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July 22, 2020
  

Formula 40:  BABIP  (Batting Average on Balls In Play

Out of an excess of caution, I am going to give a definition of Batting Average on Balls in Play:

 

BABIP = (H – HR) / (BFP – SO – BB – HBP – HR)

 

 

Formula 41:  BABIP+ v Team  (Batting Average on Balls in Play better than team)

In the 20th century, it was the essentially universal practice of baseball fans to regard "giving up hits" as something the pitcher did.  Hits allowed were a pitcher’s stat, a basic and important one.  Since Voros’ convincing argument that Batting Average on Balls in Play against a pitcher is a random and therefore meaningless stat, modern analysis has swung toward the assumption that the pitcher plays no role in getting balls in play to become outs. 

While there is no doubt that Voros’ position on this issue is much more accurate than the previous universal understanding, it is also clear that there is SOME connection between a pitcher’s performance and his BABIP.  This system assigns 90% of the deviation in BABIP to the fielders, but reserves 10% of it for the pitchers. 

The first step in that is comparing each player’s BABIP to his team’s.  We multiply the Balls in Play against the Pitcher times the team BABIP, and then subtract the pitcher’s actual Hits In Play:

 

BABIP + vs. Team = (Team BABIP) * (BFP – SO – BB – HR – HBP)  - (H – HR)

BUT NEVER LESS THAN ZERO.  

 

If the result of this formula would be less than zero, it is zero. 

 

Formula 42:  Team BABIP+  (Team Total of BABIP+)

 

The Team BABIP+ is the sum total of the of the BABIP+ for the Individual Pitchers on the staff. 

 

Formula 43:  RS-Pit-BIP-P10  (Runs Saved by the pitcher on Balls in Play; 10th Pitcher’s Value.) 

 

I will use Felipe Lira of the Detroit Tigers, 1996, to illustrate the process.  Lira was +24 when you compare his individual BABIP to the team’s average.  The batting average on balls in play against that dreadful, 109-loss team was .313.  Lira had 631 Balls in Play while he was on the mound, so he could have expected to have 198 hits on balls in play.   In fact, he had only 174, so he was 24 hits better than his team.   This is the highest BABIP+ vs. Team number on any of the 15 teams in this study.  

The total for all pitchers on the 1996 Detroit team is +57—actually, +56.999.    These are the totals for the "positive" pitchers on that team:

Felipe Lira

24

Omar Olivares

12

Richie Lewis

11

Gregg Olson

4

Brian Moehler

3

Justin Thompson

2

Joey Eischen

0

 

Eischen is at 0.45, although it rounds to zero.   Anyway, you divide of those numbers by 56.999:

 

BABIP +

Team Tot

Percentage

Felipe Lira

24

56.999

42%

Omar Olivares

12

56.999

21%

Richie Lewis

11

56.999

20%

Gregg Olson

4

56.999

8%

Brian Moehler

3

56.999

4%

Justin Thompson

2

56.999

4%

Joey Eischen

0

56.999

1%

 

So Lira gets 42% of the 10% of the Team’s Runs Saved by Range which are allocated for pitchers.  

The 1996 Tigers have 81 Runs Saved by Defensive Range; actually, 80.7.   Ten percent of that is 8.07, so the Tiger pitchers are credited with 8.07 Runs Saved by Range/BABIP.   Felipe gets 42% of that, which is 3.37 Runs Saved. 

 

 

BABIP +

Team Tot

Percentage

Team RS

Pitcher's Share

P10

Felipe Lira

24

56.999

42%

80.7

8.07

3.37

Omar Olivares

12

56.999

21%

80.7

8.07

1.73

Richie Lewis

11

56.999

20%

80.7

8.07

1.59

Gregg Olson

4

56.999

8%

80.7

8.07

0.62

Brian Moehler

3

56.999

4%

80.7

8.07

0.36

Justin Thompson

2

56.999

4%

80.7

8.07

0.34

Joey Eischen

0

56.999

1%

80.7

8.07

0.06

 

While Lira’s 24 BABIP+ vs. Team is the highest in the study, his 3.37 Runs Saved by BABIP are nowhere near the highest.   They’re in 18th place.  The highest two figures are 5.76, by Denny McLain in 1968, and 5.70, by Willie Hernandez in 1984—both of them MVPs, both for the Detroit Tigers.   McLain was +13 vs. the Team, but the team BABIP was much, much higher, and consequently the Runs Saved by range for Detroit, 1968, was more than twice as high as the Runs Saved by range for Detroit, 1996. 

 

Let’s see if I can put that in a formula:

RS-Pit-BIP-P10  = BABIP+ vs Team / (Team BABIP+) * Team-RS-Range * .10

 

Team-RS-Range was Formula 38.    These are the top 25 pitchers on these 15 teams, in terms of Runs Saved:

 

