Exploring fantasy baseball consumer behavior: examining the relationship between identification, fantasy participation, and consumption.
Shapiro, Stephen L. ; Drayer, Joris ; Dwyer, Brendan 等
Identification is the process of linking an individual's
experience and internal information processing to social networks
created through interactions with others (Callero, 1985). This
connection between "self" and "society" is the basis
for identity theory which suggests that through experience and social
interaction, individuals create various role-identities which influence
future behaviors (Ervin & Stryker, 2001; Stryker, 1980; Stryker
& Burke, 2000). Commitment to one's social network through
experience and social interaction impacts identity salience which in
turn influences individual behavior (Ervin & Stryker, 2001; Stryker,
1980).
From a spectator sport perspective, identity theory plays a
significant role in the fan connection to sport, and this framework has
been used in various forms to explain sport consumer behavior. Previous
research provides evidence that identification influences consumption of
sport-related products and services (Lavarie & Arnette, 2000;
Madrigal, 1995; Trail, Anderson, & Fink, 2000, 2005; Trail, Fink,
& Anderson, 2003). Additionally, fans appear to identify with
multiple aspects of sport (e.g., team, individual players, the sport).
These distinct points of attachment help explain individual consumption
behavior (Robinson & Trail, 2005; Trail, Robinson, Dick, &
Gillentine, 2003).
Despite the increased attention this area has received from
researchers, there have been limited investigations regarding the role
identification plays in the consumptive habits of fantasy sport
participants. Previous research has identified relationships between
identification and motives for fantasy participation and differing
levels of identification between a participant's favorite team and
fantasy team (Spinda, Wann, & Sollitto, 2012). However, the impact
of identification on consumption for fantasy participants has not been
explored. Residing primarily in a virtual world yet tied to real-world
statistics, the activity of fantasy sport allows participants to own and
manage a roster of professional athletes. The outcomes of this activity
have been found to result in enhanced professional media consumption
primarily in the form of television viewership of live games, televised
sport programming, and internet usage (Dwyer, 2011a; Nesbit & King,
2010b). However, although the focus of fantasy sport is on the
statistical output of individual athletes as opposed to teams, recent
research has determined the activity is actually complementary to
traditional professional sport fandom (Dwyer & Drayer, 2010; Dwyer,
Shapiro, & Drayer, 2011). In other words, a fantasy participant can
engage in the media consumption of his/ her fantasy players in addition
to the consumption of his/her favorite team without having to sacrifice
one for the other.
Despite these findings, little is known about a fantasy sport
participant's points of attachment with professional sport. Spinda
et al.'s (2012) findings demonstrate some distinct differences in
points of attachment between team, individual, and sport. With
additional opportunities to consume the product compared to
non-participating sports fans (e.g., favorite team, fantasy players,
opponent's fantasy players), examining various points of attachment
relative to consumption habits will provide insight into this rapidly
growing form of sport random. The population of fantasy sport
participants is also an avid consumer of technology due to the nature of
mediated participation in fantasy activities (Comeau, 2007; Farquhar
& Meeds, 2007; Smith, Synowka, & Smith, 2010). This may impact
both traditional forms of sport consumption (e.g., attendance,
merchandise purchases) and mediated consumption (e.g., television,
internet). Additional research regarding the various consumptive habits
of this population of sport consumers is warranted. In particular, a
deeper understanding of the antecedents of consumption would help media
providers, team marketers, and league officials more completely meet the
needs of this ever-expanding group of sport consumers. Taken together,
the purpose of this study was to examine the identification of fantasy
sport participants as it relates to traditional and mediated consumption
of professional sport.
Review of Literature
Fantasy Sport
Within the last two decades, fantasy sport has developed into a
multi-billion dollar industry with over 32 million participants in the
United States and Canada alone (Fantasy Sports Trade Association [FSTA],
2011). In parallel with the explosion of the internet, fantasy sport
participation has evolved into a substantial connection point for sports
fans where participants are provided an opportunity to interact with
professional sport in a manner not offered through other, more
traditional forms of sport random (Dwyer & Kim, 2011). In addition
to the large number of participants, the demographic composition (25-41,
highly-educated, income > $75,000) and consumption behavior of this
group is highly-coveted by advertisers and corporate partners as it
outpaces other sport fans and the general population (Fisher, 2008).
