Friday, December 08, 2006

Bonderman Among AL FIP Leaders

In an earlier post, I discussed team run prevention using FIP ERA to measure pitching performance and DER to measure fielding performance. Now, I will evaluate the performance of individual starting pitchers using FIP ERA. There were 56 American League pitchers with 17 starts (approximately a half season) or more in 2005. Table 1 below lists Detroit Tiger starting pitchers in 2006. Table 2 lists all 56 qualifiers in the league.


In both tables, ERA represents the pitcher’s actual ERA. FIP ERA represents the pitcher’s equivalent ERA based on fielding independent statistics (K,BB,HR) only. DER is the Defensive Efficiency Ratio of the team when the given pitcher was on the mound. A higher DER indicates that he received more fielding support. FIP-Actual is the difference between the pitcher’s FIP ERA and actual ERA. It tells how much the actual ERA was helped or hurt by non FIP factors. A negative number indicates that the pitcher probably pitched better than his actual ERA. A positive number says that he probably pitched worse than his actual ERA. LOB% is the percentage of runners put on base which were left stranded.


The tables show that Jeremy Bonderman had a FIP-Real of -0.71 indicating that he pitched better than his actual ERA. His DER (.682) was lower than any starting pitcher on the team which means that he may have received less fielding support than his pitching mates. While Bonderman’s actual ERA (4.08) was 16th in the league, his FIP ERA (3.37) was 4th.


Since FIP ERA is a better predictor of future performance than actual ERA, Bonderman’s exceptional FIP ERA in 2006 may bode well for 2007. The bad news is that his FIP ERA has been far better than his actual ERA for 4 straight years indicating that it might be something more than just bad luck. The good news is that he has indeed improved his ERA each year and in each case it has been pretty close to his FIP ERA of the previous year. That may just be a coincidence but let’s hope the trend continues next year.


On the other hand, Justin Verlander (4.37 versus 3.63), Kenny Rogers (4.68 versus 3.84) and Nate Robertson (4.73 versus 3.84) all had FIP ERAs approaching a run above their actual ERAs. All three had DERs greater than .70 which suggests that they received better fielding support than Bonderman. Verlander (78%) and Robertson (76%) were in the top 8 in the league in LOB%. LOB% is not generally a repeatable stat so I’m inclined to think that the three were a little fortunate in that respect. Bonderman stranded only 69% of his base runners as compared to the league average of 70%. This may have been a product of not pitching well with men on base and allowing big innings but that’s just a guess.



What can we expect from next year? I would expect Bonderman to continue to lower his ERA. The other 3 pitchers will likely have to pitch better if they are going to finish in the top 15 in ERA again next year. Verlander is young and developing and should keep his ERA down if his arm is healthy and strong after a heavy workload in his rookie year. Robertson and Rogers might fall back a little but maybe not too much if the Tigers continue to field well.



