Declines in Major League Batting Performance as a Function of Game Pressure: A Drive Theory Analysis

Declines in Major League Batting Performance as a Function of Game Pressure: A Drive Theory Analysis’

MARK H. DAVIS’ AND JONATHAN c. HARVEY Eekerd College

Zajonc’s (1965) drive theory explanation argues that greater arousal tends to impair performance on difficult tasks. The hypothesis that arousal generated by “pressure situations”during major league baseball games would hinder batting performance-a difficult task-was tested by examining such performance during the 1989 season. Six “pressure situations” were identified, some occurring during the late innings of close games and others occurring throughout the game when there were two outs. Two measures of batting performance (batting average and slugging average) were employed. Results indicated broad support for the hypothesis. Reasons for this pattern are discussed, as are possible alternative explanations for these findings.

One of the most influential approaches to the study of arousal effects on task performance has been Zajonc’s (1965) drive theory explanation. Utilizing Hull-Spence learning theory, Zajonc’s formulation argues that performance is a product of habit strength (H), or the behavioral tendency built up through reinforced practice, and thecurrent level ofgeneralizeddrive (D), which is the equivalent of the individual’s level of motivation. The differences in habit strength among competing potential responses to the same stimulus (Bond & Titus, 1983) are multiplied by the generalized drive, so that a dominant response in a given situation becomes even more dominant under conditions of greater arousal. According to this view, then, if the task to be performed is simple or well learned, heightened arousal will lead to improved performance. If the task is complex or not well learned, performance will generally be impaired.

Considerable support has been found for Zajonc’s general claims regarding the effect of arousal on tasks of varying complexity (e.g., Baron, Moore, & Sanders, 1978; Cottrell, Rittle, & Wack, 1967; Zajonc & Sales, 1966; see Bond & Titus, 1983, for a review). Although largely convincing, much of that research has involved laboratory settings, with the associated risks of reac- tivity and artificiality. To help provide further external validity, Jackson,

‘The authors would like to thank Linda A. Kraus and two anonymous reviewers for their useful

*Correspondence concerning this article should be addressed to Mark H. Davis, Behavioral comments on an earlier version of this manuscript.

Sciences, Eckerd College, St. Petersburg, FL 33733.

71 4

Journal of Applied Social Psychology, 1992,22, 9, pp. 714-735. Copyright @ 1992 by V. H. Winston I% Son, Inc. All rights reserved.

BATTING PERFORMANCE AND GAME PRESSURE 715

Buglione, and Glenwick (1988) recently carried out an interesting investigation of a meaningful task in a nonreactive setting: major league batting performance under conditions of high and low assumed drive. Specifically, that investigation examined batting performance under different motiva- tional or drive conditions that are associated with a player being traded from one team to another in midseason. Jackson et al. (1988) assumed that prior to being traded, a player’s chronic level of arousal would tend to increase. This would occur because players generally desire not to be traded, and feel increased pressure-as the trade rumors swirl-to perform better and avoid that fate. It was further assumed that arousal would decline following the trade for a variety of reasons, among them the fact that the player’s future with the team was at least temporarily assured, and performance expectations on the new team would typically be lower.

Analyses of the performances of 59 major league baseball players traded during a season revealed a pattern of statistically significant performance changes in directions consistent with these predictions. Specifically, batting performance prior to the trade declined significantly relative to a 3-year “baseline” period preceding the trade year. Jackson et al. (1988) argued that the arousal generated prior to being traded served to decrease batting performance. This argument follows from the fact that successful batting performance is quite obviously a difficult task-that is, high failure rates are universal. No full-time professional player has ever had a seasonal batting average of S O O , and relatively few had averages above .300. Thus, getting a hit in major league baseball is always a nondominant response; according to drive theory, situations which increase arousal should lower the likelihood of getting a hit.

The Jackson et al. (1988) investigation examined overall batting performance over time periods of months and years, and assumed that chronic arousal levels were higher during some of these periods. While this approach has merit, it also seems likely that arousal fluctuates more quickly as well, with particularly important games or situations within games producing especially high levels of arousal. In the present investigation we attempted to study the effects of arousal on batting performance by examining batting success during specific game situations likely to produce varying levels of arousal. Thus, our focus is on the degree to which batting performance will change from nonpressure situations to pressure situations.

f i e Nature of Pressure Situations

Two general classes of conditions seem likely to produce heightened pressure on the batter and thus produce greater arousal. The first condition, Lute Inning Pressure, consists of batting opportunities occurring late in close games. Such occasions create arousal since successful performance is essential

716 DAVIS A N D HARVEY

for team success and few scoring opportunities remain; as a result, batters should feel heightened responsibility, evaluation, and arousal. The second pressure condition, Two Out Pressure, occurs when the batter faces a situation, a t any point in the game, with runners on the bases and two outs. This condition should likewise create arousal, for the responsibility of scoring the runners lies solely with the batter. With fewer than two outs, later batters will have an opportunity to produce runs, even if the current batter fails. With two outs, however, failure means that the opportunity to score the runner(s) is gone. It is our belief that batting performance will generally decline under both types of pressure situations. A readily available reference work, l?te 1990 Elias Baseball Analyst (Siwoff, Hirdt, Hirdt, & Hirdt, 1990) provides information regarding season performances in all of these game situations.

