Amateur Soccer Players and the Phenomenon of Motivation

Submitted by Papanikolaou Zissis and Dr. Asterios Patsiaouras

ABSTRACT
The relationship between various types of psychological and social motivation in amateur soccer players was examined in this paper.Twenty eight males and 14females who participated in this study regularly engaged in soccer. The amateur soccer players ranged in experience from beginning to advanced soccer, with the majority self-reporting at an intermediate level. Subjects were given Butt’s Short Scales for the Measurement of Sport Motivation. Males and females soccer players scored similarly on the aggression scale. Female amateur soccer players scored significantly higher on the conflict scale than did male soccer players. Identical means were found for males and females on the competence scale. There were no differences found between males and females on the motivational scales for competition and cooperation. Due to the small number of subjects who have participated, general conclusions can only be made with great caution.

INTRODUCTION

Interest in the sport of soccer has greatly increased in recent years, bringing men and women into fields. According to FIFA survey of 2007 (41), 265 million male and female players in addition to 5 million referees and officials make a grand total of 270 million people or 4% of the world’s population-who are actively involved in the game of soccer. Among the most pleasing signs is the continuing growth of the women’s game. The number of men and women playing soccer is expanding the world over. One especially important statistic that can be drawn from the number of registered players is the proportion made up by youngsters, who constitute 54.7% of all registered male players and as many as 69.6% of the women. The greater number of young players in the women’s game is a reflection of the impressive growth in women’s football, which has also resulted in a significant increase in the number of registered amateur players (up 130% compared to 16% in the men’s game). These figures dearly indicate that FIFA and its associations are on the right track to increasing the popularity of soccer even further in the future.

Understanding and enhancing motivation has long been a major concern in sport. Without motivation athletes would not desire to excel in their sport, coaches would no longer strive to unify the team, and a player’s drive to set and reach goals would end. Roberts (28) defines motivation as “those personality factors, social variables, and/or cognitions that come into play when a person undertakes a task at which he/she is evaluated, enters into competition with others, or attempts to attain some standard of excellence”. (p. 5).

The biggest and most common reason that affects soccer performance is soccer motivation or lack of it. Without motivation all soccer players will crumble under the various pressures and problems soccer manages to throw up. Generally, speaking motivation is guided by the hope of success and the fear of failure. When you lack the self-belief and confidence, there is a good chance you also lack motivation.

Motivation is an internal energy force that determinates all aspects of our behavior, it also impacts on how we think, feel and interact with others. In sport, high motivation is widely accepted as an essential prerequisite in getting athletes to fulfill their potential. However, given its inherently abstract nature, it is a force that is often difficult to explain fully. Some coaches, appear to have a “magic touch” being able to get a great deal more out of a team than the sum of its individual parts; others find motivation to be an elusive concept they are forever struggling to master. Motivation is a dynamic and multifaceted phenomenon that can be manipulated, to some degree at least in the pursuit of superior sporting performance.

Some theories and models of motivation were examined, as they relate to sport. The study of motivation is the investigation of the energization and direction of behavior (28). Early theories of motivation (Mechanistic theories) viewed humans as being passive and driven by psychological drives. More recently, however, cognitive approaches have been developed to explain behaviour from the beliefs or thoughts that people have. The following are some major approaches to motivation, followed by the theory that is the basis of this paper.

Roberts (28) suggests that the search for the “right” theory of motivation is not yet within our grasp; however many excellent efforts are available. Need Achievement Theory, introduced by Murray (25) and further developed by McClelland and Atkinson (24), suggests two motive states that elicit action: (a) the motive to achieve success, and (b) the motive to avoid failure. This theory reflects the philosophy of our Western society, which places value on gaining rewards, high achievement, and moving forward and improving our position within society (5). Research in sport with Need Achievement Theory has been inconclusive.

In recent years, the cognitive approach has been the dominant paradigm in understanding motivation. This refers to how cognitions or thoughts govern behavior. Within this approach is Attribution Theory, which is concerned with the methods and attributes that an individual uses in attempting to account for the causes of behavior (36,37,38). The way in which one attributes the cause of an outcome will affect the expectation of future successes and failures. The expectation of future outcomes will affect the striving for achievement (28). Although this theory has focused upon why people expect to succeed, it neglects to explain why people want to succeed.

More recently, Social Cognitive Approaches have incorporated affect, expectations, and values in order to explain motivated behaviors (28). Bandura’s (2) theory of Self-Efficacy refers to the assessment of one’s own capability in performing at a given level. This theory suggests that the self-perception of the performer determines motivations and aspirations and not the actual ability of the performer. Research within the sport setting indicates self-efficacy to be a modest predictor of sport performance (11, 12, 23), although many others factors may contribute to behavioral change (3,12).

The perception of one’s competence may also determine behaviors in sport. Harter (17) developed a model of perceived competence which suggested that perceived competence and intrinsic pleasure gained from success will increase achievement striving, while perceived incompetence and displeasure may lead to anxiety and a decrease in achievement striving. Much of the research with Harter’s model has been performed with children with favourable results; however, children have notoriously been inaccurate in estimating their comparative ability (13, 26, 29,32).

A model developed by Butt (4) focuses on the motivational components specific to sport and is the basis of this study. Butt indicates that motivation in sport evolves on four levels: (a) the biological, (b) the psychological, (c) the social, and (d) the reinforcement level. The first and the fourth levels provide two major sources, or influences of sports motivation: (a) a biological energy or life force, and (b) a set of learned reinforcements. These reinforcements may be extrinsic (i.e., overt rewards) or intrinsic (i.e., feelings of well-being and personal growth). The psychological and social levels contain the five constructs that will be examined in this paper. Aggression, conflict, and competence are the three styles of sport motivation contained within the psychological level, and the other two constructs of competition and cooperation contains the level of social motivation.

The aggressive athlete appears to have a great deal of energy, and thus seems to be eager, active, and impulsive. If frustrated, the aggressive athlete may verbally or physically attack others. This involves feelings of power, vivacity, anger, and strength, and often lacks self- control. He or she may also be quick to find fault in others (5).

The conflict-ridden athlete often complains and makes excuses. This athlete may be unhappy, and is usually slow to fulfil his or her goals. Life energy is channeled into opposing purposes and pursuits, such as the desire to express impulse versus quilt for the expression of impulse. Energy is used to mediate the struggle between opposing purposes. Conflict can result in self-destructiveness, self-absorption, blaming others, complaints, worries, depression and inactivity, weeping, and other nervous symptoms (5).

The competence – oriented athlete usually displays more maturity and self–insight than the others. This athlete seeks new challenges and displays confidence in his or her sport. Life energy is channeled into interacting effectively and purposefully with the environment. The individual expects to have the effect on the environment that he or she desires to have and the expectations are realistic. Joy, pleasure, elation, and self-esteem accompany activity and interaction with the environment. Setbacks and failures are accepted as a realistic part of development from which new learning and new development may evolve(5).

The level of social motivation contains the constructs of competition and cooperation. The motivation of a competitively oriented athlete is derived primarily from the desire to defeat others. A contest or competitive sporting event is seen as a chance to dominate others and display assertiveness. The competitively motivated athlete also places importance on status and position, which may lead to frustration and resentment if such goals are not achieved (4).The individual wants to defeat others, to be number one, to have rivals, and sees the environment as an adversary over which one must triumph (5).

The cooperative athlete sees others as partners in the sporting event or contest. The contest is seen as an opportunity for personal growth and skill development. The cooperative athlete is usually good-natured and shows concern for his or her competitors while striving for personal excellence (4). The major social motive in a contest is derived from participating with others, from feeling part of the group, team or club. The individual desires to raise the performance of all as a group experience, cares for others, empathizes, and congratulates others. The perception of the environment is that of supportive and interdependent with the self (5).

One of the most popular and widely tested approaches to motivation in sport and other achievement domains is self-determination theory, that examines the effect of the social context on motivation and individual behaviors (9,10, 30). This theory is based on a number of motives or regulations, which vary in terms of the degree of self-determination they reflect. Self-determination has to do with the degree to which your behaviors are chosen and self-initiated. The behavioral regulations can be placed on a self-determination continuum. From the least to the most self-determined they are amotivation, external regulation, introjected regulation, identified regulation, integrated regulation and intrinsic motivation.

According to Hungarian psychologist MihalyiCsikszentmihalyi (7,8), the highest level of intrinsic motivation is flow state. Flow is characterized by complete immersion in an activity to the degree that nothing else matters. Central to the attainment of flow is a situation in which there is a perfect match between the perceived demands of an activity and an athletes’ perceived ability or skills. During flow, self-consciousness is last and athletes become one with the activity.
Motivation has been studied in many sports such as figure skating (31); rugby (19); and gymnastics (39). There is a lack of research, however, on the motivation of soccer. Research is necessary in this sport due to the favor of its participants and increasing popularity and participation by men and women of all ages. Therefore, this literature review is limited to test data from other types of athletes, and other psychological studies involving male and female soccer players.
Gender differences investigated in this study pertained to differences in motivation. Investigating the motivations of competitive and amateur soccer players is a necessary step in understanding this complex and popular sport. The diversity among the many theories and models of motivation reminds us of the vast number of possibilities as to why we behave the way we do in sport. Measuring a construct such as motivation in sport is a difficult task due to the endless, number of variables in an athlete’s personality. However, human nature dictates that similarities do exist among our personalities which, if measured, help us to predict our behavior.

STATEMENT OF THE PROBLEM
The purpose at this study was to examine the relationship between various types of psychological and social motivation in soccer and to compare motivation between male and female amateur soccer players. For the purpose of this paper, motivation was operationally defined as the score on the Sport Motivation Scale.The hypothesis of this study was: There will be no difference on any of motivational scales between male and female soccer players (aggression, conflict, competence, competition and cooperation).

METHODS
Research Design
The research design employed was a descriptive study. Amateur soccer players who played in the area of Philadelphia, USA, were asked to complete Butt’s (4) short scales for the Measurement of Sport Motivation. Forty-two adult male and female amateur soccer players completed and returned the questionnaires.

Subjects
Participants were 42 adult (age 18 years or over) soccer players, males (n=28) and females (n=14), who regularly engaged in soccer (worked out at least two days per week). The male subjects ranged in the age from 18 to 38 years (M=28.7±4.50), and the females ranged in age from 20 to 35 years (M=28±3.80). Subjects were members of two amateur soccer teams chosen by the first researcher.

