Saturday, August 1, 2015

Billy Pierce vs. Bob Gibson: The Only Pitchers With Five Straight Game Scores Of 80+

Since 1914. The Game Score (GS) is a stat created by Bill James to measure how good a pitcher was in a start. It takes into account IP, H, R, ER, BB and SO. Click here to read the definition from Baseball Reference. All stats used here are from BR.

This table summarizes how well each pitcher did. Gibson (1968) had 5 CGs (9 IP each). Pierce (1957) had 3 of those plus 2 games of 10IP (and by my calculation, he had a game score of at least 80 after 9IP in each one-80 in the 84 game and 89 in the 95 game).

On June 4, Pierce beat the Red Sox 1-0 in 10 innings. Ted Williams entered the game batting .407 but he went 0 for 4. Links to the game logs of each pitcher are after the table.

Stat
Pierce
Gibson
IP
47
45
AVG GS
86
82.6
ERA
0.19
0.40
W
5
0
L
5
0
H
16
26
R
2
2
ER
1
2
BB
10
6
SO
33
44
HR
0
0
Lg. AVG GS
51.76
56.85
Avg OPS+ of Teams Faced
96.2
85.8
 
For some reason, the league average OPS+ in each year/league is 93 (I think they compare each team's OPS based on all batters including pitchers to the league with the pitchers taken out). I added up the OPS+ (which is adjusted for the league average and park effects) of the teams Pierce and Gibson faced (each faced one team twice in the streak, Pierce the Indians and Gibson the Mets).

Pierce game logs

Gibson game logs

Friday, July 31, 2015

Are Balanced Teams More Successful?


This was published in SABR's Baseball Research Journal several years ago.

(This article benefited from comments made by David Gassko. Any mistakes or defects are due entirely to me, of course)

If a team scores 10% more runs than average and allows 10% fewer runs than average, they could be said to be perfectly balanced. Do such teams win more games than teams that are less balanced? For example, if another team scored 15% more runs than average and allowed 5% fewer runs than average, they would obviously be less balanced than the first team. Does the first team win more games due to greater balance, even though they seem to have about the same level of performance as the first team?

To measure a team’s offensive performance, I divided their runs scored per game by the league average. Then that was park adjusted using the park factors from the Sean Lahman database. The 1980 Orioles, for example, scored 4.97 runs per game. That divided by the league average of 4.51 leaves 1.10. But their park factor was 99, meaning that 1% fewer runs were scored in their park than average. So the 1.10 was divided by .99 to get 1.114, which is then multiplied by 100 to get 111.4, meaning the Orioles were 11.4% better than average in scoring. I performed similar calculations for runs allowed. In that case, the Orioles got 111.77, meaning they gave up 11.77% fewer runs than average (I’m following the convention that Pete Palmer uses, so above 100 means the team was better than average at preventing runs). Let’s call the runs scored measure “OFF” for offense and the runs allowed measure “DEF” for defense

To measure balance, I found the difference between their OFF and DEF and then found the absolute value. Let’s call this result “BAL” for balance. So the closer OFF and DEF are to each other, the more balanced the team is. The Orioles had a BAL of .374 (slightly different than the numbers above would imply due to rounding). Is this balance factor important or relevant? To test this, I first ran a regression in which team winning percentage was the dependent variable and OFF and DEF were the dependent variables. The equation was:

(1) Pct = -.476 + .49*OFF + .482*DEF

(I divided both OFF and DEF by 100 for the regression so, for example, instead of using 110 for BAL, I used 1.10). The coefficient on DEF is not negative for reasons explained in above. The standard error for 162 games was about 4 wins. I looked at all teams from 1980-2004.

Then I ran the regression with the balance variable added in. Here are the results:

(2) Pct = -.476 + .486*OFF + .488*DEF - .032*BAL

The standard error was still just about 4 wins for 162 games. It did fall by about .02 wins. So adding in a balance factor does not explain winning much better. The BAL variable was statistically significant with a T-value of -2.6. It has the right sign needed if balance is to help winning. As BAL gets larger (teams get less balanced), they win less. But notice that its impact is only about 1/16 of OFF and DEF. Adding BAL also had very little impact on the equation itself, which you can see by comparing equation (2) to equation (1).

It is also helpful to look at how much a one standard deviation increase in any of the variables would change a team’s winning percentage. Standard deviation (SD) is a measure of dispersion or how spread of the numbers. The SD of OFF was 9.51. If we multiply that by .486 we get 4.62. Since I divided both OFF and DEF by 100 for the regression, we have to divide 4.62 by 100, which leaves .0462. Over a 162 games, that is about 7.5 more wins. The SD of DEF was 9.07. That multiplied by .488 leaves 4.43. Over a full season, that is 7.17 more wins. For BAL, the SD was 8.11. Using the -.032 coefficient, over 162 games we get about .42 more wins. So if you made a significant improvement in how balanced your team is you add less than 1 win a season.

