Game Specific Run Effects

May 20, 2014

Identifying a Team’s Best Pitcher

                After I published the article entitled Openers and Aces (May 9), there were posted requests to explain how I had decided what who was each team’s best starting pitcher.  That decision was based on the Season Score, which is to say that it was based on a combination of Wins, Losses, Innings Pitched, ERA, Un-Earned Runs Allowed, Strikeouts and Walks.  It seems like an obvious choice for this purpose.   The weakness of the Season Score is that it doesn’t adjust for the team or for the league, but since neither of those is an issue in this case—comparing teammates—it seems right.

                The first poster speculated that I must have decided who the best pitcher on each team was based on Wins and Losses.   I don’t know what I could possibly have done that would cause anyone to think I would identify the best pitcher on a team by Wins and Losses, but it tends to confirm my suspicion that I must have been a very wicked person in a previous life.    Debating the issue of who should be identified as the best pitcher on a team, the Pirst Foster complains about Steve Trachsel with the 2006 Mets, which seems like a non-instructive example, since there is no method by which Trachsel would show up as the #1 starting pitcher on the 2006 Mets.

                A Pecond Soster brings up the equally useless and non-instructive example of Tom Sturdivant and the 1957 Yankees—non-instructive, because Sturdivant would appear to be the #1 starter on that team by any method you could come up with; I don’t see how you would avoid it.    An instructive example would be one in which one pitcher was a team’s #1 starter by one method, while another was the #1 starter by some other method.   The 2013 White Sox or Red Sox.   On the Whites, Jose Quintana pitched 200 innings and had the best won-lost record among the team’s starters (9-7).   Chris Sale was 11-14, but led the team in ERA, strikeout/walk ratio and innings.  On the Reds, Jon Lester led the team in innings pitched and won-lost record (15-8); John Lackey was 10-13 but had a better ERA and a better strikeout/walk ratio.   Season Score likes Sale more than Quintana, Lester more than Lackey.

                I got to wondering about the general issue, and. . .has there ever been a team on which one pitcher led the team in ERA, a different pitcher had the best won-lost record, a third pitcher the best strikeout/walk ratio, while a fourth pitcher led them in innings pitched?

                I would have bet that that had never happened.   In fact, it has happened 24 times since 1900. . ..very surprised.  On the famous 1971 Baltimore Orioles team which had four twenty-game winners, for example, Dave McNally had the best won-lost record (21-5), Jim Palmer the best ERA (2.68), Pat Dobson the highest total of strikeouts minus walks (187-63), and Mike Cuellar pitched the most innings (292).

`               The White Sox did this in both 2006 and 2008.   In 2006 their #1 pitcher by won-lost record was Jon Garland (18-7), by ERA Jose Contreras (4.27), by strikeouts minus walks Javier Vazquez (184-56), while Freddy Garcia led the team in innings pitched, 216.   Remarkably enough, that team’s other starting pitcher, Mark Buehrle, had about as good an argument to be considered the staff ace as any of the other four, although he didn’t lead the team in anything.  His stats that year were a little bit down, but. . .he’s Mark Buehrle.   At least you can count on him to do what he does.   In 2008 the best won-lost record was by Gavin Floyd (17-8), the best ERA John Danks (3.32), the best strikeouts minus walks Vazquez again (200-61), and the most innings pitched Buehrle (218.2).

                It’s not only good teams that have done this; the 1963 Kansas City A’s were led in won-lost record by Diego Segui (9-6), in ERA by Moe Drabowsky (3.05), in strikeouts minus walks by Orlando Pena (128-53), and in innings pitched by Dave Wickersham (238).   Drabowsky had the best ERA on the team but the worst won-lost log (7-13).   All four guys really were half-decent pitchers who had decent careers, but they were overpowered by pitching for what was otherwise a horrible team.    The 1980 Mets (67-95) were led in won-lost record by Mark (Don’t Call Me Erma) Bomback (10-8), in ERA by Pat Zachry (3.01), in strikeouts minus walks by Pete Falcone (109-58), and in innings pitched by Ray Burris (170.1).   Fifth Starter:  Craig Swan.   Falcone and Swan; it’s a two-bird rotation.

                These are the 24 teams which were led in the four categories by four different pitchers, using the term "Ace" to indicate the man my little formula decides is the team’s best pitcher:

     

1907 PHILADELPHIA ATHLETICS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Jimmy

Dygert

42

20

8

.714

261.2

151

85

2.34

 

ERA

Chief

Bender

33

16

8

.667

219.1

112

34

2.05

 

K - BB

Rube

Waddell

44

19

13

.594

284.2

232

73

2.15

 

Innings

Eddie

Plank

43

24

16

.600

343.2

183

85

2.20

Ace

                       
     

1913 CINCINNATI REDS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Rube

Benton

23

11

7

.611

144.0

68

60

3.50

 

ERA

Gene

Packard

39

7

11

.389

191.0

73

64

2.97

 

K - BB

George

Suggs

36

8

15

.348

199.0

73

35

4.03

 

Innings

Chief

Johnson

44

14

16

.467

269.0

107

86

3.01

Ace

                       
     

1917 DETROIT TIGERS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Bernie

Boland

43

16

11

.593

238.0

89

95

2.68

 

ERA

Bill

James

34

13

10

.565

198.0

62

96

2.09

 

K - BB

Willie

Mitchell

30

12

8

.600

185.0

80

46

2.19

 

Innings

Hooks

Dauss

38

17

14

.548

270.0

102

87

2.43

Ace

 

Howard

Ehmke

35

10

15

.400

206.0

90

88

2.97

 

                       
     

1923 NEW YORK YANKEES

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Sad Sam

Jones

39

21

8

.724

243.0

68

69

3.63

 

ERA

Waite

Hoyt

37

17

9

.654

239.0

60

66

3.01

 

K - BB

Herb

Pennock

35

19

6

.760

224.0

93

68

3.33

Ace

Innings

Joe

Bush

37

19

15

.559

276.0

125

117

3.42

 

 

Bob

Shawkey

36

16

11

.593

259.0

125

102

3.51

 

                       
     

1924 NEW YORK GIANTS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Jack

Bentley

28

16

5

.762

188.0

60

56

3.78

 

ERA

Hugh

McQuillan

27

14

8

.636

184.0

49

43

2.69

 

K - BB

Art

Nehf

30

14

4

.778

172.0

72

42

3.61

 

Innings

Virgil

Barnes

35

16

10

.615

229.0

59

57

3.07

Ace

 

