Continuing with the Pitchers

July 15, 2020
  

              PITCHERS, Baserunners Removed-1 and starting on DP

 

                 Formula 10:  BRR-1           (Base Runners Removed-1)

            "Base Runners Removed" is four things—Runners Picked Off, Runners Caught Stealing, Double Plays, and Outfield Assists.  Originally I was counting all four of these in one category, but that turned to be more cumbersome than separating them into two categories—BRR-1 and Double Plays.  

            Base Runners Removed is one of the two "positive" categories; that is, a high number of base runners removed is a good thing, as a high number of strikeouts is a good thing, so we don’t have to turn it upside down and estimate where the ceiling is.  

            That leaves three things in this category, and the pitcher gets no credit for Outfield Assists, so that leaves two things in this category.  A pitcher gets 100% credit for any runner that he picks off base, and 30% credit for any runner caught stealing while he is on the mound:

            BRR-1 =  PPickoff + .30 * CS

 

 

 

            Formula 11:  RR1-RS-Pit-P5   (Runners Removed-1, Runs Saved, Pitchers, 5th Pitcher’s Value)

            Each baserunner removed has a value of .516 runs:

            RR1-RS-Pit-T5 =  BRR1 * .516

            Note that this is the fifth element of a pitcher’s value, but we have now considered nine different performance elements, since Base Advancements includes four different performance measures, and Baserunners Removed includes two. 

            Again, the addition of this category does not do a whole lot to scramble the list of the pitchers preventing the most runs, within the study:

Year

Player

P1

P2

P3

P4

CS

PkOff

BRR-1

P5

Total

1968

Denny McLain

45

27

21

7

5

1

2.5

1.3

101

2004

Randy Johnson

47

20

18

4

10

0

3.0

1.6

91

1960

Bob Friend

29

27

23

7

2

0

0.6

0.3

86

1960

Vern Law

19

26

18

7

6

0

1.8

0.9

71

2008

Cole Hamels

32

18

12

5

2

1

1.6

0.8

67

1968

Mickey Lolich

32

13

14

5

7

3

5.1

2.6

66

1984

Dan Petry

23

16

17

5

15

3

7.5

3.9

65

1968

Earl Wilson

27

15

16

4

5

2

3.5

1.8

63

1976

Gary Nolan

18

25

13

4

8

0

2.4

1.2

62

2016

Jon Lester

32

13

12

3

13

0

3.9

2.0

62

1984

Jack Morris

24

13

19

4

6

0

1.8

0.9

60

1992

Jack Morris

21

13

20

4

16

0

4.8

2.5

60

2016

Kyle Hendricks

27

13

14

3

4

3

4.2

2.2

60

1976

Pat Zachry

23

9

20

4

13

2

5.9

3.1

59

1980

Floyd Bannister

25

15

14

4

3

1

1.9

1.0

59

 

            Dan Petry, who moved from 10th to 8th in the last revision of this list, now moves up to 7th, and Floyd Bannister, who was 12th before, drops to 15th; Bannister allowed 18 stolen bases with only 3 runners caught stealing, much worse data than the other pitchers on his team.  Jack Fisher, who jumped onto this list in the last round, drops off now, replaced by Pat Zachry of the 1976 Reds.   Petry is the number one pitcher in this category, with 7.5 Baserunners removed, followed by Casey Fossum (Arizona, 2004) with 6.4.

 

 

 

A Brief Essay

Almost an Apology, but it has to be done this way

            We have basically three categories of fielding performance left to discuss, although pitcher’s get five different kinds of credit (total) for the three categories.   The three things we have to deal with yet are Double Plays, Fielding Percentage, and Range / Defensive Efficiency.  

            Unfortunately, we are entering a series of long, somewhat technical explanations—and long, technical explanations which affect only very small numbers of Runs Saved by pitchers, although they allocate large numbers of Runs Saved to other defensive players, but small numbers to pitchers.   There will be several days of explanations here before we are done with the Double Plays.   