According to Zeitchick (2005), for perhaps the first time in history,
the fantasy sports subculture is driving strategy at the country's
biggest broadcasters.
As a result of this popularity, academic researchers have been
drawn to the motives of fantasy participants as well as the behavioral
and consumptive outcomes of participation (Drayer, Shapiro, Dwyer,
Morse, & White, 2010; Dwyer, 2011b; Dwyer & Kim, 2011; Farquhar
& Meeds, 2007). This research suggests participatory drivers range
from psychological, social, and market-controlled factors, and for the
most part, increased consumption habits have been linked to several
media formats (Drayer et al., 2010; Dwyer, 2011a; Nesbit & King,
2010b).
In terms of fantasy participation motives, Farquhar and Meeds
(2007) and Dwyer and Kim (2011) developed and validated distinct
motivational scales for fantasy football participation with several
overlapping drivers including entertainment, social interaction,
competition, arousal, escape, and surveillance. Spinda and Haridakis
(2008) also explored the motives of fantasy participants, and discovered
the following motivational dimensions: ownership,
achievement/self-esteem, escape/pass time, socialization, bragging
rights, and amusement. Ultimately, the authors suggested fantasy sport
participation is "a purposive, instrumental, and active media-use
endeavor [sic]" (p. 196).
The importance of establishing motives has been well documented, as
motives have been found to influence consumer behavior from a spectator
sport perspective (Kim & Trail, 2010; Trail et al., 2003) and more
notably within the realm of fantasy sport participation (Drayer et al.,
2010; Dwyer et al., 2011). Drayer et al. (2010) developed a framework
through the application and extension of Fazio, Powell, and Herr's
(1983) attitude-behavior relationship. The authors found fantasy
football participation activated additional attitudes and perceptions
with regard to the National Football League (NFL) product that, combined
with traditional sport fandom, resulted in enhanced mediated consumption
of the NFL. Dwyer et al. (2011) developed a market segmentation of
fantasy sport participants based on motives. Within each segment of
fantasy motives various aspects of fantasy sport consumption differed,
which included consumption through mediated platforms such as
television, internet, and mobile phones. These findings suggest
consumption patterns differ based on motives for participation.
Additional fantasy consumption research identified increases in
attendance for fantasy participants (Nesbit & King, 2010b) and
different levels of consumption based on varying levels of interest in
an individual's favorite team and/or fantasy team (Dwyer &
Drayer, 2010). Additionally, Dwyer (2011 a) found fantasy football
participants were not only attracted to their fantasy football players,
but were also aware of their opponent's players, and as a result,
intentionally watched and followed the live games of both sets of
players in addition to their favorite team and its rivals. In an attempt
to explore the team loyalty effects of fantasy football participation,
Dwyer (2011b) discovered that although fantasy football appears to be a
complementary activity to traditional (favorite team) random, it may
result in an incongruent disconnect between a participant's
highly-developed attitudinal team loyalty and his/her viewership
behavior of that team. Although the literature focused on attitudes and
behaviors of fantasy sport participants is growing, the relationship
between identification and traditional and mediated sport consumption
for fantasy participants is limited (Karg & McDonald, 2011).
Identification and Consumption
The importance of the relationship between identification and
sport-related consumption has been acknowledged in the literature (Trail
et al., 2000, 2005; Trail et al., 2003; Trail & James, 2001; Warm
& Branscombe, 1993). Originally, research focused on team
identification exclusively; however, Trail et al. (2003), developed the
Points of Attachment Index (PAI), which segments identification based on
specific types of fan connection: team, player, coach, sport, community,
and level of play. These different forms of identification have been
shown to influence various consumption behaviors distinctively.
Support for measuring identification as distinct categories can be
found in the work of Robinson and Trail (2005), who identified
considerably higher levels of team and sport identification compared to
player, coach, level of sport, and community. Additionally, Kwon, Trail,
and Anderson (2006) found that various points of attachment differed in
their influence on future intentions to attend games, purchase
merchandise, and purchase clothing with specific team logos.
These relationships have not been explored within the population of
fantasy consumers. Karg and McDonald (2011) found differences in
attachment to sport, team, players, and coach between fantasy and
non-fantasy players who are fans of Australian football, providing
evidence of unique attitudes for fans who participate in fantasy sport.
