Wednesday, March 25, 2026

The Problem With “Total Clutch” Hitting Statistics, Part 1

This is the follow up to yesterday's post on clutch hitting that I mentioned. It is also from articles I posted about 20 years ago. I will probably do a Part 2 very soon.

Introduction 

A recent article (late 2003) appeared in BusinessWeek magazine called “Ball Park Figures You Can Bet On” which described a “new statistic” developed by Benjamin Polak and Brian Lonergan of Yale University which measures “wins contributed” by major league hitters. (another article on their work appeared in Nov. 2004 in the NY Times-see sources below) From the online version: 

“Here's how their method works: Let's say the home team is down by two runs in the bottom of the fifth inning, with no outs and a runner on second base. At that moment, the home team has a 39% chance (or 0.39 probability) that it will win. If the batter grounds out, and the runner at second fails to advance, the team's chance of winning falls to 33%. The difference between the two, -0.06, is assigned to the batter who just grounded out.” 

Now they add this up for the whole season, every plate appearance and get wins contributed for each player (see link in sources). 

The problem with this approach is that it is not new and that it really tells us nothing about what a ball player is worth since in the long run this “total clutch” stat is highly correlated with normal hitting statistics, as I will demonstrate(my critique is not new-See the book "The Hidden Game of Baseball" by John Thorn and Pete Palmer. They discuss what Dick Cramer had to say about the Mills brothers)  By “total clutch” stat, I mean one that takes into account every plate appearance and each one is weighted by its importance according to the score and inning.  Hits when the game is late and close will count for more than hits when the game is early and the score is lopsided. 

History 

This is definitely not a new stat.  It goes back at least as far as 1970 when Eldon G. and Harlan D. Mills published their book Player Win Averages.  Polak and Lonergan’s “wins contributed” stat is similar. So is the “Player Game Percentage” in the book Curve Ball by Jim Albert and Jay Bennett.  So is the “Game State Victories (or Wins) found at the Rhoids Sports Analysis website (see sources).  So is “player's win value” by Ed Oswalt (his link is also in sources).  So what Lonergan and Polak have done is definitely not new. 

Analysis

Let’s start with the Ed Oswalt’s measure “player’s win value” (or PWV) since he uses thirty years of data, covering the years 1972-2002. The best hitters on his list will not surprise you and his stat divided by plate appearances (or PA) is highly correlated with stats like on-base percentage (OBP) and slugging percentage (SLG) as well as OPS (OBP + SLG). 

First, I looked at the top 100 players in plate appearances from 1972-2002.  I then correlated relative OPS (relative to the league average for each player) with Oswalt’s PWV/PA.  The correlation was 0.948.  This is very close to a one-to-one relationship.  If you square this (called r-squared), you get 0.898, meaning that 89.8% of the variation across hitters in PWV/PA is explained by relative OPS.  This is important because it shows that a very simple, non-clutch, non-situational, non-context stat like OPS pretty much explains a much more complex context dependent stat that is supposed to tell us the value of hitters. 

The linear regression equation is PWV/PA = .00022*OPS - 022 

In the figure below, you can see the relationship where PWV/PA is a function of relative OPS.

 

In the table below, you can see each player’s PWV/PA and his relative OPS.  Bonds, for example has 137, which means his OPS was 37% higher than the league average for the 1972-2002 period.  The top ten or twenty hitters will not surprise you.

Rank

Player

PWV/PA

Relative OPS

1

Barry Bonds

0.008

137

2

Mark McGwire

0.0068

131

3

Jeff Bagwell

0.006

127

5

Mike Schmidt

0.0049

126

6

Ken Griffey Jr.