There is an important difference, however, between the performances under conditions of high arousal examined in the present investigation and those investigated by Jackson et al. (1988). Because the putative cause of the increased arousal in the present study is a particular situation within the game-rather than a chronically higher drive state existing in the to-be-traded player-this situational pressure can reasonably be expected to raise the drive level of thepitcher as well as the batter. A natural question becomes: Will this increase in pitcher arousal produce a decline in pitching performance off- setting the expected decrement in batting? Based on the logic of drive theory, the answer to this question seems to be “No.”

The reason for this lies in the complete interdependence of pitching and batting outcomes. In each individual at bat (AB) the outcomes of the pitcher and batter are mirror images: Batter success (a hit) equals pitcher failure, and batter failure (making an out) equals pitcher success. Thus, any AB consti- tutes a system largely made up of two completely dependent tasks.3 One task-hitting-is quite difficult, with an average success rate of less than 30%; the other task-pitching-is by definition then an easy one, with an average success rate of over 70%. Increased drive will, according to the theory, tend to improve performance on the easier task as well as hurt performance on the difficult one. The vast preponderance of the evidence supporting these predictions has come from laboratory investigations in which the ease or difficulty of different tasks were independently manipulated (e.g., Cottrell et al., 1967). In the present investigation-conducted within a “messier” real world environment-it is impossible to disentangle pitching performance improvements

’A third component-fielding-also enters into the outcome of each AB. If a fielder commits an error on a ball hit to him, the batter does not receive credit for a hit, and the pitcher does not have a hit charged against him. However, given the very high levels of fielding proficiency in modern baseball (major league fielding percentages routinely fall between .950 and 1.000), the interplay between pitcher and batter still determines in large part the outcome of any particular AB.


from batting performance declines. However, from the point of view of drive theory’s predictions, it shouldn’t much matter; both effects are predicted to occur, and both will have the effect of diminishing batter success.

What this suggests is that when measures of batting performance are examined, they should be interpreted as reflecting an overall outcome- labelled, for convenience, “batting performance”-which in reality is deter- mined by both pitchers and batters. The term “batting performance” is therefore a kind of shorthand for the interactive process which pits pitchers against batters. A significant decline in “batting performance”cou1d therefore just as accurately be described as an improvement in “pitching performance.” In all probability, of course, decreased batter success usually results from both processes-an improvement in pitching coupled with a decline in batting.

Choking Under Pressure

Drive theory is not the only theoretical approach used to explain decrements in performance under pressure conditions. Another tack has been taken by Baumeister (Baumeister, 1984; Baumeister & Steinhilber, 1984), and can be briefly summarized as follows. Performance on a skilled task will tend to decline if the individual becomes self-aware; this heightened self-attention can hinder performance because it distracts one from task-relevant information and/or because it disrupts automatic response sequences. One chief cause of this increased self-awareness is said to be a heightened concern for self- presentation which arises when one has the opportunity to claim a desired self-image before a supportive audience. That is, based on Schlenker’s ( 1980, 1982) theorizing regarding the situations in which self-presentational con- cerns are strongest, Baumeister argues that very important performances in front of supportive audiences will be significantly impaired by the self-focused attention created in that situation. This general phenomenon has come to be called “choking under pressure.” In a well-known investigation, Baumeister and Steinhilber (1984) indeed found that performances in the deciding games of both professional basketball and baseball championship series were diminished when teams played at home before their supportive audiences.

At first blush this approach seems quite relevant to the present study. Might not batting performance (or pitching performance) suffer in pressure situations for similar self-presentational reasons? Upon reflection, two factors combine to make this seem unlikely. First, the importance of the self-image to be claimed in this investigation is, relatively speaking, not high. Baumeister and Steinhilber (1984) found significant performance decrements among home teams only in the final games of championship series, situations in which the powerful self-image of “world champion” could be claimed. It is difficult to imagine a more potent self-presentational opportunity. The per-

718 DAVIS AND HARVEY

formances analyzed in this investigation come from the 162 regular season games of the 1989 season, ineach of which the identity to be claimed (“winner of the game”) was, to say the least, less important than “world champion.” Thus, it is not at all clear that the identity at stake is important enough to create the kind of effect that Baumeister and Steinhilber (1984) identified.

Much more importantly, however, the interdependent relationship between batting and pitching, and the use of within-game pressure situations, makes the self-presentation explanation difficult if not impossible to apply to these data. If a supportive audience is indeed required to produce the “choking” effect, then any pressure situations within a game will tend to make the batter self-aware about half of the time (during home games for the batting team) and will tend to make the pitcher self-aware the other half (during home games for the fielding team). Quite simply, the self-attention explanation will always predict a decrement in performance for either the pitcher or batter, and these effects will tend, over all the games in the season, to cancel each other In contrast, the drive theory explanation always predicts a decrement in performance for the batter and improved performance for the pitcher, regardless of whether the game is played in front of a supportive audience. Thus, when pressure batting performance is analyzed over the entire season without distinguishing between home and away games-as is the case with the Base- ball Analyst-the self-presentation explanation would seem to predict no differences between pressure and nonpressure performances, while the drive theory analysis would clearly predict batting decrements under pressure. Thus, findings of the predicted nature-if they emerge-would seem to be more satisfactorily explained by drive theory.

