Geographical relocation, suicide, and homicide: An exploratory analysis of the geographic relocation of professional sports teams in three U.S. areas and the impact on suicide and homicide rates
Robert M. Fernquist
Central Missouri State University
Department of Sociology and Social Work
Wood Hall 203
Warrensburg, MO 64093
June 20, 2001
Phone: (660) 543-8510 fax: (660) 543-8215
Key Words: suicide, sports, geographical relocation
Tutko (1989) has argued that the performance of sports teams can greatly impact fans’ feelings about themselves and about life.
Wann, Melnick, Russell, and Pease (2001) have found that fans who identify strongly with their team have difficulty psychologically
distancing themselves from ‘their team’ when the team does not perform well. While the performance of professional sports teams
in relation to personal violence (e.g., suicide and homicide in the general population) has begun to be studied, I examine a new
angle on the relationship between professional sports teams and personal violence-that of geographical relocation. In this exploratory analysis, I look at the geographical relocation of professional sports teams from three areas: New York in 1957 (the
Brooklyn Dodgers and New York Giants’ moves), Cleveland in 1995-1996 (the Cleveland Browns’ move), and Houston in 1997-1998 (the
Houston Oilers’ move). Results indicate that, while homicide rates seem to be unaffected by these moves, suicide rates appear
It is well known that sports fans often ardently track the successes and failures of ‘their’ team(s). Tutko explains that
To see a performance where the (team) does well is tied
to the ‘good’ feeling inside of us-that feeling of
trying and doing well. We assume that the good feeling
is tied to all of the positive characteristics that
make up character (1989, p.115).
Further, sports fans often reflect on their own trials and
pressures when watching professional sports because
"athletics . . . excites our dominant personality features" (Tutko, 1989, p.115).
Branscombe and Wann (1992a, p. 1017) write that, for fans who identify strongly with ‘their team’, “An affront or loss
on the part of the team then is a loss for the self.” Building
on this concept, Mitrano (1999, p. 151) explains that, just as
people tend to go through certain stages (such as anger and
depression) when dealing with death or some other significant
loss, “. . . fans collectively experience the same stages of grieving and loss” when a pro sports team relocates to another
Fernquist (2000) has found that the performance of professional sports teams is related to local suicide and
homicide rates, whereas strikes in professional sports are
related to national homicide rates (2001). In this exploratory research, I examine how, if at all, the relocation of
professional sports teams from one geographical area to another
impacts persons in the area left behind. Specifically, I examine how the relocation of the Brooklyn Dodgers and New York Giants
after the 1957 baseball season, of the Cleveland Browns after the 1995-1996 football season, and of the Houston Oilers after the
1997-1998 football season impacted suicide and homicide rates of
persons in New York City, Cuyahoga county, and Houston city, respectively. If there is much merit to the idea that some
sports fans become closely and emotionally attached to ‘their team’, and there is much research to support such attachments (as
will be discussed below), then the examination of suicide and homicide rates among the general population in the areas left
behind warrants investigation. I use Gabennesch’s (1988) theory of broken promises and Durkheim’s concept of anomie (1897)
as theoretical guidelines for our research.
Literature review and theory
In the following literature and theoretical review, I discuss (1) sports fans’ identification with sports teams; (2)
the impact that franchise relocation, as well as sport teams in general, have on society; and (3) sociological theories related
to suicide, homicide, and the world of sports. Sports fans’ identification with sports teams: Although
the intensity of fan identification with sports teams varies from fan to fan (Wann, 1996), research still finds that following
sports teams has significant impacts on the lives of the fans. In this respect, Pooley (1980, p. 20) stated that “being a fan
usually means feeling intensely about a team as well as following its activities”, while Cialdini, Borden, Thorne, Walker, Freeman,
and Sloan (1976) similarly reported that college students tend to bask in the reflected glory (BIRG) of their respective football
team's victories. Hence, "through their simple connections with sports teams, the personal images of fans are at stake when their
teams take the field. The teams’ victories and defeats are reacted to as personal successes and failures" (Cialdini et al.,
1976, p. 374). Branscombe and Wann (1991) found strong evidence to suggest that many sports fans like following ‘their team’
because this allegiance provides them with pleasurable leisure activities and increases their self-esteem and overall positive
emotions. If such positive outcomes can result from being a sports fan, why, then, could identification with a sports team
result in aggressive and/or suicidal behavior?