Year

Player

P1

P2

P3

P4

P5

P6

P7

P8

P9

P 10

Total

1968

Denny McLain

45

27

21

7

1

1

6

3

2

6

119

2004

Randy Johnson

47

20

18

4

2

0

0

1

1

3

96

1960

Bob Friend

29

27

23

7

0

0

4

2

2

0

94

1960

Vern Law

19

26

18

7

1

1

7

2

2

4

88

2008

Cole Hamels

32

18

12

5

1

1

2

1

1

5

77

1984

Dan Petry

23

16

17

5

4

1

2

3

1

0

73

1976

Gary Nolan

18

25

13

4

1

0

2

1

1

5

71

1968

Earl Wilson

27

15

16

4

2

1

4

1

2

0

71

1992

Jack Morris

21

13

20

4

2

0

4

2

1

3

70

1968

Mickey Lolich

32

13

14

5

3

0

1

0

1

0

69

1984

Jack Morris

24

13

19

4

1

1

2

2

1

1

68

2016

Jon Lester

32

13

12

3

2

0

3

2

1

0

68

2016

Jake Arrieta

31

8

15

2

0

2

4

2

2

3

67

2016

Kyle Hendricks

27

13

14

3

2

1

2

3

1

1

67

1980

Floyd Bannister

25

15

14

4

1

0

1

1

1

5

67

1964

Jack Fisher

19

18

16

5

1

1

4

1

1

0

66

1976

Pat Zachry

23

9

20

4

3

1

1

1

1

2

65

2000

Andy Pettitte

20

11

17

5

2

1

7

1

1

0

65

1964

Al Jackson

18

16

17

5

1

0

4

1

1

0

64

1992

Jimmy Key

19

15

13

4

1

1

2

2

1

4

64

2000

Roger Clemens

30

8

12

4

2

0

3

2

1

1

63

2012

Lucas Harrell

23

9

17

3

1

0

4

3

1

2

63

1964

Tracy Stallard

19

13

17

4

2

0

2

1

1

4

62

2004

Brandon Webb

26

1

18

2

3

1

6

1

1

1

61

1984

Milt Wilcox

19

10

17

4

2

1

5

1

1

0

61

 

Willie Hernandez, 1984 MVP, is estimated to have saved "only" 51 runs, but of course Hernandez saved 51 Runs in 140 innings, whereas Denny McLain saved 119 Runs in 336 innings. 

 

Wrapping Up the Pitchers

We are temporarily done with estimating the Runs Saved by pitchers; in our next article we will move on to evaluating the Runs Saved by Catchers.   Before we move on, though, a few thoughts:

1)      We’re at the end of this road, but there is never an end of the road in

sabermetrics, or any other science.  After we run the numbers for the other positions, there will be a reconciliation process so that the numbers for every team add up to the actual successes of the team.

            But that’s not the end of the road, either.  After we do that, we have to place the Runs Saved in a competitive context.  60 Runs Saved pitching 120 innings is very different from 60 Runs Saved pitching 250 innings.   That’s not the end of the road, either; 60 Runs Saved in 1968 is very different from 60 Runs Saved in the steroid era.   Even that’s not the end of it; context is everything.  Bob Veale in 1963 pitched 78 innings with a 1.04 ERA, didn’t make a ripple in the pond.  Rollie Fingers in 1981 pitched 78 innings with a 1.04 ERA, won the Cy Young Award and the MVP Award. 

            This isn’t about evaluating pitchers, really; we have many good ways of evaluating pitchers, don’t need another one.  There are many things you would have to do to these numbers to make them work as an evaluation system. 

            It’s not about that; it’s about opening up a new area of research.   It’s about creating a new way to study issues in baseball which (a) allows you to get to a certain set of questions which you just cannot get to with the existing ways of looking at things, and (b) if properly refined, if worked over by additional researchers who see things that I have missed, can be just as accurate or more accurate than the existing analytical pathways. 

 

            2) Here is a chart of all of the pitchers on the fifteen teams who (a) pitched 150 innings, or (b) had ten saves, putting each player’s Runs Saved with his basic stat line for context:

 

Team

Year

Player

G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Pirates

1960

Bob Friend

38

275.7

183

45

18

12

1

3.00

94

Pirates

1960

Vern Law

35

271.7

120

40

20

9

0

3.08

88

Pirates

1960

Harvey Haddix

29

172.3

101

38

11

10

1

3.97

56

Pirates

1960

Vinegar B Mizell

23

155.7

71

46

13

5

0

3.12

48

Pirates

1960

Roy Face

68

114.7

72

29

10

8

24

2.90

38

Team

Year

Player

G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Mets

1964

Jack Fisher

40

227.7

115

56

10

17

0

4.23

66

Mets

1964

Tracy Stallard

36

225.7

118

73

10

20

0

3.79

62

Mets

1964

Al Jackson

40

213.3

112

60

11

16

1

4.26

64

Mets

1964

Galen Cisco

36

191.7

78

54

6

19

0

3.62

57

Team

Year

Player

G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Tigers

1968

Denny McLain

41

336.0

280

63

31

6

0

1.96

119

Tigers

1968

Earl Wilson

34

224.3

168

65

13

12

0

2.85

71

Tigers

1968

Mickey Lolich

39

220.0

197

65

17

9

1

3.19

69

Tigers

1968

Joe Sparma

34

182.3

110

77

10

10

0

3.70

48

 

Team

Year

Player

G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Rangers

1972

Pete Broberg

39

176.3

133

85

5

12

1

4.29

49

Rangers

1972

Dick Bosman

29

173.3

105

48

8

10

0

3.63

58

Rangers

1972

Rich Hand

30

170.7

109

103

10

14

0

3.32

48

Rangers

1972

Mike Paul

49

161.7

108

52

8

9

1

2.17

54

Rangers

1972

Bill Gogolewski

36

150.7

95

58

4

11

2

4.24

45

Rangers

1972

Horacio Pina

60

76.0

60

43

2

7

15

3.20

22

Team

Year

Player

   G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Reds

1976

Gary Nolan

34

239.3

113

27

15

9

0

3.46

71

Reds

1976

Pat Zachry

38

204.0

143

83

14

7

0

2.74

65

Reds

1976

Fred Norman

33

180.3

126

70

12

7

0

3.09

56

Reds

1976

Jack Billingham

34

177.0

76

62

12

10

1

4.32

49

Reds

1976

Rawly Eastwick

71

107.7

70

27

11

5

26

2.09

36

Team

Year

Player

   G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Mariners

1980

Floyd Bannister

32

217.7

155

66

9

13

0

3.47

67

Mariners

1980

Glenn Abbott

31

215.0

78

49

12

12

0

4.10

60

Mariners

1980

Rick Honeycutt

30

203.3

79

60

10

17

0

3.94

55

Mariners

1980

Jim Beattie

33

187.3

67

98

5

15

0

4.85

41

Mariners

1980

Shane Rawley

59

113.7

68

63

7

7

13

3.33

34

 

