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WINNING AN UNFAIR GAME:
HOW A RESOURCE-CONSTRAINED
PLAYER USES BRICOLAGE TO
MANEUVER FOR ADVANTAGE IN
A HIGHLY INSTITUTIONALIZED
FIELD
Ted Baker, Timothy G. Pollock and Harry J. Sapienza
ABSTRACT
In this study we examine how resource-constrained organizations can
maneuver for competitive advantage in highly institutionalized fields.
Unlike studies of institutional entrepreneurship, we investigate competi-
tive maneuvering by an organization that is unable to alter either the
regulative or normative institutions that characterize its field. Using the
‘‘Moneyball’’ phenomenon and recent changes in Major League Baseball
as the basis for an intensive case study of entrepreneurial actions taken by
the Oakland A’s, we found that the A’s were able to maneuver for
advantage by using bricolage and refusing to enact baseball’s cognitive
institutions, and that they continued succeeding despite ongoing resource
Entrepreneurial Resourcefulness: Competing with Constraints
Advances in Entrepreneurship, Firm Emergence and Growth, Volume 15, 1–41
Copyright r2013 by Emerald Group Publishing Limited
All rights of reproduction in any form reserved
ISSN: 1074-7540/doi:10.1108/S1074-7540(2013)0000015004
1
constraints and rapid copying of their actions by other teams. These
results contribute to our understanding of competitive maneuvering and
change in institutionalized fields. Our findings expand the positioning of
bricolage beyond its prior characterization as a tool used primarily by
peripheral organizations in less institutionalized fields; our study suggests
that bricolage may aid resource constrained participants (including
the majority of entrepreneurial firms) to survive in a wider range of
circumstances than previously believed.
Keywords: Bricolage; Major League Baseball; institutionalized fields;
resource-constraints; competitive advantage
Images of institutionalized organizational fields evoke expectations of
stability and behavioral constraint structured by rules, accepted ways of
doing things, and common ways of looking at the world. These three ‘‘pillars’’
of institutionalization – which Scott (2001) labeled regulative, normative, and
cognitive institutions – help explain a great deal of the observed regularity in
organizational behavior. Against this backdrop, however, institutional
research has increasingly identified processes through which organizations
in highly institutionalized environments may find ways to maneuver for
their own advantage, sometimes creating organization-level innovations
that drive interorganizational responses and field-level adaptation.
At least two circumstances increase the likelihood that organizations
will be able to maneuver for advantage. First, the resource advantages
enjoyed by elite organizations and by groups of organizations adopting a
common cause may allow them to alter the rules of competition in ways that
redefine what it means to compete at the core of a field (Scott, 2001, p. 27).
Well-documented cases of ‘‘institutional entrepreneurship’’ (DiMaggio,
1988; Maguire, Hardy, & Lawrence, 2004) involve actors envisioning and
enacting the regulatory and normative changes they desire. Second, resource-
constrained organizations may reject field-level normative pressures and
respond instead to local competitive pressures, in effect moving their activi-
ties away from the competitive core by competing in a somewhat different
game (Kraatz & Moore, 2002; Kraatz & Zajac, 1996). Such maneuvers are
not attempts by institutional entrepreneurs to change the field, but rather the
attempts of disadvantaged organizations to find alternative ways to thrive.
These findings also suggest that in highly institutionalized fields, organi-
zations that are neither resource-advantaged nor able to define and play
TED BAKER ET AL.2
a different game will face tremendous restrictions on their ability to
maneuver for competitive advantage at the core of the field. Current
theorizing suggests that such organizations – which are quite commonplace
(Hannan & Freeman, 1989) – are likely to be cultural or institutional ‘‘dopes’’
(Delmestri, 2006; Garfinkel, 1967; Giddens, 1984), enacting institutionalized
rules and processes, reproducing their own disadvantages, and, hence,
underperforming regularly (Bourdieu & Passeron, 1990). In other words,
resource-disadvantaged organizations forced to compete directly against
richer players are in effect constrained to play an unfair game.
But organizations sometimes surprise us by finding ways to maneuver
competitively despite facing combinations of institutional and resource
constraints. Even though the rules of the games in which they must compete
remain largely unchanged, they find ways to increase the usefulness of the
limited resources available to them (Penrose, 1959). In this chapter, we focus
on two primary questions: First, how can resource-disadvantaged actors
(i.e., ones that are not free to retreat to the periphery of their highly
institutionalized field) compete over time, especially when their innovations
generate adaptive responses by resource-rich competitors? Second, what
does the creative maneuvering of resource-constrained participants tell us
about the nature of organizational resources and resource constraints?
We argue that resource-constrained actors may compete by engaging in
bricolage, and through this process resist and sometimes change the
cognitive institutions, or ‘‘industry recipes’’ (Spender, 1989), that determine
what constitutes a resource and how resources are deployed, even while the
regulative and normative institutions remain largely unchallenged and
unchanged. This approach stands in contrast to the practices of institutional
entrepreneurs, who focus their efforts on the larger and more difficult tasks
of also changing the regulative and normative institutions governing a field
(Garud, Hardy, & McGuire, 2007; Kraatz & Block, 2008). Our analysis of
how firms challenge cognitive institutions departs from prior work in that
we focus only on changes in this institution, and we do so at the organi-
zational, rather than field level of analysis. Further, we study the behaviors
of actors whose motivations are to find alternative ways of competing
despite their chronically low levels of resources – a condition typical of most
entrepreneurial firms – not to revolutionize the field.
We pursue these questions by reexamining some recent changes in Major
League Baseball (MLB), and especially the remarkable success of the
Oakland A’s, who entered the popular imagination in the United States
through Michael Lewis’s (2004) bestselling book Moneyball. Baseball is a
particularly good setting for our study, because MLB is extraordinarily
Winning an Unfair Game 3
mature and highly institutionalized. The game itself is composed of a con-
straining and stable set of rules that closely define how it is to be played, both
on and off the field. Individual teams can neither change the rules of play nor
choose to play a different game. At the same time, the wealth of information
about specific teams, and the transparency and outcomes of their strategic
actions make baseball a useful context to explore the questions before us at
the organizational level of analysis (Kraatz & Block, 2008). Thus, rather
than constraining our view of what constitutes an ‘‘entrepreneurial’’ firm to
only those who are young and/or small, we focus on entrepreneurial
behaviors, and how even larger and older firms can be useful for generating
insights valuable to all types of entrepreneurial firms. Our approach harkens
back to research on entrepreneurial behavior by individuals working within
organizations, such as that by McClelland (1961).
Prior theorizing about bricolage has suggested that constructivist notions
of resource environments are useful for our understanding of entrepreneur-
ship and of the creation of resource-based advantages (Baker & Nelson,
2005; Garud & Karnoe, 2003). This view holds that resources are what
organizations make of them, and that their potential value is often entirely
hidden to observers until after someone makes use of them in a novel way.
Whereas earlier research on organizational bricolage has focused mainly on
its use by peripheral participants or those in immature and less institu-
tionalized organizational fields (Baker & Nelson, 2005; Garud & Karnoe,
2003), our study uncovers the role of bricolage in the survival and success of
resource constrained participants at the center of a mature and economically
and culturally important field. Our study thus repositions notions of bricolage
toward the core of competition, while also providing insights into processes
of change in highly institutionalized environments.
In the next section we discuss why the Oakland A’s are a useful example
of successful bricoleurs at the core of a highly institutionalized environment.
SUCCESSFUL BRICOLEURS: THE OAKLAND A’S
The Oakland A’s are a tightly resource-constrained MLB team that
managed over the 1996–2006 decade to win many more games than would
be expected given their inability to pay the salaries required to compete
for and retain star players (Hall, Szymanski, & Zimbalist, 2002; Lewis,
Sexton, & Lock, 2007). Through the early 1990s, the A’s were a resource-
rich team with one of the highest payrolls in MLB. However, the 1995 sale
TED BAKER ET AL.4
of the A’s to new owners, and their desire to increase profitability led to a
drastically reduced payroll budget – from approximately $33.4 million in
1995 to $22.5 million in 1996 and only $12.9 million in 1997 (Mondout,
2007). Such cuts severely restricted the availability of the main resource
presumed necessary to achieve success (i.e., highly talented major league
players) and created a natural quasi-experiment for our study (Cook &
Campbell, 1979).
In each of the five years before a new management team led by General
Manager Billy Beane was put in charge (1993–1997), the A’s won less than
50% of their games, compiling 329 wins and 415 losses (a 44.2% won–loss
record, overall). However, during the first five years of Beane’s tenure
(1998–2002), the resource-constrained A’s won 457 of 809 (56.5%) games,
winning 63% or more of their games in two different years. Winning 63% of
the games in a season typically means having the best or second best record
among all 30 MLB teams, and is highly unusual for a low payroll team. For
example, in 2002, the New York Yankees, number one in payroll in MLB
($126 million) and the Oakland A’s, number 27 in payroll ($40 million), tied
at 103 wins for the best record in all of MLB.
Table 1 summarizes the A’s relative performance during the period 1996–
2006. For example, the row for 2002 shows that the A’s paid only 44% as
much per win as the median team in the league, ranked by payroll dollars per
regular season win. No team paid less per win than the A’s, and only one
team had a lower total payroll. The A’s made the playoffs by winning 63.6%
of their games. Across the 11-year period, the A’s paid less than the median
payroll dollar per win every year and less than half the median in six of the
years. Despite being in the bottom quartile in total payroll every year, the
A’s won more than half of their games in 8 of 11 seasons. This earned
the A’s five appearances in the playoffs, which put them in the top quartile
of the league for this period.
However, the A’s failed to sustain this superior performance after 2007, as
other MLB teams emulated their approach. Between 2007 and 2011 the A’s
only won 47.1% of their games on average, and did not return to the
playoffs (Jaffe, 2012), illustrating the difficulties in successfully competing
with resource constraints once competitors adapt to your innovations. Their
performance during this five-year period was commensurate with expecta-
tions based on their payroll level. Table 2 provides data on winning
percentage, attendance, and payroll for the 2007–2011 period. It is notable
that in the 16 years of Billy Beane’s reign that the Oakland A’s ranked 6 out
of 30 in winning percentage, and 25th out of 30 in both payroll and
attendance. As other small market and large market teams caught on to
Winning an Unfair Game 5
Table 1. A’s’ Relative Performance.
