Development and validation of the Sport Rivalry Fan Perception Scale (SRFPS).

Development and validation of the Sport Rivalry Fan
Perception Scale (SRFPS).
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 minn kota 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
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Dianna P. Gray, James Gould, Linda A. Sharp, and Jay J. Schaffer
University of Northern Colorado
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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)
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)
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)
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
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
I feel I have bragging rights when my favorite team beats my
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Development and validation of the Sport Rivalry Fan Perception Scale (SRFPS).

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