Team

Year

Player

G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Tigers

1984

Jack Morris

35

240.3

148

87

19

11

0

3.60

68

Tigers

1984

Dan Petry

35

233.3

144

66

18

8

0

3.24

73

Tigers

1984

Milt Wilcox

33

193.7

119

66

17

8

0

4.00

61

Tigers

1984

Juan Berenguer

31

168.3

118

79

11

10

0

3.48

45

Tigers

1984

G. Hernandez

80

140.3

112

36

9

3

32

1.92

51

Tigers

1984

Aurelio Lopez

71

137.7

94

52

10

1

14

2.94

40

Team

Year

Player

G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Orioles

1988

Jose Bautista

33

171.7

76

45

6

15

0

4.30

44

Orioles

1988

Jay Tibbs

30

158.7

82

63

4

15

0

5.39

41

Orioles

1988

Jeff Ballard

25

153.3

41

42

8

12

0

4.40

38

Orioles

1988

Tom Niedenfuer

52

59.0

40

19

3

4

18

3.51

16

Team

Year

Player

G

IP

SO

BB

W

L

SV

ERA

Runs Saved

B Jays

1992

Jack Morris

34

240.7

132

80

21

6

0

4.04

70

B Jays

1992

Jimmy Key

33

216.7

117

59

13

13

0

3.53

64

B Jays

1992

Juan Guzman

28

180.7

165

72

16

5

0

2.64

60

B Jays

1992

Todd Stottlemyre

28

174.0

98

63

12

11

0

4.50

43

B Jays

1992

Duane Ward

79

101.3

103

39

7

4

12

1.95

34

B Jays

1992

Tom Henke

57

55.7

46

22

3

2

34

2.26

18

 

Team

Year

Player

   G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Tigers

1996

Felipe Lira

32

194.7

113

66

6

14

0

5.22

52

Tigers

1996

Omar Olivares

25

160.0

81

75

7

11

0

4.89

41

Team

Year

Player

   G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Yankees

2000

Andy Pettitte

32

204.7

125

80

19

9

0

4.35

65

Yankees

2000

Roger Clemens

32

204.3

188

84

13

8

0

3.70

63

Yankees

2000

O. Hernandez

29

195.7

141

51

12

13

0

4.51

56

Yankees

2000

David Cone

30

155.0

120

82

4

14

0

6.91

37

Yankees

2000

Mariano Rivera

66

75.7

58

25

7

4

36

2.85

26

Team

Year

Player

   G

IP

SO

BB

W

L

SV

ERA

Runs Saved

D'backs

2004

Randy Johnson

35

245.7

290

44

16

14

0

2.60

96

D'backs

2004

Brandon Webb

35

208.0

164

119

7

16

0

3.59

61

 

Team

Year

Player

   G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Phillies

2008

Cole Hamels

33

227.3

196

53

14

10

0

3.09

77

Phillies

2008

Jamie Moyer

33

196.3

123

62

16

7

0

3.71

58

Phillies

2008

Brett Myers

30

190.0

163

65

10

13

0

4.55

57

Phillies

2008

Kyle Kendrick

31

155.7

68

57

11

9

0

5.49

35

Phillies

2008

Brad Lidge

72

69.3

92

35

2

0

41

1.95

26

Team

Year

Player

   G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Astros

2012

Lucas Harrell

32

193.7

140

78

11

11

0

3.76

63

Astros

2012

Bud Norris

29

168.3

165

66

7

13

0

4.65

52

Astros

2012

Wilton Lopez

64

66.3

54

8

6

3

10

2.17

25

Astros

2012

Brett Myers

35

30.7

20

6

0

4

19

3.52

10

Team

Year

Player

   G

IP

SO

BB

W

L

SV

ERA

Runs Saved

Cubs

2016

Jon Lester

32

202.7

197

52

19

5

0

2.44

68

Cubs

2016

Jake Arrieta

31

197.3

190

76

18

8

0

3.10

67

Cubs

2016

Kyle Hendricks

31

190.0

170

44

16

8

0

2.13

67

Cubs

2016

John Lackey

29

188.3

180

53

11

8

0

3.35

59

Cubs

2016

Jason Hammel

30

166.7

144

53

15

10

0

3.83

49

Cubs

2016

Hector Rondon

54

51.0

58

8

2

3

18

3.53

18

Cubs

2016

Aroldis Chapman

28

26.7

46

10

1

1

16

1.01

11

 

 

 

            3)  And this chart (below) shows the Runs Saved Per Inning for all the pitchers on any of these teams who pitched at least 15 innings.    If you study the data, you can see that an ERA of 3.00 equates to a Runs Saved per inning of about .345, an ERA of 4.00 equates to a Runs Saved per inning of about .295, and an ERA of 5.00 equates to a Runs Saved per inning of about .245. 