Wayland

Dean

26

6

12

.333

126.0

39

45

5.00

 

                       
     

1935 NEW YORK YANKEES

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Johnny

Broaca

29

15

7

.682

201.0

78

79

3.58

 

ERA

Red

Ruffing

30

16

11

.593

222.0

81

76

3.12

Ace

K - BB

Johnny

Allen

23

13

6

.684

167.0

113

58

3.61

 

Innings

Lefty

Gomez

34

12

15

.444

246.0

138

86

3.18

 

 

     

1942 DETROIT TIGERS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Virgil

Trucks

28

14

8

.636

168.0

91

74

2.73

Ace

ERA

Hal

Newhouser

38

8

14

.364

184.0

103

114

2.45

 

K - BB

Tommy

Bridges

23

9

7

.563

174.0

97

61

2.74

 

Innings

Al

Benton

35

7

13

.350

227.0

110

84

2.89

 

 

Hal

White

34

12

12

.500

217.0

93

82

2.90

 

 

Dizzy

Trout

35

12

18

.400

223.0

91

89

3.43

 

                       
                       
     

1955 WASHINGTON SENATORS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Mickey

McDermott

31

10

10

.500

156.0

78

100

3.75

Ace

ERA

Johnny

Schmitz

32

7

10

.412

165.0

49

54

3.71

 

K - BB

Bob

Porterfield

30

10

17

.370

178.0

74

54

4.45

 

Innings

Dean

Stone

43

6

13

.316

180.0

84

114

4.15

 

                       
     

1963 KANSAS CITY A'S

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Diego

Segui

38

9

6

.600

167.0

116

73

3.77

 

ERA

Moe

Drabowsky

26

7

13

.350

174.0

109

64

3.05

 

K - BB

Orlando

Pena

35

12

20

.375

217.0

128

53

3.69

 

Innings

Dave

Wickersham

38

12

15

.444

238.0

118

79

4.08

Ace

 

Ed

Rakow

34

9

10

.474

174.0

104

61

3.93

 

                       
     

1966 CLEVELAND INDIANS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Sonny

Siebert

34

16

8

.667

241.0

163

62

2.80

Ace

ERA

Steve

Hargan

38

13

10

.565

192.0

132

45

2.48

 

K - BB

Sam

McDowell

35

9

8

.529

194.0

225

102

2.88

 

Innings

Gary

Bell

40

14

15

.483

254.0

194

79

3.22

 

                       
     

1971 BALTIMORE ORIOLES

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Dave

McNally

30

21

5

.808

224.0

91

58

2.89

 

ERA

Jim

Palmer

37

20

9

.690

282.0

184

106

2.68

Ace

K - BB

Pat

Dobson

38

20

8

.714

282.0

187

63

2.90

 

Innings

Mike

Cuellar

38

20

9

.690

292.0

124

78

3.08

 

                       
     

1974 SAN DIEGO PADRES

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Dan

Spillner

30

9

11

.450

148.0

95

70

4.01

 

ERA

Dave

Freisleben

33

9

14

.391

212.0

130

112

3.65

Ace

K - BB

Randy

Jones

40

8

22

.267

208.1

124

78

4.45

 

Innings

Bill

Greif

43

9

19

.321

226.0

137

95

4.66

 

 

     

1979 MONTREAL EXPOS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Bill

Lee

33

16

10

.615

222.0

59

46

3.04

Ace

ERA

Dan

Schatzeder

32

10

5

.667

162.0

106

59

2.83

 

K - BB

Scott

Sanderson

34

9

8

.529

168.0

138

54

3.43

 

Innings

Steve

Rogers

37

13

12

.520

248.2

143

78

3.00

 

 

Ross

Grimsley

32

10

9

.526

151.1

42

41

5.35

 

                       
     

1980 NEW YORK METS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Mark

Bomback

36

10

8

.556

162.2

68

49

4.09

Ace

ERA

Pat

Zachry

28

6

10

.375

164.2

88

58

3.01

 

K - BB

Pete

Falcone

37

7

10

.412

157.1

109

58

4.52

 

Innings

Ray

Burris

29

7

13

.350

170.1

83

54

4.02

 

 

Craig

Swan

21

5

9

.357

128.1

79

30

3.58

 

                       
     

1985 SAN DIEGO PADRES

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Andy

Hawkins

33

18

8

.692

228.2

69

65

3.15

Ace

ERA

Dave

Dravecky

34

13

11

.542

214.2

105

57

2.93

 

K - BB

LaMarr

Hoyt

31

16

8

.667

210.1

83

20

3.47

 

Innings

Eric

Show

35

12

11

.522

233.0

141

87

3.09

 

 

Mark

Thurmond

36

7

11

.389

138.1

57

44

3.97

 

                       
     

1986 KANSAS CITY ROYALS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Mark

Gubicza

35

12

6

.667

180.2

118

84

3.64

Ace

ERA

Danny

Jackson

32

11

12

.478

185.2

115

79

3.20

 

K - BB

Bret

Saberhagen

30

7

12

.368

156.0

112

29

4.15

 

Innings

Charlie

Leibrandt

35

14

11

.560

231.1

108

63

4.09

 

 

Dennis

Leonard

33

8

13

.381

192.2

114

51

4.44

 

                       
     

1991 PITTSBURGH PIRATES

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

John

Smiley

33

20

8

.714

207.2

129

44

3.08

Ace

ERA

Randy

Tomlin

31

8

7

.533

175.0

104

54

2.98

 

K - BB

Zane

Smith

35

16

10

.615

228.0

120

29

3.20

 

Innings

Doug

Drabek

35

15

14

.517

234.2

142

62

3.07

 

 

Bob

Walk

25

9

2

.818

115.0

67

35

3.60

 

                       
     

1997 MILWAUKEE BREWERS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Jeff

D'Amico

23

9

7

.563

135.2

94

43

4.71

 

ERA

Jose

Mercedes

29

7

10

.412

159.0

80

53

3.79

 

K - BB

Ben

McDonald

21

8

7

.533

133.0

110

36

4.06

Ace

Innings

Cal

Eldred

34

13

15

.464

202.0

122

89

4.99

 

 

Scott

Karl

32

10

13

.435

193.1

119

67

4.47

 

 

     

2004 NEW YORK YANKEES

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Jon

Lieber

27

14

8

.636

176.2

102

18

4.33

Ace

ERA

Kevin

Brown

22

10

6

.625

132.0

83

35

4.09

 

K - BB

Mike

Mussina

27

12

9

.571

164.2

132

40

4.59

 