In answer to such a query, Branscombe and Wann (1991, p. 125) have argued that
degree of threat to a social identity, combined with an inability or unwillingness to reduce the importance of
that identity, . . . is what gives rise to the negative potential involved in sports team identification. When
the threat is at reasonably low levels (for example, when a championship is not at stake), then only the
positive effects of attachment to something larger than the self will be observed. Both sides of the coin,
however, can have powerful social consequences. Branscombe and Wann (1992b) also reported similar results
regarding fan identification and sports. Further, it is common for “fans with a high degree of team identification” to be unable
to distance themselves from their team’s failures because “the concept of team follower is such a central component of (their)
self-identity (Wann, Melnick, Russell & Pease 2001, p. 171).
These fans keep hoping and waiting for their team to do better and become frustrated when their team continues to perform
poorly. There exists, therefore, sports fans who become so enmeshed with their team that these fans’ “psychological well-being . . . is jeopardized” when their team is not doing well
(Wann et al. 2001, p. 172). Branscombe and Wann (1992a, p. 1017)
further explain that when sports fans cannot or will not distance
themselves psychologically or emotionally from a sports team, “.
. . aggressive behavior may be resorted to as a means of identity
restoration”. Such aggressive behavior may surface in the form
of suicide or homicide.
Based on the review of these studies, the benefits derived
from identifying with their team (i.e., increased positive
emotions, higher self-esteem, enjoyable leisure activities) can, for fans who strongly identify with their team, result in
problems. These problems (such as aggressive behavior and/or
depression) arise because team identification is such a central a
part of their sense of self that when ‘their team’ fails they
find themselves unwilling or unable to distance themselves from the team in hope, perhaps, that the benefits will quickly return
The impact that franchise relocation and sport teams in general have on
Mitrano (1999) examined fan reaction to the franchise
relocation of the Hartford Whalers hockey team during the period
from March of 1996 to May of 1997. The last season the Whalers
played in Hartford was the 1995-1996 season. Mitrano likened the
grief and loss expressed by many of the fans he interviewed over
the franchise relocation to grief and loss people commonly go
through when a loved one dies or some other significant loss is
encountered. Some of the comments fans offered ranged from “It’s really over. I’m truly too numb to really say much” to “Now that
our team is leaving, ask yourself, ‘Will you stay in CT?’ I’m not” to “I’m completely numb . . . . my life has changed”
(Mitrano,1999, pp. 138-140). Although not all sports fans
reacted to the franchise relocation in this manner, Mitrano
(1999) indicated that a sense of loss and grief were common
reactions among the fans he studied. Another common occurrence
noted in this study was “. . . a shift from the tenets of loyalty
and stability” among fans toward both team management and sports
teams in general to tenets of “infidelity and celerity” (Mitrano,
1999, p. 151). Franchise relocation, then, cannot only make fans
change their feelings toward their team, but can also negatively
impact their sense of self.
Regarding the franchise relocations involved in the present study, Sullivan (1987 p. vii) explains that the Brooklyn Dodgers
“ . . . enjoyed a close emotional tie with” the people in
Brooklyn. Sullivan further explained that the Brooklyn Dodgers
had such a “. . . powerful emotional” effect on Brooklynites that
one New York Times writer expressed the mood of the Brooklyn fans
as ‘galling resentment’ when they learned their team would be
leaving Brooklyn and going to Los Angeles after the 1957 season (Sullivan, 1987, p. 137). The Browns moved from Cleveland
following the 1995-1996 football season; a move that was
similarly upsetting to fans. For example, fans picketed
Cleveland Stadium as owner Art Modell was expected to announce
the move from Cleveland (USA Today, 1995). However, unlike the
widespread passion that existed when the Browns and Dodgers
moved, there was more ambivalence on the part of fans when the
Oilers moved away from Houston after the 1997-1998 season
(Collegian 1996). Clearly, though, there were fans in each of
these areas that were upset over the geographical relocations of
their pro sports teams.