Spinda et al. (2012) found that participants of Strat-O-Matic Baseball
(SOMB), a baseball simulation game similar to fantasy baseball, had
stronger identification with their favorite MLB teams compared to their
SOMB team. Additionally, participation motives such as knowledge
acquisition and enjoyment predicted various levels of identification,
confirming the relationship between motives and identification from a
fantasy sport perspective. However, the specific relationship between
various points of attachment and aspects of sport consumption has yet to
be addressed.
Technological advancements have provided a multitude of consumption
opportunities for the sport consumer. These opportunities include
traditional forms of consumption and mediated consumption. Furthermore,
fantasy sport participants may be motivated to consume sport based on
favorite team interests and/or fantasy team interests. This distinction
in consumption has not been examined and may be important given the vast
growth of fantasy sport and the elevated consumption levels of its
participants. The role of sport identification on these various forms of
consumption is needed from both a practical and theoretical standpoint.
Additionally, due to the avid use of technology by fantasy sport
participants, identification may influence traditional and mediated
consumption differently for this population of sport consumers.
Finally, identification with fantasy sport specifically has not
been explored. Drayer et al. (2010) suggested that fantasy sports
participants have two distinct avenues through which to attach to
professional football: fantasy team and favorite team. The authors
concluded that there were specific behavioral differences associated
with each of these distinct aspects of football consumption. Further,
they found that participants' perceptions of the NFL were expanded
as a result of fantasy sports resulting in heightened levels of
interactivity and heightened levels of interest in individual players.
However, within their small qualitative sample, they did not explore
specific points of attachments. Their findings suggest that the nature
of fantasy participation might create an attachment to fantasy sport
that is different from the traditional forms of attachment. Additional
research is needed to confirm these findings.
In summary, the fantasy sport research suggests a link between
fantasy participation, attitudes about sport, and consumption of
sport-related products and services. Additionally, previous literature
has highlighted the influence of identification on attendance (Lavarie
& Arnette, 2000; Trail, Anderson, & Lee, 2006) and other various
consumption behaviors (Trail et al., 2003; Trail et al., 2005; Trail et
al., 2006). However, the research on identification within the
population of fantasy sport participants is limited, particularly in
terms of its effect on traditional and mediated consumption.
In addition, the context of fantasy baseball, as opposed to fantasy
football, has been neglected for the most part despite its place as the
second most popular fantasy sport activity (> 9 million participants;
FSTA, 2008). Based on the growth of fantasy sport as a complementary
activity, and the important role identification plays on sport consumer
behavior, two research questions were developed to guide the current
study:
RQ 1: How do baseball consumer points of attachment influence
traditional consumption for fantasy baseball participants?
RQ2: How do baseball consumer points of attachment influence
mediated consumption for fantasy baseball participants?
Method
Sample & Procedure
The target population for this study was current fantasy baseball
participants over the age of 18. A sample of 1,500 potential respondents
was randomly selected from a group of 3,400 FSTA members to participate
in the study. An online survey was developed and distributed through
email to the random sample of FSTA members. A follow up email was sent
two weeks after the initial distribution in an effort to increase
response rate. A total of 253 usable surveys were collected for a
response rate of 16.9%, which is common in online survey methodology
(Shapiro & Dwyer, 2011).
Instrumentation
The survey instrument contained four sections with a total of 37
items. The first section of the survey focused on fantasy participation
(3 items), measuring the number of years of participation, number of
teams owned, and time spent participating in fantasy baseball. The
second section of the survey measured multiple points of attachment for
fantasy baseball participants. A five factor, 15 item adapted version of
Trail et al's (2003) PAI was used to measure attachment to players,
team, community, and sport. Additionally a 3 item sub-dimension was
developed to measure specific attachment to fantasy sport. The third
section of the survey was comprised of various sport consumption
behaviors (7 items) which included measures of attendance, merchandise
purchases, and mediated consumption. The final section focused on
participant demographics (8 items) to profile the typical respondent.
Data Analysis
A confirmatory factor analysis (CFA) was initially conducted on the
adapted PAI to examine the factor structure of the attachment construct
based on the pooled sample of respondents. Previous theory on points of
attachment and scale development of the PAI (Robinson & Trail, 2005;
Trail et al., 2003) drove specification of the factor model. Therefore,
CFA was the most appropriate factor analytic technique (Brown, 2006).
Construct validity was assessed due to the fact that the PAI had not
been used to examine fantasy baseball participants, and a new
sub-dimension (Fantasy Attachment) was included.
