	-0.77	-1.1	-1
1030	2014	Brandon Moss	OAK	622.1	-0.77	2.3	3
1031	2013	Alexi Amarista	SDP	555.2	-0.77	-11.3	-4
1032	2015	Rusney Castillo	BOS	614.1	-0.77	10.4	15
1033	2014	Edwin Encarnacion	TOR	15.0	-0.77	-1.3	-1
1034	2012	Brandon Moss	OAK	158.1	-0.77	-1.5	-1
1035	2015	Rickie Weeks Jr.	SEA	89.0	-0.78	-2.6	-2
1036	2012	Nelson Cruz	TEX	1307.0	-0.78	-3.7	-12
1037	2016	Nomar Mazara	TEX	897.1	-0.79	8.9	-4
1038	2012	Eric Hosmer	KCR	16.0	-0.79	-1.5	-1
1039	2015	Nelson Cruz	SEA	704.0	-0.79	-6.2	-8
1040	2014	Rymer Liriano	SDP	256.1	-0.80	-2.7	-2
1041	2013	Tyler Moore	WSN	248.1	-0.80	-5.3	-3
1042	2012	Fernando Martinez	HOU	275.2	-0.80	1.9	-5
1043	2016	Whit Merrifield	KCR	78.0	-0.81	0.9	2
1044	2016	Jefry Marte	LAA	51.0	-0.81	-0.4	-2
1045	2016	Chris Owings	ARI	403.0	-0.83	-1.5	3
1046	2016	Jose Peraza	CIN	95.0	-0.83	-5.3	-2
1047	2013	Ryan Raburn	CLE	477.1	-0.83	1.6	-1
1048	2014	Nelson Cruz	BAL	580.2	-0.83	1.4	4
1049	2014	Ryan Zimmerman	WSN	265.2	-0.85	0.4	-2
1051	2015	Steven Moya	DET	45.0	-0.85	0.9	1
1050	2015	Cody Ross	OAK	52.0	-0.85	-0.6	0
1052	2013	Jose Bautista	TOR	966.0	-0.85	5.5	6
1053	2015	Angel Pagan	SFG	1061.1	-0.86	-14.3	-20
1054	2013	Kensuke Tanaka	SFG	55.0	-0.86	-1	2
1055	2014	Avisail Garcia	CHW	401.0	-0.87	-6.2	-8
1056	2012	Rick Ankiel	WSN	382.0	-0.87	-1.9	-5
1057	2012	Allen Craig	STL	212.2	-0.88	-1.3	-4
1058	2013	DeWayne Wise	CHW	149.0	-0.88	2.4	0
1060	2016	Chris Herrmann	ARI	55.2	-0.89	1	0
1059	2016	Kendrys Morales	KCR	37.0	-0.89	-1.4	-1
1061	2013	Ryan Doumit	MIN	266.1	-0.90	-7.1	-8
1062	2012	Hideki Matsui	TBR	96.1	-0.90	-2.5	-3
1063	2016	Peter O'Brien	ARI	105.0	-0.90	-0.9	-1
1064	2016	Hernan Perez	MIL	193.2	-0.90	0.1	-3
1065	2012	Eric Thames	- - -	620.0	-0.90	-5.5	-6
1066	2013	Josh Willingham	MIN	607.2	-0.90	-6.3	-6
1068	2014	Eduardo Escobar	MIN	18.2	-0.92	-0.5	0
1067	2013	Brad Hawpe	LAA	36.0	-0.92	-1	-1
1069	2014	Ryan Raburn	CLE	281.1	-0.93	-1.2	-2
1070	2012	Donovan Solano	MIA	63.0	-0.94	-1.6	-3
1071	2016	Jon Jay	SDP	562.1	-0.94	-4.6	-4
1072	2016	Howie Kendrick	LAD	491.1	-0.94	6.5	1
1074	2014	Joey Terdoslavich	ATL	12.0	-0.95	-0.1	0
1075	2013	Steve Susdorf	PHI	12.0	-0.95	-0.9	0
1073	2015	Ketel Marte	SEA	14.0	-0.95	-0.4	-1