Year Average
Team’s
$/Win
Median
Team’s
$/Win
A’s
$/Win
A’s $/Win as
% of Median
$/Win
a
No. of Teams
Paying Less Per
Win than A’s
b
No. of Teams
with Lower
Payroll than A’s
b
No. of Teams
Not Making
Playoffs
b
A’s Made
Playoffs?
c
A’s
Wins
d
1996 401,841 425,001 288,770 68 5 6 20 No 78
1997 477,849 509,964 198,152 39 1 0 20 No 65
1998 517,026 540,147 251,150 46 2 2 22 No 74
1999 600,449 599,672 289,757 48 4 6 22 No 87
2000 704,683 724,572 351,333 48 4 5 22 Yes 91
2001 815,537 792,944 331,478 42 1 1 22 Yes 102
2002 896,528 867,691 385,240 44 0 1 22 Yes 103
2003 882,856 883,911 523,550 59 2 7 22 Yes 96
2004 841,116 816,218 657,419 81 12 14 22 No 91
2005 875,469 855,264 629,838 74 6 8 22 No 88
2006 950,257 963,137 669,280 69 4 9 22 Yes 93
All data from MLB.com, calculations by authors.
a
The ordering for this measure is dollars per win measured for each team. Anything less than 100% means that the A’s are paying less per win
than the median team in this ranking.
b
For 1996–1997, there were 28 MLB teams, since 1998, there have been 30.
c
During the 11 years listed, eight teams were in the playoffs each year. The 88 appearances were distributed such that 23 teams had four or
fewer appearances (9 had zero appearances), and only six teams besides the A’s had five or more appearances.
d
MLB teams generally play 162 regular season games, thus, a team winning 82 games is doing ‘‘better than average’’ overall for the league.
TED BAKER ET AL.6
Beane’s methods, which were primarily aimed at evaluating run production,
Beane and others began to turn their attention to innovating on run
prevention, focusing on new statistics developed for pitching and defense. In
2012, the A’s returned to the playoffs, while again placing in the bottom 10
in attendance and payroll.
The behaviors that allowed the A’s to maneuver successfully despite tight
resource constraints between 1998 and 2006 match patterns of bricolage that
have been previously described (Garud & Karnoe, 2003; Hmieleski &
Corbett, 2006; Levi-Strauss, 1967). Bricolage is defined as making do by
Table 2. 2006–2011 Winning Percentage, Attendance, and Payroll
a
.
Team W L Pct Attendance Payroll
New York Yankees 1369 895 0.605 51,322,316 $2,250,097,312
Boston Red Sox 1285 982 0.567 39,145,041 $1,612,223,731
Atlanta Braves 1281 985 0.565 37,642,146 $1,235,520,754
St. Louis Cardinals 1247 1019 0.550 45,507,278 $1,146,887,994
Anaheim Angels 1221 1047 0.538 40,753,998 $1,223,135,021
San Francisco Giants 1208 1058 0.533 42,094,720 $1,096,661,143
Oakland Athletics 1206 1060 0.532 24,968,705 $691,682,891
Philadelphia Phillies 1201 1066 0.530 37,021,149 $1,178,338,229
Los Angeles Dodgers 1184 1083 0.522 47,049,011 $1,329,229,120
Chicago White Sox 1179 1089 0.520 28,955,888 $1,073,519,832
Houston Astros 1163 1104 0.513 37,731,351 $1,038,700,351
New York Mets 1156 1111 0.510 39,943,233 $1,465,690,348
Minnesota Twins 1153 1114 0.509 28,660,536 $765,234,204
Cleveland Indians 1151 1117 0.507 33,185,050 $897,281,014
Texas Rangers 1145 1123 0.505 34,900,419 $1,038,996,922
Toronto Blue Jays 1143 1124 0.504 27,843,667 $900,066,297
Arizona Diamondbacks 1129 1139 0.498 36,109,901 $948,176,895
Seattle Mariners 1120 1147 0.494 38,128,018 $1,164,266,790
Chicago Cubs 1110 1157 0.490 41,857,571 $1,290,494,258
San Diego Padres 1102 1167 0.486 34,018,968 $724,830,642
Cincinnati Reds 1094 1175 0.482 29,027,251 $790,854,221
Florida Marlins 1081 1185 0.477 19,650,689 $530,838,679
Colorado Rockies 1074 1195 0.473 38,641,011 $893,893,457
Milwaukee Brewers 1062 1204 0.469 32,999,563 $773,368,076
Detroit Tigers 1039 1228 0.458 31,125,219 $1,052,904,735
Tampa Bay Rays 1013 1252 0.447 21,195,863 $579,093,003
Montreal Expos 993 1273 0.438 20,579,468 $616,918,761
Baltimore Orioles 990 1276 0.437 35,679,071 $1,040,841,965
Pittsburgh Pirates 957 1307 0.423 24,583,214 $559,327,156
Kansas City Royals 946 1320 0.417 21,943,846 $647,640,543
a
Source:http://www.hardballtimes.com/main/content/article/50th-birthday-billy-beane/
Winning an Unfair Game 7
applying combinations of the resources at hand, including those available
cheaply or for free, to new challenges (Baker & Nelson, 2005). As Phillips
and Tracey (2007) observed, bricolage offers a useful lens for understanding
entrepreneurial behavior in institutionalized environments (Rao, Monin, &
Durand, 2005; Stark, 1996). The crux of our preliminary answer to the two
questions we posed above thus involves how the Oakland A’s ‘‘made do’’ by
applying combinations of the resources at hand to the challenges they faced
(Baker & Nelson, 2005).
First, the A’s have been able to find room to maneuver and compete
effectively at the core of a highly institutionalized field by engaging
repeatedly in bricolage. Their success has challenged long-held institutional
beliefs and practices. Their initial use of bricolage in the late 1990s – which
was informed by a longstanding but marginalized approach to analyzing
baseball statistics known as ‘‘Sabermetrics’’
1
– resulted in competitor
responses in the early to mid-2000s that made resources previously available
cheaply too expensive for the A’s.
2
In a subsequent use of bricolage
beginning around the publication of Moneyball – in which the A’s seem to
be contradicting both some Sabermetric ‘‘truths’’ and their own prior
espoused beliefs – they found new ways to make do with resources now
undervalued by other competitors, making it to the playoffs in both 2003
and 2006. These observations provide the basis for our answer to the second
question, which asked what could be learned from the creative behavior of
resource-constrained players about the nature of resources.
INSTITUTIONAL THEORY AND MANEUVERING
FOR ADVANTAGE
For many years, the central pursuit of neo-institutional theory was
confirming and explaining the existence of constraining stability and order
in mature institutional fields (Scott, 2001; Tolbert & Zucker, 1996). The
possibility of change was seen primarily in the form of organizational and
industry responses to exogenous social, technological, and legal shocks
(Clemens & Cook, 1999; Hinings & Greenwood, 1988; Meyer, 1982). More
recent scholarship, often investigating endogenous sources of change, has
identified agents and processes of competitive maneuvering under con-
straints, interests that are at the intersection of neo-institutional concerns
with constraint and ‘‘old’’ institutionalism’s concerns with human agency
and change (Hirsch & Lounsbury, 1997; Stinchcombe, 1997). Organizations
TED BAKER ET AL.8
at the core of mature, deeply institutionalized fields exhibit the ‘‘paradox of
embedded agency’’ (Seo & Creed, 2002, p. 226). When organizations are
embedded within and benefit from the status quo, they become less likely to
imagine or attempt institutional changes (Greenwood & Suddaby, 2006).
Nonetheless, competitors at the core of such fields do sometimes envision
and mobilize their resources in attempts to change the nature of the field and
of competition at its core. For example, Greenwood and Suddaby (2006)
developed a model of ‘‘elite institutional entrepreneurship’’ by studying how
major international accounting firms overcame their embeddedness in the
institutional status quo to ‘‘envision and impose’’ institutional changes in the
form of multidisciplinary practices encompassing a broad range of consulting
and legal services. These practices represented a substantial change and an
increase in competitive heterogeneity at the core of competition among
central players in public accounting, and they challenged other central players
still trying to compete in a narrow, traditional span of services.
Firms disadvantaged by the status quo (e.g., most small or new firms)
may be likely to envision ways to maneuver for advantage, but because of
resource constraints they may be unable to enact their visions. During early
processes of field development and institutionalization, maneuvering by
peripheral players sometimes results in substantial but unforeseen field-level
change. For example, in Leblebici and colleagues’ (Leblebici, Salancik,
Copay, & King, 1991) study of the early development of the radio broadcast
industry in the United States, core actors such as RCA, GE, AT&T, and
Westinghouse negotiated, partnered, and competed with one another to
shape industry practices, rules, and standards to their own advantage. At
the same time, resource-disadvantaged ‘‘fringe’’ organizations (Leblebici
et al., 1991) opened new competitive fronts and activities in their attempts to
deal with local problems and resource deficits. Though their focus was local,
the success of their work eventually altered many of the primary activities at
the core of competition in the radio broadcast industry, including such basic
features as who would determine broadcast content, who would create it,
and who would pay for it. However, the fringe actors responsible for
generating these innovations remained on the periphery of the industry,
even as their innovations migrated to the core and became institutionalized
as the industry matured.
Even in highly institutionalized fields, resource-constrained organizations
sometimes respond to local competitive pressures by pursuing changes that
move them away from the core of the field. For example, Kraatz and his
colleagues’ studies of changes among American liberal arts colleges (Kraatz &
Moore, 2002; Kraatz & Zajac, 1996) found that despite strong normative
Winning an Unfair Game 9
pressures against bringing ‘‘professional’’ programs such as business and
computer science into liberal arts curricula, many colleges added profes-
sional programs in response to local market demands. Such changes – which
moved these liberal arts colleges into competition with other colleges and
universities offering professional programs – were particularly common
among lower-status, resource-constrained liberal arts colleges.
Together, such studies of competitive maneuvering in institutional fields
suggest that (1) well-organized institutional entrepreneurs may sometimes
impose change directly and alter the nature of competition even in very
mature fields by reshaping regulatory and normative institutions; (2)
organizations may reject strong institutional norms and find advantage by
escaping the traditional core of competition in favor of serving different
local demands; and (3) resource disadvantaged-organizations seeking local
solutions in emerging industries may in the process shape the core of a
developing field to their advantage.