Multiple measures of fit were used to examine the factor structure
of the PAI. Overall goodness of fit was assessed using a robust
chi-squared test; however, according to Hu and Bentler (1999), this test
can be sensitive to sample size arid should not be used exclusively in
determining model fit. Therefore, standardized root mean square residual
(SRMR), root mean square error of approximation (RMSEA), and the
comparative fit index (CFI) were examined to provide additional sources
of fit that are widely accepted in applied research and have shown
satisfactory performance in model simulation analyses. According to Hu
and Bentler, SRMR values close to .08 or below, RMSEA values close to
.06 or below, and CFI values close to .95 or greater provide evidence of
an adequate model fit.
Additional measures of validity and reliability were assessed.
Convergent validity was evaluated through the application of Fornell and
Larcker's (1981) Average Variance Extracted (AVE) test. A third
validity measure was used exclusively on the new Fantasy Attachment
sub-dimension. To assess predictive validity, the scores for the Fantasy
Attachment factor were regressed simultaneously onto three measures of
fantasy participation selected due to both theoretical and practical
relevance (DeVellis, 1991). Finally, alpha coefficients were examined
within each factor of the PAI to assess reliability-related evidence.
Means and standard deviations were subsequently calculated for each
point of attachment in the scale.
To examine the relationships between identification and both
traditional and mediated consumption, multiple regression analyses were
conducted. Three regression models were developed to analyze RQ1 and
four regression models were developed to analyze RQ2. Multiple linear
regression assumptions were examined for these equations (Linearity,
Independence, Normality, and Equality of Variances). Descriptive
statistics, residual plots, and statistical tests for normality and
equality of variances showed that none of the assumptions were violated
in the regression equations. In addition, potential multicollinearity
issues within the model were examined through variance inflation factors
and tolerance statistics. The results suggested there were no
significant multicollinearity issues in any of the regression equations
used in the analysis.
Results
Fantasy Participation
The 253 respondents appeared to be avid fantasy participants. On
average, participants had played fantasy baseball for approximately
seven years (M = 7.04, SD = 4.90). The average number of fantasy teams
owned (of any kind) was 4.30 (6.224). The standard deviation is large
for this variable due to the fact that some participants were outliers
with a significant amount of fantasy teams owned over the course of a
year. Finally, participants spent 14.04 (10.63) hours per week playing
fantasy sport, which includes conducting research, preparing rosters,
and making lineup changes throughout the season.
Points of Attachment Index
CFA identified a five factor, 14 item solution for the adapted PAl
scale. One item was deleted from the Fantasy Attachment factor due to
poor factor loading. The final solution was found to be satisfactory
[X.sup.2] (67) = 94.53, p <.001, RMSEA = .040, CFI = .99, NNFI = .99,
and SRMR, .043. Additionally, AVE scores ranged between .689 and .810
and Cronbach's alpha scores ranged between .77 and .89. Finally,
results of the predictive validity assessment on the Fantasy Attachment
sub-dimension showed that fantasy participation had an influence on
respondents' identification with fantasy sport F(3, 249) = 5.33, p
= .001. Two of the three predictor variables, number of years playing
fantasy baseball (p = .001) and hours per week participating in fantasy
baseball (p = .014), had a significantly positive relationship with
fantasy sport attachment. Table 1 provides a summary of validity and
reliability-related evidence for the adapted PAI.
Regression Analyses
Multiple regression analyses were subsequently conducted. For RQ1,
all three regression models were found to be significant. Traditional
consumption included attendance F(5,247) = 11.63, p = <.001, general
merchandise purchases F(5,247) = 9.65, p = <.001, and favorite team
merchandise purchases F(5,247) = 18.27, p = .001. Attachment to team and
community were the only significant variables in these models. Table 2
provides a detailed summary of regression results for RQ1.
For RQ2, all four regression models were also found to be
significant. Mediated consumption based on favorite team included
television F(5,247) = 13.07, p = <.001 and internet F(5,247) = 12.14,
p = <.001. Only attachment to team was significant in these models.
Mediated consumption for fantasy purposes included television F(5,247) =
5.43, p = <.001 and internet F(5,247) = 3.37, p = .006. Attachment to
team, sport, and fantasy team were significant variables in the internet
model. Only attachment to team significantly influenced television
consumption for fantasy purposes. Table 3 provides a detailed summary of
regression results for RQ2.
