Development and validation of the Sport Rivalry Fan Perception Scale (SRFPS).
Havard, Cody T. ; Gray, Dianna P. ; Gould, James 等
In college sport, fans dedicate large amounts of resources to show
their affiliation with their favorite teams and schools (Gibson,
Willming, & Holdnak, 2002). One way to display that affiliation is
by following the rival(s) of the favorite team. The relationship between
fans, favorite teams, and favorite team rivals add to the excitement of
consuming sport. For this reason, it is short sighted to address sport
spectatorship without a discussion of the rivalries that occur between
teams, players, and fans. At the collegiate level, rivalries fill out
season schedules, make for entertaining contests, and add fervor to the
competitive nature of sport. Further, many rivalries date over 100
years, and have become engrained in the cultures of their respective
schools (Corbet & Simpson, 2004; Shropshire, 2006; Tucker, 2007).
Kilduff, Eifenbein, & Staw (2010) have identified the
antecedents to rivalry, however there is little research explaining what
sport rivalry means to fans, or how they are affected by the phenomenon.
Additionally, no operational definition of sport rivalry currently
exists in the sport or consumer behavior literature, and it is important
to study how fans perceive teams identified as rivals to further the
understanding of intergroup relations. For this reason, the current
study sought to address the lack of empirical investigation into the
phenomenon of sport rivalry by quantitatively identifying factors that
explain fan perceptions of teams identified as their favorite
team's rival. The following research question guided the study:
What identifiable factors explain rivalry?
Review of Literature
The psychology of fan and consumer behavior is an area that has
received considerable attention by academics over the past two decades.
Zaichkowsky (1985) indicated with the Personal Involvement Inventory
(PII) that two people could perceive the same product differently. In
sport, people tend to be introduced to the "product" through
family (Coakley, 2004; de Groot & Robinson, 2008; Havard, 2012) and
consume with friends sharing similar team or activity interests
(Dietz-Uhler, Harrick, End, & Jacqemotte, 2000). Fan identification
with a team can offer individuals opportunities to fulfill socialization
needs that can lead to increased mental health and self esteem
(Brascombe & Warm, 1991; Crocker & Park, 2004; Wann, 2006).
People tend to identify with others to enhance their social-identity
(Tajfel & Turner, 1979) and influence others' perceptions of
themselves. One way for a fan to do this is to identify with a sport
team (Warm, Brame, Clarkson, Brooks, & Waddill, 2008). For this
reason, literature addressing social and fan identification begins the
discussion.
Social and Fan Identification
Tajfel (1978) asserted that people strive to build and maintain a
positive concept of themselves, and desire to be favorably viewed by
others (Tajfel & Turner, 1979). Social identity theory explains how
this self-concept affects the types of people and groups with whom
individuals associates (Tajfel, 1981). In order to increase
self-identity and esteem, people will join with others who share similar
characteristics (Tajfel & Turner, 1979). When people with similar
interests join together, they form social groups (Turner, 1982), and
these groups tend to adopt a collective identity in order to distinguish
between members and non-members (Ashmore, Deaux, & McLaughlin,
2004).
Heider (1958) introduced balance theory to help explain how and why
individuals interact with others. Through unit relations, balance theory
states that things are connected in some way and that people engage in
dyadic and triadic relationships, whether positive or negative, in order
to maintain a balanced state of being. In a dyadic relationship, if
person A likes person B, balance is attained if that feeling is
reciprocated (i.e., B likes A). In a triadic relationship, a balanced
state is attained if all three people like each other or if, as posited
by Heider, two negative relationships and one positive relationship are
present. This triadic relationship is of particular interest to the
study of sport rivalry, as it helps to explain the adversarial
relationship fans often have with their favorite team's rival. For
example, a fan that has a positive relationship with his or her favorite
team will have a negative relationship with the favorite team's
rival because of the competitive, or negative relationship the favorite
and rival teams share.
Cialdini et al. (1976) utilized the unit relations principle in
balance theory to introduce Basking In Reflected Glory (BIRGing), which
explains how fan association and identification with a favorite team is
affected by game performance. In a study conducted at seven schools with
prominent college football programs, the authors found that people were
more likely to wear team apparel and use associative words the Monday
following a win than a non-win. Further, Cialdini and Richardson (1980)
found that individuals highly identified with their favorite team or
university would rather derogate, or "Blast" (p. 406) the
opposing team, university, or fans than distance themselves from the
favorite group when faced with reflected failure.