Because MLB is a mature institutional field with stable and largely
inescapable rules governing competition, however, resource-constrained
baseball teams have none of these options available to them. Every team is
forced to engage in the same structured set of competitions. Because of these
regulative and normative constraints, the primary arena in which resource-
disadvantaged teams are able to maneuver for advantage is largely limited
to how they think about and mobilize their resources, that is, by the extent
to which they adhere to or reject the cognitive institutions of MLB. Are
resource-constrained enterprises in such settings doomed to failure?
In the following sections we describe the intensive case study methodol-
ogy applied in this study and then explore how the Oakland A’s bricolage
allowed them to compete by challenging the cognitive institutions of MLB.
METHODS
Setting and Data
This chapter reports on an embedded case study (Yin, 1984) of MLB,
focusing on innovative behaviors by one team, the Oakland Athletics
(‘‘A’s’’), and responses by other teams to these innovations. Careful
observers of baseball could point to other cases in which teams, leagues,
and various stakeholders have engaged in bricolage, even forms of bricolage
very similar on some dimensions to the behaviors we analyze in this study.
However, the natural quasi-experiment that ensued when the A’s were sold to
TED BAKER ET AL.10
new owners who drastically cut the team payroll makes this a ‘‘revelatory’’
case (Yin, 2003, p. 42) for examining an organization’s responses to tight
resource constraints under conditions in which very little else has changed.
The so-called ‘‘Moneyball phenomenon’’ has drawn close attention from
analysts, journalists, other teams, and even other professional sports, and
the resulting close documentation of the focal behaviors and responses by
stakeholders with varied perspectives makes the case highly accessible for
our analysis. Events in the case were outlined by journalist Michael Lewis
and reported in his bestselling book, Moneyball. During 2002, Lewis spent
extensive time with the A’s, conducting dozens of interviews and gaining
unprecedented access to team players and staff, and observing what are
usually secretive meetings and decision-making processes. He was also
permitted to report on what he found without interference from the team or
its executives (Lewis, 2004, p. 304). Lewis’s work provided important
insights and facts about the case that would otherwise be unavailable, and
helped point us toward multiple other sources of data, including some severe
critics of the A’s approach to baseball. For example, in 2006, John
Schuerholz, the highly successful General Manager of the Atlanta Braves,
wrote (along with Larry Guest) his own book about how baseball teams
were to be built and how players were to be scouted. In it, Schuerholz was
highly critical of the ‘‘Moneyball hype’’ and its attack on traditional
scouting and player evaluation.
Some have challenged whether Lewis’s focus on Billy Beane was biased in
the service of telling a more compelling narrative. Arguably, other
participants such as Sandy Alderson (the A’s prior general manager who
brought Beane into the A’s front office) should perhaps have received more
credit for individual decisions or the introduction of Sabermetric
approaches to analyzing players. Nevertheless, the basic events are not in
dispute, and the narrative’s focus does not materially affect the theoretical
arguments we make or the conclusions we draw from this case. Further, we
have corroborated Lewis’s main facts and our central arguments with
research conducted by other baseball experts.
Unsurprisingly, baseball has generated hundreds of scholarly studies. We
drew on historical and cultural studies of MLB (e.g., Barzun, 1954; Tygiel,
2000) to understand the degree and dimensions along which baseball is
institutionalized in the United States. We also drew on studies of more
specialized subjects, such as the role and history of ‘‘scouting’’ (Kerrane,
1999; Perry, 2006; Shanks, 2005). The statistical analysis of baseball has a
long history, and the more recent history of ‘‘Sabermetric’’ analysis – which
is a primary focus of Lewis’s account – has generated a large number of
Winning an Unfair Game 11
historical and biographical (e.g., Gould, 2004; James, 1994) studies, as well
as a spate of studies applying increasingly detailed and sometimes even
exotic statistical modeling to baseball phenomena (e.g., Hall et al., 2002;
Keri, 2006a; Schmidt & Berri, 2001).
We drew heavily on these studies for two purposes: first, to understand
how it was that Sabermetric analyses and insights could be so freely
available and for so long before anyone made use of them in MLB; and
second, to understand the context and outcomes of strategic maneuvering
by the A’s and other teams. Overall, an astounding variety and detail of
statistics and statistical analyses about baseball are widely available, and we
made use of some of these in the work reported here.
The professional baseball press, various pundits, and thousands of
bloggers have continued to respond in various ways to Moneyball. In parti-
cular, many took exception to Lewis’s attack on the value of ‘‘traditional
scouting’’ techniques, practices, and assumptions in MLB. A ‘‘Google alert’’
for search results containing the terms ‘‘Moneyball’’ and ‘‘wrong’’ continued
generating new hits virtually every day between 2005 and 2007. The
controversy over the implications of Moneyball for traditional scouting, in
particular, generated a great deal of impassioned discussion, ranging from
profound and well-researched arguments (Perry, 2006) to pure silliness.
Particularly useful have been books such as Built to Win (Schuerholz &
Guest, 2006) by former Atlanta Braves general manager John Schuerholz, as
well as books detailing how the Boston Red Sox combined Sabermetric
principles with very large amounts of money to build a successful team
(Goldman, 2005; Mnookin, 2006). The controversy caused Lewis to add a
chapter to the second edition of his book labeled, ‘‘Inside Baseball’s
Religious War.’’ Largely because we suspect that fan pressures play an
important role in MLB, we also read broadly across baseball media and
blogs.
3
Finally, we had discussions with several MLB general managers and
executives to whom we promised anonymity.
Analysis
The A’s responded to the imposition of tight resource constraints by finding
ways to create useful combinations of resources, that is, baseball players
that were available to them cheaply because other teams failed to see the
same value in these players. At first blush, this pattern seemed to resonate
with current ideas about bricolage in the organizations literature (Baker &
Nelson, 2005; Garud & Karnoe, 2003; Baker, Miner, & Eesley, 2003). While
TED BAKER ET AL.12
bricolage can theoretically occur in any type of organizational context, prior
research on bricolage has focused on marginal businesses in degraded
environments (e.g., Baker & Nelson, 2005), young industries in technological
flux (e.g., Garud & Karnoe, 2003), and firms avoiding the core of
competition (e.g., Kraatz & Zajac, 1996). In contrast, the bricolage we
consider was accomplished by a resource-constrained organization at the
core of what is an extraordinarily institutionalized field.
The structure of our analysis therefore focused initially on two factors.
First, we examined the A’s behavior through the lens of bricolage, attempting
to understand how well their behavioral patterns fit with current conceptions
of bricolage and whether the patterns challenge or extend current
conceptions. This task involved iteration between the data we continued to
gather and prior notions of bricolage in a process that required a great deal of
‘‘muddling through’’ and tolerance of slow progress (Denzin & Lincoln,
2000; Miles & Huberman, 1994).
Second, we examined the A’s actions in the context of trying to understand
the institutional environment in which MLB teams were embedded and how
this environment enabled the A’s to successfully redefine and revalue
resources. In the next section we demonstrate the highly institutionalized
nature of baseball in the United States, the taken-for-granted nature of
the industry recipe for success in this environment, and what counts as a
resource. We then examine the A’s response to resource constraints in
terms of their behaviors’ fit with prior conceptions of bricolage. We then
discuss the implications of this study for institutional theory and for our
understanding of bricolage as a means for organizing and competing with
other firms, and particularly as a means for resource-constrained entrepre-
neurs to find new ways to compete.
THE INSTITUTIONALIZATION OF BASEBALL
A primary reason baseball interests us as the context for this study is that
baseball generally, and MLB in particular, are highly ‘‘institutionalized’’ in
all theoretically significant senses of the concept, whether one adopts the
theoretical perspectives of the old (Hirsch & Lounsbury, 1997; Selznick,
1966) or the new (DiMaggio & Powell, 1983; Meyer & Rowan, 1977)
institutionalism. Borrowing Scott’s (2001) typology, all three pillars of
institutionalization – the regulatory, the normative, and the cognitive – are
well developed and complementary in baseball. Below, we first touch briefly
on the regulatory and normative context of baseball in the United States.
Winning an Unfair Game 13
We then describe the cognitive institutionalization of baseball – in terms of
the MLB ‘‘industry recipe’’ – which is central to our argument.
The Regulatory and Normative Institutions of Major League Baseball
Baseball is embedded within and protected by a remarkable legal structure
that supports the concepts and practices of the baseball ‘‘draft’’ and ‘‘free
agency,’’ which plays an important part in how resources are valued and
distributed in baseball. MLB is protected by the strongest exemptions from
antitrust legislation provided to any American sport, and has been so
protected through a variety of interpretations and challenges since before
1922, when Justice Oliver Wendell Holmes wrote a decision favoring the
exemptions. In 1978, the US Congress anointed ‘‘USA Baseball’’ as the
governing body for the sport, including representing baseball on the US
Olympic Committee and the International Baseball Federation. With very
strong ties to MLB (which acquired all commercial assets of USA Baseball
in July 2006) USA Baseball governs the baseball activities of over 12 million
US amateur players (mlb.com/NASApp/mlb/usa_baseball; espn.go.com/
mlb/s/2001/1205/1290707.html).
Baseball fans follow over 300 minor league teams, more than 1,000
intercollegiate teams, and over 30,000 high school baseball and softball
teams, while also watching millions of pre-high school children play in
games administered by the Little League and similar organizations. In the
major leagues, attendance has grown recently to about 75 million people
annually (MLB.com), a figure that far surpasses the annual attendance of
American professional football, basketball, and hockey combined.
Baseball prides itself on consistency and comparability across time.
Deeply socialized fan expectations about what is authentic in baseball
strongly delimit the ‘‘acceptable’’ changes MLB can consider (Barzun, 1954;
Trilling, 1972). A simple rule change such as the 1972 creation of the
‘‘designated hitter’’ in the American League (one of two divisions in MLB)
still invokes heated debate 40 years after its introduction. Since the same
baseball statistics have been collected on players for over 100 years, fans can
compare and debate the feats of players in different eras.
4
MLB’s 122 mostly
multipart rules (supported by a formal lexicon) demonstrate a high degree of
stability and fine-tuning. Indeed, as evolutionary paleontologist and
baseball scholar Steven J. Gould (2004, p. 183) notes, ‘‘Baseball has been
a bastion of constancy in a tumultuously changing world, a contest waged to
the same purpose and with the same basic rules for one hundred years.’’