Discussion
The size and purchasing power of the fantasy sport population has
been well documented (Fisher, 2008; FSTA, 2011). As a result, sport
managers and marketers must account for the unique attitudes and
behaviors of these individuals to properly package and deliver sport
products and services. For instance, the NFL recently directed all teams
to display real-time fantasy football statistics at all home games
starting in the 2011 season (McCarthy, 2011). As the industry continues
to mature, fantasy participants are becoming a highly valued segment of
the sport consumer population. Thus, from a marketing perspective, the
investigation into attitudes and consumption habits of participants is
vital.
From a theoretical perspective, the current findings support
identity theory by providing evidence that social interaction through
fantasy participation influences various role-identities, which in turn
impacts consumption of sport-related products and services. Results
indicate identification with one's favorite team, community, and
sport appear to be the most ubiquitous connection points for fantasy
baseball participants, as these points of attachment were found to be
significant across varying forms of consumption. Identification with
one's fantasy team significantly influenced consumption modes more
specific to the activity, yet tied to the media representation of MLB.
These results also support Robinson and Trail's (2005) and Trail et
al.'s (2003) findings wherein distinct points of attachment
differed across groups, between sports, and resulted in varying
consumptive outcomes. In addition, the current study's authors
suggest identification with fantasy team should be considered in the
future application of the PAI (with respect to fantasy participants) as
it validates the burgeoning landscape of professional sport and media
consumption. This finding is supported by Spinda et al. (2012), who also
examined fantasy-specific identification and found significant
relationships, though in a different context.
These findings also confirm previous spectator consumption behavior
research which suggests attachment to team remains the most influential
with respect to television consumption (Dwyer, 2011a; Mahony &
Howard, 1998; Mahony & Moorman, 1999, 2000), as well as attendance
and future merchandise purchase intentions (Kwon et al., 2006).
Additionally, the importance of attachment to team does not appear to be
negatively affected by fantasy participation, which is also consistent
with previous research (Dwyer, 2011a; Dwyer, 2011b) and supports Drayer
et al's (2010) assertion that fantasy sport participation
complements traditional (favorite team-focused) sport consumption
behavior. This finding is noteworthy for professional teams and leagues
looking to leverage fantasy sport participation into additional
consumption without detracting from traditional (favorite team)
attachment and consumption.
A notable component to these findings is the specific influence of
the newly created attachment to fantasy team sub-dimension. Attachment
to fantasy team appears to be a source enhanced internet usage. This is
supported by previous fantasy sport investigations (Drayer et al., 2010;
Dwyer & Drayer, 2010). However, attachment to fantasy team did not
influence watching television for fantasy purposes, which is contrary to
previous research (Drayer et al., 2010; Dwyer, 2011a; Dwyer &
Drayer, 2010; Nesbit & King, 2010b). These previous studies,
however, examined fantasy football. Thus, the contradiction could be due
to the uniqueness of baseball and the lack of nationally televised games
and/or the fact that fantasy baseball would not necessarily be a reason
to watch a local broadcast. In addition, attachment to one's
fantasy team did not influence the more traditional forms of sport
consumption (e.g., attendance and merchandise purchases) which
contradicts findings from Nesbit and King (2010a). Additional research
in this area is advised.
With regard to the future application of the PAI, a few
modifications may need to be addressed when accounting for fantasy sport
participation. Given fantasy baseball's focus on individual player
statistics, one could have hypothesized that attachment to individual
players would have been more influential. Yet, it was the only
attachment factor that had no significant relationship with either
traditional or mediated consumption. This finding may have occurred for
two reasons. First, Drayer et al. (2010) determined that attraction to
individual players was shallow and less enduring due to the short time
span of ownership (one year); thus, a fantasy participant's
attachment to individual players may be lessened. Second, the wording of
two of the attachment items were related to individual players across
the league although one was related to individual players on the
participant's favorite team. Given the processes of fantasy
baseball participation, these may represent two completely different
forms of individual player fandom and may require instrument adjustment.
Regardless of the reasoning, further investigation into individual
player attachment is suggested, specifically with regard to fantasy
participation.
Similarly, the newly-created fantasy baseball attachment items may
also need re-examination. If in fact fantasy baseball participation is a
complementary activity as suggested by these findings, the wording of
the fantasy baseball attachment items may need to be addressed. Namely,
the items are worded so that fantasy participation is one's only
attachment to the league. Based on this study's findings wherein
team, community, and sport attachment were highly influential, this
attachment may need to be less polarizing. Once again, further
psychometric testing on additional samples is suggested.