Innings

Javier

Vazquez

32

14

10

.583

198.0

150

60

4.91

 

                       
     

2005 CLEVELAND INDIANS

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Cliff

Lee

32

18

5

.783

202.0

143

52

3.79

Ace

ERA

Kevin

Millwood

30

9

11

.450

192.0

146

52

2.86

 

K - BB

CC

Sabathia

31

15

10

.600

196.2

161

62

4.03

 

Innings

Jake

Westbrook

34

15

15

.500

210.2

119

56

4.49

 

 

Scott

Elarton

31

11

9

.550

181.2

103

48

4.61

 

                       
     

2006 CHICAGO WHITE SOX

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Jon

Garland

33

18

7

.720

211.1

112

41

4.51

Ace

ERA

Jose

Contreras

30

13

9

.591

196.0

134

55

4.27

 

K - BB

Javier

Vazquez

33

11

12

.478

202.2

184

56

4.84

 

Innings

Freddy

Garcia

33

17

9

.654

216.1

135

48

4.53

 

 

Mark

Buehrle

32

12

13

.480

204.0

98

48

4.99

 

                       
     

2006 COLORADO ROCKIES

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Jeff

Francis

32

13

11

.542

199.0

117

69

4.16

Ace

ERA

Jason

Jennings

32

9

13

.409

212.0

142

85

3.78

 

K - BB

Byung-Hyun

Kim

27

8

12

.400

155.0

129

61

5.57

 

Innings

Aaron

Cook

32

9

15

.375

212.2

92

55

4.23

 

 

Josh

Fogg

31

11

9

.550

172.0

93

60

5.49

 

                       
     

2008 CHICAGO WHITE SOX

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Gavin

Floyd

33

17

8

.680

206.1

145

70

3.84

Ace

ERA

John

Danks

33

12

9

.571

195.0

159

57

3.32

 

K - BB

Javier

Vazquez

33

12

16

.429

208.1

200

61

4.67

 

Innings

Mark

Buehrle

34

15

12

.556

218.2

140

52

3.79

 

 

Jose

Contreras

20

7

6

.538

121.0

70

35

4.54

 

                       
     

2011 PITTSBURH PIRATES

 
 

 

 

G

W

L

WPct

IP

SO

BB

ERA

 

W-L

Kevin

Correia

27

12

11

.522

154.0

77

39

4.79

 

ERA

Jeff

Karstens

30

9

9

.500

162.1

96

33

3.38

Ace

K - BB

James

McDonald

31

9

9

.500

171.0

142

78

4.21

 

Innings

Charlie

Morton

29

10

10

.500

171.2

110

77

3.83

 

 

Paul

Maholm

26

6

14

.300

162.1

97

50

3.66

 

 

 

                With regard to the 1966 Cleveland Indians. . .that team, which was third in the American League in ERA, may have had their best pitcher in the bullpen most of the season.   Luis Tiant opened the 1966 season throwing shutouts in his first three starts and threw a fourth shutout on May 24, but was sent to the bullpen after four bad starts in June, and didn’t return to the starting rotation until September 20.    He wound up making only 16 starts, thus failing to qualify for these charts, which require 20 starts—but led the American League in shutouts, with 5.

                The real bone of contention here is the appropriateness of including the pitcher’s won-lost record as one element by which we evaluate his performance.   I can’t tell you how surprised I am to find myself the designated defender of Won-Lost records, since I campaigned against over-reliance on them for the first 20 years of my career, and have probably, I would guess, done more than anyone else ever to discourage people from relying on pitcher won-lost records; maybe not, I don’t know, I’ll leave that up to you.    In any case, I’m not really a defender of won-lost records, but the people who don’t want to pay any attention to them at all are out of their minds, and somebody needs to tell them so.   I’ve explained why several times before, but I’ll take one more stab at it.

                The radical anti-won/lost advocate is making two mistakes.   First, he is focusing on flaws in the won-lost category, and ignoring the fact that all of the other categories that we use to evaluate pitchers have the same sort of flaws—sometimes worse, sometimes not as bad, but they all have the same kind of flaws.   And second, he is asserting that there is no information in the won-lost category which is not redundant of the other pitching categories such as innings, strikeouts, walks, and ERA.   That’s just dead wrong, because there is information in the won-lost record which is not redundant of the other pitching categories.  If a pitcher does anything well, such as showing composure in close games, winning games 4-3 and 8-7, that could be reflected in his won-lost record, even if it doesn’t show up anywhere else in his record.   It is wrong to assume that won-lost records reflect some such hidden skill, because in many cases they absolutely don’t; in many case they reflect Good Luck, and nothing else—but it is equally wrong to assume absolutely that no pitcher has a better won-lost record because he has pitched well in close games or because of some other hidden talent.    We can’t assume that absolutely because we don’t know that absolutely.

                But there’s something else here that I’ve never written about, so let me try to explain it.    Game Specific Run Effects.    Game Specific Run Effects include Temperature, Wind, the Home Plate Umpire, and various other unknown or difficult to quantify elements such as whether the grass is wet or dry, the humidity, the tendencies of the other umpires, and  . .well, who knows.

                At risk of confusing the issue, a brief diversion.   I went to a game in Kansas City about 1994, at which five or six baseballs were hit an enormous distance—five or six fair balls, and several foul balls.    I have never understood what happened; the wind was not howling out, the air was not warmer than any other days, but. ..you couldn’t avoid the feeling that there was something happening here that we didn’t understand.   Balls that ordinarily would go 400 feet, on that day, were going 430.    I remember sitting there, watching those long, long home runs, and thinking "something is going on here that none of us understands."   I have had that feeling at ballgames on other occasions—sometimes that the balls were just dying in the air, at other times that they were flying through it with un-accustomed ease.

                My off-the-topic question to you is, do you think there could be some fundamental atmospheric condition to which the human race is so far entirely blind, in the same way that we were blind to barometric pressure before 1643?    Our five senses are in some ways limited; there are things around us that we can neither see nor hear nor smell nor feel nor taste.   I’m not talking about ghosts or anything paranormal; I’m talking about the possibility of there being something entirely normal that we merely lack the ability to sense, even with the enhancements of scientific tools, because scientific tools, in the end, merely make our senses more acute.   Do you think there could be something of that nature, which affects the travel of a baseball in flight, but which we simply have not yet recognized and measured?    Or is that too speculative for you, too far out? 