TED BAKER ET AL.14
Complementing all of this, MLB’s stability, traditionalism, and institu-
tional values and practices are encouraged by its incestuous recruitment
practices. In the early days of national baseball leagues, successful players
could and sometimes did become successful baseball ‘‘magnates,’’ as owners
then referred to themselves (Tygiel, 2000). Those days are probably past, but
once we get beyond the owners, many of the roles in baseball – coaches,
managers, scouts, some executive positions – are typically dominated by ex-
players. As analyst Voros McCracken (quoted in Lewis, 2004, p. 241) notes,
‘‘The problem with major league baseball is that it’s a self-populating
institution. Knowledge is institutionalized. The people involved with
baseball who aren’t players are ex-players.’’ As the president of one major
league team pointed out to us, individual teams also develop cultures of ‘‘the
way we do things around here’’ that sometimes persist across many years
and through multiple changes of leadership. For example, Thomas Yawkey
became the owner of the Boston Red Sox in 1932 (Goldman, 2005). A well-
known segregationist and racist, Yawkey’s Red Sox was the last team in
professional baseball to become integrated, 12 years after Jackie Robinson
broke the color barrier with the Brooklyn Dodgers.
Cognitive Inertia and Enactment: The Baseball Recipe
Spender (1989, p. 6) defined industry recipes as ‘‘what everyone who knows
this industry understands,’’ and as an element of ‘‘what experienced
managers take uncritically as professional common sense.’’ Industry recipes
tend to become more coherent and closed over time, and this closure
reduces the likelihood that those who have been socialized into an industry
will mindfully consider alternatives (Fiol & O’Connor, 2003; MacKay,
Masrani, & McKiernan, 2006; Matthyssens, Vandenbempt, & Berghman,
2006). Recipes are thus an important component of the paradox of
embedded agency (Seo & Creed, 2002).
In mature, highly institutionalized industries, recipes shape behavior and
how day-to-day events are experienced (Berger & Luckmann, 1967; Schutz,
1944). Those who have been socialized into these recipes and are engaged in
enacting the patterns of behavior the recipes prescribe as normal and
appropriate become more likely to simply reject or not even notice
surprising information or new causal inferences about how to conduct their
business (Giddens, 1984; Weick, 1979). The maturity and institutionaliza-
tion of the industry recipe are reflected and supported by decision-makers’
simplified mental models of the competitive resource environments in which
Winning an Unfair Game 15
they operate (Geletkanycz & Hambrick, 1997; Huff, 1982; Porac & Thomas,
1990). At the individual level recipes function as cognitive heuristics or
shortcuts (Thaler & Sunstein, 2004). Spender’s fieldwork showed that
recipes indicate the ‘‘appropriate resources’’ for constructing a business,
including ‘‘models of the individuals the firm must employ’’ (1989, p. 177).
Recipes thus represent the core aspects of institutionalization that define
what are and are not resources, as well as how those resources are to be
combined.
The MLB recipe defines what resources – in the form of player skills and
attributes – are valued and describes how they are combined and deployed.
The power of the recipe is such that, despite some notable exceptions to
the contrary, by the late 1990s both informed observers and participants,
including the formal leadership of MLB, had largely accepted as ‘‘fact’’ a
financially deterministic model of competitive outcomes. Overall, the richest
baseball teams who can afford to acquire the best players – as defined by
the recipe – are expected to contend for championships, while resource-
constrained teams are expected to fare poorly (Hall et al., 2002). This
financial determinism has been widely considered a serious threat to MLB’s
overall appeal to consumers, who, even though biased in favor of their home
teams, are presumed to be interested in watching relatively fair contests with
uncertain outcomes (Levin, Mitchell, Volcker, & Will, 2000; Schmidt &
Berri, 2001). In the case of MLB, it was against the backdrop of this
highly institutionalized industry recipe that the possibilities for bricolage
emerged.
Defining Player Value
Many primary components of the MLB recipe are straightforward; we will
describe these in order to provide a flavor for the recipe and a backdrop for
understanding how the A’s’ bricolage violated and changed these highly
legitimated beliefs. Perhaps most importantly, the recipe calls for the
identification of potential players through the ‘‘scouting’’ process in which a
group of baseball insiders – often former baseball players whose careers
stopped short of MLB success – observe and get to know players on high
school, college, and minor league baseball teams (Kerrane, 1999). The
institution of scouting is important because scouts have traditionally played
a dominant role in determining the set of players that MLB teams will
attempt to acquire, and they are a primary mechanism through which the
details of the baseball recipe are enacted and sustained year-to-year.
TED BAKER ET AL.16
It is widely accepted that there are five ‘‘tools’’ that a baseball player can
possess: the ability to run, throw, field, hit, and hit with power. A ‘‘five-tool
player’’ is the standard baseball jargon for someone skilled in all of the
fundamental abilities important to success as a ‘‘position’’ player, that is,
the eight players with a designated fielding position on defense other than
the pitcher (Kerrane, 1999; Lewis, 2004). It is axiomatic among baseball
scouts that the fewer the tools, the less likely the individual is to succeed and
the less valuable a player is considered to be.
Part of the reason why the tools are considered so important is that scouts
are required to make judgments about players long before they have
developed their full potential, or, in the case of high school players, before
they have even developed physical maturity. Young players are judged by the
apparent presence or absence of the tools, rather than by sole reliance on
their performance in games. In turn, the practice of assessing potential early
is driven by the regulated structure of the baseball labor market. Under its
congressional exemptions from antitrust law, MLB is able to sustain a system
through which a team that successfully ‘‘drafts’’ and signs an amateur player
becomes, de facto, the only team able to bid on his services for up to 13 years
(Carfagna, Farrell, & Hazen, 2006). The five tools serve as fundamental
indicators of what a young player has the potential to become, and thereby
shape MLB teams’ efforts to draft and sign particular amateur players.
Because players develop and mature in the years leading up to any
opportunity they have to play in MLB, and because MLB is considered to
be qualitatively different from lower levels of baseball, scouts have long
considered the available objective statistics describing players’ pre-MLB
play to be poor indicators of MLB potential. Instead, assessments of the five
tools, together with scouts’ intuitive assessments of player physiology and
other factors, have long held sway as the primary way to assess potential,
one that shapes which players baseball clubs target and attempt to acquire.
Perhaps the most peculiar and striking indicator of the mixture of
knowledge, ideology, and ‘‘superstition’’ underlying scouting assessments is
the notion of ‘‘the good face’’ (Kerrane, 1999). Some scouts believe so
deeply in their own intuitive ability to detect undeveloped potential that they
have claimed they ‘‘could tell by the structure of a young man’s face not only
his character but his future in pro ball’’ (Lewis, 2004, p. 7, emphasis added).
In contrast to the good face, a variety of negative attributes, for example, a
‘‘bad body,’’ are used to devalue potential, also in largely intuitive ways
(Kerrane, 1999; Lewis, 2003).
5
Taken together, the need to assess potential early, the dominance of the
scouting ranks by baseball insiders such as ex-players, and the influence of
Winning an Unfair Game 17
a strong traditional ideology regarding player potential and value resulted in
what Jim McGlaughin, an MLB scouting director in the 1970s, called
scouting’s ‘‘dearly held reliance on subjectivity and superstition’’ (Kerrane,
1999). Scouting largely determined who gained entry to the pool of young
men considered candidates for MLB careers. Then, once a player gained
entry to professional baseball through the minor leagues, some of the same
heuristics held sway over the evaluation of players throughout their
professional careers. The five tools and traditional statistical measures were
thought by most to be the tried and true way to judge talent (Schuerholz &
Guest, 2006).
6
SABERMETRICS
Many observers and commentators on what has become known as the
‘‘Moneyball phenomenon’’ – considered to include not only the A’s’
maneuvers but also those of teams that copied Oakland, such as the Toronto
Blue Jays, the Tampa Bay Rays, and the Boston Red Sox – have viewed it
more or less as the straightforward application of the statistical analysis tools
of Sabermetrics to acquiring and deploying a team of baseball players (e.g.,
Hakes & Sauer, 2006; Schuerholz & Guest, 2006;Thaler & Sunstein, 2004;
Wolfe, Wright, & Smart, 2006). Even Lewis’s narrative is in large part a story
in which ‘‘science’’ and ‘‘analysis’’ supplant myth with truth. Sabermetric
analyses suggested that some skills – such as defense, base running, and
hitting with power – were overrated in their contributions to winning games,
and the A’s’ experiments showed that these skills were overpriced in the
market for baseball players. In some analyses, Sabermetrics was seen to
overcome heuristics and biases (Thaler & Sunstein, 2004), and in others it
was seen to overcome market failures and to cause a better alignment
between true player productivity and pay, as price theory predicts (Hakes &
Sauer, 2006).
There are at least two problems with such facile interpretations. The first
problem is that the application of Sabermetrics to the construction and
management of a real baseball team was not straightforward. It required a
great deal of fairly messy experimentation and the adaptation and extension
of the cool analytic insights of statistical analysis in the hot context of
emotional debates and politics around the accepted wisdom of baseball
insiders. Second, most of the basic ‘‘truths’’ of Sabermetrics had been
around for a long time and were well-known long before the Moneyball
TED BAKER ET AL.18
saga began. The primary statistics (which focus largely on offensive output)
to which fans and teams alike have paid the most attention have generated
controversy since the late 1860s, when British cricket fan Henry Chadwick
invented, defended, and proselytized them (Cramer, 1988; Tygiel, 2000).
Table 3 provides examples and explanations of some traditional and
Sabermetric measures of player offensive output, with comments on their
differences.
Some of the improvements to baseball statistics suggested by Bill James,
the godfather of Sabermetrics, and by others were available for more than
two decades before the A’s began experimenting with Sabermetrics. James’s
1982 Baseball Abstract (James, 1982) was well known within the baseball
community. By the early 1980s Sabermetric insights were well-enough
accepted among baseball aficionados that in 1984 Pete Palmer was finally
able to publish his statistically nuanced The Hidden Game of Baseball
(Thorn et al., 1984). He had written the book in the 1960s, but little interest
was generated until Sabermetric analysis was popularized by James’s work
(Lewis, 2004). Not only were these statistical truths there for the asking,
entrepreneurs had even attempted to provide customized Sabermetric
analyses to MLB teams and had been soundly rebuffed. In 1980, an
organization called STATS Inc., founded by two Sabermetricians, began a
five-year saga of trying to sell MLB teams on the idea of gathering and
using better statistics and analyses. Although they had few takers, their
activities ensured that Sabermetric insights were far from secret among
MLB insiders.