Ecological studies suggest that fans are impacted by the
performance of professional sports teams. Trovato (1998) found
that when the Montreal Canadiens hockey team was eliminated in an
early round from the playoffs between 1951 and 1992, the
likelihood of suicide increased for males aged 15-34 in Quebec. Similarly, Fernquist (2000) reported that suicide rates in
metropolitan areas tend to be lower when those metropolitan areas
have professional sports teams that performed well (e.g., made
the playoffs regularly and won championships). He further found
that the more times a team in a given metropolitan area made the
playoffs, the lower the homicide rate in the given metropolitan
area. Fernquist (2001) also argued that, during the baseball and
hockey strikes of 1994-1995, national homicide rates increased
while suicide rates were not significantly affected. Both
Trovato’s and Fernquist’s work suggests that social integration
among a certain segment of the population (i.e., fans who
strongly identify with ‘their team’) is significantly impacted by
the performance of professional sports teams. The impact that
the geographical relocation has on personal violence among
persons ‘left behind’ is as of yet unknown. Given the manner in
which suicide and homicide are related to phenomena in
professional sports, as described above, the study of suicide and
homicide in relation to the relocation of professional sports
teams is worthy of further investigation.
Sociological theories related to suicide, homicide, and the
world of sports: Gabennesch (1988) developed a theory in which he
describes how disappointments may result from expectations not
being met - disappointment which could result in suicide.
Gabennesch argued that suicide is likely to occur when promises are broken due to "conditions or events which induce
psychological misery" (1988 p.142). Gabennesch’s theory of
broken promises does apply to professional sports since persons
who expect ‘their’ team to do well may become extremely
disappointed when the ‘promise’ of winning is broken (Fernquist
2000). Stack (1995) argues that Gabennesch's theory of broken
promises can also be applied to homicide, since disappointment
was central to Durkheim’s (1897) short discussion of anomic
homicide. Durkheim (1897, p.357) argued that anomie
promotes "a state of exasperation and irritated weariness" which
could result in either suicide or homicide, depending upon the
person's "moral constitution" (e.g., a person with low morality
is more likely to commit homicide than suicide).
Although some sports fans tend to have a long-term ‘love
affair’ with their sports teams (Wann 1996), I use Durkheim’s
concept of anomie in addition to Gabennesch’s theory of broken
promises to guide this research. Durkheim (1897) explained
that sudden (or anomic) changes in the environment can have an
adverse impact on people. Durkheim, in his classic sociological
analysis of suicide, showed that sudden changes such as
widowhood, divorce, and economic crises can drastically change
the way people view the normative order in society. When such
sudden changes occur, it takes time for the person to adapt
himself “to the new situation in which he finds himself and
accordingly offers less resistance to suicide” (p. 259). Anomic
suicide, therefore, “results from man’s activities lacking
regulation and his consequent sufferings” (p. 258). Within this context, I acknowledge the research done by Curtis, Loy, and
Karnilowicz (1986) in which they examined social integration in
relation to professional sporting events. Curtis et al. (1986)
found significant, albeit weak, declines in suicide just before
and during the last day of the World Series and Super Bowl Sunday compared to the days immediately following these sporting events
from 1972-1978. Smith (1976) also reported that interest in
professional sports teams/persons can increase fans’ social
integration1. However, I test Durkheim’s theory that sudden
changes to one’s environment can have detrimental effects. The
sudden changes central to this study are related to the
geographical relocations of the sports teams. Even though fans
generally know the geographic relocation is imminent, the anomic
nature of the end of the last season is what causes problems
since fans feel they no longer have ‘their team’ in ‘their area’
to support. I argue that the end of the final season, not the
actual move itself, is what is anomic since the end of the season
for all intents and purposes is what signals to fans that their
team has ‘gone’. I further argue that the beginning of the next season (the first season following the move) is anomic to fans
since fans are once again reminded that ‘their team’ is no longer
in their geographical area. I hypothesize, therefore, three
contexts which increase suicide and homicide rates among persons
in the area ‘left behind’: (1) increases that occur at the end of the last season before the actual move occurs; (2) increases that
occur at the beginning of the next season; and (3) increases that
occur at both the end of the last season and the beginning of the
next season. I will first examine descriptive statistics
regarding the frequency of the number of suicides and homicides
in relation to these hypotheses and then, based on these trends,
I will estimate regression models to predict variation on suicide and homicide rates. Although such an approach to data analysis
can be termed ad hoc, an examination of trends before the
statistical modelling will allow us to see if trends present in
the descriptive analysis remain in the presence of relevant
Data and Methods
For each geographical area, I define the end of the season
as occurring during December and January for American football
and September and October for baseball (when the regular season
ends and playoffs occur). I define the beginning of the next season as occurring during August and
September for American football and March and April for baseball (when pre-season games
come to an end and the regular season begins). Monthly data for
all areas are used in this analysis. To control differences in the seasonality of suicide, I compare data for the months at the
end of the season and beginning of the next season (e.g., the
‘anomic months’) with those same months in the two years before
and the two years after the ‘anomic months’. The central
variable of interest in this analysis, the ‘relocation’ variable,
is used in regression analysis and is a dichotomous variable,
being coded 1 for anomic months and 0 for all other months. The
coding of this variable is explained in more detail below.