Method

Subjects

One set of analyses was based on the batting performances of all American and National League batters during the 1989 season. In addition, some analyses were based on the performance of the 300 major league baseball players who had at least 160 plate appearances during that season. The batting performances of pitchers were not included in these analyses.

Data Collection

The bulk of the pertinent information was extracted from The 1990 Elias Baseball Analyst (Siwoff et al., 1990). The statistics of interest were the

41f records regarding pressure performance were kept separately for home and away games, then it would be possible to examine the differing predictions of drive theory and the self- awareness explanation. Unfortunately, the Analyst does not provide such breakdowns.


player’s At Bats, Hits, Doubles, Triples, Home Runs, Batting Average, and Slugging Average; the Analyst presents each of these values not only for overall season totals, but also under nine specific game situations. Five of the nine situations can occur at any point throughout the entire nine-inning game: batting when leading off an inning, batting with runners on base, batting with runners in scoring position (i.e., on second and/ or third base), batting with runners on and two outs, and batting with runners in scoring position and two outs. As described earlier, we believe that batting with runners on and two outs, or with runners in scoring position and two outs, are both pressure situations regardless of the inning in which they occur. The remaining four conditions provided by Siwoff et al. (1990) are characterized by them as “late inning pressure situations.” Siwoff et al. define late inning pressure as all at bats occurring in the seventh inning or later with the score tied or the batter’s team trailing by one, two, or three runs, or by four runs with the bases loaded. The four late inning categories of batting performance are: total late inning pressure performance, late inning performance/ leading off, late inning performance/ runners on, and late inning performance/ runners in scoring position.

Performance Measures

We employed two measures of batting performance: batting average (BA) and slugging average (SA). Batting average is obtained by dividing the player’s total number of hits by the total number of at bats; slugging average is batting average weighted by the number of bases per hit, thus providing a measure of the player’s ability to hit with power.

The drive theory analysis specifies that performance on difficult tasks is hindered when drive is high rather than low; thus, we utilized the Siwoff et al. data to produce measures of “pure” nonpressure performance to compare with the measures of pressure performance they provide. The “pure”nonpressure performance measures which correspond to the four Lute Inning Pres- sure measures were created by subtracting performance during late inning pressure situations from the full nine-inning performance. For example, batting average in non-“late inning pressure” situations was calculated as the total number of hits minus the number of hits obtained under late-inning pressure, divided by the total number of at bats minus the number of at bats under late-inning pressure. Batting average in non-“late inning/ leadoff” situations was calculated as the total number of hits when leading off an inning minus the number of hits obtained when leading off under late inning pressure, divided by the total number of at bats when leading off an inning minus the number of at bats when leading off under late inning pressure. Similar calculations yielded non-“late inning pressure”measures corresponding to the other two late inning pressure measures (late inning/runners on and late


inning/ scoring position). In essence, this provides a measure of performance, in comparablegame situations (e.g., leading off; runners on), during non-“late inning pressure” situations.

In addition, we calculated “pure” measures of nonpressure performance corresponding to the Two Out Pressure performance measures. For example, the non-pressure measure which paralleled the “runners on/ two outs” measure was calculated by subtracting the number of hits with runners on and two outs from the total number of hits with runners on, and dividing by the total number of at bats with runners on minus the total number of at bats with runners on and two outs. In essence, this provides a measure of performance with runners on and less than two outs to compare with performance with runners on and two outs. Similar procedures were used to calculate nonpressure measures of SA.

Age and Experience

Information regarding each player’s date of birth and number of years in major league baseball was taken from Baseball Contest 1990: American League Players (Allison, 1990) and Baseball Contest 1990: National League Players (Shapiro, 1990).

Results

Team Analyses

Table 1 displays the 1989 batting and slugging averages under different game situations for all 26 major league teams. For each team, comparisons were made between (a) total late inning performance versus total non-late inning performance, (b) late inning/ leadoff performance versus non-late inning/ leadoff performance, (c) late-inning/ runners on performance versus non-late inning/ runners on performance, (d) late inning/ runners in scoring position performance versus non-late inning/ runners in scoring position performance, (e) performance with runners on and two outs versus performance with runners on and less than two outs, and (f) performance with runners in scoring position and two outs versus performance with runners in scoring position and less than two outs.

A drive theory analysis predicts that performance will tend to be lower under conditions of greater arousal. Regarding batting average, there were a total of 156 comparisons between arousal and nonarousal situations (26 teams X 6 comparisons); the expected decline in performance was apparent 80% of the time ( 1 25/ 156), which is significant @ < .05, one-tailed) by the sign test. The expected decline in performance was present 86% of the time (134/ 156) for slugging average (p < .05).