In a similar vein, the term Cutting Off Reflected Failure (CORFing)
describes the tendency of people to distance from the perceived failure
of a team, person, or group (Snyder & Fromkin, 1980; Snyder,
Lassegard, & Ford, 1986). Regarding highly identified sport fans,
Wann and Branscombe (1990) found that fans possessing a strong
identification with their favorite team were more likely to BIRG and
less likely to CORF for long periods of time as compared to fans
possessing a weak identification with their favorite team. Bizman and
Yinon (2002) assert that highly identified fans may be more likely to
CORF but continue, and even increase their involvement with the favorite
team after feelings associated with a loss have dissipated. Groups of
opposing fans varying in levels of identification often interact when
supporting their favorite teams, and these interactions lead to a review
of intergroup relations and rivalry.
Intergroup Relations and Rivalry
It is an inherent attribute of humans to strive for high
self-esteem (Crocker & Park, 2004), and the mere presence of another
can motivate an individual to act in a certain way to display mastery
(Deci, 1975), or somehow compare favorably with someone else (Mowen,
2004; Triplett, 1897). For this reason, people will participate in
activities where they can exhibit a level of self-efficacy, and one way
for a sport fan to do this is through the vicarious experience of
supporting their favorite team (Bandura, 1977). By BIRGing, sport fans
feel as though they are part of the successful team, and that they can
achieve personal goals (Cialdini et al., 1976).
When groups form and share a collective identity (Ashmore et al.,
2004), they tend to show favoritism toward in-group members and
ostracism toward out-group members. This is known as in-group bias
(Tajfel & Turner, 1979), and the Robbers Cave Experiment (Sheriff,
Harvey, White, Hood, & Sheriff, 1961) was one of the first studies
to investigate this phenomenon. Participants in the study were grade
school boys in a summer camp setting split into two teams and given the
opportunity to compete against each other. During the competitive phase
of the study, the teams displayed in-group bias (e.g., team shirts) and
out-group ostracism (e.g., vandalizing campsites of the other team) to
the point that researchers had to separate the boys on multiple
occasions.
In-group bias is also present in the descriptions individuals give
of other people (Brewer, 1979). This is known as Linguistic Intergroup
Bias (LIB), and asserts that individuals tend to describe in-group
actions more favorably and abstractly than out-group actions (Maass,
Arcuri, Salvi, & Semin, 1989). LIB is present in sport in the way
fans evaluate team and player performance (Wann & Thomas, 1994), and
the sportsmanship of in-group and out-group fans (Wann & Dolan,
1994; Wann & Grieve, 2005).
The disposition of mirth and sport disposition theories further
help to explain in-group bias in intergroup relationships, and the
feelings between fans of rival teams in particular. Disposition of mirth
theory (Zillmann & Cantor, 1976), similar to the German term
schadenfreude (Kahle & Close, 2011), states that a person will feel
joy if someone he or she likes is successful and displeasure if that
person experiences failure. Particular to sport, sport disposition
theory asserts that fans will cheer when their favorite team is
successful and the favorite team's opponent is unsuccessful when
the two teams are playing each other (Zillmann et al., 1989).
Rivalry in sport can affect a person's physiological reactions
(Hillman, Cuthbert, Bradley, & Lang, 2004), perceptions of a
team's sponsors (Davies, Veloutsou, & Costa, 2006), and the
likelihood to help others in distress (Levine, Prosser, Evans, &
Reicher, 2005). Additionally, Lee (1985) asserts that rivalries have the
ability to strengthen in-group bias and result in hostility among fans
of rival teams. This has certainly been the case with rabid soccer fans
commonly referred to as soccer hooligans (Spaaij, 2008). Some authors
have asserted that team identification or the presence of a rival did
not necessarily increase fan aggression (Dimmock & Grove, 2010;
Lewis, 2007), while other research has found that fans would be willing
to commit anonymous acts of violence, even murder, against the star
player and coach of a rival team (Wann, Haynes, McLean, & Pullen,
2003; Warm, Petersen, Cothran, & Dykes, 1999). The unfortunate story
of a University of Alabama fan poisoning the Toomer's Corner trees
near the Auburn University campus is an example of fans displaying
antisocial behavior toward a rival team (Schlabach, 2011).