 

 

City

Team

Year

Player

IP

ERA

Runs Saved

Runs Saved Per Inning

Chicago

Cubs

2016

Carl Edwards

36.0

3.75

16

.435

Chicago

Cubs

2016

Aroldis Chapman

26.7

1.01

11

.427

New York

Yankees

2000

Mike Stanton

68.0

4.10

27

.395

Arizona

Diamondbacks

2004

Randy Johnson

245.7

2.60

96

.391

Baltimore

Orioles

1988

Bob Milacki

25.0

0.72

10

.390

Chicago

Cubs

2016

Rob Zastryzny

16.0

1.12

6

.389

Houston

Astros

2012

Wilton Lopez

66.3

2.17

25

.384

Philadelphia

Phillies

2008

Brad Lidge

69.3

1.95

26

.371

Chicago

Cubs

2016

Pedro Strop

47.3

2.85

17

.367

Detroit

Tigers

1984

G. Hernandez

140.3

1.92

51

.366

Detroit

Tigers

1968

Don McMahon

35.7

2.02

13

.355

Chicago

Cubs

2016

Justin Grimm

52.7

4.10

19

.355

Chicago

Cubs

2016

Kyle Hendricks

190.0

2.13

67

.354

Houston

Astros

2012

Wesley Wright

52.3

3.27

19

.354

Detroit

Tigers

1968

Denny McLain

336.0

1.96

119

.354

Chicago

Cubs

2016

Hector Rondon

51.0

3.53

18

.353

New York

Yankees

2000

Mariano Rivera

75.7

2.85

26

.349

Houston

Astros

2012

Mickey Storey

30.3

3.86

11

.349

Toronto

Blue Jays

1992

Mike Timlin

43.7

4.12

15

.349

Chicago

Cubs

2016

Jake Arrieta

197.3

3.10

67

.342

Pittsburgh

Pirates

1960

Bob Friend

275.7

3.00

94

.340

Philadelphia

Phillies

2008

Cole Hamels

227.3

3.09

77

.340

Toronto

Blue Jays

1992

Duane Ward

101.3

1.95

34

.339

Cincinnati

Reds

1976

Rawly Eastwick

107.7

2.09

36

.337

Arizona

Diamondbacks

2004

Randy Choate

50.7

4.62

17

.335

New York

Mets

1964

Jerry Hinsley

15.3

8.22

5

.335

Chicago

Cubs

2016

Jon Lester

202.7

2.44

68

.335

Texas

Rangers

1972

Dick Bosman

173.3

3.63

58

.334

Chicago

Cubs

2016

Travis Wood

61.0

2.95

20

.334

Toronto

Blue Jays

1992

Juan Guzman

180.7

2.64

60

.333

Texas

Rangers

1972

Mike Paul

161.7

2.17

54

.333

Pittsburgh

Pirates

1960

Roy Face

114.7

2.90

38

.332

Houston

Astros

2012

Hector Ambriz

19.3

4.19

6

.331

Pittsburgh

Pirates

1960

Clem Labine

30.3

1.48

10

.330

Toronto

Blue Jays

1992

Tom Henke

55.7

2.26

18

.329

Pittsburgh

Pirates

1960

Harvey Haddix

172.3

3.97

56

.326

Houston

Astros

2012

Xavier Cedeno

31.0

3.77

10

.326

Philadelphia

Phillies

2008

Chad Durbin

87.7

2.87

29

.326

Houston

Astros

2012

Lucas Harrell

193.7

3.76

63

.324

Pittsburgh

Pirates

1960

Earl Francis

18.0

2.00

6

.323

Pittsburgh

Pirates

1960

Vern Law

271.7

3.08

88

.322

Houston

Astros

2012

Wandy Rodriguez

130.7

3.79

42

.322

Detroit

Tigers

1996

Mike Myers

64.7

5.01

21

.321

Philadelphia

Phillies

2008

Ryan Madson

82.7

3.05

27

.321

Houston

Astros

2012

Brett Myers

30.7

3.52

10

.320

Cincinnati

Reds

1976

Pat Zachry

204.0

2.74

65

.320

Detroit

Tigers

1984

Randy O'Neal

18.7

3.38

6

.320

Cincinnati

Reds

1976

Manny Sarmiento

43.7

2.06

14

.319

Detroit

Tigers

1968

Pat Dobson

125.0

2.66

40

.318

New York

Yankees

2000

Andy Pettitte

204.7

4.35

65

.316

Detroit

Tigers

1968

Earl Wilson

224.3

2.85

71

.316

New York

Mets

1964

Gary Kroll

21.7

4.15

7

.315

Detroit

Tigers

1984

Milt Wilcox

193.7

4.00

61

.314

Cincinnati

Reds

1976

Pedro Borbon

121.0

3.35

38

.313

New York

Yankees

2000

Jeff Nelson

69.7

2.45

22

.312

Detroit

Tigers

1968

Mickey Lolich

220.0

3.19

69

.312

Detroit

Tigers

1984

Dan Petry

233.3

3.24

73

.312

Chicago

Cubs

2016

John Lackey

188.3

3.35

59

.312

Pittsburgh

Pirates

1960

Joe Gibbon

80.3

4.03

25

.312

Toronto

Blue Jays

1992

Mark Eichhorn

31.0

4.35

10

.311

Pittsburgh

Pirates

1960

V. Mizell

155.7

3.12

48

.310

Cincinnati

Reds

1976

Fred Norman

180.3

3.09

56

.310

New York

Yankees

2000

Roger Clemens

204.3

3.70

63

.310

Seattle

Mariners

1980

Floyd Bannister

217.7

3.47

67

.309

Detroit

Tigers

1984

Bill Scherrer

19.0

1.89

6

.309

Texas

Rangers

1972

Jim Shellenback

57.0

3.47

18

.309

Baltimore

Orioles

1988

Scott McGregor

17.3

8.83

5

.308

Philadelphia

Phillies

2008

J.C. Romero

59.0

2.75

18

.308

Houston

Astros

2012

Bud Norris

168.3

4.65

52

.308

Detroit

Tigers

1968

John Hiller

128.0

2.39

39

.305

Philadelphia

Phillies

2008

Clay Condrey

69.0

3.26

21

.303

Houston

Astros

2012

Brandon Lyon

36.0

3.25

11

.303

Philadelphia