I also looked to see if teams that exceeded their “Pythagorean” winning percentage were more balanced than other teams. The “Pythagorean” winning percentage was invented by Bill James and it says that a team should have a winning percentage equal to runs scored squared divided by (runs scored squared + runs squared allowed). The correlation between the BAL variable and how much teams exceeded their “Pythagorean” winning percentage was .0025, meaning that there is no connection. Being more balanced did not increase a team’s number of expected wins.

How did the most balanced teams do? The table below shows the teams with the lowest 25 BAL scores.

                       
Table 1: The Most Balanced Teams










Rank
Team
Year
OFF
DEF
BAL
PCT
1
NYN
1999
110.08
110.13
0.047
0.595
2
KCA
1983
95.23
95.28
0.049
0.488
3
NYA
1997
112.67
112.62
0.050
0.593
4
SDN
1980
95.6
95.53
0.068
0.451
5
PHI
1997
89.58
89.66
0.085
0.420
6
BOS
1995
106.4
106.51
0.103
0.597
7
CHN
1987
95.21
95.32
0.113
0.472
8
TBA
2004
92.17
92
0.173
0.435
9
ATL
1985
90.49
90.27
0.224
0.407
10
TBA
1999
92.07
91.84
0.226
0.426
11
MON
1983
102.25
102.5
0.251
0.506
12
CLE
2003
95.46
95.13
0.329
0.420
13
CHN
1990
94.68
95.03
0.353
0.475
14
BAL
1980
111.4
111.77
0.374
0.617
15
NYN
1982
92.89
92.51
0.375
0.401
16
COL
1997
100.63
101.02
0.387
0.512
17
NYN
1994
97.87
98.29
0.415
0.487
18
MON
2002
100.96
101.4
0.438
0.512
19
PIT
1981
98.09
97.63
0.464
0.451
20
CAL
1996
89.65
90.14
0.486
0.435
21
PHI
1990
94.85
94.36
0.488
0.475
22
MIL
1998
94.02
93.53
0.490
0.457
23
BOS
1986
107.05
106.56
0.491
0.590
24
NYA
1982
99.76
99.26
0.502
0.488
25
CAL
1986
106.39
106.92
0.539
0.568


Their average winning percentage is .491. So they did not win any more games than normal. The next table shows the 25 least balanced teams. Their average winning percentage was .497.


                        Table 2: The Least Balanced Teams


Rank
Team
Year
OFF
DEF
BAL
PCT
1
KCA
1987
88.32
117.16
28.845
0.512
2
DET
1993
119.10
90.18
28.924
0.525
3
TEX
1991
116.43
87.47
28.952
0.525
4
SEA
1983
73.87
103.06
29.194
0.370
5
HOU
1995
120.43
91.04
29.387
0.528
6
TEX
1983
89.22
118.80
29.585
0.475
7
TOR
1991
90.52
120.32
29.797
0.562
8
ATL
1995
94.81
124.75
29.940
0.625
9
KCA
1993
85.13
115.35
30.225
0.519
10
SLN
2003
122.14
91.04
31.096
0.525
11
CIN
2004
108.46
77.07
31.390
0.469
12
TOR
1982
82.36
113.80
31.441
0.481
13
TOR
1996
82.80
114.35
31.543
0.457
14
TEX
2001
113.04
81.34
31.702
0.451
15
BOS
1992
79.96
111.98
32.024
0.451
16
ANA
2001
82.02
114.33
32.304
0.463
17
ARI
2003
86.46
118.88
32.422
0.519
18
SFN
1999
120.86
87.80
33.068
0.531
19
BOS
1993
83.31
117.97
34.658
0.494
20
TOR
1997
81.06
116.25
35.188
0.469
21
ML4
1982
129.90
94.64
35.259
0.586
22
SDN
1997
114.63
77.00
37.635
0.469
23
TBA
1998
73.44
113.49
40.053
0.389
24
MON
2003
80.65
121.04
40.389
0.512
25
LAN
2003
82.61
126.31
43.696
0.525


The next table shows the top 25 teams in winning percentage from 1980-2004. Their average BAL score was 11.737, while the average for all teams was 10.138. So the best teams are just a little less balanced than normal (remember that zero is perfect balance).