The reason that it has to be done that way is that Double Plays, Fielding Percentage and Range are credited on a TEAM basis, so we have to figure some information about the entire team before we can know how much credit to give to the individual pitcher.  I am determined to explain the entire process in a way that is logical to a programmer, so that the data can be programmed and generated, but it’s not that logical from the standpoint of a reader, slogging through long explanations in order to credit this pitcher with 6/10ths of one run saved and that pitcher with 7/10ths.   It’s just the way it has to be done;  we have to explain the entire sequence of calculations, for little immediate benefit.  Sorry about that. 

 

            Formula 12:   ERO1B-Tm  (Team Estimated Runners on First Base)  

            Pitchers get run-saving credit for (a) participating in Double Plays, as fielders, and (b) starting double plays as pitchers.  In order to give a TEAM credit for their double plays, we need to establish how many double plays we would expect them to complete, based on their team circumstances, including the number of runners on first base.  In order to do that, we need to create a good estimate of the number of runners on first base against each team.  This is the formula for that.

            ERO1B= (H – HR) * .776 + HBP + W – SB – CS – PB – WP – BK

            .776 time (hits minus home runs) because, over time, 77.6% of hits which were not home runs have been singles.  We will need to figure both the ERO1B for the team, and for the league.   I have at times used slightly different formulas for Estimated Runners on First Base.   As long as the method is consistent throughout the data, the minor variations are totally insignificant.   

            I’ll try to chart the data for each of the 15 teams which are being used in the test run.

YEAR

City

Team

H

HR

BB

HBP

SBA

OCS

PB

WP

BK

ERO 1b

1960

Pittsburgh

Pirates

1363

105

386

11

44

32

10

25

1

1261

1964

New York

Mets

1511

130

466

50

79

66

32

53

5

1353

1968

Detroit

Tigers

1180

129

486

32

80

40

10

38

4

1162

1972

Texas

Rangers

1258

92

613

48

77

56

14

44

4

1371

1976

Cincinnati

Reds

1436

100

491

21

94

51

6

43

7

1348

1980

Seattle

Mariners

1565

159

540

27

114

54

13

31

7

1439

1984

Detroit

Tigers

1358

130

489

30

68

52

16

47

6

1283

1988

Baltimore

Orioles

1506

153

523

43

136

56

18

42

25

1339

1992

Toronto

Blue Jays

1346

124

541

45

144

63

15

66

6

1240

1996

Detroit

Tigers

1699

241

784

80

117

54

7

82

4

1731

2000

New York

Yankees

1458

177

577

52

91

37

13

49

6

1427

2004

Arizona

Diamondbacks

1480

197

668

75

97

50

18

71

8

1495

2008

Philadelphia

Phillies

1444

160

533

57

109

34

5

34

3

1401

2012

Houston

Astros

1493

173

540

48

131

37

13

75

6

1350

2016

Chicago

Cubs

1125

163

495

63

133

38

12

80

0

1042

 

            Formula 13:  TXDP  (Team Expected Double Plays)

            This gets hairy when you try to explain it all at once, but if we move slowly enough through it I hope we can do without confusing you.  

            Team Expected Double Plays are:

            The league average of double plays per game,

            Times the team’s games played,

            Modified by the team’s Estimated Runners on first base per inning, compared to the league average,

            Modified by the team’s Assists per inning, compared to the league average of assists per inning. 

            Trying to put this all in one formula, it is:

   TXDP= (LgDP/G) * TG * [(TmERO1B/Inn)/(LgERO1B/Inn)] * [(TmAs/LgAs)]

            I think that to get all of this in a chart I will have to break it down into a series of charts.   For the 15 teams that we are following, these are the league Double Plays and Games Played and the team Games Played, which produces our first estimate of their expected double plays:

YEAR

City

Team

Lg DP

Lg G

Team G

Exp DP-1

1960

Pittsburgh

Pirates

1128

1238

155

141.23

1964

New York

Mets

1439

1624

163

144.43

1968

Detroit

Tigers

1388

1624

164

140.17

1972

Texas

Rangers

1770

1858

154

146.71

1976

Cincinnati

Reds

1811

1944

162

150.92

1980

Seattle

Mariners

2372

2264

163

170.78

1984

Detroit

Tigers

2179

2268

162

155.64

1988

Baltimore

Orioles

2150

2262

161

153.03

1992

Toronto

Blue Jays

2204

2268

162

157.43

1996

Detroit

Tigers

2278

2266

162

162.86

2000

New York

Yankees

2282

2265

161

162.21

2004

Arizona

Diamondbacks

2394

2590

162

149.74

2008

Philadelphia

Phillies

2323

2588

162

145.41

2012

Houston

Astros

2143

2592

162

133.94

2016

Chicago

Cubs

2130

2428

162

142.12

 

            Interrupting our narrative here for just a moment, notice the exceptional number of double plays turned in the American League in 1980.   I had never noticed that particular number before, but I have thought many times about the exceptional quality of the second basemen in the American League at that time.   

The only regular second baseman in the league who is in the Hall of Fame is Paul Molitor, Milwaukee, although Molitor actually was not an exceptional defensive second baseman.   But three or perhaps four of the others could be Hall of Famers—Willie Randolph of New York, Lou Whitaker of Detroit, Bobby Grich of California, and Frank White of Kansas City.  The fact that they were all so good tends to blind us to how good they were.

            Anyway, we have a first estimate of the number of expected DP for each team—141.23 for Pittsburgh in 1960.  We multiply this by (1) the team ratio of Estimated Runners on First Base per inning, compared to the league, and (2) the team’s assists per inning, compared to the league.   I’ll chart those separately to keep the charts small enough to be understood.  The 1960 Pirates had 5% fewer runners on first base, per inning, than the National League average:

YEAR

City

Team

Lg

ERO 1b

Tm IP

League ERO1B

Lg IP

Ratio

1960

Pittsburgh

Pirates

NL

1261

1400

10576

11123

0.947

1964

New York

Mets

NL

1353

1440

13028

14521

1.047

1968

Detroit

Tigers

AL

1162

1489

12013

14550

0.945

1972

Texas

Rangers

AL

1371

1375

14586

16653

1.138

1976

Cincinnati

Reds

NL

1348

1470

15764

17461

1.015

1980

Seattle

Mariners

AL

1439

1457

19341

20332

1.038

1984

Detroit

Tigers

AL

1283

1464

19015

20280

0.935

1988

Baltimore

Orioles

AL

1339

1416

18076

20187

1.056

1992

Toronto

Blue Jays

AL

1240

1440

18753

20329

0.934

1996

Detroit

Tigers

AL

1731

1432

20630

20272

1.188

2000

New York

Yankees

AL

1427

1424

21024

20141

0.960

2004

Arizona

Diamondbacks

NL

1495

1436

22607

23146

1.066

2008

Philadelphia

Phillies

NL

1401

1449

22821

23135

0.980

2012

Houston

Astros

NL

1350

1423

20671

23070

1.059

2016

Chicago

Cubs

NL

1042

1459

19761

21695

0.784

 

            However, the Pirates had a ground-ball pitching staff, with somewhat more assists per inning than the league average:

 

YEAR

City

Team

Lg

Tm IP

Lg IP

Team A

Lg A

Ratio

1960

Pittsburgh

Pirates

NL

1400

11123

1774

13374

1.054

1964

New York

Mets

NL

1440

14521

1914

17933

1.076

1968

Detroit

Tigers

AL

1489

14550

1615

17232

0.916

1972

Texas

Rangers

AL

1375

16653

1618

20193

0.970

1976

Cincinnati

Reds

NL

1470

17461

1678

21854

0.912

1980

Seattle

Mariners

AL

1457

20332

1930

25626

1.051

1984

Detroit

Tigers

AL

1464

20280

1667

24281

0.951

1988

Baltimore

Orioles

AL

1416

20187

1726

23558

1.045

1992

Toronto

Blue Jays

AL

1440

20329

1591

24287

0.925

1996

Detroit

Tigers

AL

1432

20272

1727

23240

1.052

2000

New York

Yankees

AL

1424

20141

1487

23255

0.904

2004

Arizona

Diamondbacks

NL

1436

23146

1706

26877

1.023

2008

Philadelphia

Phillies

NL

1449

23135

1698

26289

1.031

2012

Houston

Astros

NL

1423

23070

1729

26208

1.069

2016

Chicago

Cubs

NL

1459

21695

1635

23987

1.013

 