Measuring Instrument
Subjects completed Butt’s (4) short scales for the Measurement of Sport Motivations questionnaire. The survey was developed to measure motivation specifically in the sport context. The scales measured the motivational components of aggression, conflict, competence, competition and cooperation. These constructs were measured by 10 items on each scale. Internal consistency measures ranged from .69 (aggression) to .74 (competition). Test-retest reliability ranged from .50 (competence) to .80 (conflict) across a two-week interval. A total of 52 questionnaires were distributed (26 at each team) with 42 being returned for a return rate of 80.8%. Four weeks allowed for returning the questionnaire. No questionnaires were received after that time.

Data analysis
Descriptive statistics were calculated for the Sport Motivation Scales. A one-way analysis of variance (ANOVA) was computed to determine differences between genders. Correlation coefficients were also computed to investigate the relationships among the five components of motivation.

RESULTS
A one-way ANOVA was performed to compose gender with five components of motivation: (a) aggression, (b) conflict, (c) competence, (d) competition, and (e) cooperation. The overall scores are listed in Table 1. Table 2 indicates the mean values for this study and previously studied athletes from other areas of sport who were given the Sport Motivation Scales. Realizing the dangers of visual comparison of means, it appears that subjects in this study were responding differently from the other groups, especially in competence and cooperation. At the very least, the data suggest that further study in this area would be of interest.

Table 1.Motivational Component Scores for the Soccer Players by Gender.

Screen Shot 2014-01-14 at 9.52.27 AM

Table 2. Mean Values for the Sport Motivation Scales for Various Athletes

Screen Shot 2014-01-14 at 10.00.39 AM

With respect to male and female soccer players, females scored significantly higher on the conflict scale (M=3.14) than the males (M=1.71) (F=5.40). The other four motivational components were not found to be significantly different between males and females. Results are provided in Table 3.
Interestingly, there were identical means for both males and females on the competence scale (M=7.29).

Table 3.Results of ANOVA for Gender and the Five Motivational Components

Screen Shot 2014-01-14 at 10.04.34 AM

In an attempt to test Butt’s (4) theory, correlation coefficients were computed to investigate the relationships among the five motivational components (see Table 4). As predicted by Butt’s theory, the psychological component of competence was significantly correlated with the social component of cooperation (r=.66). Further support for her theory was a significant correlation of the psychological component of aggression with the social component of competition (r=.51). However, aggression was also correlated with competence (r=.46) and cooperation (r=.38), which were not consistent with Butt’s theory that there would be no correlation between their components.

Table 4. Correlation Coefficients Comparing the Five Motivational Components and Amateur Soccer Players

Screen Shot 2014-01-14 at 10.06.41 AM

The results indicated differences between males and females on the conflict scale, and similarities among males and females on the aggression, competence, competition, and cooperation scales.

DISCUSSION
The information gained from this study suggested more similarities than differences between male and female amateur soccer players. Due to the limited number of subjects in this study, interpreting the data for these groups was difficult, and general conclusions should be made with great caution.

Males and females scored similarly on the aggression scale. Very often society sees men as the more aggressive sex, making this similarity difficult to explain. Klein (20) suggests that women athletes may feel an increase in control over their bodies, the aging process, and other aspects that may lead to feelings of empowerment. Their feelings of empowerment by the women may have been presented on this questionnaire in the aggression scale. Some of the responses in the aggression scale included the words “powerful”, “excited”, and “full of energy”. These are all words that could suggest feelings of empowerment.

Female soccer players scored significantly higher on the conflict scale than did male soccer players. One explanation for the women’s higher scores on the conflict scale may be due to the stereotype and/or belief that muscular women do not look feminine. Klein (20) suggests that gender role conflict can occur in female athletes when women desire to build athletic body (muscle mass), but also want to remain attractive to men.

Another explanation for the higher conflict score for the women concerns the questionnaire itself. The 10 responses on the questionnaire that measured conflict contained certain words or phrases that may have been stereotypically attributed to women more than men. For instance, Item 6 reads, “moody for no real reason”, and Item 12 states, “guilty for not doing better”’. Words such as “moody” and “guilty” have been thoughtby many to pertain to women’s feelings more than men (34), possibly making it less likely for a male to answer “yes” to questions such as these.

Identical means were found for males and females on the competence scale. Both sexes scored high on this scale with the greatest number of “yes” responses than with any other scale on the questionnaire. This may be due, in part, to the ease of “taking good” on this scale. Some of the items on the competence scale include “trustworthy”, “improving yourself” and “happier than ever”, making it more likely for the participants to answer “yes” to these items if they wanted to appear in a positive manner.

According to Butt’s (4) theory a tendency of one of the psychological components of motivation would predict dominance in one of the social components of motivation of either competition or cooperation. Since there were no significant differences between males and females in the competition or cooperation scales, one cannot predict dominance at any social components of motivation with the subjects in this study. Although female amateur soccer players were significantly higher on the conflict scale, they were not higher on the competition scale, as predicted by Butt’s theory that a higher conflict score will likely result in a higher competition score.

A study examining the relationship between athletes’ goal orientations and their levels of intrinsic and extrinsic motivation indicated that British Collegiate athletes with task-related or personal mastery goals were far more likely to report high self-determination than athletes with ego-orientated or social comparision-type goals (27).

A recent study showed that during competition deemed to be important, intrinsically motivated athletes developed task-oriented (positive) coping strategies (1).Gϋrbϋzet al. (16) indicated that male soccer players rated improvement and 21,4% of the players rated the “team spirit” as their participation motive.
Results of Gillet andRosnet (15) revealed that male athletes perceived themselves as being more competent than female athletes, but female athletes exhibited a higher self-determinated profile. This is not surprising given male athletes typically display higher self-confidence than female athletes (21, 33, 35). One explanation suggested for gender differences in perceived competence may be that males are boastful and think they will do better than they do (22). Also their results showed that male athletes exhibited more external regulation and less intrinsic motivation than female athletes. In other words, females appeared to take part in sport activities for the pleasure derived from the activity itself more than for extrinsic motives. These results were in line with past studies in the sport context (6, 14) and confirmed that gender differences should be taken into consideration in the sport domain. However, contrary to a study conducted by Hollembeak and Amorose’s (18) their findings did not confirm that females reported higher scores on perceived autonomy and perceived relatedness than males. They proposed that future investigations should continue to explore gender differences in basic need satisfaction in order to gain a better understanding of the motivational processes underpinning sport participation.

When interpreting the results of this study, it is important to consider the need for a possible revalidation of Butt’s (4) Short Scales for the Measurement of Sport Motivation. Some items may need to be reworded or omitted to ensure equal interpretation by males and females, as well as subjects of various racial groups and socioeconomic statuses. Ideally, this inventory would have the ability to be valid considering the changing attitudes in society so it can be utilized in the future.

Overall, this information will be useful to those involved in the sport of soccer. Since female soccer players scored significantly higher than male soccer players on the conflict scale, soccer coaches may need to become more sensitive to issues of female soccer players, and provide a supportive atmosphere to beginning female players.

CONCLUSIONS AND RECOMMENDATIONS
The present research was on attempt to broaden our understanding of soccer players’ motivation. When comparing gender with motivation, female soccer players scored significantly higher on the conflict scale than did male amateur soccer players. No differences were found on the scales of aggression, competence, competition, or cooperation.

In conclusion, investigating the motivation of amateur male and female soccer players is a necessary step in understanding this complex and popular sport. Measuring a construct such as motivation in sport is a difficult task due to the endless number of variables in an athlete’s personality. However, human nature dictates that similarities do exist among our personalities, which, if measured, can help us to predict our behavior.

Future studies would be enhanced by administering the Short Scales for the Measurement of Sport Motivations (4) to professional, semi-professional, college, high schools competitive male and female soccer players. Generalizations may be easier to make for strictly competitive subjects due to their similar goals and soccer lifestyle. Administer the questionnaire to the same subjects over a period of time. Subjects could be tested over several months or years to investigate any changes in motivational styles. Other methods of studying soccer players should be utilized to investigate their motivational components. In-depth interviews and field studies could provide information not easily gained via questionnaire.

APPLICATIONS IN SPORT
The results of this study provide useful informationto those who are involved in the sport of soccer (coaches, educators, participants etc.). Since female soccer players scored significantly higher than male soccer players on the conflict scale, soccer coaches should be more sensitive to issues of female soccer players, trying to offer a supportive atmosphere for the amateur female players. This will be beneficial for the motivation of the players, not only for the females but also for themales.

ACKNOWLEDGMENTS
I would like to express my gratitude to all soccer players who made this research possible with their willingness to participate.