Tabl

e 1

Bat

ting

Perf

orm

ance

of th

e 26

Maj

or L

eagu

e Te

ams

Und

er C

ondi

tions

of

Low

and

Hig

h A

rous

al

Late

Inni

ng P

ress

ure

Tw

o O

ut P

ress

ure

Tota

l Sc

orin

g Sc

orin

g po

sitio

n po

sitio

n R

unne

rs o

n R

unne

rs o

n Le

ad o

ff

Late

Le

ss th

an

Tw

o Le

ss th

an

Two

inni

ng

two

outs

ou

ts

two

outs

ou

ts

m

late

La

te

Late

inni

ng

inni

ng

inni

ng

D

BA

.239

.2

14

.226

.2

18

.256

.2

57

,257

.2

50

.268

.2

42

,279

.2

33

0

SA

,361

,2

98

,349

.3

09

.380

.3

54

.372

.3

61

.386

.3

63

.391

.3

49

-u

Bal

timor

e n

BA

,254

,2

36

,251

.2

21

.266

.2

52

.262

.2

50

.274

.2

52

.271

.2

48

2 SA

.3

85

.337

.3

93

.243

,3

93

.388

.3

91

.369

.4

15

.363

.4

20

.352

B

osto

n z

BA

.279

.2

67

.282

.2

60

.285

,2

84

.28 1

.2

76

.303

.2

59

.3 15

.2

40

$ .4

05

.389

.4

27

.375

.4

10

.42 1

.4

00

.425

.4

33

.382

.4

45

.355

D

z SA

C

alifo

rnia

0

BA

.2

59

.242

.2

7 1

,256

.2

71

.239

.2

63

.246

.2

91

.254

.2

67

.253

G)

SA

.394

.3

36

.420

.4

15

.398

.2

81

.389

.2

82

.392

.3

70

.369

.3

77

BA

.275

.2

53

.281

.2

48

.284

.2

71

.283

.2

29

.302

.2

55

.3 1 1

.2

32

n

BA

.263

,2

48

.275

.2

40

.269

.2

59

.262

.2

56

.275

.2

58

.270

.2

52

n SA

.3

94

.344

.4

22

.370

.3

95

.336

.3

70

.328

.3

94

.380

.3

79

.350

cont

inue

d 2

late

in

ning

la

te

Late

in

ning

la

te

inni

ng

inni

ng

2 z A

tlant

a

5 D 5

SA

.390

.3

46

.409

.3

36

.402

.3

94

,391

.3

32

.430

.3

59

.430

.3

26

v)

v)

P

Chi

cago

(AL)

Chi

cago

(NL)

C

-I

-4 h)

h)

Tabl

e 1

Con

tinue

d

Late

Inn

ing

Pres

sure

Tw

o O

ut P

ress

ure

k! 3 po

sitio

n D

Scor

ing

Scor

ing

posi

tion

0)