0.0048

124

7

George Brett

0.0045

119

13

Fred McGriff

0.004

119

14

Rafael Palmeiro

0.0039

119

4

Will Clark

0.005

118

8

Rod Carew

0.0045

118

10

Jack Clark

0.0041

118

11

Reggie Jackson

0.004

118

26

Jim Rice

0.0032

118

49

Sammy Sosa

0.0023

118

19

Dwight Evans

0.0037

117

23

Fred Lynn

0.0035

117

32

Ellis Burks

0.003

117

12

John Olerud

0.004

116

20

Wade Boggs

0.0036

116

9

Tony Gwynn

0.0042

115

25

Jose Canseco

0.0033

115

55

Bobby Bonilla

0.002

115

15

Kirby Puckett

0.0038

114

17

Rickey Henderson

0.0038

114

18

Eddie Murray

0.0037

114

36

Dave Winfield

0.0027

114

42

Dale Murphy

0.0024

114

30

Don Mattingly

0.003

113

33

Andres Galarraga

0.0029

113

27

Dave Parker

0.0031

112

43

Al Oliver

0.0024

112

53

Bobby Grich

0.0021

112

16

Mark Grace

0.0038

111

21

Ken Singleton

0.0036

111

28

Harold Baines

0.0031

111

34

Tim Raines

0.0028

111

37

Cecil Cooper

0.0026

111

50

Wally Joyner

0.0023

111

51

Paul O'Neill

0.0022

111

56

Ron Cey

0.0019

111

58

Carlton Fisk

0.0019

111

61

Andre Dawson

0.0018

111

22

Keith Hernandez

0.0036

110

24

Darrell Evans

0.0033

110

39

Paul Molitor

0.0025

110

41

Ted Simmons

0.0025

110

44

Roberto Alomar

0.0024

110

45

Brian Downing

0.0024

110

47

Craig Biggio

0.0023

110

52

Barry Larkin

0.0022

110

59

Ryne Sandberg

0.0019

110

72

Chet Lemon

0.0009

110

29

Ken Griffey Sr.

0.0031

109

48

Dusty Baker

0.0023

109

54

Steve Garvey

0.002

109

31

Toby Harrah

0.003

108

35

Lou Whitaker

0.0027

108

40

Gary Matthews

0.0025

108

62

Chili Davis

0.0018

108

69

George Hendrick

0.0012

108

71

Don Baylor

0.0011

108

38

Pete Rose

0.0026

107

46

Jose Cruz

0.0024

107

60

Robin Ventura

0.0018

107

65

Robin Yount

0.0014

107

73

Gary Carter

0.0008

107

66

Cal Ripken

0.0014

106

67

Julio Franco

0.0013

106

63

Alan Trammell

0.0016

105

64

Chris Chambliss

0.0014

105

68

Graig Nettles

0.0013

105

70

Brett Butler

0.0011

104

74

Brady Anderson

0.0008

104

76

Ruben Sierra

0.0007

104

77

Carney Lansford

0.0007

104

78

Buddy Bell

0.0004

104

79

Joe Carter

0.0004

104

82

Todd Zeile

0.0003

103

85

Steve Finley

0

103

93

Lance Parrish

-0.0009

103

84

Jay Bell

0.0001

102

57

Tony Phillips

0.0019

101

75

Bill Buckner

0.0007

101

81

Tony Fernandez

0.0004

101

88

Tim Wallach

-0.0005

101

80

Willie Randolph

0.0004

100

86

Willie McGee

0

100

87

Gary Gaetti

-0.0003

100

83

B.J. Surhoff

0.0001

99

91

Devon White

-0.0007

99

89

Terry Pendleton

-0.0005

97

90

Dave Concepcion

-0.0006

96

92

Steve Sax

-0.0009

96

95

Willie Wilson

-0.0013

96

97

Garry Templeton

-0.0016

93

98

Frank White

-0.0018

93

94

Omar Vizquel

-0.0012

92

96

Ozzie Smith

-0.0015

92

99

Bob Boone

-0.0025

91

100

Larry Bowa

-0.0035

87

Sources

These are the sources that I listed 20 years ago. Some links might no longer work. 

"Ballpark Figures to Bet On," Nov. 21, UPFRONT section BusinessWeek magazine. Author was Brian Hindo. 

“What's a Ball Player Worth?” can be found at:

http://www.businessweek.com/print/bwdaily/dnflash/nov2003/nf2003115_2313_db016.htm?db 

Player Win Averages by Eldon G. and Harlan D. Mills.  1970. A.S. Barnes, publisher. 

Curve Ball: Baseball, Statistics, and the Role of Chance in the Game by Jim Albert and Jay Bennett. Revised 2003. Copernicus Books.

Rhoids Sports Analysis: http://www.rhoids.com/ 

Ed Oswalt’s site is at: http://www.livewild.org/bb/playervalues/index.html

The Nov. 7, 2004 NY Times article is at 

http://query.nytimes.com/gst/abstract.html?res=F30A1EFA39580C748CDDA80994DC404482 

But you will probably have to pay to read all of it. 

Other sites where you might find it are

http://www.iht.com/articles/2004/11/07/sports/base.html  http://redsox.mostvaluablenetwork.com/wp-content/sites/schwarzWRAP.html

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