The preceding literature review helps explain the underlying
theories of rivalry in sport however, there is currently little research
addressing how fans feel about their favorite team's rival. It is
difficult to properly measure the effects of sport rivalry on fan
psychology and behavior absent a valid measurement tool. Thus, the
following section details the methods used in the development and
validation of the scale.
Methods
Instrument Development
In order to address the perceptions of fans toward their favorite
team's rival, the technique for developing marketing measures
identified by Churchill (1979) was used. Churchill's technique
requires the researcher to: 1) specify the construct(s) being explained,
2) generate sample items, 3) collect data to initially test items, 4)
purify the measure, and 5) collect data to assess reliability and
validity.
Specify Construct. In order to identify the construct of rivalry in
sport, a review of the existing literature regarding fan behavior and
team identification was conducted (Creswell, 2005). Utilizing the
existing literature, general interview questions regarding rivalry in
sport were developed. In particular, these questions gauged
participants' feelings regarding their favorite team and the rival
team in direct and indirect competitive situations.
Generation of Sample Items. In order to generate sample items to be
tested, 15 semi-structured interviews using the constructivist viewpoint
(Crotty, 1998) and grounded theory (Creswell, 2007) were conducted over
one calendar year. Interview participants were asked to identify their
favorite team's rival to provide personal context for the study,
and transcripts were used to identify trends regarding fan perceptions
of favorite and rival teams. A list of 112 statements was compiled to
address the on-field successes and failures of the favorite and rival
teams, and the indirect competition (i.e., when the rival team is
playing someone other than the favorite team) of the favorite
team's rival. Next, in order to ensure the statements properly
measured the construct, an expert panel was utilized (Churchill, 1979).
The five individuals that served on the expert panel are well known for
their work in the areas of fan identification, consumption, and
behavior.
Initial Item Testing. Following an initial review by the expert
panel, a sample of fans reached through online web sites of teams
competing in the football bowl season during December 2010 and January
2011 was used for the first sample. Participants in the first sample
were directed to take the survey on formsite.com, and completed surveys
were analyzed using Exploratory Factor Analysis (EFA) in SPSS 18
(Tabachnick & Fidell, 2007).
Purify the Measure. Following the data analysis of the first
sample, the expert panelists again reviewed the construct, and
identified factors and items to determine any areas of concern regarding
question clarity and redundancy. During the second expert panel review,
some items were deleted or added to ensure that the scale properly
measured the sport rivalry construct.
Collect data to assess reliability and validity. A second sample of
374 fans was collected during February and March of 2011 using
participants reached through in-person Self-Administered Questionnaires
(SAQ) (Lohr, 2008) and online protocol. SAQ participants were reached at
three National Collegiate Athletic Association (NCAA) Division I
men's basketball games in the Mountain West region. Online
participants in the second sample were reached through team-specific fan
web pages and administered the survey via formsite.com.
Instrumentation and Distribution
The final version of the survey sent to the first sample contained
items measuring rivalry (37 questions), combined with demographic (3
questions), favorite team (8 questions), and rival team information (3
questions). Participants were asked to identify their favorite
team's rival, and indicate their perceptions toward the rival using
a 7-point Likert-type scale (1--Strongly Disagree, 3--Neutral,
7--Strongly Agree).
SAQ protocol was used because it gives participants freedom to
respond in the manner they desired (de Leeuw & Hox, 2008). An online
protocol was utilized because it allowed for a wider sample to be
reached (Gaiser & Schreiner, 2009), and visitors to a specific site
were given the opportunity to complete the survey (Manfreda &
Vehovar, 2008). Online participants in the first and second sample were
given one reminder to take the survey during collection, and SAQ
collection took place at three college basketball games in an attempt to
reach the most respondents (de Leeuw, Hox, & Dillman, 2008; Miller
& Smith, 1983). Attempts to ensure no one under the age of 18
completed a survey were taken in both the SAQ and online distribution
methods. As an incentive, participants in both samples and collection
methods were given a chance to enter for one of eight $25 VISA gift
cards.
Results
An operational definition of sport rivalry was developed and
refined through the expert panel process in the current study along with
the scale, and it is helpful to introduce such definition at this point.
Sport rivalry is defined as a fluctuating adversarial relationship
existing between two teams, players, or groups of fans, gaining
significance through on-field competition, on-field or off-field
incidences, proximity, demographic makeup, and/or historical
occurrence(s). With the preceding definition, it is now prudent to
present the results of the scale development process.