z T

otal

Le

ad o

ff R

unne

rs o

n R

unne

rs o

n

0

Late

La

te

Less

than

Tw

o Le

ss th

an

Two

I

inni

ng

late

in

ning

tw

o ou

ts

outs

tw

o ou

ts

outs

la

te

Late

La

te

inni

ng

inni

ng

inni

ng

<

late

in

ning

la

te

inni

ng

inni

ng

rn

Cin

cinn

ati

BA

S

A

BA

SA

D

etro

it B

A

SA

H

oust

on

BA

S

A

BA

S

A

BA

S

A

BA

S

A

Cle

vela

nd

Kan

sas

City

Los

Ang

eles

Milw

auke

e

.249

.3

14

.251

.3

76

.248

.3

62

.238

.3

43

.260

.3

75

.246

.3

52

.261

.3

86

.235

.3

52

.214

.3

05

.216

.3

02

.239

.3

53

.264

.3

56

.217

,2

85

,242

.3

57

,234

.3

45

.264

.4

03

.247

.3

63

.216

.3

20

,263

.3

80

.242

.3

36

.248

.3

82

.253

,3

24

.259

.4

02

.237

.3

43

.263

.3

97

.273

.3

71

.209

.2

80

.235

.3

65

.255

.3

93

.249

,3

76

.255

.3

65

.268

.3

81

.269

.3

81

.251

.3

73

.283

.4

06

.248

.4

04

,210

.2

84

.202

.2

76

.229

.3

45

,285

.3

49

.212

.2

80

.257

.3

85

.245

.3

94

.230

,3

40

.246

.3

45

,256

.3

59

.264

.3

83

.246

.3

67

,286

.4

07

.263

,4

09

.209

.2

73

,209

,2

61

.223

.3

18

.286

.3

46

.I38

.2

14

.261

,4

12

,266

.4

11

,272

.4

11

.253

.3

61

.285

.4

09

.302

.4

03

.257

.3

80

.308

.4

40

.240

.3

74

.205

,2

94

.237

.3

33

.232

.3

33

.255

.3

38

.228

.3

27

.243

.3

55

.274

.4

17

.272

.4

00

.252

.3

38

.278

.3

96

.299

.3

99

.248

.3

79

.313

.4

42

.221

.3

15

.175

.2

50

.227

.3

23

.221

.3

07

.228

.3

53

,207

.3

03

.250

.3

69

Min

neso

ta

BA

.2

76

.281

.2

72

.240

,2

71

.305

.2

55

.276

.2

90

.253

.2

90

.219

S

A

.397

.4

3 1

.397

.3

93

.390

.4

48

.378

.4

14

.427

.3

54

.455

.2

98

BA

.2

46

.247

.2

30

.253

.2

49

.257

.2

50

.272

.2

60

.237

,2

86

.220

S

A

.365

.3

42

,346

.3

35

.374

,3

59

.380

.3

35

,404

.3

28

,429

.3

14

BA

.2

68

.279

.2

69

.230

.2

77

.297

.2

62

.315

,2

94

.261

.2

92

.245

S

A

.388

.4

10

.388

,3

48

.389

,4

55

.353

.4

70

,422

.3

65

.410

.3

25

BA

.2

48

.246

.2

50

.25 1

,2

58

.217

.2

5 1

.218

.2

75

.224

.2

66

,226

5

SA

.3

88

.367

.4

00

.419

.3

93

.324

.3

78

.321

,4

31

.323

.4

09

.331

$ rn

B

A

.265

.2

3 1

.271

.2

47

.269

.2

53

.264

.2

72

.28 I

.2

47

.297

,2

28

I]

SA

.3

91

,334

.3

98

,394

.3

91

.378

.3

75

,386

.4

16

.354

.4

36

.308

BA

.2

44

.237

.2

42

.260

.2

62

.23 1

,2

41

.241

.2

74

,234

.2

74

.207

4

SA

.3

69

.333

.3

68

.405

.4

02

.310

.3

71

.328

,4

12

.352

.4

06

.318

2 z

BA

.2

44

.228

.2

41

,234

.2

52

.227

,2

68

.206

.2

62

.229

.2

95

.216

0

SA

.3

65

.331

.3

79

.336

.3

70

.320

.3

84

.342

.3

79

.339

.4

35

.314

BA

.2

59

.258

.2

55

.265

,2

74

,258

.2

64

.255

.2

75

.267

.2

67

.259

7)

SA

.367

.3

42

.353

.3

88

.388

.3

21

.392

.3

10

.378

.3

77

.379

.3

81

$

BA

.2

49

.262

.2

70

.268

.2

48

.249

.2

33

.216

.2

78

.204

,2

66

.I90

5

SA

.3

74

.336

.4

08

.3 1 1

.3

81

.337

.3

86

.271

.4

20

.310

.4

22

.310

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It is also possible to examine the patterns for each of the six comparisons separately. Regarding batting average, the expected pattern emerged significantly (at least 18 of 26 times) for five of the six comparisons, failing to emerge only for the “late-inning lead off” versus “non-late inning lead off” comparison. The pattern for SA was even stronger, with the expected pattern emerging significantly for all six comparisons.

Individual Analyses

Two series of analyses were next conducted on the 300 players with the most at bats during the 1989 season. Players were selected for these analyses if they had accumulated at least 160 at bats during the season. To examine the possibility that pressure situations would have differential effects on younger and older players, the players were assigned, in one series of analyses, to one of three categories: youngest (less than 27 years of age), middle (27 to 29 years of age), and oldest (older than 29). In the other series, they were classified according to their years of major league experience: youngest (less than 4 years experience), middle (from 4 to 7 years), and oldest (more than 7 years).

In each series, the first step was to conduct a 1-between (age or experience) X 1-within (pressure vs. nonpressure) MANOVA on the dependent variable in question (BA or SA), examining the six pressure situations simul- taneously. When significant multivariate effects were discovered, follow-up univariate tests were also conducted. The results of these are displayed in Table 2.

For BA, the overall MANOVAs revealed no significant multivariate effect for age or experience (both F s < 1) and no significant interactions between either of these variables and pressure (both Fs < 1.7; both p’s > .07). However, both MANOVA’s revealed strong multivariate main effects for game pressure (both Fs > 23.7; both p’s < .001). An identical pattern was found regarding SA; significant multivariate main effects of game pressure were found (Fs > 16.8; p’s < .001), but none for age, experience, or their interactions with game pressure (all F s < 1.24; allp’s > .25). Based on these significant multivariate effects, univariate analyses for each of the six pressure situations were next conducted. As the table reveals, significant or nearly significant univariate main effects of “game pressure” on batting average were apparent for all of the comparisons except for “late inning lead off” performance (all Fs > 2.92; all p’s < .09); in each case batting average declined under greater pressure. Significant declines in SA were found for all six comparisons (all Fs > 4.46; all p’s < .05). In all of these univariate analyses only one interaction between game pressure and age emerged, for SA in the “runners on12 outs” situation, F(2,297) = 3.27, p < .05; player

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experience never interacted with game pressure to affect performance at all (all Fs < 2.23; all p’s > .lo); thus, no reliably greater susceptibility to the debilitating effects of arousal was found for younger or less experienced players.