                                    Table 3: The Best Teams


Rank
Team
Year
OFF
DEF
BAL
PCT
1
SEA
2001
126.60
118.04
8.561
0.716
2
NYA
1998
121.31
118.79
2.513
0.704
3
CLE
1995
115.25
117.67
2.416
0.694
4
NYN
1986
119.28
111.23
8.059
0.667
5
ATL
1998
108.76
128.15
19.385
0.654
6
MON
1994
109.94
116.04
6.104
0.649
7
SLN
2004
117.27
110.64
6.635
0.648
8
DET
1984
116.93
109.15
7.785
0.642
9
OAK
1988
116.84
108.16
8.674
0.642
10
ATL
1993
103.40
130.09
26.689
0.642
11
NYA
2002
118.18
108.89
9.289
0.640
12
NYA
1980
114.63
106.95
7.677
0.636
13
OAK
1990
109.59
116.13
6.540
0.636
14
SFN
1993
115.74
109.77
5.971
0.636
15
ATL
1999
110.23
116.51
6.273
0.636
16
OAK
2002
98.71
123.92
25.215
0.636
17
ATL
2002
98.83
126.79
27.959
0.631
18
HOU
1998
119.78
115.28
4.498
0.630
19
OAK
2001
116.95
118.41
1.452
0.630
20
NYN
1988
119.16
108.57
10.590
0.625
21
ATL
1995
94.81
124.75
29.940
0.625
22
SLN
1985
114.52
112.88
1.637
0.623
23
ATL
1997
103.99
128.35
24.357
0.623
24
NYA
2003
115.31
107.33
7.988
0.623
25
ATL
2003
125.16
97.93
27.225
0.623

A couple of teams are interesting here. One is the 2002-3 Braves. In 2002, they rank #17 having an OFF of just 98.83 and a DEF of 126.79. So they had great pitching and about average hitting. But the next year, 2003, ranked #25, they were very unbalanced, but in the opposite direction. They had great hitting (an OFF of 125.16) and just so-so pitching (a DEF of 97.93). The other is the 2001-02 A’s. In 2001, they were very balanced, with a BAL of 1.452. Their winning percentage was .630. The next year, they became very imbalanced when BAL rose to 25.215. But they actually saw a slight rise in their winning percentage, to .636. So for the A’s, going from being very balanced to being very imbalanced did not hurt their record.

The next table shows the lowest 25 teams in winning percentage. Their average BAL was 10.165. So the worst teams are just about as balanced as anyone else. Lack of balance is not why they lost so much.

                                    Table 4: The Worst Teams

Rank
Team
Year
OFF
DEF
BAL
PCT
1
CIN
1982
80.68
103.19
22.513
0.377
2
CLE
1987
92.56
84.60
7.962
0.377
3
SDN
1993
90.65
97.02
6.374
0.377
4
MIN
1981
78.82
99.60
20.776
0.376
5
SDN
1981
95.48
87.93
7.544
0.373
6
MIN
1982
87.96
92.09
4.132
0.370
7
SEA
1983
73.87
103.06
29.194
0.370
8
CLE
1985
99.75
85.74
14.006
0.370
9
CHN
1981
85.82
90.98
5.164
0.369
10
SEA
1980
82.23
94.47
12.234
0.364
11
DET
1989
90.49
83.56
6.930
0.364
12
NYN
1993
96.26
94.81
1.447
0.364
13
KCA
2004
93.35
86.13
7.219
0.358
14
PIT
1985
87.62
92.49
4.867
0.354
15
CLE
1991
78.49
96.68
18.193
0.352
16
TOR
1981
71.86
100.10
28.231
0.349
17
MIL
2002
90.61
85.16
5.445
0.346
18
DET
2002
79.83
84.26
4.429
0.342
19
TBA
2002
86.90
84.37
2.531
0.342
20
ATL
1988
85.11
89.68
4.567
0.338
21
BAL
1988
80.82
87.14
6.313
0.335
22
FLO
1998
93.32
78.25
15.071
0.333
23
DET
1996
90.63
79.91
10.714
0.327
24
ARI
2004
79.44
86.12
6.678
0.315
25
DET
2003
79.01
80.60
1.591
0.265

The interesting team here is the 1981-82 Twins. In 1981, their BAL was 20.776. So they were unbalanced and they had a winning percentage of just .376. The next year, their BAL fell to 4.132, meaning they became more balanced. Yet their winning percentage also fell to .370.

