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How worried or heartened should we be by the St. Louis Cardinals' early batting stats?

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Jasen Vinlove-USA TODAY Sports

The St. Louis Cardinals have played eight games so far this year. That's 4.9% of the club's 162 slated games this season. Almost anything is possible statistically in a mere eight baseball games. The difference between early April and mid-June, however, is that a player's statistical line is blank slate at the start of April. How well or poorly he has hit in the last handful of games is there for all to see in his seasonal stat line. Hence the common refrain that early-April stats are by and large meaningless. This is at once true and false.

What do I mean by this? A player's great or poor performance in the season's opening games should not cause one to leap to any conclusions about how he will hit for the rest of the year. However, a bad or stupendous opening to a baseball season will likely have a small impact on the player's end-of-season statistical line. The ZiPS projections to illustrate my point.

I put together some charts of the Cardinals' primary position players. They show the player's 2015 batting line to date, his preseason 2015 ZiPS projection, his current Rest of Season ZiPS projection, and his updated ZiPS projections (which is based on the inputs that generated his preseason projection as well as his 2015 performance to date). They include the stats plate appearances (PA), strikeout rate (K%), walk rate (BB%), Batting Average on Balls In Play (BABIP), batting average (BA), on-base percentage (OBP), slugging percentage (SLG), Isolated Power (ISO), Weighted On-Base Average (wOBA), and Weighted Runs Created Plus (wRC+). I've ordered the individual player charts from largest decrease in ZiPS projected wOBA from preseason to updated ZiPS as of the morning of April 17, 2015.

Jason Heyward

Stats

PA

K%

BB%

BABIP

BA

OBP

SLG

OPS

ISO

wOBA

wRC+

ZiPS P

597

17.3

10.1

.306

.269

.348

.424

.773

.155

.343

-

2015

37

18.9

2.7

.276

.222

.243

.333

.606

.111

.252

63

ZiPS R

573

17.3

9.7

.304

.267

.344

.420

.764

.153

.339

117

ZiPS U

610

17.4

9.3

.302

.264

.338

.414

.752

.150

.334

114

Diff.

+13

+0.1

-0.8

-.004

-.005

-.010

-.010

-.021

-.005

-.009

-

Matt Adams

Stats

PA

K%

BB%

BABIP

BA

OBP

SLG

OPS

ISO

wOBA

wRC+

ZiPS P

501

22.2

5.0

.332

.281

.317

.457

.775

.176

.337

-

2015

26

19.2

7.7

.167

.167

.231

.292

.522

.125

.237

52

ZiPS R

481

22.1

5.1

.327

.277

.315

.452

.766

.175

.334

114

ZiPS U

507

21.9

5.2

.319

.271

.310

.443

.754

.172

.329

111

Diff.

+6

-0.3

+0.2

-.013

-.010

-.007

-.014

-.021

-.004

-.008

-

Jon Jay

Stats

PA

K%

BB%

BABIP

BA

OBP

SLG

OPS

ISO

wOBA

wRC+

ZiPS P

530

15.3

6.6

.332

.284

.352

.374

.726

.090

.324

-

2015

29

17.2

0.0

.273

.222

.276

.259

.535

.037

.246

59

ZiPS R

505

15.4

6.4

.330

.282

.349

.369

.719

.088

.322

105

ZiPS U

534

15.5

6.0

.327

.278

.345

.363

.708

.085

.317

103

Diff.

+4

+0.2

-0.6

-.005

-.008

-.007

-.011

-.018

-.005

-.007

-

Yadier Molina

Stats

PA

K%

BB%

BABIP

BA

OBP

SLG

OPS

ISO

wOBA

wRC+

ZiPS P

508

11.0

6.3

.310

.292

.340

.426

.766

.134

.336

-

2015

34

20.6

11.8

.364

.276

.364

.310

.674

.034

.298

94

ZiPS R

487

11.5

6.6

.314

.292

.342

.421

.763

.129

.335

115

ZiPS U

521

12.1

6.9

.316

.291

.344

.414

.758

.123

.333

113

Diff.