                OK, put that question aside, or post your answer if you prefer; back to the main topic.   Game Specific Run Effects vary at least with temperature, wind, and umpiring, and they vary as well with other game conditions which we more dimly understand.    Some days the game is 12 to 10, not simply because the pitching is bad and the hitting good, but because it is hot, the wind is blowing out, and the umpire won’t give a pitcher a corner; some days it is 1 to 0, not because the pitcher is great but because it is cold, the wind is pushing in and the umpire is calling everything a strike.    Game Specific Run Effects; GSRE for short.

                The question is, do GSRE even out for a pitcher, over the course of a season?   

                We don’t really know—but I don’t see how they possibly could, a pitcher making only 32 or 33 starts in a season.  Let us suppose that there are two pitchers, teammates, and that Pitcher A makes 8 starts under strong hitter-friendly GSRE, while Pitcher B, just by the luck of the draw, makes NO starts under strongly hitter-friendly GSRE.   Pitcher A is supported by 180 runs, has a 4.20 ERA and finished the season 16-11; Pitcher B is supported by 110 runs, has a 3.30 ERA and finishes the season 9-13.

                The radical anti-won/lost advocate will tell us that this difference in offensive support is merely luck, and consequently that it should be factored out of the pitcher’s evaluation—but the fact is that we do not KNOW that it is entirely luck.  The Radical Anti-Won/Lost Advocate is implicitly asserting that Game-Specific Run Effects even out over the course of the season, but the fact is that we do not know that they even out over the course of the season, and in my view it is enormously unlikely that they even out over the course of the season.  32, 33 starts. . .that just isn’t enough for anything to even out, generally speaking.

                I set up a model to estimate what the residue of Game-Specific Run Effects over the course of a season might reasonably be. . .I don’t know if this is interesting or not, but it was interesting to me so I’ll pass it along.   Let’s assume that an average team scores 4.50 runs per game, and let’s assume that that expectation is set by five factors:

                1)  0.50, standard for every game,

                2)  A random number between 0 and 2, reflecting the temperature at game time,

                3)  A random number between 0 and 2, reflecting the wind conditions,

                4)  A random number between 0 and 2, reflecting the umpiring, and

                5)  A random number between 0 and 2, reflecting the four factor, the sum of the other known and unknown elements which work to increase or suppress scoring.

 

                I use four random numbers to represent the game conditions, rather than one, because when you use four random numbers you get a bell-shaped curve, whereas when you use one you get a flat-line distribution.     The more random numbers you use, the tighter the distribution of the bell-shaped curve.

                Anyway, using these assumptions, the average Expected Runs Scored for a team in a game is 4.50, but the standard deviation is 1.15.    The actual standard deviation of runs scored for a team in a game is 3.07, so what we are implicitly saying here is that of all the variance in runs scored in a game, 14% is caused by Game Conditions, and 86% is caused by other factors (such as luck, the performance of the pitchers, and the performance of the hitters.)   That seems to me like a reasonable estimate.  

               

                Well, IF those conditions described above are an accurate model, then the standard deviation of Game Specific Run Effects, over the course of 32 or 33 starts, is .2013 runs per game; let’s call is .200.    In other words, there probably are Game Specific Run Effects embedded in a pitcher’s ERA on the level of .200 runs per game more or less than average.

                Did that make sense?   Let me try again.   I took the five-step assumptions outlined above, and simulated Game Conditions for hundreds of thousands of games.   Then I broke out groups of 32 and 33 starts (40% 33 starts, 60% 32 starts), and looked at the issue of whether or not Game-Specific Run Effects would even out over the course of 32 or 33 starts.  The standard deviation of Average Expected Runs for pitchers making 32 or 33 starts was .200.

                What that means—assuming that my model is reasonable—is that if a pitcher’s run context is estimated at 4.50 runs per game without any consideration of Game Specific Run Effects, then the "real" number would virtually never be 4.00 or 5.00, but that it would quite commonly be 4.30 or 4.70.

                And if Game-Specific Run Effects are real, then ONLY the won-lost record is going to automatically adjust for them; the ERA won’t, the strikeout to walk ratio won’t.   The won-lost record will, because the Game-Specific Run Effects should affect both teams in a game.  Effect, affect. . .I’ve never been able to figure that one out.  And don’t try to explain it to me.

 
 

COMMENTS (34 Comments, most recent shown first)

Steven Goldleaf
If you're using a noun, the word you want (almost certainly) is "effect"; If you're using a verb, the word you want (almost certainly) is "affect"--there, didn't hurt a bit, did it? If you want a little more detail (explaining the rare exceptions) see "http://writingexplained.com/affect-vs-effect"--otherwise noun=effect, verb=affect.
8:02 PM May 23rd
 
OldBackstop
@tango. Walt Terrell.
6:22 PM May 23rd
 
tangotiger
Joe asked about the differing relievers for each pitcher.

I looked at all the relievers that Lee and Hamels had in their starts. Cliff Lee's relievers were a bit worse, at around 0.25 runs per 9IP, if we use their seasonal stats. That's a far cry from the 2.5 runs or so difference that we observe of these relievers in the Lee/Hamels games.
9:58 PM May 22nd
 
tangotiger
After you account for the average runs scored and runs allowed for all the games a starting pitcher was in, what's left is two things:

1. Are they independent?
2. Are their distributions different?

For #1, they are dependent. After all, just think of Colorado pitchers. They are dependent on the park, and, what Bill is getting at, the "game specific" effects. So, we can't just necessarily take the average of everything. We probably have more 1-0 and 2-1 and 2-0 games than we'd predict, simply because there is a dependency, be it park, weather, or two teams adopting similar styles of play.

For #2, they are different. One team plays small ball, another team plays long ball, and even though they might score the same number of runs, their distributions are different. And that means we won't get a .500 record for both teams, but possibly .510 and .490.

Once we account for these two things (the dependence of runs scored and allowed, along with the distributions of those runs), there is nothing left for a pitcher's W/L record to tell us about the pitcher himself.

***

Bill had a great piece in one of the Abstracts that highlighted a couple of pitchers. One was Danny Jackson I think. I can't remember the other. If someone knows what I'm talking about, feel free to summarize it.

2:44 PM May 22nd
 
joedimino
I think he's saying (please correct me if I'm wrong that even after accounting for everything we can account for, things like run support and bullpen support, etc. there is still a delta between predicted W-L based on everything we can account for and actual W-L. I think he's saying that this delta isn't just luck. There might be something to it, that we aren't able to measure, but isn't just bad or good luck.

I agree with that thinking.
1:55 PM May 22nd
 
joedimino
I hear you Tango, but I agree with Bill that there are things that aren't measurable that we could be missing.