Limitations with regard to the current study certainly exist. For
instance, although enlightening with regard to varying points of
attachment, this study was limited to a cross-section of fantasy
baseball fans. An interesting extension would incorporate both fantasy
baseball participants and non-participating MLB fans to compare and
contrast points of attachment and consumption behavior. In addition, an
extension to fantasy football and the other fantasy sports may be a
fruitful line of research as would be a comparison between the media
consumption habits of fantasy baseball and fantasy football
participants. Rigorous inquiry of other well-researched attitudinal
constructs (e.g., risk aversion, control) in conjunction with fantasy
participation is always needed as the field is very much emerging and
requires further exploration. Lastly, as mentioned above, future
application of the PAl should consider the usage of the fantasy
attachment items, as further psychometric validation is strongly
suggested.
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Stephen L. Shapiro
Old Dominion University
Joris Drayer
Temple University
Brendan Dwyer
Virginia Commonwealth University
Address correspondence to: Stephen L. Shapiro, PhD. Old Dominion
University, Student Recreation Center #2012 Norfolk, VA 23529. Email:
[email protected]
Table 1--Reliability and validity testing for the adapted PAI
Factors and Items Factor
Loading t SE AVE [alpha]
Attachment to Team .79 -- -- -.754 0.86
--I consider myself to be
a "real" fan of (team)
--I would experience a .92 20.12 * .06
loss if I had to stop
being a fan of (team)
--Being a fan of (team) .89 19.52 * .06
is very important to me
Attachment to Players .810 0.89
--I am more a fan of .79 -- --
individual players than
the (team) in general
--I am a big fan of .93 17.69 * .07
certain players more than
I am a fan of the (team)
--I consider myself to be .97 19.34 * .06
a fan of players rather
than a fan of the (team)
Attachment to Community .789 0.89
--I feel connected to .84 -- --
numerous aspects of the
community
--I feel a part of the .96 19.34 * .06
community in which the
(team) calls home
--I support the .86 19.85 * .05
city/region which is home
to the (team) as a whole
Attachment to Sport .764 0.86
--First and foremost, I .61 -- --
consider myself a
baseball fan
--Baseball is my favorite .97 10.88 * .15
sport
--Of all sports, I prefer .99 10.57 * .15
baseball
Attachment to Fantasy .689 0.77
--Fantasy baseball is the .85 -- --
reason for my interest in
MLB
--I would experience a .81 21.08 * .05
loss if I could not play
fantasy baseball
Note: * p <.05; [varies] = Cronbach's alpha coefficient;
AVE = Average variance extracted;
SE = Standard error; t = t-values
Table 2--OLS Regression Results--RQ1 (Traditional Consumption)
p-
DVs Selection Variables Rz Beta values
Game Attendance .191
Player -.006 .935
Team .161 .030
Community .192 <.001
Sport .075 .099
Fantasy Team -.023 .705
MLB Merchandise Purchase .163
Player -.040 .613
Team .229 .009
Community .123 .016
Sport .073 .173
Fantasy Team -.042 .563
Favorite Team
Merchandise Purchase .270
Player .069 .359
Team .424 <.001
Community .096 .047
Sport -.004 .940
Fantasy Team -.127 .065
Note: DV = Dependent Variable; Beta = Unstandardized
Beta Coefficient
Table 3--OLS Regression Results--RQ2 (Mediated Consumption)
DVs Selection [R.sup.2] Beta p-
Variables values
.064
Internet Player -.087 .366
Consumption Team .261 .015
for Fantasy Community -.040 .522
Purposes Sport .150 .022
Fantasy Team .220 .013
Television .099
Viewership for Player .456 .012
Fantasy Team .646 .001
Purposes Community -.043 .710
Sport .305 .012
Fantasy Team .184 .262
Internet .197
Consumption for Player -.057 .738
Favorite Team .836 <.001
Team Purposes Community -.152 .164
Sport .056 .623
Fantasy Team -.161 .299
Television .209
Viewership for Player .197 .239
Favorite Team Team .918 <.001
Purposes Community -.012 .910
Sport .006 .959
Fantasy Team -.267 .082
Note: DV = Dependent Variable;
Beta = Unstandardized Beta Coefficient