It is also the case that there were other individuals at different teams with
an interest in Sabermetrics, but none of them influenced the dominant
industry recipe. Craig Wright of the Texas Rangers was the first front-office
executive to hold the title of ‘‘Sabermetrician’’ in the 1980s (www.base-
ballamerica.com), and Oakland’s Paul DePodesta filled a similar position
for the Cleveland Indians before Billy Beane hired him away. Indeed, John
Henry, then owner of the Florida Marlins and more recently the owner of
the Boston Red Sox, read Bill James’s work and used Sabermetrics to
compete with his fantasy league baseball team, but he apparently never even
considered applying the same tools in managing the Marlins until after
Oakland’s success employing these techniques (Lewis, 2004).
Generally forgotten in most analyses of the Moneyball phenomenon
is that the focus of Sabermetrics is on uncovering the patterns of activi-
ties and skills that lead to success at winning baseball games, not on pro-
viding tools to reshape how resource-constrained teams compete.
7
Its tools
are at least as available and perhaps even more valuable to the already
Winning an Unfair Game 19
Table 3. Some Traditional and Sabermetrics-Influenced Player
Offensive Statistics: From Most to Least Traditional.
Statistic Comments
Batting Average (AVG
a
): Hits divided by at-
bats. Note: for all calculations, at-bats is an
adjusted number that ignores, for example,
walks, ‘‘sacrifice’’ hits, and getting hit by a
pitch.
Developed and promoted by Henry
Chadwick in the late 19th century, it’s
appropriateness was debated for several
decades before it became the defacto
standard measure of individual batting
prowess (Thorn, Palmer, & Reuther, 1984;
Tygiel, 2000, p. 115). Since the 1970s has
been demonstrated repeatedly to predict
contribution to team offensive performance
less well than OBS (below) or its
components. It nevertheless is still the most
likely statistic to be reported, and is still the
basis for the MLB ‘‘Batting Champion’’
title.
Stolen Bases (SB
a
): A simple count of the
number of bases a player has ‘‘stolen,’’
often divided by the number of times the
player attempted to steal.
Traditionally, stealing bases is considered
both valuable and exciting. In
Sabermetrics, base stealing attempts are
more likely to be discouraged because of
analyses showing that they generally ‘‘cost’’
more in the likelihood of generating outs
than the benefits they bring in terms of
gaining a base (Thorn et al., 1984). A
Sabermetric analysis of the entire 2004
season suggests that ‘‘no player in all of
MLB added so much as a single win
through base stealing alone’’ (Click, 2006,
p. 115).
On-base percentage (OBP
a
): Number of times
got on base through a hit, walk, or hit by
pitch divided by times at-bat, walks, and
sacrifice flies.
Forms of these measures were debated as
early as the late 1800s (Tygiel, 2000), and
were unsuccessfully promoted by baseball
innovator Branch Rickey in the 1950s
(Rickey, 1954; Schwartz, 2004). Versions
were introduced as prime Sabermetrics
measures by Bill James starting in the late
1970s. OBS is a superior measure,
compared to batting average, of a player’s
history of actually getting on base, and of
keeping a team’s offense alive by avoiding
an out. SLG measures power to generate
extra-base hits, which AVG ignores (Keri,
2006c).
Slugging percentage (SLG
a
): Like batting
average, but rather than adding ‘‘1’’ in the
numerator for any hit, scores ‘‘2’’ for a
double, ‘‘3’’ for a triple, and ‘‘4’’ for a
homerun; thus, the weighted sum of these
hits divided by plate appearances excluding
walks and hit-by-pitch.
TED BAKER ET AL.20
resource-advantaged teams, as later adoption of Sabermetrics by rich teams
such as the Red Sox would demonstrate. What needs explanation is not how
the application of Sabermetrics improves the matching of player price and
productivity; rather, what requires explication is how, after years of industry
blindness and resistance to Sabermetric principles, the A’s challenged
the firmly institutionalized baseball recipe in a manner that changed the
recipe in fundamental ways. The newly important theoretical ‘‘truths’’ had
been out there for a long time. What did it take for the Oakland A’s to make
them real? Our analysis suggests that the Moneyball phenomenon can be
better understood as driven by bricolage than as a straightforward
application of statistical analysis to generate arbitrage benefits in inefficient
markets.
Table 3. (Continued )
Statistic Comments
On-base plus slugging (OBS): OBP+SLG.
(Note that this involves adding together
two numbers calculated with different
denominators).
Developed by Sabermetricians Pete Palmer
and Dick Cramer (Thorn et al., 1984). OPS
‘‘combines’’ the advantages relative to
AVG of both OBP and SLG (Hample,
2007). Because of Sabermetric analyses
OBP is often overweighted relative to SLG
in the formula. Paul Podesta drastically
increased this weighting due to a belief in
the critical value of not making an out,
which OBP measures more directly than
does SLG (Lewis, 2004).
Equivalent Average (EqA): Complex
calculations combining a large number of
factors that affect a player’s offensive
output.
Nominally similar to AVG, but makes
adjustments for the characteristics of the
park and the league in which a player plays,
the player’s baserunning and the quality of
pitching faced (Keri, 2006c). Creates
greater comparability between players who
work in different contexts.
Value Over Replacement Player (VORP):
Complex calculation.
Estimates the number of runs a player
generates over the number of runs a player
in the same position just barely good
enough to be playing in the major leagues
would generate (Keri, 2006c).
a
An official Major League Baseball statistic as of 2007.
Winning an Unfair Game 21
BRICOLAGE AND THE INDUSTRY RECIPE
Baker and Nelson’s (2005) survey of the development of bricolage across
many fields identified three primary aspects: making do, relying on the
resources at hand, and combining resources to meet new challenges. In this
section, we examine the A’s’ initial responses to their new resource
constraints against these core aspects of bricolage and suggest that their
behavior closely fit the general pattern of bricolage.
Making Do
Baker and Nelson (2005) characterized ‘‘making do’’ in terms of a bias for
action and the refusal to enact accepted limitations regarding what is
considered a resource. Both of these criteria are reflected time and again in
Oakland’s behavior.
Bias for Action
As highlighted by Lewis (2004), the A’s management, led by Billy Beane,
was both willing and apparently eager to make substantial changes to the
team on the fly. For example, they structured major moves around
opportunities that occurred near mid-season trading deadlines, frequently
jettisoning current players for new ones even if they only expected the new
players to stay with the A’s for the remainder of that season. Indeed, one of
Billy Beane’s rules was, ‘‘No matter how successful you are, change is
always good. There can never be a status quo. When you have no money,
you can’t afford long-term solutions, only short-term ones. You have to
always be upgrading’’ (Lewis, 2004, p. 193).
The A’s bias for action encompassed a willingness to engage in near-
constant experimentation. Such tinkering is consistent with other studies of
bricolage, which suggests that because solutions rendered through bricolage
are usually imperfect, they tend to be temporary (Ciborra, 1996; Ciborra &
Lanzara, 1990).
8
Dorado (2006) also suggested that bricolage is always a
‘‘work in progress.’’ Oakland’s experimentation and active testing of
‘‘institutionalized definitions of orthodox practice’’ (Baker & Nelson,
2005, p. 335) frequently uncovered useful insights unforeseen by outside
analysts.
For example, Beane moved players into positions for which they had no
prior experience. Although an excellent hitter, catcher Mark Hatteberg
sustained an injury that inhibited his ability to make the essential throw
TED BAKER ET AL.22
from home to second base, effectively ending his career as a catcher.
However, recognizing that Hatteberg could still be a useful addition to his
team, Beane salvaged Hatteberg’s career by reassigning him to play first
base (Lewis, 2004, pp. 162–187). Hatteberg had never played first base
before, but he learned to do so by practicing with his wife on rain-soaked
tennis courts near their Seattle home during the off season. Hatteberg
became a competent first baseman and his hitting prowess continued to
improve. In 2007, the 37-year-old provided the Cincinnati Reds with the
best offensive performance of his career, generating an On Base Plus
Slugging (see Table 3 for definitions) percentage of .868 (vs. a career average
.776) and a batting average of .310 (vs. a career average of .274).
Another experiment involved the acquisition of aging slugger David
Justice, who, like Hatteberg, ‘‘most teams didn’t want to have anything to
do with’’ (Lewis, 2004, p. 142). Beane’s assistant Paul DePodesta described
the move this way: ‘‘He’s an experiment for us yWhat we want to see is: at
an age of physical decline does the skill maintain its level, even when a
player no longer has the physical ability to exploit it?’’ (1993, p. 150).
This bias for action and willingness to experiment was in stark contrast to
the passivity of many MLB teams facing resource disadvantages. As Lewis
(2004, p. 124) describes it, MLB teams in disadvantaged financial positions
frequently ‘‘abandon all hope of winning,’’ and simply excuse themselves as
engaging in a lengthy process of ‘‘rebuilding,’’ a process which seldom
works as intended. Statistical analyst Keri (2006b, p. 312), analyzing the
ineffectiveness of long-term planning in baseball, argued, ‘‘Having the
flexibility to adjust to opportunities ytends to work better than X-year
plans, no matter what number X represents.’’ It is important to note that the
bias for action cannot be directly inferred from Sabermetric analysis.
Statistical analysis suggested what skills and player behaviors might
contribute to winning games, but it could not suggest how a resource-
constrained team might try to assemble or deploy these skills and behaviors,
or even why it should not give up and claim to be rebuilding.
Refusal to Enact Resource Limitations
The MLB industry recipe defines what is valued as a player resource and, as
importantly, what is not. Statistical analysts challenged the recipe for two
decades, but their work had little effect on MLB despite the fact that it was
widely available. Clearly, Sabermetric ‘‘insights’’ were viewed as little more
than curiosities; academic novelties whose conclusions looked nice on paper
but were irrelevant for assessing real men engaged in the heat of combat.