REFERENCES
1. Amiot, C. E., Gaudreau, P., & Blanchard, C. M. (2005).Self-determination, coping, and goal attainment in sport. Journal of Sport and Exercise Psychology, 26, 396-411.
2. Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice-Hall.
3. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory.Englewood Cliffs, NJ: Prentice-Hall.
4. Butt, D.S. (1978). Short scales for the measurement of sport motivations. International Journal of Sport Psychology, 10, 203-216.
5. Butt, D.S.(1987).Psychology of sport (2nd ed.). New York: Van Nostrand Reinhold.
6. Chantal, Y., Guay, F., Dobreva-Martinova, T., &Vallerand, R. J. (1996). Motivation and elite performance: An exploratory investigation with Bulgarian athletes. International Journal of Sport Psychology, 27,173–182.
7. Csikszentmihalyi, M. (1975). Beyond Boredom and Anxiety. San Francisco, CA: Josey-Bass.
8. Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. New York: Harper and Row.
9. Deci, E. & Ryan, R. (1985).Intrinsic Motivation and Self-determination in Human Behavior. New York: Plenum.
10. Deci, E. L., & Ryan, R. M. (1991). A motivational approach to self: Integration in personality. Nebraska symposium on motivation, 38,237-288. Lincoln, NE: University of Nebraska Press.
11. Feltz, D. L. (1982). Path analysis of the casual elements in Bandura’s theory of self-efficacy and an anxiety-based model of avoidance behavior. Journal of Personality and Social Psychology, 42, 764-781.
12. Feltz, D.L. (1988). Gender differences in the causal elements of self-efficacy on a high avoidance motor task’. Journal of Sport Psychology, 10, 151-156.
13. Feltz, D.L., &Petlichkoff, L. (1983). Perceived competence among interscholastic sport participants and dropouts. Canadian Journal of Applied Sport Sciences, 8, 231-235.
14. Fortier, M. S., Vallerand, R. J., Brière, N. M., &Provencher, P. (1995). Competitive and recreational sport structures and gender: A test of their relationship with sport motivation. International Journal of Sport Psychology, 26,24-39.
15. Gillet, N., &Rosnet, E. (2008). Basic Need Satisfaction and Motivation in Sport. www.athleticinsight.com, vol. 10/3.
16. Gϋrbϋz, B., Altintas, A., Asci, F.M. (2007). Participation motives of 9-15 years old Turkish soccer players’. Journal of Sports Science and Medicine, suppl.10, http://www.ssm.org.jssm.org.
17. Harter, S. (1978). Effectance motivation reconsidered: Toward a developmental model. Human Development, 21, 34-64.
18. Hollembeak, J., &Amorose, A. J. (2005). Perceived coaching behaviors and college athletes’ intrinsic motivation: A test of Self-Determination Theory. Journal of Applied Sport Psychology, 17, 20-36.
19. Kerr, J.H. (1988). A study of motivation in rugby. The Journal of Social Psychology, 128, 269-270.
20. Klein, A.M. (1993).Little big men. New York: State University of New York Press.
21. Krane, V., & Williams, J. M. (1994) Cognitive anxiety, somatic anxiety, and confidence in track and field athletes: The impact of gender, competitive level and task characteristics. International Journal of Sport Psychology, 25, 203–217.
22. Lirgg, C. D. (1991). Gender differences in self-confidence in physical activity: A meta-analysis of recent studies. Journal of Sport and Exercise Psychology, 13, 294–310.
23. McAuley, E. (1985). Modeling and self-efficacy: A test of Bandura’s model. Journal of Sport Psychology, 7, 283-295.
24. McClelland, D. C., & Atkinson, J. W. (1953).The achievement motive. New York: Appleton-Century-Crofts.
25. Murray, H.A. (1938).Explorations in personality. New York: Oxford University Press.
26. Nicholls, J.G. (1978). The development of the concepts of effort and ability, perception of attainment, and the understanding that difficult tasks require more ability. Child Development, 49, 800-814.
27. Ntoumanis, N. (2001). Empirical links between achievement goal theory and self-determination theory in sport. Journal of Sports Sciences, 19, 397-409.
28. Roberts, G.C. Motivation in sport and exercise. Champaign, IL: Human Kinetics, 1992.
29. Roberts, G.C., Kleiber, D.A., &Duda, J.L. (1981). An analysis of motivation in children’s sport: The role of perceived competence in participation. Journal of Sport Psychology, 3, 206-216.
30. Ryan, R.M., &Deci, E.L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68-78.
31. Scanlan, T.K., Stein, G.L., &Ravizza, K. (1989). An in-depth study of former elite figure skaters: 2.Sources of enjoyment. Journal of Sport and Exercise Psychology, 11, 65-83.
32. Ulrich, B.D. (1987). Perceptions of physical competence, motor competence, and participation in organized sport: Their interrelationships in young children. Research Quarterly for Exercise and Sport, 58, 57-67.
33. Vargas-Tonsing, T. M., & Bartholomew, J. B. (2006). An exploratory study of the effects of pregame speeches on team efficacy beliefs. Journal of Applied Sport Psychology, 36, 918–933.
34. Walsh, M.R. (1987). The psychology of women: Ongoing debates. New Haven: Yale University Press.
35. Wark, K. A., & Wittig, A. F. (1979). Sex role and sport competition anxiety. Journal of Sport Psychology, 1, 248-250.
36. Weiner, B. (1979). A theory of motivation for some classroom experiences. Journal of Educational Psychology, 71, 3-25.
37. Weiner, B. (1986).An attributional theory of motivation and emotion. New York: Springer-Verlag.
38. Weiner, B., Frieze, I., Kukla, A., Reed, L., Rest, S., & Rosenbaum, R. M. (1971). Perceiving the causes of success and failure. In E.E. Jones, D.E. Kanose, H.H. Kelly, R.E. Nisbett, S.Valanis, & B. Weiner (Eds.), Attribution: Perceiving the causes of behavior. Morristown, NJ: General Learning Press.
39. Weis, M.R., Weise, D.M., &Klint, K.A. (1989). Head over heels with success: The relationship between self-efficacy and performance in competitive youth gymnastics. Journal of Sport and Exercise Psychology, 11, 444-451.
40. Wrisberg, C.A., Donovan, T.J., Britton, S.E., & Ewing, S.J. (1986). Assessing the motivations of athletes: Further tests of Butt’s theory. In D.M. Landers (Ed.), Sport and elite performers. 3, 185-194. Champaign, IL: Human Kinetics.
41. FédérationInternationale de Football Association (2007). Retrieved Dec. 15, 2010, from www.fifa.com.

2014-01-14T10:21:08-06:00January 14th, 2014|Contemporary Sports Issues, Sports Studies and Sports Psychology|Comments Off on Amateur Soccer Players and the Phenomenon of Motivation

A Comparison of Body Image Perceptions for Female Competitive Dancers, Fitness Cohort, and Non-Dancers in a College Population

 

ABSTRACT

Body image is a complex synthesis of psychophysical elements that are perpetual, emotional, cognitive, and inesthetic (1). The desire to achieve and maintain an ideal weight is a prevalent goal among females. The purpose of this study was to examine a female population of competitive dancers, control, and fitness cohorts’ body image and eating characteristics. A total of 51 (29 dancers, 12 control, and 10 fitness) subjects completed the MBSRQ-AS, EAT-26, a Physical Activity Questionnaire, Stunkard Figural Silhouettes, and body fat measurements. A MANOVA was conducted to determine group differences and showed a significant relation (Wilk’s Lambda = .106, F=8.735, p<001). Post hoc tests were conducted to determine directionality and showed that the dancers scored significantly higher on the Appearance Orientation subscale (p =.034) with no difference between the control and fitness cohort. Dancers also significantly perceived themselves to be overweight (p=.048) with no difference between the other two groups. Both the dancers (p<.001) and the fitness cohort (p<.001) scored as exhibiting disordered eating patterns as rated by the EAT-26. Even though the dancers had a low percent body fat (M=17.6), they tended to place more importance on how they look. The dancers perceived themselves to be overweight and engaged in disordered eating patterns. These types of perceptions and behaviors are disturbing, but not surprising since dancers have a drive for thinness to compete (2). To fully understand the scope of the issue and the psychological factors that accompany the quest for achieving a certain appearance, future research should include other female cohorts such as elite athletes, obligatory exercisers, and sedentary females to determine any similarities and differences in the groups.

INTRODUCTION

Research has documented and quantified a shift towards a thinner ideal shape for females in the Western culture for the past 20 years (3). Body image has been shown in numerous studies to be a key issue for females. Body image has been described as a multidimensional construct that describes internal,subjective representations of physical and bodily appearance (4). The internal representations of one’s own body include both cognitive and perceptual elements (5). In addition, eating disorders have been shown to be prevalent in females with more than 90 percent of those with eating disorders are women between the ages of 12 and 25 years of age (6, 7, 8). Research indicates that both of these factors (body image and eating disorders) are present among elite performers of certain sports or physical activities, ballet dancers, and professional dancers (8). Yet little has been reported on dance team participants (9, 10, 11).

Dance team is difficult to research due to the paucity of literature available and the complexity of terminology. Also, dance team is a nebulous term to define. Research demonstrates common referrals to spirit teams, spirit squads, dance teams, as well as pom squads. While the confusion in labeling and current argument as to whether this is an activity or a sport still looms, one fact that remains constant is competitive spirit teams is one of the fastest growing areas of participation for females (12).

Among high school participants, over 96,718 females were accounted for in the 2010-2011 high school athletics participation survey conducted by the National Federation of State High School Associations, ranking competitive spirit teams ninth for female participation. At the college level, the National Collegiate Athletic Association (NCAA) reported that spirit squad has experienced the most growth for women’s sport (13, 14). A nationwide Division I study conducted during the 2001-02 academic school year investigated the prevalence of dance and cheerleading programs and reported 89% of the institutions contacted indicated they sponsored competitive dance (12).

The current emerging phenomenon of dance teams has witnessed the rise invisibility of participants at sporting events and are known for their pre-game and half-time routines. Dance teams are comprised of competitive dancers who are required to practice for long hours in movements, choreography, and synchronicity among dancers. Participants are also required to incorporate specific choreography (i.e., contemporary, hip-hop, or jazz) and technical skills (jumps, kicks, and other gymnastic-type skills) into the routine. It is highly competitive and requires hours of rehearsal to master precise movements in harmony with other members of the team.

The increasing number of females participating in dance team competition is prevalent. Long rehearsal hours, use of mirrors, and dance outfits, place dance team participants at risk of body image concerns (15, 16, 17, 18). Of additional concern is the presence of wearing dance outfits which possibly place them as subjects of objectification, or being evaluated by gazing or being observed or “checked out” on the basis of their appearance(17, 19, 10).

With the growing number of females participating in dance team competition,a further examination of the psychosocial factors that accompany this new sport warrants investigation including the importance of assessing potential body image disturbance. This study was designed to examine the perceptions of dance team participants, fitness participants, and non-dancers in a college population.

METHODS

Upon Internal Review Board (IRB) approval, fifty one subjects were recruited from two university campuses. Informed consent was obtained prior to the study through an information letter that was administered to participants in dance and physical fitness classes.

Participants

Participants were female students enrolled in university classes and dance teams. Two university campuses were involved in the study and yielded a total of 51 participants. The study was comprised of 29 dancers, 10 fitness students,and 12 control subjects. The mean age and standard deviation for the participants were: dancers (M = 20.69, SD = 2.25), fitness (M = 25.40, SD =8.67), and control (M = 20.42, SD = 0.996). The dancers were from university dance teams, the fitness participants were enrolled in fitness classes, and the participants in the control group were randomly selected from general university courses.