Batting Average Versus Slugging Average

One problem with separately analyzing BA and SA is that the two measures of batting performance are substantially correlated ( r= .61 for overall season averages). This high correlation results from the fact that batting average- the rate at which one reaches base via a hit-is a substantial component of SA. The other component of SA is the rate at which one hits with power (doubles, triples, and home runs). To determine whether the pure ability to hit with power, relatively uncontaminated by batting average, was similarly affected by pressure situations, a final set of analyses was conducted. The dependent variable in these analyses was a measure described by the baseball statistician Bill James (1982): isolated power. Isolated power is that part of slugging average which is not batting average; it consists simply of SA minus BA, and provides a relatively pure measure of the ability to hit with power. Indeed, the correlation between batting average and isolated power is only .17.

An overall within-subjects MANOVA was first carried out on batters’ isolated power in the six pressure versus nonpressure situations. The multivariate effect of game pressure on isolated power was significant, F(6,294) = 6.27;p< .OOI; thus, a series of univariate ANOVAs were next conducted. The results of these analyses closely paralleled those of the original SA measure. In five of the six comparisons there was a significant loss of isolated power in pressure situations (all Fs> 7.88; allp’s< . O l ) ; in the sixth comparison (“late inning/ scoring position”) the decline in power only approached significance ( F = 3.47;p< .07). Thus, the decline, under pressure, in the ability to hit with power does not appear simply to be the result of the overlap of the SA and BA measures.

Discussion

In general, the results of this study support the hypothesis that batting performance, a difficult task, will decline under conditions of heightened arousal resulting from specific game situations. This general pattern emerged for the team analyses, and also for the analyses based on the individual players accumulating the most at bats. Thus, using a different operationalization of arousal, we conceptually replicated the pattern originally described by Jack- son et al. (1988). As mentioned previously, however, an equally appropriate way to interpret these findings is in terms of heightened performance-


resulting from increased arousal-by the pitcher. In the absence of any compelling reason to think otherwise, it seems reasonable to suppose that improved pitching and diminished batting both contribute to the observed change in batting outcomes.

Regarding the relative size of their contributions nothing can be stated with certainty. It is interesting to note, however, that in their review of the social facilitation literature, Bond and Titus (1983) found the evidence for performance increases on easy tasks to be notably weaker than the evidence for performance decrements on difficult tasks. This might lead one to tentatively expect batting failure to play a larger role in the observed pattern than pitching improvement. Any definitive answer to this question, however, de- pends on successfully distinguishing pitching improvement from batting declines.

Although the currently available data do not permit a separation of pitching improvements and hitting decrements, it seems at least theoretically possible to partially disentangle the two. For example, there are some measur- able elements of pitching which seem to be less intertwined with the batter’s abilities than the simple hit/no hit outcome. Such pitching outcomes as wild pitches, balks, and (to a lesser degree) bases on balls and hit batsmen could be taken as indicators of pitching performance which do not depend on characteristics of the batter. As such, they may provide a relatively uncontaminated measure of pitching performance. Unfortunately, most information regarding these outcomes is not routinely available in the necessary form; that is, broken down according to performance in pressure and nonpressure situations.

Finally, it is interesting to note that we, like Jackson et al. (1988), found no evidence for the idea that older or more experienced batters are somewhat “protected” from the negative effects of arousal on performance. Player age and experience virtually never interacted with game situation to affect performance on any batting measure. One way to interpret these findings is to view them as incompatible with a drive theory analysis. According to this view, older or more experienced players should eventually habituate to arousing pressure situations and consequently display smaller performance decrements as a result. The fact that no such pattern was found by Jackson et al. or in the present investigation therefore calls into question the drive theory explanation.

While we would agree that such a pattern-had it been found-would be highly compatible with the drive model, we are less convinced that the absence of this pattern represents a serious threat to the model. After all, the funda- mental focus of the drive theory explanation is on the effects of arousal on performance; the question of how much one habituates to arousing situations seems to be an interesting but separate issue, one which lies outside the model proper. The tentative conclusion we are led to by these results is that the power


of these arousal-creating situations is very strong; in fact, strong enough to affect the performances of all players, young and old alike. With such a powerfully arousing stimulus, the stereotype of the “grizzled veteran,” im- pervious to pressure situations, or the “untried rookie,” likely to choke at critical times, may ingeneral be untrue. These results suggest that the negative impact of arousal on batting happens to everybody-or a t least to all the categories of age/ experience identified in this investigation. Because a similar analysis of pitchers’ age and experience was not possible with these batting statistics, however, the effect of pressure on more and less experienced pitchers is still open.

Alternative Explanations

Because the key variables in archival research must often be inferred and are never manipulated, one common problem is the possibility of plausible alternative explanations. This investigation is certainly no exception. In the present case there are a number of factors other than heightened arousal which might have caused the apparent decline in performance during the situations we have designated as pressure situations. Let us examine some of the most plausible possibilities.