Following a pilot study conducted on the popular online social
networking site Facebook, the first expert panel reviewed the scale and
survey containing the list of 37 items addressing rivalry along with the
external questions (14 items). It was suggested by the expert panel that
the Out-group Consumption (OC) factor be deleted from the survey because
the factor was measuring consumption rather than perception. It was also
suggested that the Out-group Linguistic Bias (OLB) factor be renamed to
better represent the items explaining the factor. For this reason, the
factor was renamed Out-group Sportsmanship (OS). Additionally, it was
advised that team identification information be added to the survey for
future use. For this reason, the Team Involvement Inventory (TII) was
added to the survey (Trail, Fink, & Anderson, 2003).
Of the 587 participants in the first sample who initially started
the survey, 457 completed the instrument and provided useable data, for
a completion rate of 78%. Male (89.7%) football fans (98.2%) made up the
vast majority of respondents in the first sample, and 59.4% of
participants were 18 to 40 years of age. The data were analyzed using
EFA with promax rotation in SPSS 18 and factors were identified using
the Kaiser criteria, which identifies eigenvalues over 1.0 (Tabachnick
& Fidell, 2007). The promax rotation consisted of four factors, 15
items and explained 72.2% of the variance. Items were identified by
loadings greater than .40, which represent component salience
(Guadagnoli & Velicer, 1988), and not double loadings greater than
.50.
Results from the EFA were submitted to the second expert panel, and
it was suggested that the Competition/Vicarious Achievement factor be
renamed Sense of Satisfaction (SOS). An additional item was added to
both the Out-group Sportsmanship (OS) factor and the SoS factor.
Further, one SoS item was replaced because it did not properly measure
the factor. It was also suggested to add questions addressing favorite
and rival team consumption habits to the survey. The survey distributed
to the second sample consisted of 45 questions, with 17 items addressing
rivalry in sport.
The second sample consisted of fans following their favorite teams
online and attending live games. Of the 387 participants that started
the online survey, 292 finished the survey and provided usable data, for
a 75% completion rate. In addition, 82 of the 100 participants that
started the SAQ survey provided finished instruments with usable data,
for a completion rate of 82%. Using both the online and SAQ distribution
methods, 374 participants provided usable data from the second sample.
Again, male participants (85.3%) made up the majority of respondents.
Participants followed football (44.9%) and basketball (42.5%) teams at
about the same rate and 65.2% were 18 to 40 years of age.
Data from the second sample were analyzed using Confirmatory Factor
Analysis (CFA) in LISREL 8.8. The final model consisted of four factors
and 12 items, which are presented in Table 1. The factors identified
were 1) Out-Group Competition against Others (Indirect) (OIC), 2)
Out-Group Academic Prestige (OAP), 3) Out-Group Sportsmanship (OS), and
4) Sense of Satisfaction (SOS).
Fit indices showed good fit for the model, and can be found in
Table 2. The Non-Normed Fit Index (NNFI) was acceptable according to
Tabachnick and Fidell (2007). Another method commonly used to evaluate
model fit, the Comparative Fit Index (CFI) was also acceptable (Hu &
Bentler, 1999). The Standardized Root Mean Square Residual (SRMR), and
the Root Mean Square Error of Approximation (RMSEA) also indicated
strong fit for the model. The [chi square] value (74.64) for the model
was statistically significant at p < .05 (df = 48).
Chi square scores showing correlations among factors are presented
in Table 3 and among items In Table 4 (Glass & Hopkins, 1996). The
reliability of the scale was acceptable, indicated by the
Chronbach's a for the four factors ranging from .77 to .91. The
measure proved to demonstrate acceptable convergent and discriminant
validity, as indicated by the Average Variance Extracted (AVE) scores
(Fornell & Larcker, 1981).
The Sport Rivalry Fan Perception Scale (SRFPS) demonstrated good
model fit, and is a reliable and valid measure of fan perceptions toward
a favorite team's rival. Table 5 identifies the final SRFPS, which
contains four factors and 12 items, and can be used to properly measure
fan perceptions of rival teams.