Instruments

Each subject completed questionnaires assessing participant demographics,physical activity involvement using the NASA Physical Activity Scale and body image perceptions using the Stunkard Figural Rating Silhouettes. Eating behavior patterns were assessed utilizing the Eating Attitudes Test (EAT-26)and attitudes concerning body image were assessed with the Multi-dimensional Body-Self Relations Questionnaire (MBSRQ). Anthropometric measurements (height and weight) were then taken. Weight was taken using a Tanita WB-110A Digital Scale and height was taken using a using a Seca 420 measuring stadiometer. Body fat measurements were taken on each participant using an Omron Fat Loss Monitor, Model HBF-306C. The Fat Loss Monitor (Omron Fat Loss Monitor, ModelHBF-306C) displays the estimated value of body fat percentage by bioelectrical impedance method and indicates the Body Mass Index (BMI). The bioelectrical impedance, skinfold, and hydrostatic weighing methods have all been shown to be reliable measures of body composition (r = .957-.987). (23)

Eating Attitudes Test (EAT-26)

The Eating Attitudes Test (EAT-26) was used to differentiate participants with anorexia nervosa, bulimia nervosa, binge-eating, and those without disordered eating characteristics. It is a 26-item measurement consisting of three subscales: 1) dieting, 2) bulimia and food perception, and 3) oral control. Scoring for this instrument was a Likert scale of six possible answers(always, usually, often, sometimes, rarely, never). Scores ranged from zero to three for each question and a total score greater than 20 indicates excessive body image concern that may identify an eating disorder (20, 21). The EAT-26has been proven to be a reliable (r =.88) measurement. (7)

Figural Rating Silhouettes

Body size judgments were obtained using the Stunkard Figure Rating Scale(see figure 1). This scale consists of a nine-figure scale of numbered silhouettes that increase gradually in size from very thin (a value of 1) to very obese (a value of 9). (22) Two body size perception variables were included in the current study. “Self-perceived body size” is the number of the figure selected by participants in response to the prompt“Choose the figure that reflects how you think you currently look.”“Ideal body size” is the number of the figure chosen in response to the prompt “Choose your ideal figure.” This scale has good test-retest reliability and adequate validity (23, 24). Following the methods of other investigators, we defined body size satisfaction as the difference between self-perceived body size and ideal body size (25, 26, 27, 28). A body size discrepancy index variable was created for each participant by subtracting the number of the figure selected as the ideal body size from the number of the figure selected as the self-perceived current body size (28). A high body size discrepancy value signifies low satisfaction with body size, and a low value signifies greater satisfaction with body size.

Multidimensional Body-Self Relations Questionnaire

The Multidimensional Body-Self Relations Questionnaire (MBSRQ) is a 69 item self-report inventory for the assessment of self-attitudinal aspects of the body image construct. The MBSRQ measures satisfaction and orientation with body appearance, fitness, and health. In addition to seven subscales (Appearance Evaluation and Orientation, Fitness Evaluation and Orientation, Health Evaluation and Orientation, and Illness Orientation), the MBSRQ has three special multi-item subscales: (1) The Body Areas Satisfaction Scale (BASS)approaches body image evaluation as dissatisfaction-satisfaction with body areas and attributes; 2) The Overweight Preoccupation Scale assesses fat anxiety, weight vigilance, dieting, and eating restraint; and 3) The Self-Classified Weight Scale assesses self-appraisals of weight from“very underweight” to “very overweight.” Internal consistency for MBSRQ subscales range from .74 -.91. This questionnaire has been studied and used extensively in the college population. Internal consistency for the subscales of the MBSRQ ranged from .67 to .85 for males and .71 to .86 for females (9).

Physical Activity Scale

Level of physical activity was obtained by self-report with the NASA Activity Scale (NAS) (29, 30). The scale enables subjects to rate their general activity behavior over the previous 30 days. The scale range is from 0 to 10,which is based on the total weekly minutes spent in exercise or the total weekly miles run or walked. A NAS of 0-1 represents very low activity. A rating of 2-3 represents regular recreation or work of modest effort in such activities as golf or yard work for a weekly total of between 30 min to 2 h.Ratings of 4-10 represent regular participation in aerobic exercise ranging from light to heavy exercise.

Procedures

The participants were instructed by a trained individual to fill out the information packets provided on clipboards. First, the participants completed a personal identification and demographic sheet that contained general information such as age and dance or sport category. The participants then completed the MBSRQ-AS, the EAT-26, Physical Activity Questionnaire, and the Stunkard Figural Rating Scale (31, 20, 29, 22). As the participants completed the written component of the study, another trained individual took height and weight measures of the participants and recorded the body mass index (BMI) from a hand-held BIA analyzer. Weight was taken using a Tanita WB-110A Digital Scale and height was taken using a using a Seca 420 measuring stadiometer. A test/retest method was utilized for both measures to offset measurement error.In the measure of weight, the individual’s weight was recorded, the participant stepped off the digital scale and the scale was returned to“zero”. The measure was then taken again and recorded. In the measure of height, the same procedure of test/retest was used. When all measures were taken, the average of the two measures was then recorded. The measures were then taken by the researchers and converted using the formula(BMI = weight/height M2). BMI was then calculated and recorded for all participants. When the information was completed, the participants returned the packets to the trained administrator. Data sheets were collected and kept in a locked file cabinet for confidentiality.

A total of 51 participants completed the MBSRQ-AS, EAT-26, a Physical Activity Questionnaire, Stunkard Figural Silhouettes, and body fat measurements. Descriptive statistics are presented in Table 1. The Dancers and the Fitness group were significantly lower in body fat and higher in physical activity and the on the EAT-26. A MANOVA was conducted to determine group differences among the different measures and the subscales.

<img
alt=”Table 1 – Figure Rating Means for each Group (dancer, fitness, & control)”
src=”http://www.thesportjournal.org/files/Table 1 – Figure Rating Means for each Group (dancer, fitness, & control).png”
width=”470″ height=”233″ />

RESULTS

The MANOVA indicated a significant relation (Wilk’s Lambda = .106, F =8.735, p<.001). Post hoc tests were conducted and analyses were examined to determine directionality. Results showed that the dancers scored significantly higher on the Appearance Orientation subscale (p=.034) with no difference between the control and fitness cohort. Dancers also significantly perceived themselves to be overweight (p=.048) with no difference between the other two groups. Both the dancers (p<.001) and the fitness cohort (p<.001) scored as exhibiting disordered eating patterns as rated by the EAT-26 (see Table 2).

<src=”http://www.thesportjournal.org/files/Table 2-Percent Fat and Eat-26 Totals for Subjects.png”
width=”461″ height=”239″ />

 

Even though the dancers had a low percent body fat (M=17.6), they tended to place more importance on how they look. Body dissatisfaction measures often focus on body build and are operationalized as the difference between ideal and self-perceived current figure as selected from a group of drawings (32, 33,34). Measures of body dissatisfaction were computed by subtracting participants’ ratings of their Current Body Size (CBS) from their Ideal Body Size (IBS) to create a discrepancy index (DI). (28) The DI’s for each group were calculated with means and standard deviations recorded: Dancers(-.59/1.11), Fitness Group (-1.04/.966), and Control (-1.55/.85). The dancers in this study were dissatisfied with their bodies and wanted a thinner body as described in the discrepancy index, indicating a higher level of importance on their appearance (p=.045).

DISCUSSION

The primary focus of this investigation was to examine collegiate dance team participants to see if they exhibited body image distortions and disordered eating habits as exhibited in other female performers. Even though the dancers had a low percent body fat (M = 17.6), they tended to place more importance on how they look. The dancers perceived themselves to be overweight and engaged in disordered eating patterns. These types of perceptions and behaviors are disturbing, but not surprising since dancers have exhibited a drive for thinness to compete (2).

The findings of the data for this study are consistent with previous studies regarding body image in females (6, 35, 36). The females in this study perceived their current figure as heavier than their ideal figure. Although literature available on dancers exists, many of the studies have focused on ballet dancers and other professional dancer types. Future research should examine dance team participants to see if the pressures are similar (i.e.,rehearsing with mirrors and being viewed during their performance by an audience). To fully understand the scope of the issue and the psychological factors that accompany the quest for achieving a certain appearance, future research should include other female cohorts such as elite athletes, obligatory exercisers, and sedentary females to determine any similarities and differences in the groups.

These results indicate that dancers had higher incidence of negative body image disturbances as compared with the controls. Dancers are usually expected to be slim, well-proportioned, and toned and are placed under a great deal of pressure to maintain these features. Often, the various aspects of a dance class can potentially lead to a negative body image (37). The pressures of being thin may present negative body images for dance team members (38). A national survey conducted reported that body image concerns continue to be prevalent among American women (39). Levels of body dissatisfaction may also foster negative affect because appearance is a central dimension for women in our culture (40).

While the dangers of distorted body image are present in the dance world,measures to minimize their impact should include coaches who focus on performance rather than personal appearance. Taking an active interest in how their dancers view themselves is critical to a more comprehensive understanding of the causes of body image concern. By further addressing this issue,researchers can also help minimize health risks in female participants as well as reduce body image dissatisfaction.

Limitations & Implications

Limitations to this study include the sample size. In addition, this study investigated indicators of disordered eating attitudes and behaviors rather than clinical diagnoses of eating disorders. Other variables that are contributing factors to the prevalence of disordered eating were not investigated. The results of the EAT-26 test were not intended to diagnose nor suggest an eating or life-threatening disorder; however, the EAT-26 was used because it has proven to be an effective screening tool in identifying eating disorder symptomology and allows for further investigation for treatment.

APPLICATIONS IN SPORT

Body image has been the subject of much research conducted in recent years.As a result, body image is now recognized a multidimensional construct with complex aspects, particularly perceptual. The majority of the existing data indicates that body image concerns are prevalent among American females. With the recent phenomenal growth of dance team participation and the increasing number of female participants; a closer examination is warranted. Yet, there is a paucity of research available on dance team participants and their perceptions of their body appearance. Because dance team members wear a designated uniform/outfit, dance to a learned synchronized routine, and perform in front of an audience, they are subjected to visual scrutinization of fans/viewers. The uniqueness of the stressors and demands placed on the dancers complicates this issue. Additional knowledge of how dance team members perceive how they look and what the audience thinks of them in regards to abilities and their physical appearance deserves further investigation. Dealing with such information will not only benefit dance team members body image and self-esteem, but assist coaches and directors in ways to assist young women in resulting body image dissatisfaction.

REFERENCES

1. Thompson, K. (1999). Exacting beauty: Theory, assessment, and treatment of body image disturbance. Washington, DC: American Psychological Association.

2. Wood, K. C., Becker, J. A., & Thompson, J. K. (1996). Body image dissatisfaction in preadolescent children. Journal of Applied Developmental Psychology, 17, 85-100.

3. Garner, D. M., Garfinkel, P. E., Schwartz, D., and Thompson, M. (1980). Cultural expectations of thinness in women. Psychological Reports, 47,483-491.

4. Cash, T. F., & Pruzinsky, T. (1990). Body images: development,deviance, and change. New York: NY, Guilford Press.

5. Cash, T. F., & Brown, T. A. (1987). Body image in anorexia nervosa and bulimia nervosa: A review of the literature. Behavioral Modification, 11, 487-521.