The Brooklyn Dodgers and New York Giants’ moves: Data on the number of suicides and homicides in New York City are from the
New York City Department of Health (2000). Data for individual
boroughs were unavailable. For the last season’s end, the anomic
months are September and October 1957 and I compare these months
to September and October, 1956, 1958, and 1959 (1955 data were
not available). For the beginning of the season after the
baseball teams moved, the anomic months are March and April,
1958, and I compare these months to March and April, 1956, 1957,
1959, and 1960.
The Cleveland Browns’ move: Data in this instance were
obtained from Cuyahoga county, the county in which the city of
Cleveland is located. Data on suicides and homicides in Cuyahoga
county are from the Ohio Department of Health, Center for Public
Health Data and Statistics (2000). For the last season’s end,
the anomic months are December 1995 and January 1996, and I
compare these months to December 1993, 1994, 1996, 1997 and to
January 1994, 1995, 1997, and 1998. For the beginning of the
season after the Browns moved, the anomic months are August and
September 1996, and I compare these months to August and
September 1994, 1995, 1997, and 1998.
The Houston Oilers’move: Data on the number of suicides and
homicides in Houston city are from the Texas Department of Health
(2000). For the last season’s end, the anomic months are
December 1997 and January 1998, and I compare these months to
December 1995, 1996, 1998, 1999 and to January 1996, 1997, and
1999 (2000 data were not available). For the beginning of the season after the Oilers moved, the anomic months are August and
September, 1998, and I compare these months to August and
September 1996, 1997, and 1999.
In the regression models, I examine how the geographic relocations impact suicide and homicide rates per 100,000
population. The central independent variable in the regression
models, the ‘relocation’ variable, is a dichotomous variable
comparing suicide and homicide rates in the anomic months to the
same months in the years preceding and succeeding the anomic
period. To convert the number of suicides and homicides to rates
per 100,000 population for the regression analysis, I obtained
population estimates for the three areas. In the regression
models, birth rates, marriage rates, and unemployment rates per
1,000 population are controlled for, variables which are relevant
to the sociological study of suicide and homicide (Fernquist
2000; Lester 1994).
For New York City, data on the number of births and
marriages, as well as estimates of population size, are from the
New York State Department of Health (2000). Data on unemployment rates for New York City are from the New York State Department of
Labor (2001). Unfortunately, unemployment data prior to 1958
were not available, and so 1958 data are also used for 1956 and
1957. For Cuyahoga county, data on the number of births and
marriages are from the Ohio Department of Health, Center for Public Health Data and Statistics (2000),while the unemployment
rates are from Labor Market Information (2000). The population
estimates are from the Ohio Department of Development (2000).
For Houston, data on the number of births and marriages were
available only for Harris county (the county in which the city of
Houston is located), not for the city of Houston proper. Data on
the number of births and marriages are from the Texas Department
of Health (2000). Unemployment rates for the city of Houston are from Economagic (2001). Population estimates for persons in
Harris county (to calculate birth and marriage rates) are from
the Texas Department of Health (2000) while population estimates
for city of Houston (to calculate suicide and homicide rates) are
from the Texas State Data Center (2000).