1076	2012	Eduardo Nunez	NYY	25.1	-0.96	0.8	0
1077	2013	Mark Kotsay	SDP	152.2	-0.96	-5.7	-7
1078	2015	Leonys Martin	TEX	673.1	-0.96	8.5	15
1079	2012	Jeremy Hermida	SDP	40.1	-0.96	1.3	1
1080	2016	Nelson Cruz	SEA	400.2	-0.96	-2.6	-3
1081	2013	Jason Pridie	BAL	27.0	-0.96	-2.7	-3
1082	2014	Caleb Gindl	MIL	48.1	-0.98	-0.6	0
1083	2012	Alex Presley	PIT	688.0	-0.98	3.6	-4
1084	2012	Matt Carpenter	STL	108.1	-0.98	-3.1	-4
1085	2014	Yangervis Solarte	SDP	40.0	-0.98	-2.1	-2
1086	2016	Tyler Holt	CIN	284.1	-0.98	-0.1	-4
1087	2014	Mike Carp	- - -	70.2	-0.99	0.9	0
1088	2015	Mark Canha	OAK	422.2	-0.99	1.3	-1
1089	2016	Michael Martinez	- - -	118.0	-0.99	1.5	1
1090	2013	Jason Bourgeois	TBR	34.0	-1.00	-0.5	-2
1091	2012	Raul Ibanez	NYY	651.0	-1.00	1	-5
1092	2015	Eduardo Nunez	MIN	14.0	-1.01	0.4	1
1093	2015	Michael Morse	MIA	35.0	-1.02	-0.1	1
1094	2016	Justin Upton	DET	975.2	-1.03	-5.3	-1
1095	2016	Christian Bethancourt	SDP	56.2	-1.04	-1.4	-2
1096	2015	Cory Spangenberg	SDP	11.0	-1.04	-0.8	-1
1097	2016	Jorge Soler	CHC	294.1	-1.04	-1.9	-2
1098	2016	Melky Cabrera	CHW	961.0	-1.04	-3.3	-6
1099	2014	Kyle Parker	COL	18.1	-1.04	-0.4	-1
1100	2014	Skip Schumaker	CIN	418.1	-1.05	-7.7	-6
1101	2014	Shawn O'Malley	LAA	28.2	-1.05	-0.6	0
1102	2014	Torii Hunter	DET	1114.0	-1.06	-18.3	-17
1103	2014	Gregory Polanco	PIT	619.0	-1.06	-3.2	-2
1104	2013	Nolan Reimold	BAL	90.0	-1.06	-1.2	-4
1105	2013	Charlie Culberson	COL	177.0	-1.06	2	-2
1106	2012	Michael Cuddyer	COL	593.1	-1.07	-0.9	-8
1107	2014	Jay Bruce	CIN	1136.1	-1.08	-6.1	-6
1108	2016	Adam Duvall	CIN	886.0	-1.09	6.2	12
1109	2015	Nick Swisher	- - -	208.0	-1.10	-1.1	-6
1110	2016	Junior Lake	TOR	93.0	-1.10	-0.8	0
1111	2013	Brian Bogusevic	CHC	328.0	-1.10	3.6	-4
1112	2013	Julio Borbon	CHC	151.0	-1.10	-1.7	0
1113	2016	Chris Heisey	WSN	201.2	-1.12	-1.6	1
1114	2012	Ben Francisco	- - -	289.2	-1.12	-2.7	-6
1115	2014	Adam Dunn	CHW	38.0	-1.14	-2.1	-2
1116	2012	Alex Castellanos	LAD	51.1	-1.15	-2.2	-2
1117	2015	Jordan Schafer	MIN	187.0	-1.16	-5.7	-3
1118	2012	Will Venable	SDP	931.2	-1.17	-0.5	-3
1119	2012	Mark Kotsay	SDP	192.1	-1.17	-1	-1
1120	2012	Alex Liddi	SEA	46.0	-1.18	0.4	-1