He isn't saying that it's a huge impact, but there could definitely be something there.

From my own work (well, interpreting others' work for my own system) I've seen that bullpen support definitely does not even out over a season either, so I'm not sure that just looking at runs and bullpens gets at the things Bill talks about.




1:51 PM May 22nd
 
tangotiger
Joe: it wasn't my study. In any case, given that Lee and Hamels had similar performances, wouldn't you expect the relief pitchers to be rather similar? But the results were far different.

Think also of run support. There was a big gap in run support as well, and that's over 9 innings x 30-whatever starts. And that's virtually the same hitters. So, now we're at 2-something innings x 30-whatever starts. Don't you think the bullpen support will show larger variation simply because we've got one-fourth the sample size of the offensive support?

Anyway, this is n=2. If someone wants to do the research, the path is there.

My larger point is that we don't need to rely on W/L to infer anything. We have the runs the offense scored and we have the runs the bullpen allowed. In terms of "game specific runs effects", we may as well look at the actual game specific runs for everyone outside of the SP we are interested in to determine the effects. No need to use W/L.
9:03 AM May 22nd
 
joedimino
Tango ... Did you control for the quality of the RP in the Lee/Hamels scenario? Don't better RPs pitch in games where a team is winning?
6:38 AM May 22nd
 
tangotiger
It would certainly not be the currently constructed W/L system.

And I already created such a system. It's called WAR. In any case, we're getting away from the topic at hand.
8:50 PM May 21st
 
OldBackstop
@tangotiger A not-Bomber fan wrote to me awhile back: "Whitey Ford was like 150-and 50 (158-63, .715) in his first twelve years, but the Yankees were in the World Series 10 of those 12 years, so his numbers are inflated to your average Joe pitcher of that era." Which seems like it might be right, although there was some war year muddiness in there I didn't parry back on.

So I sez, "Yeah, but Stengel didn't use a set rotation, and when Whitey was ace, which was pretty quick, Casey held him back to face the stronger teams. Like in 1960, he started five times against the White Sox, who won 89 games, and went 1-4. But he only got to work twice in relief against Boston, who won just 65 games. Once Stengel left and Houk came in, Ford braced him and said he wanted to work regularly, and his winning percentage went from .715 to .743 the rest of his career."

Only I didn't say that, I just said "Yeah", because I didn't know that until I read it in Bill's Guide To Baseball Managers, a fine read.

So, that story is a zebra and not a horse maybe. But to me, it might be nice to read an article that just says "Ford started 29 games in 1955 with a league high 21 Superior Quality Starts." (that stat needs defining, but what else do you want out of an SP?).

My question is....if you came into this game without there being any history of stats, and you had to characterize a starting pitcher's season by one stat to an audience with no predetermined stat prejudices, what stat would you use? Create one if you want, but would it be the W/L as currently constructed.



8:21 PM May 21st
 
garywmaloney
You used "affect" correctly. To "effect" something (i.e. effect as a verb, rhymes with "defect") is to make something happen. (As in, "Voros McCracken effected a major change in baseball thinking.") And having read your stuff from the late 1970s to the present, Bill, it's clear to me (trained to be a journalist and niggling editor) that you get virtually all of these English usage questions right. Plain speaking (and writing) like yours places a premium on clarity, not unnecessarily fancy terms.
8:02 PM May 21st
 
tangotiger
My go to for SP is Cliff Lee (6-9) v Cole Hamels (17-6) in 2012, both pitching for the Phillies, with virtually identical performances.

A reader suggested that maybe Cliff Lee pitched in more favorable conditions than Hamels. Except the RELIEF pitchers in Cliff Lee games did far worse than Hamels' relief pitchers.

Someone else brought up Orel Hershiser 1988 v 1989? Go look it up. You'll be shocked.
7:57 PM May 21st
 
BobGill
Bill: Thanks for the list of all the different staffs. Some of them were rather familiar, others not at all; I'm looking them up now. I guess if you limited the number of starters to four, or five, you'd get a few different teams in the list -- the 1966 Dodgers, for instance, would probably show up if you set the limit at four starters.

Tangotiger: Maybe a picky point, but it seems to me that the example of Tyler Clippard doesn't have anything to do with the current discussion of W-L records, since the focus is exclusively (or almost exclusively) on starters. And nobody today pays any attention to relievers' W-L records; I doubt that anybody has since the early '80s, when guys like Quisenberry could still go 12-7 with 39 saves.
7:18 PM May 21st
 
bjames
Responding to the comment posted by Bob Gill, I got interested in the question of the most impressive starting rotations of all time, based on the career won-lost records of the four, five, or six starters on the team. I set up a little method to rank the teams. . ..it doesn’t really matter what it is. …and ranked all teams ever.

The most impressive starting rotations of all time, I concluded, were the 1997 and 2002 New York Yankees. The 2002 rotation was Roger the Rocket (354-184), Mike the Moose (270-153), Andy Pettite (256-153), David Wells (239-157) and El Duque (90-65). . .that’s a pretty decent rotation, even though El Duque’s career record is not as impressive as it might be if he had been able to start his major league career in his 20s.

That ranks second to the 1997 Yankees: Pettite (256-153), Wells (239-157), Kenny Rogers (219-156), David Cone (194-126), Doc Gooden (194-112), and sixth starter Ramiro Mendoza (who cares?).
The 2001 2003 Yankees also had great pitching staffs, but we’ll skip those because it’s just the same pitchers in rotating combinations.

In third place is the rotation of the 1908 New York Giants, who had six starting pitchers with 100+ career wins: Christy Mathewson (373-188), Iron Man McGinnity (246-142), Red Ames (183-167), Hooks Wiltse (139-90), Luther Taylor (116-106) and Doc Crandall (102-62). Great nicknames on that team: Taylor was called “Dummy” because he was a deaf mute, Ames was called “Red” because he had flaming red hair, Wiltse was called “Hooks” because he threw a big curve ball, McGinnity was called “Iron Man”, I believe, because he had married a woman whose father owned an iron works or something like that, and “Doc” was called “Doc” because he was kind of a scholarly type guy who used some big words. . .that’s from memory; feel free to correct me if you know something more. The 1905 and 1906 Giants would also score well by my method. The 1912 Giants. . .it’s a close call whether that’s the same rotation or a different one, but I guess I’ll ignore them because three of their five starters were the same guys as in 1908.