How a player was to be assessed (and why) was already thoroughly
Winning an Unfair Game 23
understood and little could be done to alter the fundamental economics of
the game.
It was the A’s’ refusal to enact the limitations defined by the deeply
institutionalized baseball recipe that began to change the recipe. Although
Beane, Paul DePodesta, and Sandy Alderson were loosely guided by
statistical insights, it was their willingness to use the statistical insights
creatively and in unconventional ways that allowed the A’s to find value
where other teams saw none. The theme of refusing to enact resource
limitations suffuses the A’s narrative more than any other idea. Alderson
framed the situation this way, ‘‘We suddenly were put into the position of:
we can only afford a one-tool player. Which tool is it going to be?’’ (Lewis,
2004, p. 58). During the period through 2002, the A’s’ answer was, in
oversimplified terms, to emphasize tools that got players on base and
deemphasize tools that seemed to contribute less directly to winning and
were overpriced, including running, fielding, and hitting with power.
Subsequently, when others began to mimic the A’s approach, the answer
would change.
To other teams looking for players with more balance across the ‘‘five
tools,’’ and indeed even to the A’s own scouting staff, most players that were
attractive to Beane and DePodesta simply did not appear to be worth
employing. Bill James encapsulated the opportunities squandered by failure
to move beyond enacted resource limitations and the potential in what was
at hand to MLB teams at little cost when he described the situation of Ken
Phelps, a player he believed was inappropriately languishing in the minor
leagues: ‘‘Ken Phelpses are just available; if you want one, all you have to do
is ask. They are players whose real limitations are exaggerated by baseball
insiders, players who get stuck with a label, the label of the things they can’t
do – while those that they can do are overlooked’’ (Gray, 2006, p. 189).
Players the A’s targeted lacked most of the tools, the ‘‘good face’’ and the
‘‘body you could dream on.’’ For example, while Beane and DePodesta
coveted Kevin Youkilis (‘‘a fat third baseman who couldn’t run, throw or
field’’ (Lewis, 2004, p. 19)) because of his ability to draw walks (a way of
getting on base not included in the five tools), the scouts resisted even going to
see him. To scouts who scorned players with faces or bodies deemed
inappropriate for baseball, Beane would sometimes retort, ‘‘we’re not selling
jeans here’’ (Lewis, 2004, p. 34). The continued enactment of resource
limitations by other MLB teams and their scouts allowed the A’s to
accumulate a group of undervalued players with useful skills. Other teams
didn’t want Scott Hatteberg with his crippling injury or the aged David
Justice. Indeed, Jeremy Brown, a college player from Alabama who held most
TED BAKER ET AL.24
of the collegiate Southeastern Conference hitting records, was mocked by
one of the A’s scouts for his weight: ‘‘when he walks, his thighs stick together’’
and ‘‘if you put him in corduroys, he’d start a fire’’ (Lewis, 2004, p. 34).
But for the A’s, the refusal to enact these limitations created opportunity.
As DePodesta put it, ‘‘We don’t get the guys who are perfect ythere has to
be something wrong with them for them to get to us yWhat gets me really
excited about a guy is when he has warts, and everyone knows he has warts,
and the warts just don’t matter’’ (Lewis, 2004, pp. 142–149).
9
Indeed,
another apparent characteristic of the standard industry recipe – that traits
which did not fit the preconceived mold were ridiculed – made it easier for
Beane to operate; because others did not want to be the subject of ridicule
themselves, he could cheaply pluck players others were afraid to pick.
Following this approach, by 2002 the A’s had the best pitching staff in the
American League, ‘‘yet of all their pitchers only Mark Mulder, one of the
team’s three brilliant starters, had failed to inspire serious doubts at some
point in his career in the baseball scouting mind’’ (Lewis, 2004, p. 221). By
refusing to enact taken for granted limitations regarding what constitutes a
resource – limitations completely natural and taken for granted by other
teams – the A’s were able to assemble a winning team on a shoestring
budget; as Keri noted (2006b, p. 211) ‘‘Beane grabbed freely available talent
for next to nothing, gaining solid production from scrap-heap survivors.’’
A Certain Contrarian Impulse
Lewis claims that Billy Beane was particularly well-positioned to challenge
accepted truths in baseball because Beane’s personal experience as a player
made him simultaneously an insider and an outside critic. From his days in
high school, scouts had celebrated Beane’s prowess and carried forward the
assumption that he was destined to be a star. Indeed, so clearly was he
marked by the face,‘‘a body you could dream on,’’ and all five tools that
managers and scouts appeared to have difficulty even noticing that as he
moved through the ranks of professional baseball he simply didn’t play very
well. Beane struggled in and out of MLB right up until the day that he
voluntarily quit the game, and in a previously unheard of move, asked to be
demoted from player to scout. In Lewis’s rendering, the A’s’ challenge to
how scouts and baseball insiders think about the game was driven in part by
Beane’s need to understand and come to terms with what had happened to
him and how he had failed despite all his outward predictors of potential
and success.
Perhaps for these reasons, Beane, with DePodesta’s help and Alderson’s
support, seemed to take particular pleasure in publicly flying in the face of
Winning an Unfair Game 25
all that baseball holds sacred. Other research has described a similar pattern
of behavior among bricoleurs, who appeared to be motivated in part by
their disdain for competitors who were immobilized unless they were able to
acquire exactly the right resources for every task. Bricoleurs appeared to be
saying to their competitors, in effect, ‘‘see what I can do!’’ and their desire to
maintain this posture fed into a strong bias for action and willingness to
compete under tight resource constraints (Baker & Nelson, 2003).
Beane, too, appeared to relish his contrarian role. Rather than trying to
hide what he was doing, an approach that might have allowed him to take
advantage of others’ biases a little bit longer, Beane aimed to make trades
that caught everyone’s attention, what he called, ‘‘a Fucking A trade yone
that causes everyone else in the business to say ‘Fucking A’’’ (Lewis, 2004,
p. 179). During the 2002 draft, when the A’s had a large number of valuable
early-round draft picks, they used these picks to acquire players whom they
could probably have acquired with much lower and less valuable picks in
later rounds because other teams did not share Oakland’s assessment of
these players’ value. It appears Beane may have ‘‘squandered’’ an advantage
simply to make a point along the lines of ‘‘see what I can do!’’ To us, this
suggests the likelihood that – particularly under resource-disadvantaged
conditions – bricolage may often be driven by a contrarian impulse that
creates a bias for action and refusal to enact resource limitations, but which
in competitive circumstances also makes effective copying of the innovation
more likely because its practitioners revel in the visibility of their
unconventional actions.
Relying on the Resources at Hand
Prior studies of bricolage have included among the resources at hand both
those already under the control of an organization and those available
cheaply or for free relative to standard resources (Baker & Nelson, 2005;
Garud & Karnoe, 2003; Levi-Strauss, 1967). Because of the structure and
rules of MLB, the A’s drew primarily from two pools of resources. First, as
described above, the A’s cheaply
10
accumulated players for whom they were
able to see potential beyond their ‘‘warts.’’ Second, because of antitrust
exemptions and the rules of free agency, the Oakland A’s organization was
able to employ drafted players in the minor leagues for up to seven years at
low wages and without the threat of salary competition from other teams.
Even more importantly, if a player was moved to the major league team, the
A’s could pay the player the league minimum salary (10–15% of league
TED BAKER ET AL.26
average wages) for three years before the player could file for salary
arbitration and low wages for six years before the player became a ‘‘free
agent’’ able to enter the open market for bidding by other teams (Carfagna
et al., 2006;http://mlbplayers.mlb.com/pa/info/faq.jsp). During this time,
even if a player demonstrated the superior potential the A’s had envisioned
and became more broadly recognized as valuable, the player remained
available to the A’s at a much lower price than bidding would have
established absent the MLB’s antitrust exemption.
Because of the structure of free agency in MLB, the ability to see potential
invisible to other teams created benefits that remained available for a long
time. For example, the A’s drafted one of the best pitchers in baseball, Barry
Zito, in 1999 and were able to pay him a total of $940,000 during the three
years ending in 2002, during which time his value on the open market would
have been in excess of $10 million per year (Lewis, 2004, p. 22). Further,
even when they lost their young stars to free agency – an outcome often seen
as devastating to other teams – the A’s were able to treat these losses as an
opportunity for resource acquisition because they would then receive a
‘‘compensating’’ pick in the next year’s draft from the team who acquired
their player (http://mlb.mlb.com/mlb/events/draft/y2007/index.jsp?conten
t=order). Many teams faced with losing a star to free agency attempt to
retain that player by offering him a big increase in salary. The A’s, who did
not have the resources to compete in the free agent market, either simply let
these players become free agents or traded them. Thus, while they ‘‘lost’’
players as they became expensive-to-retain stars, they were able to garner
multiple first and second round picks in the next year’s draft that they used
to refill their pipelines with future talent which they could utilize more
inexpensively and for a longer period of time than the players they lost.
Combining Resources
Penrose (1959) argued that it is not resources themselves, but managerial
talent that creates new opportunities for organizations by identifying and
combining resources in idiosyncratic ways that generate valuable hetero-
geneity across organizations. A primary driver of the A’s ability to rely on
the resources at hand was their ability to rethink how player skills might be
combined and deployed. As noted above, because they could afford to keep
very few players once they became eligible for free agency, the A’s expected
to lose their stars. How they dealt with the impending change made such
losses less damaging to team performance.
Winning an Unfair Game 27
At the same time the A’s lost first baseman Jason Giambi to the richest
team in baseball, the New York Yankees, they also lost outfielder Johnny
Damon to the second richest team, the Boston Red Sox, and they
simultaneously needed to replace their designated hitter. While such losses
might result in declaring the need for a ‘‘rebuilding’’ year for most resource-
constrained teams, Billy Beane instead noted, ‘‘The important thing is not to
recreate the individual yThe important thing is to recreate the aggregate’’
(Lewis, 2004, p. 141). The answer? The A’s acquired the two inexpensive
‘‘has-beens’’ we discussed above – David Justice and Scott Hatteberg – and
added a third unproven player with a troubled personal history who was
also therefore inexpensive – Jason Giambi’s younger brother, Jeremy. Thus
the A’s responded to the loss of their stars to richer teams by replacing them
with three players who collectively had about the same on-base percentage
(the element of performance that the A’s were most intent on maintaining)
and who could play the three positions that had been vacated (once
Hatteberg retrained himself to play first base).
