Wednesday, December 24, 2008

Run Preventing Events - 2008

A couple of years ago, I developed a crude but I believe useful statistic called Run Preventing Event Percentage. Here is how it works: An at bat can result in any of the following events:

  • Strikeout
  • Base on balls
  • Hits batsman
  • Ground ball
  • Line drive
  • Outfield fly
  • Infield fly
Three of those events are generally favorable events for pitchers:

  • Strikeout
  • Ground ball
  • Infield fly
I call these run preventing events (RPE). Of course, a ground ball is not as easy an out as a strikeout or an infield fly and can have a negative result for a pitcher. However, inducing a lot of ground balls will help to prevent runs over the course of a season. On the other hand, it is good for pitchers to avoid, for the most part, the following events:

  • Base on balls
  • Hits batsman
  • Line drive
  • Outfield fly
Run Preventing Event percentage (RPE%) is calculated as follows: (SO + GB + IFF)/BFP. Striking out batters and inducing grounders have been shown to be repeatable skills. Getting batters to hit infield flies is not very stable from year to year. However, infield flies are relatively rare compared to other batted ball types and including them does not change the RPE% substantially in most cases. Plus, I suspect (without statistical evidence) that this is a real ability for some power pitchers.

RPE% is essentially a fielding independent statistic because, although the end result is not independent of fielders, getting a grounder or infield fly to happen in the first place has nothing to do with fielders. It is as stable or more stable from year to year as FIP ERA but it is not weighted and thus does not explain quite as much about runs allowed. The value of RPE% is its simplicity.

There were 53 American League starters with 125 or more innings pitched in 2008. Table 1 lists the RPE% rankings for Tigers starters. Table 2 lists the top 20 pitchers in the league. In general, the RPE% seems to be good for identifying effective pitchers but sometimes it gives surprising results.

From Table 1, we can see that Nate Robertson (RPE%=51.4) ranked a lot better on RPE% (28th in the AL) than he did on ERA (53rd or dead last). Robertson had a league average ground ball percentage and walked batters in only 8% of plate appearances (league average = 10%). However, when he did give up a line drive or a fly ball, it tended to end up really bad. According to The Hardball Times Baseball Annual 2009, he allowed more runs per line drive than the average American League pitcher (.43 versus a .39) and far more runs per outfield fly than average (.28 versus .18). Part of this was Robertson's relatively high homeruns per flyball (13%). It's also possible, he allowed a lot of his line drives and fly balls with runners on base.

Recently acquired Edwin Jackson posted a low 47.1% RPE% but still managed a 4.42 ERA. In his case, he had a very low strikeout rate (14% versus a league average of 18%) and ground ball rate (39% versus 44%). However, his line drives (.35 runs) and outfield flies (.17) did a lot less damage than Robertson's line drives and fly balls.

What does this all mean for the future? Well, run preventing events are more predictive than runs per line drive/fly ball. Thus, if Robertson and Jackson pitch the same way they did last year, we can expect Nate's ERA to go down and Edwin's to go up.

The raw data used in calculating RPE% were abstracted from The Hardball Times database.

Table 1: Run Preventing Events for Tigers Starters in 2008

Rank

Name

BFP

SO

GB

IF

RPE

RPE%

24

Galarraga

746

126

241

25

392

.525

28

Robertson

761

108

262

21

391

.514

38

Verlander

880

163

246

26

435

.494

45

Jackson

792

108

237

28

373

.471

46

Rogers

782

82

257

24

363

.464

**

Miner

509

62

180

8

250

.491

**

Bonderman

319

44

112

9

165

.517


Table 2: Top 20 AL Starters by RPE% in 2008

Rank

Name

Team

BFP

SO

GB

IF

RPE

RPE%

1

Halladay

TOR

987

206

392

17

615

.623

2

Burnett

TOR

957

231

306

24

561

.586

3

Hernandez

SEA

857

175

309

14

498

.581

4

Pettitte

NYA

881

158

340

12

510

.579

5

Mussina

NYA

819

150

306

13

469

.573

6

Lee

CLE

891

170

313

27

510

.572

7

Buehrle

CHA

918

140

358

19

517

.563

8

Shields

TB

877

160

308

20

488

.556

9

Lester

BOS

874

152

307

26

485

.555

10

Santana

LAA

897

214

244

37

495

.552

11

Hochevar

KC

566

72

229

9

310

.548

12

Beckett

BOS

725

172

208

16

396

.546

13

Greinke

KC

851

183

260

19

462

.543

14

Litsch

TOR

735

99

286

10

395

.537

15

Lackey

LAA

675

130

223

7

360

.533

16

Garza

TB

772

128

241

42

411

.532

17

Danks

CHA

804

159

250

19

428

.532

18

Sonnanstine

TB

819

124

275

36

435

.531

19

Marcum

TOR

630

123

194

17

334

.530

20

Garland

LAA

864

90

353

15

458

.530



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