Fourth is the 1900 Pirates; the compression of the league due to the elimination of four franchises left some unusual combinations of talent. The 1900 Pirates had five starters with almost the same won-lost records: Jack Chesbro (198-132), Jesse Tannehill (197-116), Sam Leever (195-100), Rube Waddell (193-143) and Deacon Phillippe (189-109). The 1902 Pirates also would rank very well.

Fifth is a team that nobody would guess would be on the list, but they’re here because they, again, have six starting pitchers with 100+ career wins: the 1937 Cleveland Indians. Bob Feller (266-162), Mel Harder (223-186), Earl Whitehill (218-185), Willis Hudlin (158-156), Johnny Allen (142-75) and Denny Galehouse (109-118). The 1938 Indians also score well; it’s the same guys but no Galehouse.

Sixth is the 1925 Yankees. . .more or less the pitchers you mentioned: Pennock (240-162), Hoyt (237-182), Sad Sam Jones (229-217), Bob Shawkey (196-150), and Urban Shocker (187-117). The 1922, 1923, 1924 and 1927 Yankees are also near the top of the list, although we’re ignoring them for obvious reasons.

Sixth on the list is the 1998 Atlanta Braves: Maddux (355-227), Glavine (305-203), Smoltz (213-155), Kevin Millwood (163-140) and Denny Neagle (124-92). The 1999, 2000 and 2001 Braves are also on the list, although we’re ignoring them.

Next are two teams you wouldn’t expect to be on this list: Craig Wright’s 1989 Texas Rangers, and Eddie Epstein’s 1993 Baltimore Orioles. The Rangers had Nolan Ryan (324-292), Jamie Moyer (267-204), Rough, Tough, Charlie Hough (216-216), Smiling Kevin Brown (211-144), Control Artist Bobby Witt (142-157) and Mike Jeffcoat (Ugh). Eddie’s 1993 Orioles are perhaps even more suprising; that list is Moose and Moyer (270-153 and 267-204), Fernando Valenzuela (173-153), and Rick Sutcliffe (171-139), with Arthur Rhodes as the fifth wheel (87-70) and Ben McDonald the sixth (78-70).

Ninth and 10th on the list are two teams from the 1970 season. The St. Louis Cardinals were headed by Hall of Famers Steve Carlton (329-244) and Bob Gibson (251-174), but backing them up were Jerry Reuss (220-191), Mike Torrez (185-160), and Strummin’ Nelson Briles (129-112). In the other league, the Minnesota Twins featured four pitchers with 215 or more career wins: Blyleven (287-250), Kaat (283-237), Tiant (229-172) and Jim Perry (215-174). Fifth starter was Dave Boswell, (68-56), and sixth starter was Bill Zepp (10-5), who was the brother of George Zepp from the movie Airplane.

In 11th place would be the 1932 Cubs, National League champions, with Burleigh Grimes (270-212), Charlie Root (201-160), the Arkansas Humming Bird (192-121), Guy Bush (176-136), and Irish Pat Malone (134-92). We’ll see Grimes again in a moment, in a different rotation.

12th and 13th are a couple of Yankee teams that aren’t related to the ones we have already listed. The 1953 Yankees had Whitey Ford (236-106), Allie Reynolds (182-107), Ed Lopat (166-112), Johnny Sain (139-116), Vic Raschi (132-66) and somebody named Jim McDonald (24-27). The 1932 Yankees, who beat the afore-mentioned Cubs in the World Series, had Red Ruffing (273-225), Pennock (240-162), Lefty Gomez (189-102), Johnny Allen (142-75), and George Pipgras (102-73).


14th is the 1906 Philadelphia Athletics, headed by three Hall of Famers: Eddie Plank (326-194), Chief Bender (212-127), and Rube Waddell (193-143); they were followed by Colby Jack Coombs (158-110), Andy Coakley (58-59), and little Jimmy Dygert (56-49); Dygert only weighed about 115 pounds. (Some Encyclopedias list him at 185 pounds, but that’s just totally absurd; he was famous for his miniscule size, and there are many news stories about it from that era. I’m not sure how the Encyclopedias screwed that one up.)

The 1931 St. Louis Cardinals, World Champions, had six 100-game winners in their rotation Burleigh Grimes (270-212), Paul Derringer (223-212), Jesse Haines (210-158), Syl Johnson (112-117), kidnap victim Flint Rhem (105-97) and Wild Bill Hallahan (102-94). That’s in 15th place; in 16th is another Yankee unit, the 1979 rotation of Tommy John (288-231), Luis Tiant (229-172), Catfish (224-166), Ron Guidry (170-91) and Ed Figueroa (80-67).

17th place is the team the 1931 Cardinals beat, basically. . .a little different year. The 1927 Philadelphia Athletics had a rotation of Lefty Grove (300-141), Jack Quinn (247-218), Eddie Rommel (171-119), Howard Ehmke (166-166) and Rube Walberg (155-141).

18th is the famous “perfect rotation” of the 1954 Cleveland Indians, headed by Hall of Famers Early Wynn (300-244), Bob Feller (266-162) and Bob Lemon (207-128). Fourth starter Mike Garcia led the league in ERA; he was as good as the other guys, only he got hurt in mid-career (142-97) and the fifth starter was Art Houtteman (87-91). Actually Feller was more the fifth starter, but I’m ranking them by career records.

19th is the 1984 Dodgers: Jerry Reuss (220-191), Bob Welch (211-146), Orel (204-150), Fernando (173-153), Rick Honeycutt (109-143) and Alejandro Pena (56-52). 20th is the 1999 Toronto Blue Jays: David Wells (239-157), Roy Halladay (203-105), Chris Carpenter (144-94 so far), Pat Hentgen (131-112), Kelvim Escobar (101-91) and Joey Hamilton (74-73).

I’ve gone on too long about this, but I’ll mention a couple of teams that don’t quite rank. The best rotation the Red Sox have ever had was the 2004 team that broke the curse: Pedro (219-100), Curt Schilling (216-146), Wakefield (200-180), Derek Lowe (166-146) and Bronson Arroyo (138-127 at the start of this season, still pitching the way he always has.) That team is actually still moving up the list, because Bronson is still winning games.

Also, the 2010 Phillies could ultimately rank very high, depending on how much we see in the future of Cole Hamels. After they traded for Roy Oswalt they had six starters: Jamie Moyer (267-204), Roy Halladay (203-105), Oswalt (163-102), Whole Camels (99-74 so far), Joe Blanton (85-89 so far), Nate Robertson (57-77) and Kyle Kendrick (64-55 so far).