6. Fallon, A. E. & Rozin, P. (1985). Sex differences in perceptions of desirable body shape. Journal of Abnormal Psychology, 94, 102-105.

7. Garner, D. M. & Garfinkel, P. E. (1979). The Eating Attitudes Test:An index of the symptoms of anorexia nervosa. Psychological Medicine,9, 273-279.

8. National Alliance for the Mentally Ill (2003). Fact sheet,http://www.ncsacw.samhsa.gov/files/

9. Sundgot-Borgen, J. (1993). Prevalence of eating disorders in elite female athletes. International Journal of Sport Nutrition, 3, 29–40.

10. Tiggemann, M., and Slater, A. (2001). A test of objectivity theory informer dancers and non-dancers. Psychology of Women Quarterly, 25, 1,57-64.

11. Pierce, E. F., & Daleng, M. L. (1998). Distortion of body image among elite female dancers. Perceptual and Motor Skills, 87, 3,769-770.

12. Sowder, K., Hennefer, A., Pemberton, C., & Easterly, D. (2004). Defining “Sport”. Athletic Management, 16.02,February/March.

13. National Federation of State High School Associations(http://www.nfhs.org/)

14. National Collegiate Athletic Association (NCAA) (http://www.ncaa.org/)

15. Carman, J. (2011). Passing on the Magic. Dance Magazine, 85,12, 50-54.

16. Radell, S. A., Adame, D.D., & Cole, S.P. (2002). The effect of teaching with mirrors on body image and locus of control in women college dancers: A pretest- post test study. Research Quarterly for Exercise and Sport, 74, 1, A-3.

17. Schneider, D. J. (1974). Effects of dress on self-presentation.Psychological Reports, 35, 1, 167-170.

18. Fredrickson, B. L., Roberts, T., Noll, S. M., Quinn, D.M., & Twenge,J.M. (1998). That swimsuit becomes you: Sex differences in self-objectification, restrained eating, and math performance. Journal of Personality and Social Psychology, 75, 1, 269-284.

19. Price, B. R., & Pettijohn, T. F. (2006). The effect of ballet dance attire on body and self-perceptions of female dancers. Social Behavior and Personality, 34, 8, 991-998.

20. Garner, D. M., Olmsted, M. P., Bohr, Y., & Garfinkel, P. (1982). The eating attitudes test: Psychometric features and clinical correlates.Psychological Medicine, 12, 871 878.

21. Williamson, D. A., Davis, C. J., Goreczny, A. J., & Blouin, D. C.(1989). Body image disturbances in bulimia nervosa: Influences of actual body size. Journal of Abnormal Psychology, 98, 97-99.

22. Stunkard, A., Sorensen, T. & Schulsinger, F. (1983). Use of the Danish adoption register for the study of obesity and thinness. In S. Kety(Ed.), The genetics of neurological and psychiatric disorders (pp.115-120). New York: Raven Press.

23. Thompson, J. K. & Altabe, M. N. (1991). Psychometric qualities of the figure rating scale. International Journal of Eating Disorders,10, 5, 615-619.

24. Smith, D. E., Thompson, J. K., Raczynski, J.M., and Hilner, J. E.(1999). Body image among men and women in a biracial cohort: The CARDIA study.International Journal of Eating Disorders, 25, 1, 71–82.

25. Garner, D. M., Garfinkel, P. E., and O’ Shaughnessy, M. (1985). The validity of the distinction between bulimia with and without anorexia nervosa.American Journal of Psychiatry, 142, 581-587.

26. Flynn, K., & Fitzgibbon, M. (1996). Body images and obesity risk among Black females: A review of the literature. Annals of Behavioral Medicine, 20, 1, 13-24.

27. Furnham, A., Badmin, N., & Sneade, I. (2002). Body image dissatisfaction: Gender differences in eating attitudes, self-esteem, and reasons for exercise. The Journal of Psychology, 136, 6, 581-596.

28. Thompson, K. (1996). Assessing body image disturbance: Measures, methodology, and implementation. In J.K. Thompson (Ed.), Body image, eating disorders, and obesity (pp. 49-81). Washington, DC: American Psychological Association.

29. Jackson, A.S., et al. (1996). Changes in aerobic power of women, ages 20to 64 years. Medicine and Science in Sports and Exercise, 28: 884-891.

30. Jackson, A.S., et al. (1990). Prediction of functional aerobic capacity without exercise testing. Medicine and Science in Sports and Exercise,22:863-870.

31. Cash, T. F. (1990). Body images: Development, deviance, and change. Cash, Thomas F. (Ed.); Pruzinsky, Thomas (Ed.); New York, NY, US: Guilford Press, 1990. pp. 51-79.

32. Thompson, J. K., and Smolak, L. (2001). Body Image, Eating Disorders, and Obesity in Youth: Assessment, Prevention, and Treatment.2ndEd., Washington, DC, US: American Psychological Association, 389. pp. 54-55.

33. Candy, C. M. & Fee, V.E. (1998). Underlying Dimensions and Psychometric Properties of the Eating Behaviors and Body Image Test for Preadolescent Girls. Journal of Clinical Child Psychology, 27, 117-127.

34. Collins, M. (1991). Body figure perceptions and preferences among preadolescent children. International Journal of Eating Disorders, 10,100-108.

35. Tiggemann, M. (1992). Body-size dissatisfaction: Individual differences in age and gender, and relationship with self-esteem. Personality and Individual Differences, 13, 39-43.

36. Demarest, J. & Langer, E. (1996). Perception of body shape by underweight, average, and overweight men and women. Perceptual and MotorSkills, 83, 569- 570.

37. Oliver, W. (2008). Body image in the dance class. Journal of Physical Education, Recreation & Dance (JOPERD), 79, 5, 18-25.

38. Irving, L. (1990). Mirror images: Effects of the standard of beauty onthe self- and body-esteem of women exhibiting varying levels of bulimic symptoms. Journal of Social and Clinical Psychology, 9, 230-242.

39. Cash, F. & Henry, E. (1995). Women’s Body Images: The results of a national survey in the USA. Sex Roles, 33, 19-28.

40. Thompson, K. & Stice, E. (2001). Thin-Ideal Internalization: Mounting Evidence for a New Risk Factor for Body-Image Disturbance and Eating Pathology.Current Directions in Psychological Science, 10, 5, 181-183.

 

2015-11-08T07:39:52-06:00August 22nd, 2013|Contemporary Sports Issues, Sports Studies and Sports Psychology, Women and Sports|Comments Off on A Comparison of Body Image Perceptions for Female Competitive Dancers, Fitness Cohort, and Non-Dancers in a College Population

Security Models in Mega Sport Events between Safety and Human Rights (Case of Vancouver 2010)

Authors: Moez Baklouti*(1), Ph.D. & Zakaria Namsi, M. A.(2)

(1) Moez Baklouti is a Faculty member (Associate Professor) at Tunis University and the Research Unit Head of Tunis Sports Academy located in Vancouver, Canada.

(2) Zakaria Namsi is a Faculty member (Assistant Professor) at Ksar Said Sports and Physical Education Institute, Tunis.

*Corresponding Author:
Moez Baklouti, Ph. D.
14065 77A Ave Surrey, V3W2X2 BC Canada
phd_3a@yahoo.com
778-628-8019

ABSTRACT

This study examines the conflict between liberty and security in sporting mega-events by ensuring that prohibited items do not enter an Olympic Games venue while guaranteeing service excellence. A random sample of spectators and journalists (N= 1081) from Vancouver 2010 Winter Olympics responded to a survey about customer service and security in the event. Chi-square tests for two independent samples were used along with Crosstabs procedures to test the differences in service and security between journalists and spectators.

The results revealed that a successful security model in mega-sport events is based on two pillars: service excellence that depends on the time spent at the portal, the communication with customers, the kind of staff serving in the venue, and mainly on the cooperation between all security corps in charge.

INTRODUCTION

Sport managers’ focus on security became after the New York terrorist attacks on September 11, 2001 the main concern of sport management, especially in the field of sport event organization. Other aspects, such as, organizational theory, sport marketing, sport facility management, sport law and policy, economics and finance, gender and diversity, have been classified less important, because they cannot stand in the absence of security. In the last few decades, there has been a growing concern regarding individuals’ safety, because the 9/11 incident showed that terrorists, who hit The World Trade Center and killed around 3000 people, could land with those 4 planes on 4 stadiums and harm 400000 spectators. Such scenario proved that the majority of our sport venues were and are still not protected. As an example of the difficulty of articulating the concept, Rothschild (1995) describes human security philosophically as part of both a broadening and a deepening of what we once viewed as security. She argues that the focus on state security must be extended to include supranational systems as well as the individual condition,and the range of included harms must be broadened to include serious threats to either. Also, the responsibility to ensure security must be diffused to include local governments, international agreements, NGO’s [non-governmental organization], public opinion, and the financial market. Although not an explicit definition, this conceptualization provides an example of how narrow the traditional paradigm has been as well as how complex the expansion of the concept can become” (Owen, 2004).

However, the controversy over the security concept leads sport managers to exaggerate and reach extreme resolutions that may harm the dignity of the people and threaten the human rights value. So, how can we reach a compromise whereby we protect our spectators by avoiding any prohibited item to get into the venues while ensuring an excellent customer service? “ ForMontesquieu, this was a singular focus on freedom and the perceived rights of individuals over the dictated security provided by the state. Security for Adam Smith meant the protection of the individual from ‘sudden or violent attack on one’s person or property’–this security being the most important prerequisite for a successful and ‘opulent’ society.Similarly, Condorcet described a societal contract in which the security of the individual was the central principle” (Owen, 2004).

This discussion leads us to better understand the role of each individual in the security process and to determine the responsibility of the highest rank of government officials to the common security agent in charge of a simple task during the sport event. “For Hobbes, it meant little whether aman’s insecurity was at the hands of a local thief, or an invading army.Protection from either, he believed, was the absolute responsibility of the state. For this protection, the citizen should give up any and all individual rights to his country, his protector— security prevailing over liberty” (Ullman, 1983). Liberty stands behind a mutual race between the anticipation of security measures and terrorists’ up-to-date attempts to transgress these boundaries, “ terrorists are explicitly in the business of uncertainty. They play on randomness to keep whole populations in fear,anticipation, and disestablishment. They precipitate the urge for more certainty, expressed through escalating security measures” (Ericson &Doyle, 2004).