Ordinary least squares estimation (OLS) is used to model
variation in suicide and homicide rates. Given that the OLS
regression models in table 2 employ cross-sectional, time-series
data, I checked for harmful autocorrelation (significant
correlations among the disturbances) and heteroskedasticity
(unequal variances among the disturbances) since these problems
may produce incorrect OLS regression coefficients (Stack 1992).
I also checked for problematic collinearity among the predictors.
After the suicide and homicide models were corrected for first-order autocorrelation, the regression models were acceptable in
terms of autocorrelation and heteroskedasticity levels (see table
2). Since the value of the Durbin-Watson statistic, a commonly
used test to examine the degree of autocorrelation present in
regression, is close to 2.0 in both models, and since neither statistic that measures the presence of heteroskedasticity (the
Glejser  test) is significant at the .05 level, we can be
confident that neither autocorrelation nor heteroskedasticity
will bias results from the regression models. Allison (1999)
explains that the use of Variance Inflation Factors (VIFs) can
show whether or not collinearity among the independent variables
will bias regression estimates. Each predictor in the models in
table 2 was regressed on all others simultaneously to calculate
the VIF for each predictor. Each VIF is calculated by 1/1-R2 and
Allison (1999) explains that any VIF of 2.5 or larger indicates
problematic collinearity. No VIF was 2.5 or larger, suggesting
that collinearity was not a problem for the models in table 2.
Table 1 shows the number of suicides and homicides and the percentage changes in the anomic months versus those same months
before and after the anomic months. Based on these percentage
changes, I will categorize New York City and Houston as being
anomic at the beginning of the next season since percentage
changes in suicide and homicide are greater at the beginning of
the next season relative to the end of the last season. I put
Cuyahoga county in the category of being anomic at season’s end
since, especially for suicide, percentage changes were greater at
season’s end relative to the beginning of the next season. I
feel this categorization best explains increases in suicide and,
to a lesser extent, homicide in each of these areas.
Table 1 Suicide and Homicide in Three U.S. Areas: Raw Numbers and
Percentage Change Over Previous Period
||New York City
Comparisons at End of Season (Annual Averages)
||Dec 1993 - 4 Jan 1994 - 5
||Dec 1995 Jan 1996
||Dec 1996 - 7 Jan 1997 - 8
||Dec 1995 - 6 Jan 1996 - 7
||Dec 1997 Jan 1998
||Dec 1998 - 9 Jan 1999
Comparisons at Beginning of Next Season (Annual
In the regression analysis, I examine suicide and homicide
rates per 100,000 population in the three areas combined with the
relocation variable coded 1 in New York City and Houston for the
anomic months during which the respective sports seasons began the season after the geographic relocations while in Cuyahoga
county the move variable is coded 1 for the anomic months at the
end of the last season before the geographic relocation. All
other months are coded 0.
The regression models in table 2 show that the geographic
relocation of all three teams is significantly related to
increased suicide rates in New York City, Cuyahoga County, and
Houston City, holding all else constant in the model. In
Cuyahoga County, the impact on suicide was more immediate (since Cuyahoga was modeled as a ‘season’s end anomic’ area), while the
impact on suicide in New York and Houston was delayed until the
next season began. Geographic relocation was not significantly
related to variation in local homicide rates. Regarding the
control variables, birth rates are positively related to both
suicide and homicide rates, while marriage rates are inversely
related to both suicide and homicide rates. Unemployment rates
are not significantly related to either suicide or homicide
rates, even though the coefficient in the homicide model is
larger than the other coefficients. Explained variance is fairly
high in both the suicide and homicide models (.53 and .74,
Table 2: Unstandardized Regression Estimates of
Suicide and Homicide Rates in Three U.S. Areas (N=30)
||-0.97* * *
|Method of Estimation
||Corrected for First-Order
||Corrected for First-Order
|Glejser test for
||7.3 9 (p>. 11)
|Largest Variance Inflation Factor
|p<.05; **p<.Ol; ***P<.001
Discussion and Conclusion
As Trovato has so correctly stated, “The association of
major sport occasions and mortality has received scant attention
in the literature, and our understanding of this phenomenon is
far from complete” (1998, p. 119). In response, within this
study, I have attempted to shed more light on the relationship
between sporting ‘events’ and suicide and homicide. This
exploratory analysis reveals support for the hypotheses that
suicide rates increase due to geographic relocation of professional sporting teams both at the end of the last season
before the actual move occurred (Cleveland) and at the beginning
of the next season after the relocation (New York and Houston).