            In the first chart in this series the 1964 New York Mets and the 1968 Detroit Tigers had about the same number of expected double plays, just based on the league averages—144.4 for the Mets, and 140.2 for the Tigers.   However, the 1964 Mets had both a higher-than-league-average number of opposing runners on first base, and a higher-than-league-average number of Ground Balls (as measured in Assists).   The 1968 Tigers had both a lower-than-average number of opposing runners on first base, and a lower-than-average number of ground balls.  

Because of that, the 1964 Mets’ expected Double Plays increase to 163, while the 1968 Tigers’ expected Double Plays drop to 121:

YEAR

City

Team

Lg

Runners on First Ratio

Team Assists Ratio

Exp DP-1

Actual Expected Double Plays

1960

Pittsburgh

Pirates

NL

0.947

1.054

141.23

141.02

1964

New York

Mets

NL

1.047

1.076

144.43

162.74

1968

Detroit

Tigers

AL

0.945

0.916

140.17

121.30

1972

Texas

Rangers

AL

1.138

0.970

146.71

161.99

1976

Cincinnati

Reds

NL

1.015

0.912

150.92

139.74

1980

Seattle

Mariners

AL

1.038

1.051

170.78

186.30

1984

Detroit

Tigers

AL

0.935

0.951

155.64

138.34

1988

Baltimore

Orioles

AL

1.056

1.045

153.03

168.79

1992

Toronto

Blue Jays

AL

0.934

0.925

157.43

135.90

1996

Detroit

Tigers

AL

1.188

1.052

162.86

203.48

2000

New York

Yankees

AL

0.960

0.904

162.21

140.82

2004

Arizona

Diamondbacks

NL

1.066

1.023

149.74

163.26

2008

Philadelphia

Phillies

NL

0.980

1.031

145.41

146.99

2012

Houston

Astros

NL

1.059

1.069

133.94

151.70

2016

Chicago

Cubs

NL

0.784

1.013

142.12

112.86

 

 

 

 

 
 

COMMENTS (4 Comments, most recent shown first)

bjames


Sometime when there is a break in the narrative (maybe after the pitchers are done?), will you please provide us with context where this is going?


I have already done that. Twice.
2:07 PM Jul 17th
 
CharlesSaeger
Why the sudden shift to using league averages when evaluating double plays?
8:36 AM Jul 16th
 
MWeddell
Sometime when there is a break in the narrative (maybe after the pitchers are done?), will you please provide us with context where this is going? Will this be the basis of a revamped Win Shaires (or Win Shares and Loss Shares) system? How far back in time can this system be extended (either due to data limitations or because conditions are differ too radically)? Are there plans to make the new calculations available to either subscribers or the general public? Or is the scope of this project much more limited than I've indicated above?

Right now, it is difficult to use Win Shares because the only version that is readily available is on BaseballGauge.com, and you've written that it is not accurate.

No need to reply here in the comments. My questions are too broad for this format.
8:06 AM Jul 16th
 
MarisFan61
Thanks especially for the caveat about it not necessarily all the way being clear to the reader.
(Really!)
As long as we (or at least I) know it's not your intent to make it easily clear, I won't look for it to be, and will know that we're not supposed to do more than glide through it and try to follow in a general way where you're going.
Actually I do find this article pretty easy reading, albeit without paying much attention to the formulas per se, because of your caveat.
4:27 AM Jul 16th
 
 
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