The full protection of people and facilities in sport events cannot be reached instantly, rather it is a long-term and highly complex process requiring considerable data gathering. “ The context of terrorism has relevance to sport events, and the potential and realized impacts on the management of contemporary sport events have been profound” (Taylor &Toohey, 2006). For this reason, sport managers are dealing in each event with different platforms, new criteria of the hosting country, its own history with terrorism, its prior experience with events, and mainly its proper philosophy of the security model whether the so-called hard model, or the soft model, or even an intermediate model. Therefore, “by understanding the risk society and what this means in for sport event management, we can challenge dominant sport management paradigms and provide an emergent theoretical background by which to understand the impact of terrorism on sport event spectators”(Toohey & Taylor, 2008).

LITERATURE REVIEW

From this perspective, sport mega-events (SMEs) have become global occasions of economic, political, and social importance, for its impact on tourism (Degen, 2004; Euchner, 1999), and international status (Ahlert, 2006). To observe the aspects of SMEs, social development and cultural politics were delighted by (Close, Askew, & Xin, 2006; Marivoet, 2006; Roche, 2000, 2003;Whitson & Horne, 2006). “Sport mega-event security, in itself, is a complex assemblage of social control mechanisms that is undergoing profound change, notably in terms of costs, personnel, the rising influence of private security, the perceived dangers of terrorism, and the focus on indigenous crime” (Giulianotti & Klauser, 2010).

We should be alert that critical infrastructure (CI) is a vital component to develop any security strategy. This strategy must be based on continuous prevention regardless if the event takes place, or not because the reduction of certain pattern makes EMs more comfortable vis-à-vis the international instances. International Sport Institutions (ISI; i.e., IOC, FIFA, NFL) coerce complying with the basic requirements to hold an event, which give a packed confidence of safety and security in mega events. However, prototypes must respect the psychological states of spectators, because they are attending a show and provide an excellent customer service in sport events. The security process in the airports, for example, cannot be compared with the one of entering the venues. Even if the physical objective and the manipulation are the same, the traveler is somehow forced to make his/her trip; however, the sport spectator attends the games for fun, and the security measures should not affect this purpose and intervene with the human rights standards.

These norms are valid for different event sizes and for multiple levels of broadcasting. According to Gibson (1998), event sport tourism refers to tourists who travel to watch sporting events. Examples of event sport tourism may include events, such as, the Olympic Games, World Cup, Professional Golf Association (PGA) tournaments, and events related to professional sport teams or top U.S. college basketball and football teams.

To frame the theory context of our study, we consider SME with two essential grounds. First, the socially contested domain, that is develop the concept of the security field, as derived particularly from the sociology of Bourdieu (1990, 1993, pp. 72-76; see Wacquant, 1989), and as adapted and extended by Crossley (2002, p. 674). Second, risk theories here would include the concept of “reflexive modernization” (Beck, 1992; Lash, Szerszynski, &Wynne, 1996), Foucauldi an thinking regarding new forms of“governmentality” for shaping public actions (O’ Malley,2004), and new perceptions or cultural senses of risk within late-modern societies (Boyne, 2003; Lupton, 1999; Slovic, 2000; Tulloch, 2006). “Risk theory in this regard helps to clarify and to explicate a wide range of social processes associated with sport mega-event securitization: for example, how specific security risks and “risk groups” are identified by relevant stakeholders at different sport mega-events, how security institutions(both public and private) implement specific risk-management techniques within particular contexts and how risk legacies remain in post sport mega-event contexts” (Giulianotti & Klauser, 2010).

Critical Infrastructure

Moteff & Parfomak (2004) define “critical infrastructure as systems and assets, whether physical or virtual, so vital to the United States that the incapacity or destruction of such systems and assets would have a debilitating impact on security, national economic security, national public health or safety, or any combination of these matters.” As such, critical infrastructure is a highly complex phenomenon. In fact, critical infrastructure for sport venues is interconnected with other systems: facilities, technologies, networks, assets and services essential to the health, safety, security, or economic well-being of citizens, and the effective functioning of government. That is why, it is necessary for sport managers to be updated with the protection strategies provided by the government; unfortunately, “few sporting event organizers use strategic risk management plans. The main hindrance appears to be a lack of information and expertise available on risk management for sporting events. Risk management plans varied to a large extent, which may be due to the absence of accepted national standards for managing risk for sporting events and to the heterogeneous nature of sporting events” (Eisenhauer, 2005).

The major gap in CI lies in the difference in security strategies between the public sector managed by the government and the private sector owned by individuals or institutions. Whereas, “over 85 percent of the critical infrastructure in the United States is controlled by the private sector”(Forest, 2004), it seems that only 15 percent of the facility controlled by the government obeys to strict norms and control.

Indeed, it is worth highlighting that the National Strategy and Action Plan for CI establishes a risk-based approach for strengthening the resiliency and demands billion of dollars. Sport facilities also need an enormous segment to mend its vulnerabilities. “It has been estimated that organizers of sporting events worldwide spend over $2 billion perannum on security, although in years where “blanket security” is required for major events,this figure can rise to $6 billion” (Coaffee & Wood, 2006).

Safety and Security in Mega Events

Governments fear terrorist attacks and political demonstrations during sport mega events, mainly when we consider all Olympics have witnessed terrorist threats, “because there have been 168 terrorist attacks related to sport between 1972 and 2004” (Clark, 2004; Kennelly, 2005). “Since 9/11,the increased threat of terrorism has brought risk management to the forefront of mega-sport-event planning and has resulted in a range of new security measures for sport spectators and tougher safety standards for organizers” (Toohey & Taylor, 2008).

More importantly, protecting CIs must endure with the effective training of staff members and provide the necessary training to enhance performances in skill development processes. Training should frame incidents’ management,risk management and practices of protective measures, safety and security strategies, and business continuity and recovery principles. As “ threats of terrorism and political violence are often not only seen as to endanger the athletes, spectators and local population but also as a symbolic and political embarrassment—and hence financial risk— for host nations and organizing institutions” (Giulianotti & Klauser, 2010).

Atkinson and Young (2002) provide a general explanation of the nexus between sport and terrorism: for many reasons, individual terrorists or terrorist organizations might find suitable targets in athletes participating in games, spectators attending the events, or selected corporate sponsors of sports contests. Especially in those situations where athletic contests draw sizable international audiences in geographical settings already embroiled in strife, sport can be utilized as a vehicle for political sparring and waging and disseminating forms of political violence against others.

Whereas usually audiences attend sport mega events for a noble cause, such as, to apprehend peace principals and to spread camaraderie among people coming from all over the world. This kind of image gets disfigured in the presence of a terrorist act, because an act of terrorism leads to the opposite facade of people’s desire and turns the situation into a deeply dramatic scenario. Researchers are actually focused on the link between sport events and terrorism; “most of these studies have been located in discourses of sport sociology, psychology, and criminology, investigating the cognitive, affective, and overt behavioral aspects of violence. Implications drawn for sport management have primarily been associated with crowd control, risk management and athlete management” (Rubin, 2004; Whisenant,2003).(connect these lines)

For this particular reason, “terrorists also plan their acts to get as much media exposure as possible, thus giving attention to their cause”(Whisenant, 2003). The Olympics have grown with the increase of television broadcasting, “it is logical that terrorists will choose methods of mass destruction, such as bombings, and target transport or places where people gather, such as sport stadia. These reasons explain why mega sport events, such as the Olympic Games, are seen as possible terrorist targets” (Toohey andTaylor, 2008).

As a consequence, “more recently, the Olympic security paradigm has shifted. It now augments the rings of steel attitude, to one that has also encouraged resilience, both physically and managerially, through more counter terrorism measures and dispersing security responsibilities to different agencies and governments, rather than just organizing committees”(Coaffee & Wood, 2006). First, security from the gate should prevent unauthorized entrance to the venue and perform the following duties: keep prohibited items out of the venue, secure perimeters around the venue, conduct security inspections, verify tickets and authenticate credentials. This is a final check that follows extra-large security procedures: no fly zone, protecting access from water, precautions through roads, control of high buildings, preventing electronic and internet attacks, and‘sweeping’ all facilities designated to athletes, media people and spectators.

Indeed, “in planning and executing an attack, terrorists spend a lot of time selecting the target, analyzing and assessing opportunities and vulnerabilities as well as conducting their own research to secure the attack’s successful execution. Considering the time frame and activities associated with hosting the event, the threat to the World Cup starts with the building and renovation of sport facilities. On a strategic level, being able to gain access to plans of stadiums and actual access to facilities during the event takes time and careful planning, but contributes to the success full execution of an attack” (Botha, 2010).

Although infusing the event preparation with high level of security, such pact could be the reason for jamming the host country to gain the organization,the high expenses may be the cause for this failure. Johnson (2008) affirms that “successful security operations at recent games raise questions about whether the high levels of expenditure are proportionate to the level of threat. The security budget is often cited as a reason why many cities will not host the Games. It has also been used by one city to justify their decision not to host the Winter Olympics even after it had been awarded”.

Customer Service in Sporting Venues

Enhancing customer service by event managers (EMs) is now included in the requirements of human rights institutions, for spectators may not be treated as criminals when attending a sport show. The moment of entering a game venue is one of the most sensitive sensations for spectators. This feeling amplifies with the size of the event; therefore, the more important the event is, the greater its historical dimension becomes for the spectator. That is why, dealing with this situation is delicate, because EMs aim at delivering excellent customer service while ensuring strict security rules. Most researchers agree that “one way that a sport event can be differentiated from another event is on the basis of providing a high quality of service. One could argue that it is the only way for event planners to gain a competitive advantage” (Dwyer & Fredline, 2008). The expectations of spectators regarding the event service are associated with the importance of the event itself and with the EM before preparing their customers for admittance procedures to enter the venue. Therefore, “providing the visitor with a superior experience is based upon the event planners’ ability to help coordinate or provide a bundle of high quality services that meet or exceed the expectations of the guests visiting the city. Sport tourism is a service industry which is influenced by the quality of services provided”(Kouthouris & Alexandris, 2005).

Customer Satisfaction

“Customer satisfaction is defined as a pleasurable fulfillment response toward a good, service, benefit, or reward” (Oliver, 1997). Customer satisfaction has been considered as an interpreter of intentions to attend future sporting events (Cronin et al., 2000; Kwon, Trail, &Anderson; 2005; Wakefield & Blodgett, 1996), it has been understood in relation to service quality (Cronin & Taylor, 1992; Dobholkar, Shepherd,& Thorpe, 2000; Parasuraman, Zeithaml, & Berry, 1994), and increases the likelihood of enhanced customer loyalty (Cronin et al., 2000; Oliver,1997). Greenwell et al. (2002) examined how customers’ perceptions of as port facility within the context of service experience influence customer satisfaction. The findings suggest the customers’ perceptions of the physical facility were moderately associated with customer satisfaction.