Discussion
The purpose of the current study was to develop and validate a
scale to measure fan perceptions toward the team identified as their
favorite team's rival. The four-factor, 12 item SRFPS was validated
on two groups of college football and basketball fans, and was
determined to be an acceptable measure of fan perceptions toward their
favorite team's rival. This discussion will address the theoretical
implications of the SRFPS, limitations to the current investigation, and
areas for future study.
Implications
Previous research has used rivalry in sport as a variable to
explain fan behavior (Davies et al., 2006; Hilman et al., 2004; Luellen
& Wann, 2010; Mahony & Moorman, 1999; Sierra et al., 2010;
Spaaij, 2008; Warm et al., 2003; Wann et al., 2006), but until now
virtually no research existed explaining what a sport rivalry means to
fans or how they perceive their favorite team's rival. Providing an
operational definition of sport rivalry, along with the development and
validation of the SRFPS provides the theoretical basis for future
researchers to properly measure fan perceptions toward a rival team.
Although further use and validation of the SRFPS is recommended, it can
be used in its current form by academics and practitioners studying
variables of fan behavior to differentiate fans based on their
perceptions of a rival team in collegiate football and basketball.
One way the scale can be used is in the study of fan behavior
toward a favorite team or conference. If academics can properly measure
the perceptions fans have for their favorite team's rival, they can
begin to use the scale in conjunction with other variables and scales to
gain a better understanding of how the presence of a rival affects fan
behavior. The SRFPS provides another way for academics to continue the
study of intergroup relationships, and lends support to the disposition
of mirth theory (Zillmann & Cantor, 1976). The various forms of
rival derogation stated by fans in the current study (e.g., "Texas
Shorthorns", "Kuck Fansas", "Dirty
Hillbillies") is consistent with prior research (Wann et al., 1999;
Wann et al., 2003).
Limitations
The distribution method through online surveys and in-person SAQ is
a possible limitation, as potential respondents were inevitably missed.
This is a product of the availability of fans through online and
in-person mediums. The SAQ was distributed at college basketball games
in reasonable proximity to the researcher, and attempts to distribute at
more high-profile games was not logistically possible. Another
limitation worthy of mention is that rival team names were piped (i.e.,
visible) throughout the online survey to add salience for the
participant (Luellen &Wann, 2010); this option was not available on
the SAQ instrument.
The online version of the survey was posted on fan pages that did
not require a paid subscription. It was decided that this method was the
best way to reach fans that may not have the financial means or desires
to pay for subscription content of their favorite team, but this
approach may have resulted in missed potential participants. Some people
paying for subscriptions to favorite team content could have different
rival perceptions.
Future Study
First, further study is needed to determine the validity of the
Out-Group Academic (OAP) factor, or the refinement of the SRFPS to three
factors and nine items (Isreal, 1992). For example, some populations in
future study (e.g., professional teams) may not lend themselves to the
use of the OAP factor. Another area for further study is to compare
college sports fans perceptions of rival teams by sex, sport, and
competition level. The current scale was developed on fans of college
football and men's basketball, and comparing data from women's
sports may reveal interesting results. Football and men's
basketball are known as revenue producing sports in high-profile
intercollegiate athletics, and a comparison of revenue versus
non-revenue sports may also provide interesting findings. Rival
perceptions may differ at the Division II, III, or NAIA level. It is
asserted that the construct, or concept of rivalry remains constant
anywhere there is competition, but the extent of perceptions may differ
between these groups.
Also, administering the survey to fans with apriori teams
identified to determine if fan rival perceptions differ toward various
teams within a league or conference would provide valuable results. This
was evidenced in the current study by the inconsistencies with which
fans identified rivals. For example, Texas A&M fans identified the
Texas Longhorns as their biggest rivals, while Texas fans placed the
Oklahoma Sooners in the same category.
Administering the SRFPS at the professional level may reveal
interesting results. Doing so would allow the validity and reliability
of the scale to be tested at the professional level, and may tap into
fan perceptions regarding teams in these leagues. For example, an
investigation of the New York Yankees/Boston Red Sox rivalry or the
intense relationship between the religious-tied Celtic and Ranger
football clubs of the Spanish Premier League would provide a wealth of
information.
As previously mentioned, it is imperative that the SRFPS be
administered to more fan groups so that discernable differences among
groups may be identified. It is also recommended that the SRFPS be used
in cooperation with other fan identification scales to test for
differences in rival perceptions. The SRFPS should also be used to
determine favorite team consumption habits among fans. For example, fans
of intercollegiate athletics could be administered the survey to
determine if and how the rival team's performance affects their
likelihood to support their favorite team through the purchase of
licensed products, mediated viewership, or monetary support in the form
of donations.