1121	2016	Carlos Beltran	- - -	467.0	-1.18	-2	-7
1122	2015	Josh Harrison	PIT	141.2	-1.18	-3.9	-1
1123	2012	Scott Moore	HOU	89.2	-1.19	-0.1	-2
1124	2015	Chris Davis	BAL	253.1	-1.23	2.6	-3
1125	2016	Gerardo Parra	COL	580.1	-1.23	1.6	-8
1126	2012	Brandon Belt	SFG	27.1	-1.23	-0.2	-1
1127	2013	Angel Pagan	SFG	579.2	-1.24	-4.8	-9
1128	2012	Nate Schierholtz	- - -	533.1	-1.25	-1.1	1
1129	2016	Cole Gillespie	MIA	49.1	-1.25	-4.3	-3
1130	2014	Roger Kieschnick	ARI	64.1	-1.25	-2.2	-2
1131	2012	Kosuke Fukudome	CHW	97.0	-1.26	2.8	1
1132	2012	Josh Willingham	MIN	1027.2	-1.27	-9	-12
1133	2014	Arismendy Alcantara	CHC	421.0	-1.29	-2.7	2
1134	2015	Danny Valencia	TOR	237.0	-1.30	-1.5	-3
1135	2013	Reymond Fuentes	SDP	75.2	-1.32	0.5	0
1136	2016	Brandon Guyer	- - -	481.1	-1.32	-4.4	-2
1137	2013	Raul Ibanez	SEA	832.1	-1.32	-17.1	-18
1138	2016	Ji-Man Choi	LAA	107.0	-1.32	1.8	-2
1139	2016	Alex Dickerson	SDP	262.1	-1.33	-4.5	-3
1140	2012	Jesus Guzman	SDP	412.2	-1.33	-0.7	-1
1141	2015	Grady Sizemore	- - -	469.1	-1.33	-8.4	-8
1142	2016	Coco Crisp	OAK	703.1	-1.33	-11.2	-10
1143	2013	Sean Halton	MIL	43.0	-1.34	-1.5	-1
1144	2012	Jose Tabata	PIT	736.1	-1.37	-3.5	4
1145	2014	Corey Dickerson	COL	870.0	-1.37	-5.6	-2
1146	2014	John Mayberry	- - -	219.0	-1.37	-2.1	-2
1147	2016	Cameron Maybin	DET	523.0	-1.38	-5.8	-11
1148	2016	Jeff Francoeur	ATL	470.0	-1.39	2.7	6
1149	2015	Matt Szczur	CHC	144.1	-1.40	-2	-3
1150	2015	Ezequiel Carrera	TOR	456.2	-1.41	-2.9	-10
1151	2012	Michael Morse	WSN	774.1	-1.42	-10.5	-6
1152	2015	Hunter Pence	SFG	441.0	-1.43	4.9	0
1153	2015	Clint Robinson	WSN	269.1	-1.44	-6	-5
1154	2014	Coco Crisp	OAK	900.2	-1.44	-13.7	-18
1155	2012	Casper Wells	SEA	694.0	-1.45	4.8	3
1156	2015	Jorge Soler	CHC	825.2	-1.45	-7	-8
1157	2016	Ramon Flores	MIL	593.2	-1.45	-0.1	-3
1158	2014	Melvin Upton Jr.	ATL	1218.1	-1.47	-2	-8
1159	2014	Austin Jackson	- - -	1326.0	-1.48	-8.6	-1
1160	2013	Alex Rios	- - -	1366.0	-1.48	3.7	-4
1161	2014	Colby Rasmus	TOR	719.1	-1.50	-9.1	-6
1162	2012	Mark Trumbo	LAA	761.0	-1.51	-4.7	-1
1163	2014	Tony Campana	- - -	159.2	-1.51	-3.2	0
1164	2015	Jarrett Parker	SFG	114.2	-1.51	-0.5	-3
1165	2012	Greg Dobbs	MIA	227.2	-1.52	-4.4	-7