5:48 PM May 21st
 
hotstatrat
Going through the list, thanks, Bill, to see if either of the four ace markers was a stronger or weaker indicator of the pitchers' overall career, I didn't find one. They all had about their fare share of representing the better career pitchers of the quartet.
2:16 PM May 21st
 
tangotiger
The general idea of a W-L record is one thing.

The actual rule as written out in 700+ words is another. The current example in 2014 is Tyler Clippard who already has 4 wins, basically because he holds a tie for one inning (or worse he blows the lead), while his team then takes the lead in the next half inning, making Clippard the "winner".

The W-L record, as presently codified in the rules, adds nothing to our understanding of the pitcher, if we already have the runs his team scored, and the innings in which they were scored. There's no reason to then REMOVE all of that information, and then limit ourselves to the W-L record.

And if we INCLUDE all of that information, having it ALSO synthesized in a W-L record adds no new information with respect to what it tells us of understanding the pitcher.


1:48 PM May 21st
 
bjames
Responding to the comment posted by Cypher, about six comments below.

I worked in salary arbitration cases for about 12 years, 1979 to 1991. The MOST memorable, most effective salary arbitration exhibit that I ever created was exactly what you suggest. In 1980 Steve Trout finished 9-16 but with a decent ERA, 3.70 against a league average of 4.04. The White Sox had scored very few runs for him; he was one of the three or four poorest supported starting pitchers in the league. We prepared an exhibit for his arbitration case explaining the Pythagorean won-lost theory in one paragraph, demonstrating that Trout’s 9-16 won-lost record was a normal and predictable outcome of his lack of offensive support, and then demonstrating that had Trout’s offensive support been league average, his won-lost record would have been. . .I forget whether it was 14-11 or 13-12, something like that.

The reason this was such a memorable moment—it absolutely was THE highlight of my arbitration career—is that the White Sox did EXACTLY what we had hoped they would do: They ridiculed the exhibit. Nobody had ever heard of the Pythagorean Won-Lost approach; they just thought it was nonsense, and they talked about Trout not pitching well when the game was on the line, badmouthed the whole idea that it might be possible to predict a pitcher’s won-lost record from his run support and the number of runs he had allowed, and pointed out that there was no data for any other pitcher.

At which point we introduced a chart giving the same data for every other American League pitcher, and demonstrating that almost every pitcher had exactly the won-lost record you would expect him to have, given his run support. That was the year that Steve Stone had won the American League Cy Young Award with a 25-7 record, because the Orioles had scored a huge number of runs for him. Nobody knew that at that time, but on the chart, you could see it as clear as day. I think Stone’s expected record was actually 23-9, but still. . .and MOST of the pitchers in the league that year actually had exactly the record the Pythagorean approach would have predicted they would have.

It was beautiful. We set a trap for them, they walked right into it, and we mowed them down, because we were ahead of the curve and they were behind it; it was gorgeous. You’re always trying to do stuff like that in an arbitration case, in any legal case, but 99 times in 100 it doesn’t quite work. Trout won the case, which won him. . ..I forget what it was, but I think it was less than $100,000.

That was 33 years ago, February of 1981. But what I am trying to say NOW is that, while the Pythagorean approach does remove ONE level of bias, a large level of bias, that there is ANOTHER level of bias that this approach does not remove. It’s a smaller level of bias, but it’s still there, and the Pythagorean approach doesn’t do anything at all to remove it, so we need to think about how we could remove it. And some of you guys now are playing the exact same role that the White Sox were playing in 1981, that the traditional baseball community played throughout the 1980s: you’re saying, “Oh, no, we understand this problem. We’ve got this all figured out; we don’t need to pay attention to any of this new-fangled Bill James nonsense. We know everything about this that we need to know.”

And what I am telling you—then and now—is: No, you don’t. We DON’T completely understand the problem. There is another level of bias in there that we DON’T know how to remove, don' t even know how to estimate the size of, and because there is that other level of bias, we need to be respectful of the possibility that the won-lost record is actually trying to tell us something that we should know. Not saying that the won-lost record isn’t subject to bias; I know very well that it is.

10:07 AM May 21st
 
mauimike
"do you think there could be some fundamental atmospheric condition to which the human race is so far entirely blind?" Yes and I don't believe in anything. Have you seen that when you rake up a pile of leaves, a gust of wind blows them away? Have you ever put a cup of something on a level surface and the wind blows it away. Do you ever have the sense that the universe is laughing at you. That little things that happen, are not your fault, but that something is conspiring against you? Even if you're not 40 and living in your mother's basement? They're out to get you. Who they are I don't know, but the next time the napkin you needed, to wipe that snot of your nose, in front of that girl you were trying to impress, gets blown away, you know that the Universe is laughing at you. As it should, you are a joke.
3:43 AM May 21st
 
OldBackstop
@BobGill: The way to build that rotation is the Yankee way. The Yankee owners held a $300,000 mortgage on Fenway Park. Pitchers Waite Hoyt, Sad Sam Jones, Bullet Joe Bush, Herb Pennock, Carl Mays and a sort of chubby pitcher/slugger all came to the Yankees from the Red Sox in the few years prior to 1923, traded or sold.

That is off the top of my head, I wrote it up for an article elsewhere, but check it out and correct me if I'm wrong.

My son fell on the ground laughing a few years ago when he heard the Yank's GM was named "Cashman"...
11:40 PM May 20th
 
BobGill
This is outside the main thrust of the article, but what strikes me the most is the Yankees' top five pitchers in 1923. Granted, there's nobody there to compare with Walter Johnson or Lefty Grove, but Pennock won 241 games altogether, Hoyt 237, Jones 229, Bush 196, Shawkey 195. I wonder if any other team has ever had five pitchers of that quality, with all of them working regularly, not just getting started in the majors or just hanging on at the end of a career. It's really impressive, at least to me.

9:06 PM May 20th
 
OldBackstop
Thanks. BBR is like an onion. I keep thinking I know it, and then somebody puts a slice in my face, and I cry.
8:18 PM May 20th
 
tangotiger
You don't have to be that savvy. Here's Cliff Lee's career record by run support:

www.baseball-reference.com/players/split.cgi?id=leecl02&year=Career&t=p#rs_extra

Here's all pitchers with at least 1000 IP when given 3-5 runs of support, 1914-present:

bbref.com/pi/shareit/PDixG

Pedro is #1 with a .760 wins%. Mike Torrez is last at .450.