The “relief ace. ” The most obvious alternative explanation may be that during late inning pressure situations the batters often face the “relief ace”of the fielding team (i.e., the very effective pitcher used by that team during important late inning situations). If starting pitchers on the fielding team are, on the average, replaced by superior relief pitchers capable of keeping the batting team’s success to a minimum, then batters’ performance decrements late in the game may largely be due to the greater talents of the relief pitcher and not to the effects of heightened arousal on the batter and/ or pitcher.

While this explanation seems plausible, the “relief ace” argument is under- cut by the fact that significant declines in performance-in fact, the largest declines in the study-were found in the two arousal conditions not occurring in the late innings: the “two out” pressure situations which can occur in any inning of the game. Relief pitchers generally (though not always) perform in the later innings, with some of the best ones appearing only in the ninth inning, and thus they have a more limited effect on batting performance in the early and middle innings. Because the “two out” situations occur throughout the entire game, the “relief ace” argument seems unable to fully explain the performance decrements evident under conditions of two out arousal. We would of course not argue that relief pitchers play no role prior to the seventh inning, but their impact clearly is less pervasive in the first six innings. To find, then, that the batting decrements are larger in the two out situations than in


the late inning situations in which relief pitchers more usually appear clearly undercuts the relief ace argument.

Game strategies. Another alternative explanation for the decline in late inning and/or two out performances is that specific game strategies are employed by the fielding team at those times, and that these strategies result in poorer batting performance. For example, with a runner at third base late in close games, the fielding team often shifts the location of the fielders- bringing them closer to the batter-in order to “cut off the runner at the plate.” This strategy may affect the batter’s likelihood of success independent of any arousal the batter may be experiencing. Upon closer examination, however, such a strategy seems more likely to help the batter, and would thus work against the arousal hypothesis. “Bringing in” the infielders is a strategy which allows the fielding team to maximize its chances of stopping a base- runner at home plate, as long as the ball is hit directly at a fielder. If the ball is not hit in such a fashion-and most are not-the strategy actually increases the batter’s likelihood of success. Thus, a common game strategy employed during pressure situations in all likelihood serves to increase batting success and thus works against the predicted decline in performance. In fact, after considerable reflection, we are unable to generate any late inning or two out defensive strategy which would seem to substantially diminish the chances of batter success.

Information processing. A third alternative explanation is that during many pressure situations there is an increased amount of game information that batters must process (e.g., more coaching instructions; shifts in the position of fielders to be taken into account). According to this explanation, batting performance may suffer as a result of the distractions produced by this greater cognitive load, and not as a result of greater arousal.’ Although plausible, some arguments against this explanation can be offered. First, it would seem likely that the cognitive load on the pitcher would be similarly increased in these situations-as he must be aware of and react to the same events as the batter-and that pitching performance would be expected to suffer commensurately. The fact that it is batting performance which consis- tently exhibits significant declines runs somewhat counter to this notion. Second, it is important to recall that the six pressure/nonpressure comparisons in this study were deliberately chosen so as to equate the two situations, as much as possible, on all characteristics other than the degree of game pressure. In particular, all six comparisons were equated with regard to one important source of cognitive load on the batter: the presence or absence of

’We are indebted to a thoughtful reviewer for this alternative explanation and the one which follows.


base runners, with the attendant effect that they have on coaching instructions and adjustments by the infielders. Given that these comparisons were equated on this important variable, the question becomes what additional cognitive load faces the batter when there are two outs, or during a late inning pressure AB?

Consider the simplest situation: leading off an inning under either late inning pressure or non-late inning pressure. With no runners on base the cognitive demands on the batter should be minimal (and similar) in both cases, with the difference between those two situations seeming to lie largely in the greater arousal inherent in late inning pressure. Consistent with the information-processing explanation, there was in fact no significant decline in batting average for this comparison; there was, however, a significant decline in slugging average which does not seem to be attributable to information processing differences. Alternatively, consider the Two Out Pressure comparisons, in which the largest batting declines occurred. With the presencelab- sence of base runners already held constant, what additional cognitive load faces the batter when there are two outs as opposed to when there are not? Shifts in fielding position, which might constitute one source of distraction to the batter, are probably less likely with two outs; because the fielding team needs only to record one out to end the inning they need not employ any unusual strategies (e.g., bringing in the infield) which would increase the batter’s cognitive load. Are more coaching instructions transmitted to the batter in two out situations? Although this cannot be ruled out, it does not seem immediately apparent that this would routinely happen. Coaching instructions designed to coordinate the behaviors of the batter and base- runners (e.g. the “hit and run”) would seem to be equally likely to occur in both situations. In fact, one common strategy-using the “hit and run” specifically to avoid hitting into a double play-would never be used with two out, making the two out situations cognitively simpler in at least one respect. Taken as a whole, then, the available evidence suggests that while the information-processing explanation is at least plausible, it does not seem capable of fully explaining the observed pattern of results.