1166	2015	Steven Souza Jr.	TBR	884.0	-1.53	-0.4	-4
1167	2012	Chone Figgins	SEA	347.2	-1.55	-8.3	-9
1168	2015	Steve Tolleson	TOR	18.0	-1.56	-2.6	-1
1169	2015	Eddie Rosario	MIN	1035.2	-1.56	7.4	11
1170	2014	Bobby Abreu	NYM	206.0	-1.57	-5.4	-8
1171	2014	Justin Upton	ATL	1319.2	-1.58	-0.9	-3
1172	2013	Andrew Brown	NYM	248.0	-1.58	-2.6	0
1173	2016	Paulo Orlando	KCR	764.1	-1.59	1.2	12
1174	2015	Justin Ruggiano	- - -	286.1	-1.60	-3.1	-7
1175	2015	Delino DeShields	TEX	926.2	-1.62	-7.5	-9
1176	2013	Chris Colabello	MIN	78.0	-1.63	-0.2	0
1177	2015	Jerry Sands	CLE	229.0	-1.64	-2.2	-3
1178	2016	Steven Souza Jr.	TBR	751.0	-1.64	2.5	2
1179	2016	Lonnie Chisenhall	CLE	698.0	-1.65	-1.5	1
1180	2016	Reymond Fuentes	KCR	98.0	-1.67	-1.5	-3
1181	2015	Brandon Belt	SFG	96.1	-1.70	-0.4	-2
1182	2013	Steve Pearce	BAL	117.1	-1.71	1.1	2
1183	2012	Carlos Quentin	SDP	590.0	-1.74	-7.8	-10
1184	2015	Ben Zobrist	- - -	380.2	-1.74	-4.3	-5
1185	2015	Cameron Maybin	ATL	1129.2	-1.75	-7.2	-16
1186	2014	Cory Spangenberg	SDP	25.1	-1.75	-0.7	0
1187	2013	Michael Cuddyer	COL	992.0	-1.76	-13.4	-15
1188	2012	Ryan Doumit	MIN	184.1	-1.77	-3.1	-4
1189	2013	Melvin Upton Jr.	ATL	975.1	-1.78	1.1	0
1190	2015	Nolan Reimold	BAL	366.0	-1.78	0.3	-6
1191	2012	Scott Hairston	NYM	772.2	-1.78	-3.9	-4
1192	2014	Tommy Medica	SDP	136.1	-1.79	-1.7	-4
1193	2014	Jonny Gomes	- - -	631.2	-1.79	-4.2	-7
1194	2014	Sean Rodriguez	TBR	106.1	-1.80	-3.6	-5
1195	2016	Starling Marte	PIT	916.0	-1.80	-0.5	13
1196	2015	Ivan De Jesus	CIN	123.2	-1.82	-2.4	-6
1197	2014	Carlos Quentin	SDP	229.0	-1.86	-4.6	-3
1198	2015	Dalton Pompey	TOR	216.1	-1.86	-0.2	6
1199	2013	Drew Stubbs	CLE	1124.0	-1.89	-2.8	-7
1200	2012	Pedro Ciriaco	BOS	20.0	-1.90	-0.3	-1
1201	2016	Carlos Gomez	HOU	677.0	-1.90	-0.1	-5
1202	2012	Andrew Brown	COL	234.0	-1.91	3	2
1203	2014	Abraham Almonte	- - -	429.2	-1.92	9.2	7
1204	2013	Luke Scott	TBR	21.0	-1.92	-1.5	-1
1205	2015	Darnell Sweeney	PHI	109.2	-1.92	-3.6	-2
1206	2016	Jimmy Paredes	- - -	181.0	-1.94	1.4	4
1207	2015	Preston Tucker	HOU	655.0	-1.97	-4.6	-5
1208	2016	J.B. Shuck	CHW	469.0	-1.98	-5.5	-9
1209	2015	Colby Rasmus	HOU	1029.0	-1.99	0.5	2
1210	2014	Drew Stubbs	COL	835.0	-2.00	-1.4	0