Jack Morris is neck-and-neck with Blyleven, and Frank Tanana, and Dave Stieb... behind El Presidente... and wayyy behind Rick Reuschel.
7:54 PM May 20th
 
OldBackstop
@Tangotiger: [/b]While everything contains some information, there's a larger danger with the W/L record of not underweighting it enough than to completely ignore it.[/b]

I don't have the spreadsheet savvy (I would if they brought back Lotus 123,) but it would be interesting to see historic W/L records where a pitcher's run support was in the range where his mettle was tested. Eliminate games where he got more that X (say 5, era appropriate) or less than Y (say 1 or 2, era appropriate). With all necessary weightings and etc.

I suppose "record in one run ball games" gets there a little. But then there is the example of Steve Trachs...nevermind.
7:13 PM May 20th
 
OldBackstop
Okay, I am, I assume, “The Radical Anti-Won Lost Advocate” AKA “Pirst Foster”....but I always believe people are talking about me on trains. I will go forth under that assumption, although using that word is a fault of mine, as we shall soon see.

BJ: “The first poster speculated that I must have decided who the best pitcher on each team was based on Wins and Losses. I don’t know what I could possibly have done that would cause anyone to think I would identify the best pitcher on a team by Wins and Losses….”(snip to below)

FML. Just looked. I did do that. I said “I assume that was done here.” The article was silent on method and did not list Season Scores, and the only season-specific performance chart was the Opening Day record one that listed GS, W, L and ERA. My bad. Assume. Assume a can opener.

Debating the issue of who should be identified as the best pitcher on a team, the Pirst Foster complains about Steve Trachsel with the 2006 Mets, which seems like a non-instructive example, since there is no method by which Trachsel would show up as the #1 starting pitcher on the 2006 Mets.

Trachsel was 15-8, Glavine was 15-7. What I said was: “I guess Glavine with the same wins but one less loss was the “best pitcher”, but Trachsel came just-this-close to earning the title by W-L measures.” (emphasis added)

On that squad, by the way, in addition to those W/Ls, John Maine led the qualifying starters in ERA with 3.60, Pedro Martinez led in SO/W with 3.61 and total Ks with 137 and also H/9 and K/9, Glavine was first in GS and IP, and El Duque led in FIP.

BJ…it tends to confirm my suspicion that I must have been a very wicked person in a previous life.

That wasn't me, that was The Vatican.



6:45 PM May 20th
 
3for3
One obvious factor left out is the other 8 players on your team. I pitch with the weak hitting defensive daemon for a shortstop, you get the big bat no field guy. This might be especially relevant for the pitchers who insist on certain catchers, who usually swing a limp noodle.
5:25 PM May 20th
 
Cypher
It seems that, if Runs For - Runs Against is predictive of a team's record, then it "should" be predictive of a starter's record, at least for the time he's in the game, though perhaps less so than for a team. Has this been examined? Does it work? It seems like the beginning of an idea, anyway.
5:08 PM May 20th
 
colinb
Don't know how relevant this is to the discussion, but I found it interesting so I'll share; that way everyone else doesn't have to count like I did. For Bill's teams that had four categories led by four different pitchers, the numbers for which leader was the designated Ace are:

W-L: 13
ERA: 4
K-BB: 2
Innings: 5

Obviously a very small sample size but interestingly K-BB ratio has the lowest indicator of the Ace. This is interesting because in Bill's article "On the Relative Importance of Pitching Categories" K-BB ratio was the best indicator of true value.
12:27 PM May 20th
 
mskarpelos
Bill, you call the third component strikeout/walk ratio, but it looks like you calculate strikeouts minus walks (i.e. strikeout-walk delta). Intuitively, I prefer the ratio to the delta, but I'd be interested in knowing your reasoning for choosing a delta.
12:16 PM May 20th
 
wovenstrap
Actually, I suppose if the advocate is "radical," as you assert, you might be right.
10:56 AM May 20th
 
wovenstrap
Not very important, but I don't see the connection between asserting that it might be luck and the second premise, that it evens out in a season. Those seem like very different propositions to me, and if you're accusing a person who says one of saying the other, you've set up a straw man. If it's luck, it's luck. It doesn't suggest anything about the time frame it would take to even out. It's implicit in YOUR framing of that problem that your argument-opponent would insist that it evens out in a GAME, which seems obviously false.
10:45 AM May 20th
 
tangotiger
While this is n=2, it's a great way to look at a starter by seeing how his bullpen did the same day he pitched.

www.thegoodphight.com/2012/12/18/3780882/lee-and-hamels-statistical-twins-but-not-in-wins

Conclusion:
"if it’s the game conditions helping Lee out, then the bullpens would likely benefit from the same conditions, so the spreadsheet tracks that, too (very simply, using only ERA), and as you might expect of one who pitched brilliantly and won six games, Lee was backed up by an awful bullpen, posting an ERA very near 5.00 in 60 ? innings; the same bullpen was brilliant for Hamels, with a 2.39 in 64 innings.

So if there was some invisible set of factors such that Lee was pitching in more favorable conditions than Hamels was, it appears that those conditions immediately reversed themselves once the starters were pulled."


10:31 AM May 20th
 
tangotiger
Rather than relying on a pitcher's W/L record, why not rely on the number of runs the offense scores?

The W/L record has so much random variation associated to it that to rely on it we'd need to heavily underweight it.

While everything contains some information, there's a larger danger with the W/L record of not underweighting it enough than to completely ignore it.

It's similar with the BABIP. Yes, BABIP has information to it. And personally, I heavily regress it. But, given the choice between no regression and completely ignoring it, I ignore it.

The key point is the amount of regression. And the W/L record, when it is used, is not regressed enough. So, better to ignore it if the user doesn't want to be troubled with regression. (I.e., regress it 100%.)
10:09 AM May 20th
 
Robinsong
I like the basic point of this analysis -win--loss records normalizae for some hidden game-day effects. This is also true of win-loss and park or era effects. I think that wind and temperature are open to study and adjustment, at least potentially, the way that park effects are. Indeed, they might be correlated with park effects; Wrigley Field is notorious for its winds on certain days. I am not as confident as Bill that win-loss records normalize fully for this. One team may have fly-ball hitters or pitchers, the other ground-ball hitters or pitchers differentially affected by game day conditions. Even the umpire's bias may have a differential effect: Maddux and Glavine lived on and off the outside corner and would be disproportionately affected by the strike zone.
8:46 AM May 20th
 
chill
I like to use "uffect" just to keep them guessing.
8:43 AM May 20th
 
 
©2019 Be Jolly, Inc. All Rights Reserved.|Web site design and development by Americaneagle.com|Terms & Conditions|Privacy Policy