Putting everyone who wanted access to the venue through a magnetic detector and searching their bags (mag-and-bag) is actually quietly accepted because sport customers know well that sport venues are not excluded from terrorist attacks and everyone will be subject to airport-type security with mag-and-bag and X-ray machines. “These processes functioned according to an agreed level of service; for example, a person queuing for security checking should not wait longer than three minutes. The level of service achieved depended on allocating adequate resources to that process, for example, by allocating 20mag-and-bag security gates to a venue entry”. (Beis et al., 2006).

Although event spectators recognize that these security measures are first established for their protection, they are concerned about the class of people dealing with them at the gates, spectators are undoubtedly anxious when treated by police officers, or military soldiers. Therefore, the major concern of spectators is no longer the way they have been welcomed, nor the security check time, it is rather that civilians have to do with officials while attending a show. The recent security procedures and techniques are far from being complex,for instance, “in terms of the Olympic Games, the variety of tactics used have included the deployment of Olympic police and military units to dedicated Olympic units to patrol the host city and country; the creation of Olympic Intelligence Centers to monitor information and coordinate responses; the formation of international Olympic Security task forces to share information between nations; the increasing use of surveillance, including digital surveillance to augment people; and the implementation of progressively more complex technology to prevent unauthorized access” (Johnson, 2008).

Service quality

Service quality is the conformity to the standard required by ISI. The organization committee has a propensity to achieve all the requirements and to satisfy the customer’s perceptions of that service. The consumer satisfaction literature views these expectations as predictions about what is likely to happen during an impending transaction, whereas the service quality literature views them as desires or wants expressed by the consumer(Kandampully, 2002). Grönroos (1984) defines service quality as “the outcome of an evaluation process where the consumer compares his expectations with the service he perceived he has received.”

Debates lay many concepts to measure service quality. Grönroos (1984)solicited technical quality for what the consumer receives and functional quality to answer how the consumer receives the service. Burns, Graefe, &Absher (2003) focused on the disagreement whether the consumer’s‘desires’ or ‘ideal standard’ should be measured.

Lehtinen and Lehtinen (1991) proposed two approaches to the analysis of service quality and its dimensions. The first approach contains three dimensions consisting of physical quality, interactive quality, and corporate quality. The second approach to the analysis of service quality and its dimensions was composed of two dimensions: process quality and output quality.

A positive experience for spectators let them return for future games. Therefore, EMS make spectators enjoy spending time at the stadium. Various attributes are crucial to attain the constancy of spectators in attending games: quality and outcome of the game, cleanliness of the arena, security in the parking area, seat location, parking location, and cleanliness of the restrooms (Kelley & Turley, 2001). However, venue access is actually a pillar in service quality. Venue access is also different from an event to another and from a country system to another and is mainly managed each time by staff, by civilian employees in the reception, or by official security people.

According to Kelley & Turley (2001), service quality attributes are employees, price, facility access, concessions, fan comfort, game experience,show time, convenience, and smoking. The evaluation of service quality depends on knowing and comparing price, employee action, ambiance stimulation, program evaluation, privilege appreciation and security. Chelladurai and Chang (2000) cite three targets of quality evaluations: a) the core service, b) the physical context such as the physical facilities and equipment in which the service is provided, and c) the interpersonal interactions in the performance of the service.

Authors classify service quality in special dimensions, but focus on the outcome quality in determining the overall service quality with search and experience outcome quality. Brady and Cronin’s (2001) model of service quality has three primary dimensions: a) interaction quality, b) physical environment quality, and c) outcome quality. Ko and Pastore (2004) propose a dimensional model of service quality in the recreation industry composed of program quality, interaction quality, and outcome quality.

Human Rights

“Anti-terrorism laws in a democratic state ruled by law only serve their purpose if they improve the ability of the state to defend itself against terrorist attacks, without excessively restricting the civil rights of the citizens” (Meyer, 2004). The controversy over the balance between liberty and security highlights that jeopardizing freedom for the sake of security creates the tension between security policies and freedom security prevailing over liberty. “The vague definition of public order and thus what may breach it jeopardizes not only the ideally equal implementation of the law in a given territory, but also the protection of civil rights and liberties in that the consequent weakening of the principle of legality entails that of the principle of proportionality and in some cases the principle of accountability” (Tsoukala, 2007).

Liberties are not established by the law and rules only, but are applied by agents who may not conform their practices to those rules; it is not about a misinterpretation but about entity philosophy of priorities’categorization, “while the defenders of human rights see in this shift the symptom of an ongoing redefinition of the power relations between the executive and the people or the (re)positioning of the state and civil agents in the political and security fields (or both), the executive branch refuses to see in it any jeopardizing of civil rights and liberties” (Tsoukala,2007).

Besides economic and sport developments, a mega event serves as a historical landmark and brings prestige and prosperity to the host country.“Research into mega-events and developing nations has been centered about questions of development, place promotion, signaling, identity building and human rights and political liberalization” (Black and Bezanson 2004; Black and van der Westhuizen 2004).

Hosting sport mega events is the responsibility of the government. In case of errors, such burden has been criticized from the international opinion and has also been disparaged by domestic politicians. “Because absolute security cannot be attained, politicians worry about leaving gaps in prevention, because this could have the side effect of making them take responsibility for the harms inflicted the next time. Therefore, politicians tend to maximize their security preparation, at the price of more restrictions on citizens’ freedoms and civil rights than are necessary for effective prevention” (Meyer, 2004).

The protection of human rights must be imbedded in the strategy for the effective combat against terrorism and it cannot be successful safety if there is a lack of respect for human beings and the values of freedom. “The subject of counter-terrorism and human rights has attracted considerable interest since the establishment of the Counter-Terrorism Committee (CTC) in 2001. In Security Council (2003) and later resolutions, the Council has said that States must ensure that any measures taken to combat terrorism comply with all their obligations under international law, and should adopt such measures in accordance with international law, in particular international human rights, refugee, and humanitarian law” (CTC, 2003).

Precarious balance between security and freedom

The Canadian Charter of Rights and Freedoms (5th Amendment in the USA) obliges the state to prove criminal behavior and not to take any action against a person suspected of a crime, so everyone is presumed innocent until proven guilty. Ashworth (1998) has rightly suggested that the notion of balance is a rhetorical device of which one must be extremely wary. “Balance” is self-evidently a worthy goal and, thus, acts as a substitute for real argument. Waldron (2003) has identified a problematic connotation of quantity and precision in the language of balance, including the assumption that the relation between security and liberty is a zero-sum game.

Perhaps a separate definition of security and liberty cannot find an intersection that satisfies both; however, we do not need to identify security with liberty. An American hurdler explains, “Every step you take, there are guards with machine guns in the Olympic Village, I know they’re there to protect you, but it’s scary. I’m not used to it, so it makes me cringe a little bit. It wasn’t like this at all in Sydney” (May, 2004).

Foucault (1991, 1997, 2000a, 2000b) has shown how liberalism enacts another form of political rationality that sets mechanisms for a ‘society of security’ in place rather than resist the push to security in the name of liberty. Johnson (2008) further supported: “The Atlanta bombing demonstrated that massive security investments cannot guarantee the safety of the public”Authors, politicians, managers, and philosophers have been conferring to challenge the idea of an equilibrium between security and liberty “to different political projects for the shaping of the modern state, the value of security remained the same. The difference between absolutism and liberalism is, therefore, not that where one stresses security the other stresses liberty; the difference does not lie in the tipping of a mythical ‘balance’ between liberty and security in one direction rather than another. Rather, the difference lies in the fact that absolutists saw no need to identify security with liberty” (Neocleous, 2007). “Much of the discussion concerning the theory and practices surrounding security centers on the relationship between these and their consequences for liberty. Either explicitly or implicitly, the assumption is that we must accept that we have to forgo a certain amount of liberty in our desire for security. The general claim is that in seeking security, states need to constantly limit the liberties of citizens, and that the democratic society is one which has always aimed to strike the right ‘balance’ between liberty and security” (Neocleous, 2007).

Is ‘Vancouver 2010’ a soft Model?

Security became the main condition to host the Olympic Games and other large scale sporting events. Winning these games’ elections for any country is also conditioned by the promotion of human rights and liberties, such events are great occasions to push dictatorship regimes, leading to an improvement in the human rights movement.

“The human rights organization ‘Human Rights Watch’ hopes, that the attention China will get as a result of the Olympic Games will help to improve the human rights situation” (OG & HR, 2008). Gill &Worden (2009) state as an example: “Given the serious ongoing human rights concerns in Russia, we respectfully reiterate our call for the IOC to establish a standing human rights committee or similar mechanism to monitor the adherence by Olympic host countries to basic human rights standards.”

The venue of Salt Lake City Winter Games was heavily populated by officials from the army, the police and many security companies. It is very understandable that ‘there is too much security’ because the Games were hosted a few months after 9/11. “The Athens security operations cost€1 billion, and represented more than 10% of the total direct costs. The expenditure was almost four times greater than for Sydney. There were approximately twice as many security personnel available in 2004 compared to the summer games four years before” (Johnson, 2008). ‘Athens2004’ meant a higher level of security than ever before provided for the games. However, unlike Greece, Italy’s ‘Turin 2006’ has more than enough military personnel and special forces to deal with the threat of all possible terrorist attacks, ranging from bombs to planes and even weapons of mass destruction. The Chinese government in “Beijing 2008” has implemented extraordinary security measures, including the mobilization of the military. “Security has not been thought to require special justification because in many ways it seems preferable to punishment” (Zedner, 2003). The cited Olympics were known as “hard security models” adoption,either the Games were after 9/11, or the political system is based on military management (i.e., China under a communist regime).

Vancouver Winter Games opted for what we call a “mild security model” because the security company charged in flowing spectators to the venues (Contemporary Security Canada) and used civilians to perform mag-and-bag and X-Ray machines. Thus, spectators, while entering to watch the games, are not facing military people or police officers (Figure 1). The second‘layer or belt’ is managed by security supervisors. Then, the role of the police officer (third layer) comes in case of prohibited items found with the intention to infiltrate the venue. In this situation, a male factor is treated with the right corps, and human rights rule is respected. The timing goal set up for the security procedures in the gate is thirty seconds perspectator. The training of screeners, X-Ray operators, and their supervisors was based on ensuring full security vocation while providing gentle spectator access through their portals with the finest performances and an excellent customer service.