1211	2016	Keon Broxton	MIL	319.2	-2.01	-0.3	2
1212	2016	Nolan Reimold	BAL	451.0	-2.02	-2.1	-1
1213	2012	Emilio Bonifacio	MIA	427.1	-2.03	-3.7	-3
1214	2013	Junior Lake	CHC	498.2	-2.04	3.7	-2
1215	2015	Yasmany Tomas	ARI	494.2	-2.04	-8.4	-8
1216	2014	Justin Ruggiano	CHC	461.2	-2.05	-4.5	-10
1217	2014	Delmon Young	BAL	159.1	-2.06	-0.6	-4
1218	2016	Drew Stubbs	- - -	151.0	-2.08	-3.8	-3
1219	2014	Chris Colabello	MIN	123.0	-2.09	-7.6	-7
1220	2015	Jay Bruce	CIN	1319.2	-2.11	-4.2	5
1221	2014	Scott Hairston	WSN	90.0	-2.12	-2.1	-1
1222	2016	Yoenis Cespedes	NYM	728.1	-2.13	-9.5	-8
1223	2012	Delmon Young	DET	226.1	-2.13	-4.1	-3
1224	2014	Chris Parmelee	MIN	387.1	-2.18	-3.2	-9
1225	2016	Denard Span	SFG	920.0	-2.19	-9.2	-8
1226	2015	Oswaldo Arcia	MIN	146.0	-2.21	-2.7	-2
1227	2016	Mikie Mahtook	TBR	220.0	-2.23	0.2	-1
1228	2013	Matt Diaz	MIA	27.0	-2.23	-0.1	1
1229	2016	Robbie Grossman	MIN	508.0	-2.28	-7.2	-14
1230	2012	Tyler Moore	WSN	235.0	-2.28	-2.8	-8
1231	2012	Jason Kubel	ARI	1076.0	-2.29	-5	-4
1232	2015	Joey Butler	TBR	216.1	-2.30	1.1	2
1233	2015	Justin Upton	SDP	1260.1	-2.30	2	8
1234	2015	Brennan Boesch	CIN	144.1	-2.32	-6.1	-3
1235	2015	Domingo Santana	- - -	398.1	-2.32	-5.6	-4
1236	2012	Logan Morrison	MIA	479.1	-2.32	-6.9	-6
1237	2012	Jeff Francoeur	KCR	1299.1	-2.33	-5.8	-11
1238	2013	Lucas Duda	NYM	494.0	-2.33	-12	-11
1239	2012	Bobby Abreu	- - -	377.2	-2.33	-3.8	-8
1240	2013	Corey Dickerson	COL	366.1	-2.36	0.5	0
1241	2015	Matt Kemp	SDP	1282.0	-2.36	-17.2	-15
1242	2016	Michael Taylor	WSN	431.2	-2.36	1.7	-4
1243	2012	Yoenis Cespedes	OAK	900.2	-2.36	-10.1	-6
1244	2013	Chris Young	OAK	739.1	-2.37	0.2	-7
1245	2013	Ryan Ludwick	CIN	250.1	-2.38	-3.4	-3
1246	2015	Eduardo Escobar	MIN	236.2	-2.38	-5.2	0
1247	2016	Preston Tucker	HOU	144.0	-2.40	-1	-4
1248	2012	Jason Bay	NYM	457.1	-2.45	-2.2	-2
1249	2015	Rafael Ynoa	COL	112.2	-2.45	-2.6	-4
1250	2013	Jimmy Paredes	HOU	286.1	-2.47	-2.1	-5
1251	2012	Alfonso Soriano	CHC	1183.0	-2.48	11.9	-5
1252	2013	Delmon Young	- - -	503.1	-2.49	-9.4	-9
1253	2014	Brandon Guyer	TBR	537.2	-2.50	2.8	3
1254	2014	Alfonso Soriano	NYY	264.0	-2.52	-5.8	-5
1255	2015	Tyler Collins	DET	358.1	-2.52	-2.9	-5