Phillies

2008

Brett Myers

190.0

4.55

57

.300

New York

Mets

1964

Tom Parsons

19.3

4.19

6

.300

New York

Mets

1964

Al Jackson

213.3

4.26

64

.300

Detroit

Tigers

1968

John Wyatt

30.3

2.37

9

.300

Philadelphia

Phillies

2008

J.A. Happ

31.7

3.69

9

.298

Cincinnati

Reds

1976

Gary Nolan

239.3

3.46

71

.298

Seattle

Mariners

1980

Shane Rawley

113.7

3.33

34

.298

Houston

Astros

2012

Jordan Lyles

141.3

5.09

42

.297

Houston

Astros

2012

J.A. Happ

104.3

4.83

31

.297

Texas

Rangers

1972

Bill Gogolewski

150.7

4.24

45

.297

Arizona

Diamondbacks

2004

Elmer Dessens

85.3

4.75

25

.297

Detroit

Tigers

1984

Roger Mason

22.0

4.50

7

.296

New York

Mets

1964

Galen Cisco

191.7

3.62

57

.296

Cincinnati

Reds

1976

Will McEnaney

72.3

4.85

21

.296

Baltimore

Orioles

1988

Dave J. Schmidt

129.7

3.40

38

.295

Texas

Rangers

1972

Horacio Pina

76.0

3.20

22

.295

Detroit

Tigers

1984

Dave Rozema

101.0

3.74

30

.295

Arizona

Diamondbacks

2004

Brandon Webb

208.0

3.59

61

.294

Philadelphia

Phillies

2008

Jamie Moyer

196.3

3.71

58

.293

Toronto

Blue Jays

1992

Jimmy Key

216.7

3.53

64

.293

Chicago

Cubs

2016

Jason Hammel

166.7

3.83

49

.293

Houston

Astros

2012

E. Del Rosario

19.0

9.00

6

.292

Detroit

Tigers

1984

Aurelio Lopez

137.7

2.94

40

.292

Arizona

Diamondbacks

2004

Mike Koplove

86.7

4.05

25

.292

New York

Mets

1964

Jack Fisher

227.7

4.23

66

.291

Toronto

Blue Jays

1992

Jack Morris

240.7

4.04

70

.291

Detroit

Tigers

1984

Doug Bair

93.7

3.75

27

.290

New York

Mets

1964

Tom Sturdivant

28.7

5.97

8

.289

Pittsburgh

Pirates

1960

Fred Green

70.0

3.21

20

.289

Houston

Astros

2012

David Carpenter

29.7

6.07

9

.289

Texas

Rangers

1972

Steve Lawson

16.0

2.81

5

.289

Chicago

Cubs

2016

Trevor Cahill

65.7

2.74

19

.287

Cincinnati

Reds

1976

Don Gullett

126.0

3.00

36

.286

Houston

Astros

2012

Fernando Abad

46.0

5.09

13

.285

New York

Yankees

2000

O. Hernandez

195.7

4.51

56

.285

Detroit

Tigers

1996

Jose Lima

72.7

5.70

21

.285

Detroit

Tigers

1968

Daryl Patterson

68.0

2.12

19

.284

New York

Yankees

2000

Todd Erdos

25.0

5.04

7

.283

Detroit

Tigers

1984

Jack Morris

240.3

3.60

68

.283

Arizona

Diamondbacks

2004

Brian Bruney

31.3

4.31

9

.281

New York

Mets

1964

Willard Hunter

49.0

4.41

14

.281

Texas

Rangers

1972

Rich Hand

170.7

3.32

48

.281

Texas

Rangers

1972

Paul Lindblad

99.7

2.62

28

.280

New York

Mets

1964

Dennis Ribant

57.7

5.15

16

.280

Seattle

Mariners

1980

Rob Dressler

149.3

3.98

42

.280

Detroit

Tigers

1984

Carl Willis

16.0

7.31

4

.279

Seattle

Mariners

1980

Dave Roberts

80.3

4.37

22

.279

Baltimore

Orioles

1988

Tom Niedenfuer

59.0

3.51

16

.279

Seattle

Mariners

1980

Glenn Abbott

215.0

4.10

60

.279

Detroit

Tigers

1968

Fred Lasher

48.7

3.33

14

.278

Houston

Astros

2012

Edgar Gonzalez

25.0

5.04

7

.278

New York

Yankees

2000

Dwight Gooden

64.3

3.36

18

.277

Toronto

Blue Jays

1992

David Cone

53.0

2.55

15

.277

Detroit

Tigers

1996

Joey Eischen

25.0

3.24

7

.276

Texas

Rangers

1972

Pete Broberg

176.3

4.29

49

.276

New York

Mets

1964

Tracy Stallard

225.7

3.79

62

.276

Cincinnati

Reds

1976

Jack Billingham

177.0

4.32

49

.276

Detroit

Tigers

1996

Justin Thompson

59.0

4.58

16

.272

New York

Mets

1964

D. Sutherland

26.7

7.76

7

.271

Baltimore

Orioles

1988

Mike Boddicker

147.0

3.86

40

.271

Detroit

Tigers

1984

Juan Berenguer

168.3

3.48

45

.270

Seattle

Mariners

1980

Rick Honeycutt

203.3

3.94

55

.270

Toronto

Blue Jays

1992

Dave Stieb

96.3

5.04

26

.269

Baltimore

Orioles

1988

Mike Morgan

71.3

5.43

19

.269

Detroit

Tigers

1968

Jon Warden

37.3

3.62

10

.269

Detroit

Tigers

1996

A.J. Sager

79.0

5.01

21

.268

Detroit

Tigers

1968

Dennis Ribant

24.3

2.22

7

.268

Arizona

Diamondbacks

2004

Oscar Villarreal

18.0

7.00

5

.268

Pittsburgh

Pirates

1960

Paul Giel

33.0

5.73

9

.267

Detroit

Tigers

1996

Felipe Lira

194.7

5.22

52

.265

Texas

Rangers

1972

Don Stanhouse

104.7

3.78

28

.264

Arizona

Diamondbacks

2004

Greg Aquino

35.3

3.06

9

.264

Chicago

Cubs

2016

Spencer Patton

21.3

5.48

6

.264

Philadelphia

Phillies

2008

Tom Gordon

29.7

5.16

8