Table 1 – FIP ERA for Tiger Starters in 2006


FIP ERA Rank

Name

IP

ERA

FIP ERA

DER

FIP-Actual

LOB %

4

Bonderman

214.0

4.08

3.37

.682

-0.71

.69

28

Verlander

186.0

3.63

4.37

.706

0.74

.78

35

Rogers

204.0

3.84

4.68

.738

0.84

.72

36

Robertson

208.7

3.84

4.73

.723

0.89

.76

N/A

Ledezma

60.3

3.58

4.20

.718

0.62

.73

N/A

Maroth

53.7

4.19

5.93

.709

1.74

.84

N/L

Miner

93.0

4.84

4.57

.699

-0.27

.68


Table 2 – FIP ERA for AL starters in 2006


FIP ERA Rank

Name

Team

IP

ERA

FIP ERA

DER

FIP-Actual

LOB %

1

Santana

MIN

233.7

2.77

3.11

.731

0.34

.78

2

Sabathia

CLE

192.7

3.22

3.32

.706

0.10

.72

3

Lackey

LAA

217.7

3.56

3.35

.703

-0.21

.70

4

Bonderman

DET

214.0

4.08

3.37

.682

-0.71

.69

5

Kazmir

TB

144.7

3.24

3.44

.691

0.20

.77

6

Mussina

NYA

197.3

3.51

3.51

.716

-0.00

.70

7

Bedard

BAL

196.3

3.76

3.64

.691

-0.12

.72

8

Halladay

TOR

220.0

3.19

3.66

.725

0.47

.75

9

Schilling

BOS

204.0

3.97

3.67

.676

-0.30

.76

10

Escobar

LAA

189.3

3.61

3.68

.694

0.07

.69

11

Burnett

TOR

135.7

3.98

3.73

.688

-0.25

.71

12

Vazquez

CHA

202.7

4.84

3.76

.692

-1.08

.66

13

Hernandez

SEA

191.0

4.52

3.93

.688

-0.59

.68

14

Millwood

TEX

215.0

4.52

3.94

.694

-0.58

.68

15

Westbrook

CLE

211.3

4.17

3.94

.678

-0.23

.70

16

Weaver

LAA

123.0

2.56

3.95

.764

1.39

.86

17

Wang

NYA

218.0

3.63

4.00

.708

0.37

.72

18

Contreras

CHA

196.0

4.27

4.07

.717

-0.20

.68

19

Haren

OAK

223.0

4.12

4.10

.711

-0.02

.72

20

Loewen

BAL

112.3

5.37

4.11

.686

-1.26

.64

21

Padilla

TEX

200.0

4.50

4.13

.696

-0.38

.70

22

Blanton

OAK

194.3

4.82

4.20

.665

-0.62

.69

23

Wright

NYA

140.3

4.49

4.22

.685

-0.27

.70

24

Loaiza

OAK

154.7

4.89

4.22

.689

-0.67

.66

25

Cabrera

BAL

148.0

4.74

4.22

.691

-0.52

.70

26

Johnson

NYA

205.0

5.00

4.25

.719

-0.75

.62

27

Santana

LAA

204.0

4.28

4.26

.735

-0.02

.67

28

Verlander

DET

186.0

3.63

4.37

.706

0.74

.78

29

Garland

CHA

211.3

4.51

4.39

.691

-0.12

.71

30

Shields

TB

124.7

4.84

4.39

.672

-0.45

.72

31

Garcia

CHA

216.3

4.53

4.61

.718

0.08

.70

32

Meche

SEA

186.7

4.48

4.62

.705

0.14

.70

33

Bonser

MIN

100.3

4.22

4.65

.706

0.43

.76

34

Janssen

TOR

94.0

5.07

4.66

.718

-0.41

.64

35

Rogers

DET

204.0

3.84

4.68

.738

0.84

.72

36

Robertson

DET

208.7

3.84

4.73

.723

0.89

.76

37

Lee

CLE

200.7

4.40

4.73

.704

0.33

.71

38

Radke

MIN

162.3

4.32

4.76

.685

0.44

.73

39

Washburn

SEA

187.0

4.67

4.79

.721

0.12

.70

40

Byrd

CLE

179.0

4.88

4.81

.682

-0.07

.65

41

Zito

OAK

221.0

3.83

4.84

.719

1.01

.79

42

Wakefield

BOS

140.0

4.63

4.84

.736

0.21

.69

43

Lilly

TOR

181.7

4.31

4.85

.712

0.54

.74

44

Lopez

BAL

189.0

5.90

4.97

.672

-0.93

.67

45

Redman

KC

167.0

5.71

4.97

.681

-0.74

.66

46

Beckett

BOS

204.7

5.01

5.10

.737

0.09

.69

47

Moyer

SEA

160.0

4.39

5.10

.710

0.71

.74

48

Fossum

TB

130.0

5.33

5.17

.714

-0.16

.66

49

Pineiro

SEA

165.7

6.36

5.18

.673

-1.18

.64

50

Koronka

TEX

125.0

5.69

5.19

.698

-0.50

.68

51

Buehrle

CHA

204.0

4.99

5.31

.693

0.32

.71

52

Benson

BAL

183.0

4.82

5.60

.721

0.78

.73

53

Silva

MIN

180.3

5.94

5.77

.687

-0.17

.67

54

Hernandez

KC

109.7

6.48

6.28

.678

-0.20

.67

55

Chacin

TOR

87.3

5.05

6.33

.741

1.28

.77

56

Elarton

KC

114.7

5.34

6.72

.753

1.38

.74

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