1256	2012	Shelley Duncan	CLE	410.2	-2.52	-3.2	-3
1257	2013	J.D. Martinez	HOU	563.2	-2.55	-7.2	-9
1258	2016	Hunter Pence	SFG	578.2	-2.56	2.9	-2
1259	2016	Delino DeShields	TEX	365.0	-2.60	3.8	0
1260	2012	Jordany Valdespin	NYM	245.2	-2.60	-2.5	-4
1261	2016	Jay Bruce	- - -	969.1	-2.60	-13.2	-12
1262	2014	Junior Lake	CHC	633.2	-2.61	-4.5	-5
1263	2016	Tommy Pham	STL	302.0	-2.63	-7.5	-4
1264	2016	Matt Kemp	- - -	961.1	-2.63	-8.8	-10
1265	2015	Wil Myers	SDP	328.2	-2.65	-6.8	-6
1266	2016	Avisail Garcia	CHW	203.0	-2.71	-1.2	-2
1267	2012	Dayan Viciedo	CHW	1093.0	-2.72	-3.3	2
1268	2013	Jesus Guzman	SDP	246.2	-2.75	-1.1	-3
1269	2016	Odubel Herrera	PHI	991.0	-2.77	-2.8	0
1270	2014	Shin-Soo Choo	TEX	627.1	-2.78	-8.6	-12
1271	2016	Ryan Raburn	COL	285.2	-2.85	0.5	0
1272	2015	Brad Miller	SEA	253.0	-2.85	-14.4	-14
1273	2014	Andre Ethier	LAD	714.1	-2.85	-2	-7
1274	2015	Marcell Ozuna	MIA	1047.1	-2.90	-1.5	-3
1275	2016	Ian Desmond	TEX	1054.0	-2.97	6.7	-2
1276	2014	Josh Willingham	- - -	447.1	-2.99	-2.7	-2
1277	2012	Shane Robinson	STL	304.2	-3.00	3.6	2
1278	2015	Paulo Orlando	KCR	604.1	-3.05	6.1	8
1279	2013	Jeff Francoeur	- - -	565.1	-3.06	-1	0
1280	2016	Steven Moya	DET	190.1	-3.07	-6.4	-6
1281	2014	Ryan Kalish	CHC	237.1	-3.10	-6.7	-6
1282	2016	Michael Saunders	TOR	849.2	-3.11	-4.2	-5
1283	2012	Moises Sierra	TOR	316.0	-3.15	-3.5	-6
1284	2015	J.D. Martinez	DET	1306.1	-3.19	7.7	4
1285	2013	Chris Carter	HOU	352.2	-3.20	-6.7	-4
1286	2014	Jason Kubel	MIN	353.1	-3.26	-9.3	-9
1287	2012	Cody Ross	BOS	972.0	-3.26	3.2	0
1288	2015	Mike Napoli	TEX	50.0	-3.27	-1.5	-2
1289	2016	Matt Holliday	STL	644.0	-3.33	-4.8	-7
1290	2015	Chris Young	NYY	781.2	-3.36	-0.7	-3
1291	2012	Rajai Davis	TOR	1037.2	-3.40	-5.4	3
1292	2012	Jason Bourgeois	KCR	140.2	-3.41	-3.4	-5
1293	2014	Jayson Werth	WSN	1220.2	-3.42	-1.6	-4
1294	2014	Ezequiel Carrera	DET	160.1	-3.48	0	0
1295	2014	Danny Santana	MIN	535.2	-3.50	-5.4	0
1296	2012	Giancarlo Stanton	MIA	1034.1	-3.52	9.1	9
1297	2016	Yasmany Tomas	ARI	860.0	-3.61	-6.5	-7
1298	2015	Jayson Werth	WSN	720.2	-3.63	-6.7	-11
1299	2016	Seth Smith	SEA	545.0	-3.67	-8.7	-10
1300	2015	Charlie Blackmon	COL	1303.2	-3.68	-7.3	-7
1301	2014	Carlos Beltran	NYY	259.2	-3.69	-3.9	-5