.263

Detroit

Tigers

1968

Joe Sparma

182.3

3.70

48

.262

Philadelphia

Phillies

2008

Adam Eaton

107.0

5.80

28

.261

New York

Mets

1964

Bill Wakefield

119.7

3.61

31

.261

Philadelphia

Phillies

2008

Rudy Seanez

43.3

3.53

11

.261

Toronto

Blue Jays

1992

David Wells

120.0

5.40

31

.259

Detroit

Tigers

1996

Omar Olivares

160.0

4.89

41

.259

Houston

Astros

2012

F. Rodriguez

70.3

5.37

18

.259

Baltimore

Orioles

1988

Doug Sisk

94.3

3.72

24

.258

Toronto

Blue Jays

1992

Bob Macdonald

47.3

4.37

12

.257

Baltimore

Orioles

1988

Jay Tibbs

158.7

5.39

41

.257

New York

Mets

1964

Frank Lary

57.3

4.55

15

.255

Arizona

Diamondbacks

2004

Jose Valverde

29.7

4.25

8

.255

Baltimore

Orioles

1988

Jose Bautista

171.7

4.30

44

.254

Houston

Astros

2012

Rhiner Cruz

55.0

6.05

14

.253

Chicago

Cubs

2016

Mike Montgomery

38.3

2.82

10

.252

Pittsburgh

Pirates

1960

Red Witt

30.0

4.20

8

.252

Baltimore

Orioles

1988

Mark Williamson

117.7

4.90

30

.251

Philadelphia

Phillies

2008

Joe Blanton

70.7

4.20

18

.251

Pittsburgh

Pirates

1960

Bennie Daniels

40.3

7.81

10

.249

Baltimore

Orioles

1988

Jeff Ballard

153.3

4.40

38

.249

Texas

Rangers

1972

Jim Panther

93.7

4.13

23

.249

Seattle

Mariners

1980

Mike Parrott

94.0

7.28

23

.247

New York

Mets

1964

Larry Bearnarth

78.0

4.15

19

.247

New York

Yankees

2000

Ramiro Mendoza

65.7

4.25

16

.246

Arizona

Diamondbacks

2004

B. Villafuerte

20.0

4.05

5

.246

Baltimore

Orioles

1988

Oswaldo Peraza

86.0

5.55

21

.245

Arizona

Diamondbacks

2004

Casey Fossum

142.0

6.65

35

.245

Toronto

Blue Jays

1992

Todd Stottlemyre

174.0

4.50

43

.245

New York

Yankees

2000

Jason Grimsley

96.3

5.04

23

.240

Texas

Rangers

1972

Casey Cox

65.3

4.41

16

.239

Detroit

Tigers

1996

John Cummings

31.7

5.12

8

.238

New York

Yankees

2000

David Cone

155.0

6.91

37

.238

Seattle

Mariners

1980

Dave Heaverlo

78.7

3.89

19

.237

Pittsburgh

Pirates

1960

Tom Cheney

52.0

3.98

12

.237

New York

Yankees

2000

Denny Neagle

91.3

5.81

22

.236

Arizona

Diamondbacks

2004

Andrew Good

40.7

5.31

9

.233

Detroit

Tigers

1984

Sid Monge

36.0

4.25

8

.233

Houston

Astros

2012

Dallas Keuchel

85.3

5.27

20

.232

Arizona

Diamondbacks

2004

Steve Sparks

120.7

6.04

28

.230

Cincinnati

Reds

1976

Santo Alcala

132.0

4.70

30

.230

Detroit

Tigers

1968

Les Cain

24.0

3.00

5

.229

Detroit

Tigers

1996

C.J. Nitkowski

45.7

8.08

10

.228

Detroit

Tigers

1996

Richie Lewis

90.3

4.18

21

.227

New York

Yankees

2000

Randy Choate

17.0

4.76

4

.227

Baltimore

Orioles

1988

Mark Thurmond

74.7

4.58

17

.226

Toronto

Blue Jays

1992

Pat Hentgen

50.3

5.36

11

.225

Detroit

Tigers

1996

Trever Miller

16.7

9.18

4

.224

Philadelphia

Phillies

2008

Kyle Kendrick

155.7

5.49

35

.224

New York

Mets

1964

Ron Locke

41.3

3.48

9

.223

Seattle

Mariners

1980

Jim Beattie

187.3

4.85

41

.219

Baltimore

Orioles

1988

Don Aase

46.7

4.05

10

.219

Detroit

Tigers

1996

Gregg Olson

43.0

5.02

9

.218

New York

Mets

1964

Carl Willey

30.0

3.60

6

.214

Cincinnati

Reds

1976

Pat Darcy

39.0

6.23

8

.214

Chicago

Cubs

2016

Adam Warren

35.0

5.91

7

.211

Arizona

Diamondbacks

2004

Mike Fetters

18.7

8.68

4

.209

Pittsburgh

Pirates

1960

Jim Umbricht

40.7

5.09

8

.205

Arizona

Diamondbacks

2004

Scott Service

20.3

7.08

4

.204

Arizona

Diamondbacks

2004

Steve Randolph

81.7

5.51

17

.204

Detroit

Tigers

1984

Glenn Abbott

44.0

5.93

9

.204

Detroit

Tigers

1996

Scott Aldred

43.3

9.35

9

.202

Detroit

Tigers

1996

Greg Keagle

87.7

7.39

17

.197

Detroit

Tigers

1996

Randy Veres

30.3

8.31

6

.194

Detroit

Tigers

1996

Brian Williams

121.0

6.77

23

.193

Seattle

Mariners

1980

By McLaughlin

90.7

6.85

17

.193

Detroit

Tigers

1996

Greg Gohr

91.7

7.17

18

.193

Houston

Astros

2012

Kyle Weiland

17.7

6.62

3

.192

Toronto

Blue Jays

1992

Doug Linton

24.0

8.62

5

.191

Arizona

Diamondbacks

2004

Edgar Gonzalez

46.3

9.32

9

.187

Houston

Astros

2012

Chuckie Fick

23.0

4.30

4

.184

Arizona

Diamondbacks

2004

Casey Daigle

49.0

7.16

9

.174

Cincinnati

Reds

1976

Rich Hinton

17.7

7.64

3

.164

Arizona

Diamondbacks

2004

Mike Gosling

25.3

4.62

4