Qualitative research into rivalry can also provide areas for future
research. With the recent conference expansion and changing conference
affiliation of college teams, academics may be able to determine how
fans feel about the end of traditional competitive rivalries and the
beginning of new ones. Qualitative research would also help to shed
light on how fans feel toward rival teams when a coach or player from
the team gets into trouble with the NCAA or legal system. A Michigan fan
billboard aimed at derogating former Ohio State football coach Jim
Tressel for an NCAA investigation is such an example (Michigan
billboard, 2011).
Outside of sport, the SRFPS adds to the intergroup relations
literature and with further refinement may lend itself to the continued
study of groups sharing adversarial relationships (e.g., gangs,
factions). Through the understanding of what causes adversarial
relationships, we can also gain knowledge on what may diminish some of
the negative attributes of such relationships. The participants in the
Sheriff et al. (1961) study were able to work together on tasks when the
group competition was removed. Aside from few situations involving
natural or manmade disasters such as the 2011 storms in Tuscaloosa,
Alabama (Auburn offers aid, 2011) or the bonfire tragedy at Texas
A&M University (Rivalry takes back seat, 1999), it is yet to be seen
if rival fan groups would be willing to work cooperatively toward common
goals. It is also important that academics and practitioners note the
social responsibilities owed by teams and fans to communities and sport.
It is with caution that the SRFPS is presented as a scale to
measure the perceptions fans feel toward a rival team. Further research
should focus on how the SRFPS can be used to better understand the
adversarial relationship between rival fans and teams and regulate
potentially negative encounters in and out of the competitive arena. The
graphic fight between Cincinnati and Xavier men's basketball
players illustrate what can happen when negative feelings in a rivalry
are not properly controlled (Katz, 2011).
In conclusion, the SRFPS was demonstrated as a reliable and valid
measure of fan perceptions toward a favorite team's rival. The area
of sport rivalry has received little attention in the sport literature,
and the SRFPS provides academics and practitioners a tool to properly
gauge perceptions toward a rival and possible affects to fan behavior
and consumption. It is important for academics and practitioners to gain
a better understanding of rival perceptions in order to continue study
into the phenomenon, and the current study provides such a basis.
Acknowledgements
Portions of this manuscript were developed through Dr.
Havard's dissertation at the University of Northern Colorado. Dr.
Havard would like to thank Dr. Daniel Warm of Murray State University,
Dr. Daniel Mahony of Kent State University, Dr. Daniel Funk of Temple
University, Dr. Stephen Shapiro of Old Dominion University, and an
unnamed individual for their help while serving as expert panelists
during the development of the SRFPS.
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Cody T. Havard
The University of Memphis
Dianna P. Gray, James Gould, Linda A. Sharp, and Jay J. Schaffer
University of Northern Colorado
Address Correspondence to: Cody T. Havard, Health and Sport
Sciences, The University of Memphis, 310 Elma Roane Fieldhouse, Memphis,
TN 38152-3480. Phone: 901-678-5011, Fax: 901-678-3591, Email:
chavard@memphis.edu.
Table 1.
Factors and Items identified from Maximum Likelihood CFA
Factors and Items Factor
Loading
Out-Group Competition against Others (Indirect) OIC (3
items)
Sample mean = 2.52 Std. Deviation = 1.67
I would support my favorite team's rival in a championship .880
game.
I would support my favorite team's rival in .870
out-of-conference play.
I want my favorite team's rival to win all games except when .750
they play my favorite team.
Out-Group Academic Prestige OAP (3 items)
Sample mean = 3.87 Std. Deviation = 1.64
The academic prestige of my favorite team's rival is poor. .970
I feel people who attended school where my favorite team's .850
rival plays missed out on a good education.
I feel the academics where my favorite team's rival plays is .830
not very prestigious.
Out-Group Sportsmanship OS (3 items)
Sample mean = 3.87 Std. Deviation = 1.64
Fans of my favorite team's rival demonstrate poor .920
sportsmanship at games.
Fans of my favorite team's rival are not well behaved at .900
games.
Fans of my favorite team's rival do no show respect for .810
others.