1302	2016	Andrew McCutchen	PIT	953.2	-3.70	-7.9	-17
1303	2016	Domingo Santana	MIL	296.0	-3.71	-5.4	-7
1304	2012	Jayson Werth	WSN	692.0	-3.74	-13.9	-11
1305	2014	Matt Kemp	LAD	1195.2	-3.75	-22.4	-22
1306	2012	J.D. Martinez	HOU	833.0	-3.78	-6.5	-2
1307	2014	Michael Choice	TEX	495.0	-3.82	-9.8	-9
1308	2013	Dayan Viciedo	CHW	892.2	-3.93	-6	-4
1309	2015	Austin Jackson	- - -	1048.2	-4.04	7.2	-1
1310	2016	Randal Grichuk	STL	627.0	-4.04	-3	8
1311	2012	Carlos Gonzalez	COL	1127.2	-4.17	-6.8	-13
1312	2012	Colby Rasmus	TOR	1237.1	-4.21	0.4	7
1313	2014	Mark Trumbo	ARI	358.2	-4.26	-5.2	-7
1314	2012	Justin Upton	ARI	1280.2	-4.38	-3.1	1
1315	2015	Jeff Francoeur	PHI	658.2	-4.41	-7	-11
1316	2012	Matt Holliday	STL	1312.2	-4.41	-4	-6
1317	2016	Rickie Weeks Jr.	ARI	187.2	-4.46	-4.6	-5
1318	2012	Hunter Pence	- - -	1408.1	-4.48	-2.8	-6
1319	2014	Michael Morse	SFG	579.0	-4.49	-10.8	-10
1320	2014	Eduardo Nunez	MIN	101.0	-4.55	1.4	1
1321	2016	Oswaldo Arcia	- - -	335.0	-4.59	-4.2	-4
1322	2016	Mark Trumbo	BAL	580.0	-4.74	-4.3	-6
1323	2015	Mark Trumbo	- - -	670.0	-4.79	-2.8	-4
1324	2015	Kelly Johnson	- - -	228.1	-4.79	-0.7	-1
1325	2015	Shin-Soo Choo	TEX	1262.0	-4.81	-3.9	-11
1326	2014	Matt Holliday	STL	1280.2	-4.82	-1.9	-1
1327	2015	Jonny Gomes	- - -	453.0	-4.89	-9.3	-7
1328	2016	Tyler Naquin	CLE	599.1	-4.97	-6.1	-14
1329	2013	Evan Gattis	ATL	342.1	-5.05	-7.3	-10
1330	2015	Alex Rios	KCR	914.2	-5.06	4.5	-6
1331	2016	Miguel Sano	MIN	312.2	-5.10	-2.7	-9
1332	2014	Oswaldo Arcia	MIN	846.2	-5.11	-4.5	-9
1333	2013	Matt Holliday	STL	1150.1	-5.15	-5.1	-13
1334	2013	Oswaldo Arcia	MIN	712.1	-5.27	-12.3	-16
1335	2015	Carlos Beltran	NYY	968.1	-5.28	-4.5	-14
1336	2014	Dayan Viciedo	CHW	1030.1	-5.34	-10.8	-15
1337	2012	Lucas Duda	NYM	846.1	-5.41	-22.5	-17
1338	2016	J.D. Martinez	DET	682.0	-5.54	-10.2	-14
1339	2014	Yoenis Cespedes	- - -	1125.2	-5.58	8.4	10
1340	2013	Caleb Gindl	MIL	292.1	-5.71	-1.4	-2
1341	2015	Hanley Ramirez	BOS	747.2	-5.99	-17.8	-19
1342	2015	Chris Colabello	TOR	365.0	-6.06	-13.7	-14
1343	2016	Danny Santana	MIN	440.1	-6.48	-3.9	-10
1344	2015	Avisail Garcia	CHW	1124.0	-7.21	-6.2	-11
1345	2015	Adam Eaton	CHW	1280.0	-7.40	-10.2	-14