Although these changes resulted in some loss of defensive skills,
Sabermetric analysis suggested that the foregone defensive capabilities
added less value than baseball insiders commonly assumed and that it could
be compensated for by the expected increase in offensive productivity (Gray,
2006; Lewis, 2004). In other words, while the runs allowed per game might
go up marginally, the runs scored per game would be maintained at low
cost. Thus, by focusing on the possibilities inherent in combinations of
resources available cheaply rather than the particular skills instantiated in
individual players, and by being willing to accept a serviceable although
imperfect solution, the A’s managerial talent identified and created
idiosyncratic combinations of resources that provided services from inexpen-
sive players that were a reasonable replacement for the almost inevitable loss
of expensive stars.
From the A’s to MLB: Changing the Recipe
As a consequence of their success, the A’s bricolage brought Sabermetrics
into the core of MLB. The first legitimating effect of the A’s successful
bricolage and ‘‘in your face’’ attitude was that other teams noticed what the
A’s were doing and began trying to do the same thing (Pollock & Rindova,
2003; Scott, 2001; Suchman, 1995). Other resource-disadvantaged teams
hired analysts steeped in Sabermetric approaches and took their prescrip-
tions seriously. Several of Beane’s colleagues were hired away to become the
TED BAKER ET AL.28
general managers of other teams. For example, J.P. Ricciardi, former
Director of Player Personnel with the A’s, became the general manager of
the Toronto Blue Jays in 2001.
In addition, some resource-advantaged teams recognized that Sabermetric
approaches were not only advantageous to resource-constrained teams.
Consequently, Paul DePodesta, Beane’s top aide, was hired as the GM of
the Los Angeles Dodgers in 2004. Further, at one point the Red Sox had
actually reached an agreement to hire Billy Beane himself, although Beane
quickly decided to renege on the contract and stay with Oakland. Instead,
John Henry, the erstwhile fantasy baseball sabermetrician and new owner of
the Red Sox, hired Bill James as an analyst and advisor and Theo Epstein, a
baseball outsider and Sabermetrics aficionado, as the youngest general
manager in the history of baseball. Sabermetrics was further legitimized in
2004, when the Boston Red Sox, with a team designed using Sabermetric
principles, were finally able to win the World Series for the first time in 86
years (Goldman, 2005; Mnookin, 2006). The current general manager of a
competing team indicated to us in an interview that common parlance in
MLB now identifies teams’ strategies as falling along a range from
traditional scouting-dominated to heavy reliance on Sabermetric statistics.
The incorporation of Sabermetric insights into MLB no longer relies on
bricolage, but is instead being institutionalized as a commonplace and
accepted routine in baseball’s industry recipe.
Still, not every team has adopted the new Sabermetrics gospel; indeed,
even as Sabermetrics and Moneyball have become a part of everyday
baseball parlance, some serious baseball thinkers have rejected many of its
tenets. For example, the Atlanta Braves, whose extraordinarily successful
general manager John Schuerholtz moved up to President of the team in
October 2007, continue to follow an approach that is explicitly ‘‘anti-
moneyball’’ (Schuerholz & Guest, 2006; Shanks, 2005). Further, the debate
over the relative value of scouting versus statistical analyses continues
unabated (Perry, 2006).
Overall, however, Sabermetrics has flourished. As we noted above, a
primary effect of many teams chasing the sorts of players that the A’s
showed could be accumulated cheaply and deployed effectively has been to
increase the price of those sorts of players to something more closely aligned
with their newly recognized productivity (Hakes & Sauer, 2006). Saber-
metrics has also flourished as an analytic activity. Although the insights of
Bill James, Voros McCraken, and others have been rendered private as these
analysts have become MLB team employees, other analysts, such as those
associated with Baseball Prospectus, Inc., continue to make prodigious
Winning an Unfair Game 29
strides in improving the statistical analysis and objective understanding of
patterns of performance in baseball (Keri, 2006a).
Despite the impressive scholarship of such analyses, because Sabermetrics
has become a legitimate tool of MLB (and has even spread to other sports),
it may now be much more difficult for any team to create advantages
through application of these insights alone. Indeed, the powerful statistical
tools that have been developed are increasingly directed at answering
questions that are interesting for aficionados but relatively trivial for
managing a team; for example, what would happen to team performance
if you combined the complementary physical attributes of two specific
players – for example if the fastest runner in the league was also the best
hitter? (Keri, 2006a). The initial space for competitive maneuvering that the
A’s created through bricolage has thus largely been closed (Isidore, 2006).
Beyond Sabermetrics: Bricolage and the Resource-Disadvantaged
Sabermetrics is increasingly part of the baseball recipe; bricolage is not. An
important question, therefore, is what did the A’s do once the rest of the
league adapted to their competitive maneuvering? We lack the detailed sorts
of detailed insider reporting that Lewis (2004) and others provided on the
A’s earlier activities, but watching Beane and the A’s is now almost a
spectator sport in itself, and the available evidence suggests that, as much of
the rest of the league adopted Sabermetrics, the A’s continued engaging in
bricolage even while they veered away from Sabermetric insights. As the
Yankee’s General Manager Brian Cashman (reported in Heyman, 2006)
noted, ‘‘Billy Beane is a very bright individual who knows there are many
different ways to skin a cat and find a way to be successful yEvery year he
comes up with a different game plan and finds a new way to win. He’s no
one-trick pony.’’
Oakland continued to maneuver and experiment with new ways of
deciding which players they want and how to use them. Perhaps the most
surprising change was the A’s increased emphasis on defense (Wilson, 2006).
As noted above, one of the core tenets of the A’s earlier approach was the
idea that defensive inadequacies were best dealt with not by shoring up the
team’s defense, but by further improving its offense (Lewis, 2004). Indeed,
despite their regular season successes, one of the continued knocks against
the A’s was that they were unable to make it past the first round of the
playoffs. Beane himself was famously quoted by Lewis as noting ‘‘my shit
doesn’t work in the playoffs’’ (Lewis, 2004, p. 275). An analysis exploring
TED BAKER ET AL.30
this issue (Silver & Perry, 2006) concluded that Oakland’s failure to advance
in the playoffs was due to their weaknesses in pitching and defense.
Similarly, one of the key statistical points around which the A’s earlier
behavior pivoted was rejection of the scouting norm of placing high value on
the potential of high school players, because of the difficulty in predicting
MLB performance from high school performance and James’s Sabermetric
demonstrations of the high risk that high school stars will not make it to the
major leagues. Early on, Beane and DePodesta caused the A’s to focus their
draft choices on more developed college players and to treat statistical
measures of their college play as useful predictors of MLB potential.
However, as other teams began following that pattern the A’s began
pursuing high school players other teams left available (Heyman, 2006).
What was undervalued changed, and the direction of the A’s bricolage
changed as well. This approach resulted in continued success for the A’s,
culminating in their making it to the 2006 American League Championship
Series for the first time since 1992, where they were swept by the Detroit
Tigers.
In the first five years following this ‘‘golden era,’’ the A’s were unable to
duplicate their success. While none of their seasons have been terrible, their
average won–loss record hovered under 50% (.471) and they continually
failed to make the playoffs (see Table 2). Nevertheless, with a retooled
approach and a shift in focus, the A’s returned to the playoffs in 2012
following a furious September charge in which they caught the Texas
Rangers just in time to return to postseason play.
The fortunes of Beane’s prote
´ge
´s and Sabermetric analytic experts, J.P.
Ricciardi and Paul DePodesta, offer further evidence that it was messy
bricolage, and not Sabermetrics per se, that led to Oakland’s success.
Ricciardi never achieved the same degree of middle market success with the
Toronto Blue Jays that Beane displayed with the A’s. Between 2002 and
2007, Ricciardi’s team finished third or lower in the AL East Division five
out of six years. It should be noted that the Blue Jays are competing in the
same division as the Yankees and the Red Sox – a challenge that the A’s did
not have to directly face.
Paul DePodesta was hired to become the GM for the Los Angeles
Dodgers, but his career as a GM was short-lived. After a promising start in
2004, when the Dodgers won the NL West Division, he was fired by the
Dodgers at the end of the 2005 season for making what were perceived to be
a number of disastrous trades during the 2004–2005 off-season, trades that
were blamed for the Dodgers’ second-worst single season record in club
history (http://en.wikipedia.org/wiki/Los_Angeles_Dodgers). After a brief
Winning an Unfair Game 31
period of unemployment, DePodesta was hired in 2006 as special assistant
for baseball operations by the San Diego Padres. Thus, despite their
involvement in the early, successful applications of Sabermetrics, neither
Ricciardi nor DePodesta were able to replicate their original success.
DISCUSSION
How do Resource-Disadvantaged Entrepreneurs Compete?
In terms of the primary questions that motivated this chapter, our study
demonstrates that by engaging in bricolage, resource-disadvantaged
participants can make room for competitive maneuvering even when they
are constrained to compete at the core of a highly institutionalized field.
Explaining the dynamics of such competition is essential to understanding
the processes through which entrepreneurs, whether at the helm of new
organizations or existing ones they seek to transform, can find ways to
compete against richer and entrenched competitors. Unlike much work on
so-called institutional entrepreneurship, our study shows that resource-
constrained entrepreneurs needn’t create substantial changes to regulatory
and normative institutions in order to create a space in which to compete.
Instead, successful challenges to cognitive institutions, through bricolage or
some other process can be enough to allow resource-constrained entrepre-
neurs to compete even in highly structured and institutionalized industries
dominated by wealthy firms.
We showed that MLB is a highly institutionalized field, and that when the
new ownership of the A’s created a resource-disadvantaged situation, the
leadership of the A’s adopted a pattern of behavior that rejected the bonds
of the existing industry recipe and closely matched prior descriptions of
bricolage. Refusing to hide passively behind excuses about financial
determinism and ‘‘rebuilding,’’ or to enact taken-for-granted resource
limitations, the A’s were able to compete effectively against teams with far
more money to spend.
Our answer to the question of how such a resource-disadvantaged
competitor can continue to maneuver for advantage when its innovations
result in adaptive responses by competitors is more tentative. The evidence
suggests that the A’s are continuing to engage in bricolage, rejecting some of
the earlier findings of Sabermetrics while many other MLB teams are actively
following its tenets. The A’s continued to perform well for a time with a team
possessing substantial differences from those that Beane and DePodesta built
TED BAKER ET AL.32
earlier, but have struggled in more recent years. Future research should
continue to explore the sustainability of bricolage as a way to maneuver for
advantage in highly institutionalized competitive environments.