.159

Detroit

Tigers

1996

Mike Christopher

30.0

9.30

4

.149

New York

Yankees

2000

Allen Watson

22.0

10.23

3

.142

Detroit

Tigers

1996

Tom Urbani

23.7

8.37

3

.135

Arizona

Diamondbacks

2004

Lance Cormier

45.3

8.14

6

.132

Houston

Astros

2012

A. Galarraga

24.0

6.75

3

.122

Detroit

Tigers

1996

Clint Sodowsky

24.3

11.84

3

.109

Detroit

Tigers

1996

Mike Walker

27.7

8.46

2

.090

Detroit

Tigers

1996

Todd Van Poppel

36.3

11.39

3

.076

 

Formula 44:  Pitcher’s Value --  Total Value for a Pitcher

For some reason, both Vicks and Grecian Formula use "Formula 44" in their advertising, or once did.  I knew something sounded odd about "Formula 44", but I couldn’t remember if it was Vicks Formula 44 or Grecian Hair Color Formula 44, so I googled it, and. . . it’s both of them.  Weird. 

Anyway, this may not need to be said, but just being careful. . . a pitcher’s value is the sum of P1, P2, P3, P4. . .through P10:

Pitcher’s Value = Sum of P as P goes from P1 to P10

 

 

 
 

COMMENTS (19 Comments, most recent shown first)

jgf704
Thanks, formersd!
7:40 AM Jul 24th
 
CharlesSaeger
My reading of P7 was DP impact *after* accounting for grounders, which was my objection to it. Did I miss something?
7:32 PM Jul 23rd
 
formersd
I am not Bill, but here's my summary of the pitcher values.

P1 - Strikeouts
P2 - Control
P3 - Home Run Avoidance
P4 - Base Saved (Balks, WP, PB?)
P5 - Base Runners Removed (CS, Pickoffs)
P6 - Double Plays Made by Pitcher (Fielding)
P7 - Double Play impact by inducing Grounders
P8 - Error Avoidance by Pitcher
P9 - Pitcher Fielding Range
P10 - Pitchers credit for runs saved on Balls in Play
11:49 AM Jul 23rd
 
jgf704
A couple request for Bill...

* Would you be willing to provide a one-line description of each of the 10 elements (P1, P2..., P10)?

* How about Runs Saved per 9 innings for each pitcher (rather than per single inning). It's a slightly more familiar scale.
9:56 PM Jul 22nd
 
MarisFan61
Further discussion of the "no-negative" for Formula 41 will be on Reader Posts.
(maybe with clarification to me about why what I'm wondering about is untenable)
Seems to me that besides not differentiating between different degrees of 'badness,' it also unduly blunts the calculated benefit to pitchers who are in positive territory.
7:33 PM Jul 22nd
 
shthar
Not really seeing any surprises in these numbers.


4:48 PM Jul 22nd
 
bjames
Not sure if I clear about Hunter. It might be, because Hunter's batter's faced total is so large, and because his data is so extreme, it might be that he is the only pitcher on the team who had a positive total. If that was the case, then it makes no difference at all to do this; Hunter simply winds up with 44 out of 44, rather than 35 out of 35. If there are other pitchers on the team who have smaller totals, which is likely, then I'm not whether it would make any difference at all, or whether it would just make a tiny, tiny difference.
12:24 PM Jul 22nd
 
bjames
Would it make sense to compare Hunter's numbers with the Oakland numbers MINUS his own?
Team - Hunter: 3,460 BIP, 895 HIP.
Average: .25867 (10 points higher than before)

Comparing Hunter to the team, with and without him:
With: 863 BIP x .24844 team = 214 expected HIP. (Hunter saves 35 hits)
W/out: 863 BIP x .25867 team = 223 expected HIP. (Hunter saves 44 hits)



I'm not sure this would make any difference at all. It would give Hunter a larger figure, but it would also give a larger figure to every other pitcher on the team who had a positive ratio. Since the only thing that matters is the ratio of the player to the team total, the effect would be extremely minimal. I'd be extremely surprised if it was as much as a quarter of a run.
12:05 PM Jul 22nd
 
bjames
CharlesSaeger
This is more a general question, but how would you work the doubles and triples allowed into these equations? It looks like you're ignoring them given your double play equations, though we have them on a team level going back to 1901.


Not sure what you mean by "How WOULD I work them into the system." I didn't, and I'm not going to. The system is complicated enough as it is.
12:01 PM Jul 22nd
 
bjames
CharlesSaeger
This is more a general question, but how would you work the doubles and triples allowed into these equations? It looks like you're ignoring them given your double play equations, though we have them on a team level going back to 1901.