The most balanced team was the 1999 Mets. They boasted very good hitting and pitching, with their OFF and DEF both being just about 110. This lead to an excellent .595 winning percentage, a wild card birth in the playoffs, and a tough loss to the Braves in the NLCS (equation (1) predicts that they would have a .594 winning percentage). They boasted a star-studded lineup. The table below shows how the Met regulars hit:

Table 5: 1999 Mets Hitting












Player
AB
HR
RBI
AVG
SLG
OBP
OPS
SB
Edgardo Alfonzo
628
27
108
0.304
0.502
0.385
0.886
9
John Olerud
581
19
96
0.298
0.463
0.427
0.890
3
Robin Ventura
588
32
120
0.301
0.529
0.379
0.908
1
Mike Piazza
534
40
124
0.303
0.575
0.361
0.936
2
Rey Ordonez
520
1
60
0.258
0.317
0.319
0.636
8
R. Henderson
438
12
42
0.315
0.466
0.423
0.889
37
Roger Cedeno
453
4
36
0.313
0.408
0.396
0.804
66
Brian McRae
298
8
36
0.221
0.349
0.320
0.669
2
Benny Agbayani
276
14
42
0.286
0.525
0.363
0.888
6


The Mets were a solid fifth in runs scored, averaging 5.23 runs per game.

The table below shows how the performance of the key Met pitchers:


Table 6: 1999 Mets Pitching

















Pitcher
W
L
SV
IP
BB
SO
ERA
Al Leiter
13
12
0
213
93
162
4.23
Orel Hershiser
13
12
0
179
77
89
4.58
Masato Yoshii
12
8
0
174
58
105
4.40
Rick Reed
11
5
0
149
47
104
4.59
Octavio Dotel
8
3
0
85.1
49
85
5.39
Turk Wendell
5
4
3
85.1
37
77
3.07
Armando Benitez
4
3
22
78
41
128
1.85
Kenny Rogers
5
1
0
76
28
58
4.03
Pat Mahomes
8
0
0
63.1
37
51
3.71
Dennis Cook
10
5
3
63
27
68
3.86
Bobby Jones
3
3
0
59
11
31
5.64
John Franco
0
2
19
40.1
19
41
2.92

The Mets were fifth in ERA in the NL at 4.28. The pitching staff was helped by Gold Glove winners Ventura at 3B and Rey Ordonez at SS. Two other players won at least 1 Gold Glove in their careers, but not 1999, Rickey Henderson and John Olerud. The Mets also only made 68 errors that year, by far the lowest in the league, and also a record at that time. Every other team made at least 100.

The least balanced team was the 1987 Royals. They had a fairly weak hitting attack, with an OFF of just 88.32. The next table shows the Royals key hitters:

Table 7: 1987    Royals Hitting

Player
AB
HR
RBI
AVG
SLG
OBA
OPS
SB
Kevin Seitzer
641
15
83
0.323
0.470
0.399
0.869
12
Danny Tartabull
582
34
101
0.309
0.541
0.390
0.931
9
Willie Wilson
610
4
30
0.279
0.377
0.320
0.698
59
Frank White
563
17
78
0.245
0.400
0.308
0.708
1
George Brett
427
22
78
0.290
0.496
0.388
0.884
6
Bo Jackson
396
22
53
0.235
0.455
0.296
0.750
10
Steve Balboni
386
24
60
0.207
0.427
0.273
0.700
0
Jamie Quirk
296
5
33
0.236
0.345
0.307
0.652
1
Angel Salazar
317
2
21
0.205
0.246
0.219
0.465
4

Seitzer, Tartabull and Brett all had good years, but the rest of the hitters did not. The Royals were last in runs scored, averaging 4.41 runs per game (and tied for next-to-last in OPS). Their park factor was 106 that year, meaning it was slightly a better than average run environment. Now for the pitchers:


Table 8: 1987 Royals Pitching


Pitcher
W
L
SV
IP
BB
SO
ERA
Bret Saberhagen
18
10
0
257
53
163
3.36
Mark Gubicza
13
18
0
241.2
120
166
3.99
Charlie Leibrandt
16
11
0
240.1
74
151
3.41
Danny Jackson
9
18
0
224
109
152
4.02
Bud Black
8
6
1
122.1
35
61
3.61
Steve Farr
4
3
1
91
44
88
4.15
Jerry Don Gleaton
4
4
5
50.2
28
44
4.30
Dan Quisenberry
4
1
8
49
10
17
2.76
John Davis
5
2
2
43.2
26
24
2.29
Bob Stoddard
1
3
1
40
22
23
4.28
Dave Gumpert
0
0
0
19.1
6
13
6.13
Gene Garber
0
0
8
14.1
1
3
2.55


Saberhagen, the leader of the staff, was a two-time Cy Young award winner. The Royals were second in the league in ERA at 3.87, only .13 behind the league leading Toronto Blue Jays (a little impressive since their park was favorable to hitters). Frank White (2B) won the last of his eight Gold Gloves. Willie Wilson had one career Gold Glove, but not in 1987.

(This is an expanded version of an article that originally appeared at the “Beyond the Boxscore” website)

Cyril Morong, a member of SABR since 1995, teaches economics at San Antonio College and is lifelong White Sox fan

Source:
The San Lahman database
Retrosheet
Lee Sinin’s Complete Baseball Encyclopedia
Baseball Reference