The Nature of Organizational Resources
The answer to the second major question motivating our study (what could
be learned about the nature of resources from the creative maneuverings of
bricoleurs?) supports the line of research extending from Penrose (1959),
that the distinctive, advantage-generating characteristics of resources are
based on the capabilities of managers to combine and deploy them in
idiosyncratic ways (Baker & Nelson, 2005;Mishina, Pollock, & Porac,
2004). It also supports the Weickian notion that resource limitations are
enacted and the claim that bricolage includes a bias for testing taken-for-
granted limitations (Baker & Nelson, 2005; Weick, 1979). In a mature
institutionalized field, it is ‘‘natural’’ (Berger & Luckmann, 1967; Schutz,
1944) to assume that the industry recipe describes the correct use and
appropriate valuation of useful resources. This was the case with baseball’s
valuation and devaluation of player attributes and it helps to explain why
Sabermetric insights could exist for so long in parallel to the routine
behavior and decision making of MLB teams, without causing substantial
changes to the baseball recipe.
Our study dispels the notion that consistent adherence to Sabermetrics is at
the core of the A’s continued success, and shows instead that Sabermetrics
is now a part of the industry recipe that defines the context in which the A’s
now maneuver for advantage through bricolage. Our study supports the
Penrosian argument that, to a large extent, resources are what organizations
make of them. This argument provides some comfort for the majority of
entrepreneurial firms who strive to persist and flourish despite severe resource
deficits relative to larger, more established competitors. Firms that can
achieve consistently superior financial results, that can dominate their
competitors, and that can sustain resource and competitive superiority are
rare indeed. Yet, our study suggests that even under the most limited of
circumstance, firms can and do find ways to be resourceful and achieve
viability and relative success. It also helps to explain why trying to compete
on the same basis as richer competitors is oftentimes a mistake for the typical
resource constrained start-up, and suggests that the willingness and ability
to engage in bricolage may be an effective entrepreneurial strategy for using
limited resources, even in mainstream and highly institutionalized industries.
Winning an Unfair Game 33
Contributions to Institutional Theory Research
Our study contributes to the stream of research in institutional theory that
seeks to explain sources of institutional change. As we went to some lengths
to demonstrate, MLB is extraordinarily institutionalized, with a mature
industry recipe and patterns of recruitment and socialization that contribute
to a high degree of stability. MLB teams are constrained to compete within a
rigid and stable set of rules guiding competition on the field, while laws, court
rulings, regulatory procedures, and even public opinion guide many of the
behaviors off the field. Prior institutional research would suggest that under
these circumstances, resource-disadvantaged organizations are unlikely to be
able to create space for effective competitive maneuvering and even more
unlikely to create innovations that generate institutional change.
In contrast, our study extends institutional theory’s grasp of endogenous
change by focusing specifically on the cognitive institutions susceptible to
change and by describing a mechanism through which such innovations may
occur. The fact that Sabermetric truths lay underutilized for so many years
throws into stark relief the limitations of simple knowledge or discovery as a
means for resource-poor firms to maneuver competitively at the core of
institutionalized fields, and reinforces the primacy of stability and constraint
in highly institutionalized fields. Sabermetrics was not employed to
undermine the MLB recipe until a set of bricoleurs wielded it to support
their belief that they need not accept their own apparent limitations. Still, it
was but one tool among many used by the A’s to challenge the taken-for-
granted practices and constraints of MLB. The bricolage we have described
was not easy, obvious, or simple to sustain.
An important advantage of our study is that it takes place in a context in
which institutional maturity and the nature of the field leaves no
‘‘periphery’’ to which resource-constrained organizations can move; every
team plays a similar schedule against the same sets of competitors. There is
no movement to another, more open field (Kraatz & Zajac, 1996); MLB
teams have no other league to which they can move. The legal environment
and the rules of the game are extremely resilient and slow to change. Thus,
resource-disadvantaged teams can maneuver mainly through bricolage –
through finding ways to test enacted limitations and to combine the
resources at hand in novel ways. Indeed, the A’s bricolage challenged the
cognitive elements MLBs institutions, leaving the regulatory and normative
pillars largely unchanged. The A’s were not engaged in institutional
entrepreneurship, but were simply trying to win more games. Ironically,
by demonstrating that a resource-constrained team could maneuver for
TED BAKER ET AL.34
advantage, the A’s may have reduced the pressure on MLB to make the top-
down regulatory changes necessary to make baseball less unfair. The success
of other small market teams in recent years, such as the Tampa Bay Rays,
Minnesota Twins, and Milwaukee Brewers also likely reduce the pressures
to enact significant normative or regulatory changes.
The context of our study allowed us to closely examine an important
example of bricolage in MLB, but it does not allow us to address
endogenous institutional change in fields where participants face different
sets of constraints on their competitive maneuvers. An important question
for future research involves trying to understand more generally the effects
of highly institutionalized environments on how resources are valued and
combined. For example, prior to the changes wrought by the A’s, the
institutionalization of baseball and its powerful recipe clearly formed an
effective barrier against new ideas and approaches. On the other hand, by
retarding incremental changes to how players were valued and combined,
this same institutionalization created a substantial opportunity for an
organization to compete through bricolage. Future studies should examine
the interplay between institutionalization as a drag on change and the
slowness of change as a source of opportunity for effective competition
through bricolage.
CONCLUSION
As numerous analysts (e.g., Hakes & Sauer, 2006; Lewis, 2004) have noted,
MLB is extraordinarily information rich and highly competitive. The A’s
creation of valuable resources from combinations of players available at low
cost and the subsequent revaluation of player skills across MLB suggest that
other economically and culturally important fields may present substantial
opportunities for competing through skillful bricolage. And even in mature
and deeply institutionalized organizational fields, bricolage may be an
important engine of endogenous change for firms of any age or size.
NOTES
1. Derived from the Society for American Baseball Research, ‘‘Sabermetrics’’
refers to a set of statistics aimed at providing more valid measures of contributions
to run scoring and run prevention than prior, simple statistics.
Winning an Unfair Game 35
2. Arguably, the use of Sabermetrics allowed the A’s to obtain better players at
lower costs or better selections of players in annual drafts than other teams were
obtaining. It also gave them advantages in trades and in retaining high draft choices.
Even though their focus was initially on hitting, the advantages spilled over into
pitching in that they had better draft picks than other clubs. This is not to say that
they did anything special in the years of 2003 and 2006, but simply that their better
overall performance across several years placed them higher in the standings. In 2003
and 2006 this better performance resulted in playoff appearances.
3. Even executives of small market baseball teams with extremely limited
resources are continually barraged by pleas to ‘‘play the game’’ as do large market
teams, regardless of the success of the team or the ability of the teams to take this
path. For example, Jim Souhan, the primary baseball reporter for the Star Tribune in
Minneapolis, criticized the Twins’ management for not behaving like the Yankees,
Red Sox, Angels, and Cubs in an article published on October 3, 2007, the day the
2007 playoffs commenced. The tagline read, ‘‘The Twins often get applauded for
their low budget successes, but some of the big spenders are playing October ball this
year.’’ Yet the Twins had been in the playoffs five of the previous six years. Terry
Ryan, the Twins’ general manager, resigned that August despite his success in the
face of overwhelming disadvantages.
4. This is one reason steroid use poses a huge conundrum, because it muddies
fans’ abilities to make comparisons, for example, of the performance of Babe Ruth in
the 1920s and 1930s with that of Barry Bonds in the 1990s and 2000s.
5. The belief in the ability of scouts to ‘‘know’’ talent intuitively or by how a player
looks goes back at least 100 years. Leigh Montville, in his biography of Babe Ruth,
reported the legend of the scout Jack Dunn who signed Ruth out of a Baltimore area
orphanage: ‘‘[Jack Dunn] would check out the player the way a trainer or potential
buyer might look at a young Thoroughbred horse. If he liked the player’s size, the
way the player moved just walking across a room, he might make an offer.
Dunn sometimes never even saw the player play a game’’ (Montville, 2006, p. 33).
6. The core batting statistics by which offensive performance had been tradi-
tionally judged include the three numbers that comprise the elements of the ‘‘triple
crown’’: home runs, runs batted-in, and batting average. These simple measures have
been somewhat supplanted in the post-Sabermetric era by more complex metrics such
as ‘‘on-base-plus slugging’’ (OPS) and ‘‘wins above replacement’’ (WAR).
7. Perhaps because of the longer history of and greater availability of hitting
statistics, Bill James’ earliest work was on analyzing statistics aimed at uncovering
contributions to the number of runs a team scored over the course of a season. It was
these insights that Beane’s brain trust focused on in gaining competitive advantage in
hitter evaluation. However, this advantage also allowed the A’s to achieve superior
pitching selections, because they were able to delay picking undervalued hitters in
draft competitions, using earlier picks for promising pitchers, and they were able to
gain more draft selections by trading overvalued hitters. In essence, their valuation
advantage enabled run-scoring parity at a much lower cost and it enabled
opportunities to acquire superior young pitching.
8. We might add that because in MLB all such strategic moves are fully
transparent, even strategies that are nearly ‘‘perfect’’ can be quickly imitated and are
also rendered temporary.
TED BAKER ET AL.36
9. As is discussed in the next section, Billy Beane’s personal experiences and
cognitive disposition play an important role in this story; however, the infusing of
these bricolage-type cognitions and attitudes into the mindset and behaviors of the
entire organization was necessary to make them work.
10. There are two main costs to acquiring an MLB player: compensation to the
player’s prior team and subsequent salary costs. In theory, a player can be just about
‘‘free’’ because prior teams trying to unload players sometimes subsidize their
salaries with new teams. For the most part, though, the players we refer to in this
study were relatively inexpensive but not free; henceforth we will use the words
‘‘cheap’’ or ‘‘cheaply.’’
ACKNOWLEDGMENT
We would like to thank Jim Detert, Matt Kraatz, Myleen Leary, Mike
Pfarrer, Steve Ross, Jaume Villaneuva, and Marvin Washington for their
helpful comments on earlier drafts of this manuscript.
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