The hypotheses about homicide rates, however, were not supported.
Although these data are not individual-level thus not allowing us
to ascertain if those fans who highly identify with ‘their’ team
are the persons whose suicide rate increases upon franchise
relocation, the results are suggestive that this may be the case.
Whereas Durkheim (1897 ) argued that anomie promotes a
state of exasperation which could result in either suicide or
homicide, I find that exasperation related to geographic relocation is related to increases in suicide rates, but not
homicide rates. The sudden change brought about due to the
geographic relocations of pro sports teams does appear to, at
least for a short time, make highly identified fans drastically
change the way they view the normative order in society. Unable
(or unwilling) to adapt to the new environment, an environment
which no longer contains ‘their team’, their sense of self may
become seriously damaged with suicide more likely to result.
They may come to feel as if they are losing control of the world around them (Grossberg 1992). As Tutko (1989) said, fans put
much feeling into following the progress of ‘their team’, thus
when that team is no longer in the specific area anomie
increases. These fans end up having a difficult time letting go
of their team because they “experience depression and an intense
negative affective state and adopt a poor outlook on life
subsequent to” the team’s geographic relocation (Wann et al. 2001, p. 172).
From the point of view of Gabennesch’s (1988) theory, highly
identified fans may come to see the geographic relocation of
their team as breaking the promise that, at least in the fans’
minds, their team will always be in that geographic area for the
fans to cheer and follow. Although there is certainly never a
guarantee that a professional sports team will remain in a given
area indefinitely, fans apparently hope/expect their team to
stay. Although aggregate data cannot be used to make specific individual references, the data from this study, in agreement
with Gabennesch (1988), suggest that when the team does move,
fans may feel that these expectations are broken, and these broken promises have detrimental effects.
I also realize that the nature of being a sports fan has
changed over the past several decades. With the introduction of
free agency in the 1970s, fans have come to realize that players
will come and go from team to team (Wann et al. 2001). Since
this study entails data from pre-free agency years (the Dodgers
and Giants) as well as data after the introduction of free
agency, could the nature of fans’ identification with ‘their
team’ have changed over the years? I argue that the nature of
fans’ identification with their team has not significantly
changed during this period since all three geographic relocations were related to increased suicide rates. If fans have become
less attached to ‘their’ team, we would not have seen suicide
rates rise after the Oilers and Browns relocated. Therefore,
even though fans know players will come and go, they still today
expect ‘their team’ to remain in its geographical location.
I realize that there are other factors related to suicide
and homicide rates that were not included in the study.
Variables such as religiosity, per capita income, and cohort size
are relevant control variables I was unable to include in the
analysis due to a lack of data. It is unclear if the inclusion
of these control variables in the regression models would alter
the impact of geographic relocation on suicide or homicide.
Urban revitalization has also been occurring in the Cleveland
metropolitan area during the 1990s and this phenomenon could also
be responsible for significant variation in the Cuyahoga county
suicide and homicide rates. Therefore, I acknowledge
shortcomings in the current aggregate analysis on suicide and
homicide rates in the New York, Cleveland, and Houston areas.
Nonetheless, this research does suggest that the association
between geographic relocation and suicide (and even homicide)
should be studied in more detail. In particular, due to the
difficulty highly identified fans have of letting go of ‘their
team’ (Wann et al. 2001), it is recommended that the emphasis of
future research on geographic relocation and suicide should be
placed on the differences in suicidal behavior between highly
identified fans and less identified fans.
Thanks are expressed to the following persons for the generous
help in providing the author with vital data: Donna Smith
(Cuyahoga county); Anna Vincent (Houston city and Harris county);
Elizabeth Acevedo, Louise Berensen, Robert Roddy, and Al Wolf
(New York City). Thanks also go to Joyce Knapton and Charlene
Zion for further help with obtaining data and to the anonymous
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