Not sure what you mean by "How WOULD I work them into the system." I didn't, and I'm not going to. The system is complicated enough as it is.
12:01 PM Jul 22nd
 
MarisFan61
(make that "Hits-Allowed + v. Team" -- meant to type that but left out the +)
11:54 AM Jul 22nd
 
MarisFan61
Bill: Thanks for the answers!
About the first thing: But why not then label it as something like "Hits-Allowed v. Team" rather than "BABIP+ v Team (Batting Average on Balls in Play better than team)"?
I know that you're not necessarily writing for "us," you're working out a method. But you can be sure there are many others who will be derailed a bit, and might think (as I did) that they must be misunderstanding the formula and slaving over it to see how it could be a batting-average-unit thing, since "BABIP" has such a firmly established meaning in terms of that.
Why not just call it that other thing, which after all anyway is what it is?

About the second thing: I hear you, but don't get it, presumably because of the "pay grade" thing. I can't see why we'd want to let a pitcher who gives up more hits than expected be treated the same in the system as one who was neutral, or a pitcher who gives up way more hits to be treated the same as one who gave up just a few more.
Regarding it "not working" in terms of measuring a pitcher's contribution, which I understand has to be a positive number, would it not work to do what I'm suggesting but just to make the "floor" be in a negative place rather than at zero?
In any event, I can't see how you'd be content to let it be as explained above.
P.S. Need I say, no need to answer further. I appreciate that first answer.
11:52 AM Jul 22nd
 
henryfyfe
Cubs fan here. Wild to see Carl's Junior and Rob Z at the top of this list.
10:45 AM Jul 22nd
 
chuck
Bill, regarding the figuring of hits better than team BABIP, I'm wondering about the cases (and/or recognition) of pitchers who do have an outsized effect on the team's BABIP. Take Catfish Hunter in 1972.

Team balls in play (BIP): 4,323
Team hits in play (HIP): 1047
Average: .24844

Hunter
863 BIP, 179 HIP.
Average: .2074

Here, Hunter's balls in play represent a good chunk of the team's BIP. (20%). In comparing his .207 to the team's .248, his own BABIP (due partly to the many infield flys he induced) had a fairly large impact on the team BABIP.

Would it make sense to compare Hunter's numbers with the Oakland numbers MINUS his own?
Team - Hunter: 3,460 BIP, 895 HIP.
Average: .25867 (10 points higher than before)

Comparing Hunter to the team, with and without him:
With: 863 BIP x .24844 team = 214 expected HIP. (Hunter saves 35 hits)
W/out: 863 BIP x .25867 team = 223 expected HIP. (Hunter saves 44 hits)

It's kind of like the WOWY system for evaluating catcher stats by looking at runs allowed by team with that catcher behind the plate, as opposed to other catchers.

Where I wonder if this subtract-the-pitcher first approach might yield extreme results is in cases like the early 1900s, where just a few pitchers would have the great bulk of team innings, and where one pitcher might have a very different BABIP allowed than another. The team BABIP would then be quite different for each pitcher, after first subtracting their own input.
10:14 AM Jul 22nd
 
evanecurb
For Riceman: I think the 1968 Tigers' shortstops, primarily Ray Oyler and Dick Traczewski, if memory serves, were good defensive players who were automatic outs when at bat.
9:26 AM Jul 22nd
 
TheRicemanCometh
Weren't the 68 Tigers the team with three bad shortstops that CF Mickey Stanley played SS in the World Series? Odd that a team with mediocre SS play can be so good at Hits Avoided.
8:37 AM Jul 22nd
 
CharlesSaeger
This is more a general question, but how would you work the doubles and triples allowed into these equations? It looks like you're ignoring them given your double play equations, though we have them on a team level going back to 1901.
8:10 AM Jul 22nd
 
bjames
1) It is not a normal rule that the credit given for something is expressed in the units of the work. If you have a job sacking groceries in the grocery store, you don't get paid for that in groceries. If you are working at a fast food joint, you don't get paid in hamburgers. If you hire someone to pour concrete for you, you don't pay him in concrete. When you are rewarding pitchers for having a positive BABIP, you don't pay them off in BABIP. RUNS are the currency of the on-field economy.

2) If you gave negative points for a high BABIP, then the sum total of BABIP+ for every team would be zero. Felipe Lira's share of the 1996 Tigers team total would be 24 over 0. Wouldn't work. You'd have to use some entirely different approach to recognize this contribution to the team's success.

We're not charting failures. We're charting Runs Saved, runs prevented. A negative figure gives an absence of evidence for credit to in this area.
8:02 AM Jul 22nd
 
MarisFan61
Recognizing that I'm usually playing in a league "above my pay grade" when I get into something like this, and so I'll more than understand if this isn't felt to be a relevant question....

In Formula 41 (near the top) it seems that different kinds of 'units' are being mixed, or that even if they aren't, what you're calculating is different from what it's called -- and in this case it's not one of my semantic "what-you're-calling-it" things.

It says that the thing the formula is calculating is:
"Batting Average on Balls in Play better than team"

....which seems like the 'unit' we're dealing with is batting average units, not 'hit-numbers' units.

BUT: In the formula, you're taking the team's BABIP and multiplying it by the pitcher's balls-in-play -- which gives basically the pitcher's "expected hits in play," i.e. a 'hits'-number -- and then subtracting his actual number of hits-in-play, which also gives a hits-number.

How does that give something whose units is batting-average units?
Wouldn't you need to take that result and divide it by the pitcher's balls-in-play?


And, a second question about that, unrelated:
Why wouldn't you let it be a negative number? Seems to me that if you get a negative result, it means the pitcher's actual hits-allowed was higher than expected. Why would we want to let this pitcher show the same as one who allowed just the expected number?
2:49 AM Jul 22nd
 
 
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