+13

+1.1

+0.6

+.006

-.001

+.004

-.012

-.008

-.011

-.003

-

Kolten Wong

Stats

PA

K%

BB%

BABIP

BA

OBP

SLG

OPS

ISO

wOBA

wRC+

ZiPS P

552

15.2

5.6

.297

.264

.310

.389

.700

.125

.309

-

2015

32

9.4

15.6

.250

.231

.344

.308

.652

.077

.285

85

ZiPS R

529

14.9

6.0

.294

.263

.311

.387

.697

.124

.308

96

ZiPS U

561

14.6

6.6

.291

.261

.313

.383

.695

.121

.306

95

Diff.

+9

-0.6

+1.0

-.006

-.003

+.003

-.006

-.005

-.004

-.003

-

Matt Holliday

Stats

PA

K%

BB%

BABIP

BA

OBP

SLG

OPS

ISO

wOBA

wRC+

ZiPS P

584

16.6

10.4

.304

.275

.363

.456

.819

.181

.361

-

2015

37

18.9

18.9

.435

.333

.459

.333

.792

.000

.360

137

ZiPS R

561

16.7

10.8

.309

.277

.367

.451

.818

.173

.361

132

ZiPS U

598

16.8

11.3

.316

.281

.373

.444

.817

.163

.361

132

Diff.

+14

+0.2

+1.1

+.012

+.006

+.010

-.012

-.002

-.018

+/-0

-

Jhonny Peralta

Stats

PA

K%

BB%

BABIP

BA

OBP

SLG

OPS

ISO

wOBA

wRC+

ZiPS P

543

17.7

7.9

.301

.265

.326

.423

.749

.158

.330

-

2015

35

20.0

5.7

.440

.364

.400

.545

.945

.182

.412

172

ZiPS R

522

17.8

7.8

.307

.270

.329

.429

.758

.159

.334

114

ZiPS U

557

17.9

7.7

.315

.276

.334

.436

.770

.160

.339

117

Diff.

+13

+0.2

-0.2

+.014

+.011

+.008

+.013

+.020

+.002

+.009

-

Matt Carpenter

Stats

PA

K%

BB%

BABIP

BA

OBP

SLG

OPS

ISO

wOBA

wRC+

ZiPS P

630

15.6

11.0

.317

.276

.360

.404

.764

.128

.340

-

2015

37

10.8

10.8

.393

.364

.432

.576

1.008

.212

.437

190

ZiPS R

599

15.5

11.0

.323

.279

.365

.412

.777

.132

.346

122

ZiPS U

636

15.2

11.0

.328

.284

.369

.421

.791

.137

.352

126

Diff.

+6

-0.4

+/- 0

+.011

+.008

+.009

+.017

+.027

+.009

+.012

-

As fans it's understandable that we worry. We watch the games and see Molina hit many a grounder and hardly anything with authority, Adams looking lost, Carpenter locked in, or Holliday's singles barrage and wonder what they mean. ZiPS doesn't see the way a player looks while producing his stat line. All it sees is the stat line. This makes ZiPS at once more ignorant and more rational.

Eight games (i.e., 4.9%) into the season, the ZiPS Rest of Season (ZiPS R) and ZiPS Updated (ZiPS U) projections give us an idea of how worried we should be. For the most part, ZiPS R forecasts the Cardinals to be the same players stats-wise that it projected before opening day with a point or three added or subtracted here and there. However the slow or hot starts will have a negative or positive effect on the players' end-of-season stat lines.

The season is long and the bend of stat lines is typically toward a regression to something close to a player's preseason projections. There's not much to be overly enthusiastic or worried about today. Throughout the season, we'll touch base with the ZiPS R and ZiPS U projections to gauge the arc of a player's season to date against his expectations.

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