Sense of Satisfaction SoS (3 items)
Sample mean = 5.96 Std. Deviation = 1.04
I feel a sense of belonging when my favorite team beats my .760
favorite team's rival.
I feel a sense of accomplishment when my favorite team beats .750
my favorite team's rival.
I feel I have bragging rights when my favorite team beats my .680
favorite team's rival.
Table 2.
Fit Indices for Four-Factor Model of Sport Rivalry
Fit Indices
Normed Fit Index (NFI) 0.98
Non-Normed Fit Index (NNFI) 0.99
Comparative Fit Index (CFI) 0.99
Standardized Root Mean Square Residual (SRMR) 0.037
Root Mean Square Error of Approximation (RMSEA) 0.040
Chi Square (degrees of freedom) 74.64 * (48)
* significant at the. 05 level
Table 3
Correlations among Factors
Factor OIC OAP OS SoS
OIC 1.00 -- -- --
OAP -.153 ** 1.00 -- --
OS -.321 ** .455 ** 1.00 --
SoS -.159 ** .244 ** .237 ** 1.00
** Correlation is significant at. 001 (2-tailed)
Table 4
Correlations among Items
Factor 1 2 3 4 5
Champ 1.00 -- -- -- --
DemPoor -300 ** 1.00 -- -- --
Bragging -.170 ** .229 ** 1.00 -- --
NotBch -288 ** .821 ** .185 ** 1.00 --
Accomp -.150 ** .116 * .508 ** .160 ** 1.00
NResp -.269 ** .743 ** .196 ** .736 ** .166 **
Belong -.074 ** .174 ** .508 ** .198 ** .581 **
NofPrest -.149 ** .362 ** .176 ** .339 * .146 **
ExFav .699 ** -.212 ** -0.071 -.170 ** -.104 *
AcnPoor -145 ** .453 ** .210 ** .411 ** .147 **
OutConf .757 ** -.320 ** -.169 ** -.314 ** -.165 **
Educ -.142 ** .463 ** .223 ** .442 ** .181 **
Factor 6 7 8 9 10
Champ -- -- -- -- --
DemPoor -- -- -- -- --
Bragging -- -- -- -- --
NotBch -- -- -- -- --
Accomp -- -- -- -- --
NResp 1.00 -- -- -- --
Belong .205 ** 1.00 -- -- --
NofPrest .321 ** .168 * 1.00 -- --
ExFav -.182 ** -.023 -.073 ** 1.00 --
AcnPoor .353 ** .195 ** .808 ** -.034 1.00
OutConf -.312 ** -.146 ** -.193 ** .650 ** -.187 **
Educ -.340 ** .235 ** .691 ** -.014 .821 **
Factor 11 12
Champ -- --
DemPoor -- --
Bragging -- --
NotBch -- --
Accomp -- --
NResp -- --
Belong -- --
NofPrest -- --
ExFav -- --
AcnPoor -- --
OutConf 1.00 --
Educ -.185 ** 1.00
** Correlation significant at 0.01 level (2-tailed);
* Correlation significant at 0.05 (2-tailed)
Table 5
Final Sport Rivalry Fan Perception Scale (SRFPS) with factors,
factor descriptions, and items.
Out-Group Competition against Others (Indirect) OIC--Likelihood
that a fan will support the athletic efforts of the favorite team's
rival in indirect competition.
I would support my favorite team's rival in a championship game.
I would support my favorite team's rival in out-of-conference play.
I want my favorite team's rival to win all games except when they
play my favorite team.
Out-Group Academic Prestige OAP--The amount of respect a fan has
for the academic prestige of the institution where the favorite
team's rival plays.
The academic prestige of my favorite team's rival is poor.
I feel people who attended school where my favorite team's rival
plays missed out on a good education.
I feel the academics where my favorite team's rival plays is not
very prestigious.
Out-Group Sportsmanship OS--The perceptions of fan sportsmanship
of the favorite team's rival.
Fans of my favorite team's rival demonstrate poor sportsmanship at
games.
Fans of my favorite team's rival are not well behaved at games.
Fans of my favorite team's rival do no show respect for others.
Sense of Satisfaction SoS--The satisfaction a fan gets when the
favorite team defeats the favorite team's rival.
I feel a sense of belonging when my favorite team beats my favorite
team's rival.
I feel a sense of accomplishment when my favorite team beats my
favorite team's rival.
I feel I have bragging rights when my favorite team beats my
favorite team's rival.