Frequency of pressure situations. A final alternative explanation is based on the relative frequency with which pressure and nonpressure situations occur. According to this argument, pressure situations occur relatively less frequently than nonpressure situations. Because people typically perform worse when faced with unfamiliar situations, any lower performance in pressure situations may be due simply to the novelty of the situation and not to arousal. At least on the face of it, this explanation seems quite plausible. When examining the Late Inning Pressure situations, for example, the mean number of non-late inning pressure AB’s for the total sample was 343; the mean number of late inning pressure AB’s was only 60. On the other hand, the


number of AB’s in the Two Out Pressure situations-where the largesr performance decrements were found-were not nearly as discrepant. The mean number of AB’s with two outs and runners on base was 72, compared to 100 with less than two outs and runners on. The ratio was even closer for the two out/ scoring position comparison; the comparable number of AB’s were 46 (two outs) and 53 (less than two outs).

To directly test this explanation, we carried out follow-up analyses in which we tested each of the significant univariate effects of game pressure appearing in Table 2, and used the number of AB’s for those two situations (pressure and nonpressure) as covariates. Thus, these analyses of covariance indicate the effect of pressure situations on performance, controlling for the relative frequencies of the two situations. Of the five significant or marginally significant effects involving BA (the original effect of pressure was nonsignificant for the late inning/ leadoff comparison), four remained significant after controlling for frequency (all four Fs > 4.38; p’s < .05). The late inning/scoring position comparison, marginally significant in the original analysis, dropped to nonsignificance in the covariance analysis (p > .15). Of the six statistically significant effects involving SA, four remained significant in the covariance analyses (all four F s > 4 . 2 0 ; ~ ’ ~ < .05). The two that dropped to nonsignificance were the late inning/ leadoff and late inning/ scoring position comparisons (Fs < 1 . 7 6 ; ~ ’ ~ > .15). Thus, controlling for the frequency with which players face pressure and nonpressure situations did have a limited effect, especially for the late inning pressure situations. Most of the significant effects remained, however, again suggesting that this explanation cannot fully account for the findings, especially with regard to the two out pressure situations.

Implications

The results of this research seem to have implications in two areas. The first involves the use of naturally occurring performance measures, rather than laboratory tasks, in studying arousal’s effects on performance. The problems of using in vivo performance measures are clear; outside the controlled environment of the laboratory, it is difficult to fully control for alternative explanations. The advantages of such an approach, however, are equally clear. To find that decrements in performance on a meaningful task reliably occur during naturally occurring times of heightened arousal provides additional support for the conclusion that drive theory phenomena are in fact robust, and that the voluminous laboratory evidence in support of Zajonc’s approach does not simply reflect a “hothouse flower” phenomenon, limited to the rather artificial world of the controlled experiment.

The second implication has to do specifically with the use of baseball


statistics as a source of data. The unusual thoroughness and level of detail in the record keeping of this sport make it highly attractive for archival investigations. An almost overwhelming number of specific performance outcomes from each game are systematically recorded and catalogued on a permanent basis. These include performance outcomes for batters (e.g., batting average, slugging average, strikeouts, walks, etc.), pitchers (strikeouts, walks allowed, wild pitches, runs allowed, etc.), and fielders (putouts, assists, errors, total chances in the field). Given the technological advances in computerized data base management in recent years, a huge amount of information is now routinely available regarding performance under a variety of different game conditions. Although the “messiness” of such real world data requires a special attention to alternative explanations, the rich detail provided by this data source makes baseball records a potentially fertile source for archival investigations of a variety of social phenomena.

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Baumeister, R. F., & Steinhilber, A. (1984). Paradoxical effects of supportive audiences on performance under pressure: The home field disadvantage in sports championships. Journal of Personality and Social Psychology, 47,

Bond, C. F., & Titus, L. J . (1983). Social facilitation: A meta-analysis of 241 studies. Psychological Bulletin, 94, 265-292.

Cottrell, N. B., Rittle, R. H., & Wack, D. L. (1967). The presence of an audience and list type (competitional or noncompetitional) as joint deter- minants of performance in paired-associates learning. Journal of Personal- ity, 35, 425-434.

Jackson, J. M., Buglione, S. A., & Glenwick, D. S. (1988). Major league baseball performance as a function of being traded: A drive theory analysis. Personality and Social Psychology Bulletin, 14, 46-56.

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Schlenker, B. R. (1982). Translating actions into attitudes: An identity- analytic approach to the explanation of social conduct. In L. Berkowitz (Ed.), Advances in experimental socialpsychology (Vol. 15, pp. 194-247). New York: Academic Press.

Shapiro, B. (1990). Baseball Contest 1990: National League Players. New York: Cloverdale Press, Inc.

Siwoff, S., Hirdt, S., Hirdt, P., & Hirdt, T. (1990). The 1990 Elias Baseball Analyst. New York: MacMillan.

Zajonc, R. B. (1965). Social facilitation. Science, 149, 269-274. Zajonc, R. B., & Sales, S. M. (1966). Social facilitation of dominant and

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Documents

Declines in Major League Batting Performance as a Function of Game Pressure: A Drive Theory Analysis