2013 Fantasy BaseballFantasy BaseballFront Office

Looking Back at the 2013 Draft: NL Left Fielders

At some point, the whole “early stats don’t matter” mantra begins to get old. The question is when we should discard it like yesterday’s garbage. Play in fantasy baseball for long enough and you will face this dilemma with your fantasy roster. You have guys on your team that you drafted based on past performance. They aren’t performing and the calendar has hit May. How much rope do you give these guys? Meanwhile, guys you passed up are torching through the league like they did back in Little League. It can be enough to shake your confidence at times.

Different experts have different time frames that they start looking at. In many respects, it depends on the particular categories you are focused on. For the most part, six weeks seems to be a magic line, but some want to push that out until Memorial Day. Holidays rarely ever signify anything in quantifiable statistics, but if it gives you a date on the calendar to circle then it works as well as any. Left field perhaps more than position represents the gaps between expectations and present realities.

[am4show have=’p4;p7;p3;’ guest_error=’Front Office’ user_error=’Front Office’ ]

Owned

TAV

BR

RC

Carlos Gonzalez

99

.284

15.4

94

Ryan Braun

99

.332

49.9

131

Bryce Harper

99

.291

15.1

85

Justin Upton

99

.279

5.8

85

Matt Holliday

98

.310

33.7

108

Carl Crawford

89

.267

0.8

18

Starling Marte

77

.261

-0.1

20

Alfonso Soriano

49

.278

12.0

84

Jason Kubel

47

.286

10.2

81

Gerardo Parra

33

.259

-4.3

50

Domonic Brown

23

.254

-2.2

22

Juan Pierre

22

.272

-0.7

55

Carlos Quentin

16

.319

18.5

53

Ryan Ludwick

8

.290

18.7

74

Delmon Young

6

.252

-7.6

63

Collin Cowgill

2

.242

-1.8

10

John Mayberry

2

.262

-7.2

47

Scott Hairston

1

.287

8.4

54

Gregor Blanco

1

.266

-4.7

50

Chris Heisey

1

.248

-3.3

41

Median

—-

.275

3.3

55

When we look at our list we first have to distill out the guys that are now injuried. That class includes Jason Kubel and Ryan Ludwick. Delmon Young just returned from injury so he could fit into that category as well. Then, there are guys that we might classify as part-time players. That would include Chris Heisey, Scott Hairston, John Mayberry, Collin Cowgill, and Gerardo Parra. The rest could be called regulars and for the first time in this series, we are going to take a look at what is happening this season. In this regard we will look at only one number: BABIP.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . .BABIP

  • Starling Marte. . . . . . . . . . . .402
  • Carlos Gonzalez. . . . . . . . . ..360
  • Ryan Braun. . . . . . . . . . . . . ..351
  • Gregor Blanco. . . . . . . . . . . .351
  • Carl Crawford. . . . . . . . . . . ..338
  • Alfonso Soriano. . . . . . . . . ..317
  • Bryce Harper. . . . . . . . . . . . .315
  • Justin Upton. . . . . . . . . . . . ..293
  • Domonic Brown. . . . . . . . . ..288
  • Matt Holliday. . . . . . . . . . . ..269
  • Juan Pierre. . . . . . . . . . . . . ..242
  • Carlos Quentin. . . . . . . . . . ..225

We’ve learned a great deal about batting average on balls in play in the last several years. When Voros McCracken first started tracking this statistic, it was assumed that most players would gravitate around the league average (roughly .300). If they were significantly above or below it was assumed that it had more to do with luck than anything else. That thinking has changed as we have become more sophisticated in tracking the kinds of balls that are in play. With the advent of pitch f/x and other computer based metrics, we can now track the percentage of balls that are line drives, groundballs, and fly balls. Undoubtedly, we might even start tracking the velocity of the ball in play and other factors to determine whether that ball in play would be easily fielded or a more difficult play.

The long and short of it is that some players will naturally outproduce the league average in BABIP while others will not. When looking at statistics like above, it pays to go back on each player in question to determine their particular norms in this area. It isn’t normal for anyone to produce a .350 or above BABIP over an extended period of time. Certainly, Starling Marte is benefitting from a very prosperous streak of batted ball luck. He is going to face the angry mistress that is regression at some point.

On the flip side, inconsistent playing time and a rough start have combined to make Carlos Quentin very underappreciated at this point. He is owned by only 16 percent of players in mixed leagues at this point. If he is on the waiver wire I wouldn’t waste anytime picking him up. Remember, he hadn’t had a single plate appearance by this time last year and still produced around the median in runs created last season. He should easily surpass that this season and his batted ball luck will certain turn around by then.

However, I have to spend much of this article eating a helping serving of crow. You would think that Justin Upton was a candidate to see some regression coming his way and he certainly should on his home runs per fly ball ratio, but overall as a hitter he is right around where he should be in terms of BABIP. At .293 he might even see some improvement when you compare that rate with his career norms. In other words, Upton is very much for real and I missed the boat on that one. Everyone makes mistakes I guess.

All that being said, I stand by what I have said about Carlos Gonzalez and that angry mistress will prove me right eventually. I always thought there were a few left fielders that should have gone above him in the draft and Matt Holliday is one of them. His .269 BABIP certainly points towards some positive regression in the near future. Regression is much like gambling, over a long enough timeline the house always wins. If you allow time before you panic, you will see that most players will settle around where they should be. The key is always knowing when to say when.

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