Figure 1

It is worth highlighting that the Special Reporter on the Promotion and Protection of Human Rights while countering terrorism, operating under the new Human Rights Council, works to identify, exchange, and promote best practices on measures to counter terrorism that respect human rights and fundamental freedom. Security agents represent a brilliant facet to implement the respect for human rights. Sport event spectators admire the fact that they are well informed and welcomed and the security system guarantees 100% of their safety. With a purpose to reach a complete enjoyment for the sports show customers, such “model” is essentially based on two pillars: security and service excellence (Figure 2).

Figure 2

Figure 2 – Tools concept for Sport’s Show Joy through Security& Service Excellence.

This study focuses on the conflict between “liberty” and“security” and what model sport event organizers should adopt to match the characteristics of the host country? Then, what are the tools to provide quality service for the spectators? Do timing, security people, and quality information guarantee the comfort desired by the customers? Johnson (2008) also considered the timing and asked: “The organizers of the Turin games advised spectators to leave more than three hours to enter some venues for the 2006 winter games. Such delays raise important questions about how long it is reasonable to expect people to wait in order for security measures to be completed”. Moreover, who is responsible for taking the security measures to prepare, prevent, deter, or delay a future terrorist attack on a sporting event or stadium? How people deem about the concept of ‘CI’?Ultimately, what are the means to raise the trust that spectators are fully protected while attending the games?

These research questions culminate to our main hypothesis: A security model in sport events should respect both the full protection of the venue and the value of human rights while welcoming spectators and subsequently:

  • Providing spectators’ service excellence depends on the time spent at the portal before entering the venue, the quality of communication, the serving staff, and the previously provided information regarding the security measures.
  • The success of a security model in mega sport events is highly conditioned by the cooperation between all corps in charge of this mission, such as government, police, local city head, athletic directors, private security companies, and the structure in use.

METHOD

Supported by the literature review a total of ten questions were generated to represent two items: (A) ‘Customer service in the event’ and (B)‘Security in the event’.

Participants

The study sample covered 1081 respondents (Table 1), composed of 286 journalists and 795 spectators. Journalists were contacted before the games start at MMC, during the competitions in the venues (indoors or outdoors) and in MMC, and after the games in MMC again. Spectators were met on the opening and closing ceremonies, during the competitions in the venues (indoors or outdoors).

<imgalt=”Table 1- The study sample (Journalists & Spectators) for ‘Vancouver 2010’ Winter Olympics.”src=”Desktop/Table 1- The study sample (Journalists & Spectators) for ‘Vancouver 2010’ Winter Olympics..png”width=”673″ height=”329″ />

Table 1- The study sample (Journalists & Spectators) for‘Vancouver 2010’ Winter Olympics.

Media people in the study sample were represented by 75 journalists from Canada (26.2%), 45 journalists from USA (15.7%), 27 journalists from China, 25 journalists from Russia and 15 journalists from Germany. The percentages of spectators are as follows: 53.7% Canadians, 20.5% Americans, 5.5% Chinese, and 3.1% French (Table 2).

<imgalt=”Table 2- Countries of journalists and spectators with classification and percentages”src=”Desktop/Table 2- Countries of journalists and spectators with classification and percentages.jpg”width=”644″ height=”552″ />

Table 2- Countries of journalists and spectators with classification and percentages

Procedures

Respondents were informed that they are helping a scientific research regarding the service and security in the event. Trained volunteers (event services) of the organization committee conducted the survey in their day-off by contacting the spectator after he/she takes seat and before the game starts to guide the respondent, and as tested before, the tête-à-tête takes six to seven minutes. Extra information was included in the survey content regarding the citizenship and the gender of the respondent. The respondents were randomly assigned for City Venues: Vancouver Olympic Center, Pacific Coliseum, Cypress Mountain, Canada Hockey Place, UBC Thunderbird Arena, Richmond Olympic Oval,and Main Media Center, or for Whistler Venues: Whistler Creekside, Whistler Olympic Park, and The Whistler Sliding Center, which created relatively equal samples for each condition.

Measures

The questionnaire consists of items. Item A measures the comfortable time judged when dealing with the security procedures at the venue gates (A1 &A2), the information about the regulations regarding the entrance of the venue and the cooperation (A3 & A4), and the evaluation of service quality provided by the security people (A5). In item (B), the focus was on the security filter met at the portal when entering the venue (B6 & B7), the concept of ‘CI’ (B8), responsibility measures (B9), and the level of security felt by spectators (B10).

The response format for all questions was the five-point Likert scale, with the following values: 1 (Strongly disagree), 2 (Disagree), 3 (Neutral), 4 (Agree), and 5 (Strongly agree). Other five-point summated rating scale used the following format: 1 (Insecure), 2 (Somehow not secure), 3 (Don’tknow), 4 (Somehow secure), and 5 (Secure). In B6 and B9, attendees determine and classify responsibilities.

To determine the content validity of this survey, three experts—university professor specialist in sport event organization, a mega EM, and professional in customer service and marketing—were invited to provide feedback concerning the conceptual appropriateness of the items. Based on this feedback, modifications were made. Then, a pilot test was made and granted a reliability coefficient of .92, the test-retest had a two-week interval for the eighteen spectators who attended hockey games with the same security setup for the 2010 Vancouver Winter Olympics. There was an eight-day interval for the seven reporters, because MMC (Main Media Center at Canada place Vancouver) was not operational beyond this range. Based on the relevant results of validity and reliability, the questions were judged to be conceptually appropriate.

RESULTS

The data collected were analyzed using chi-square analyses (X2) and mean scores (M) and standard deviations were calculated (SD). A level of significance of .05 was used to test the results of the study.

Customer service in the event

The study gave a special importance to the timing as a component of quality service. The time spent at the portal for the security procedures before entering the venue was 30 seconds (sec.) per person and Games Security Screening (GSS) targeted it to ensure the visitors’ comfort and security.

Approximately 71% of journalists (M = 95.33; SD = 35.726) declared that they spent less than 30 sec. to get into the venue, but spectators (M =265.00; SD = 301.448) were not in this range because 76% judged that they spent over 30 seconds and even over one minute. The difference between groups is very significant (X2: 328.606, df: 2, p-value: 0). Conformably, the timing cited above influenced the position of journalists (M = 95.33;SD =38.280), half of whom notice that the time granted to the security procedures is reasonable, but the majority of spectators (M = 265.00;SD = 301.448) claimed that the time is uncomfortable. The difference between groups is very significant (X2: 365.561, df: 2, p-value: 0).

Statistics showed a significant difference between both categories of our samples (X2: 208.69, df: 1, p-value: 0); ¾ of journalists (M = 125.00;SD = 70.711) confirmed they were vaguely informed about the regulations regarding the entrance of the venue before they arrived. However, 4/5 of the spectators (M =317.00; SD = 277.186) stated they were not well informed. Regarding cooperation before coming to the venue, results showed that 51% of the journalists (M = 118.50; SD = 4.950) took some precautions and the majority (82%) of spectators (M = 363.50; SD =352.846) did, too. The difference between groups is again significant (X2:208.69, df: 1, p-value: 0).

Although journalists (M = 95.33; SD = 85.043) are satisfied with the service quality provided by the security people (65%), spectators (M =265.00; SD = 56.956) expressed equal evaluations about that service ranging between the dissatisfactory, average, and satisfactory judgements. However, the difference between groups remains significant (X2: 161.478, df: 2,p-value: 0).

Security in the event

While going through security portals, the study population (N: 1081) noticed that the security people they met are mostly “mixed corps” or“no official,” with the following ratio: 39% and 20%, respectively. The respondents did not recognize security people in charge (M = 216.2; SD =124.728), with a percentage of 18%, and no more than 12% distinguished“security company” and 9% “official police” (Figure 3).

Figure 3

Figure 3- Security people recognition by respondents

Respondents (787 of 814) confirmed that the security filter at the portalranges between hard to very strong. Statistics confirm that there is no significant difference between journalists and spectators (X2: 0.039, df: 1,p-value: 0.8434).

“The political agenda is ruling the concept of ‘critical infrastructure’ instead of the technical scientific conception”. After investigating into this new design, the majority of our respondents(82.2%) approved of the exposed idea. No significant difference between groups(X2: 1.899, df: 1, p-value: 0.1681) is noticed.

The rank ratio of the classification (Figure 4) made by the respondents in each venue showed that journalists and spectators consider the Local Police or Mounted Police the first people responsible for implementing the security measures to prevent, deter, or delay a future terrorist attack on a sporting event or stadium. Respondents also agreed to classify local city head in the second rank. Journalists, however, gave more importance to Politicians in the Government for the cited task unlike the spectators. Private Security Company was classified fourth for this responsibility. Finally, respondents determined the Private Security Company and the structure in use as last.

Figure 4

Figure 4 – Classification for structures taking the security measures.

When attending these winter Olympics, respondents felt safe at all venues,but with minor differences. The difference between groups is significant (X2:6.951, df: 1, p-value: 0.0083) as the majority of journalists (M = 107.50;SD = 126.572) and 85% of the spectators confirmed feeling very secure(M = 369.50; SD = 361.332).

DISCUSSION

Customer service in the event rises from the expectation of customers. Spectators seek comfort and security when attending the games, but have some directions to follow from buying the access tickets, to being seated and watching the game. Journalists enter the venue with an accreditation card, which was issued based on a previous security check. The situation explains the timing gap between journalists and spectators. Somehow, media people are trusted customers, so the screening at the gate venue is quick, and accurate recommendations during GSS training were delivered to pay special attention to them, because any incident could spread through the media and ultimately hurt the reputation of the organization. Spectators are considered as unknown customers, so GSS persons deal with different people with diverse backgrounds and different social levels. As a consequence, spectators judged that the security procedure timing exceeds the promised timing. It may represent confusion regarding the waiting time on line and the time spent on the security check before entering the venue, yet statistics confirmed the different attitudes of both the journalists and spectators.

Accordingly, journalists were comfortable to that timing whereas spectators were not. The timing target was not realistic for spectators, if we identify the screeners’ duty as searching bags, magnetometer operation, wanding, physical search, and ticket or accreditation checking, how can we set 30 seconds as the timing target? Event managers with GSS must adjust their timing target vis-à-vis the spectators, media, and especially human rights institutions. Statistics advise to keep the 30 seconds with journalists and aim 1 minute for spectators. Data shows that 1-minute target time for security procedure covers ¾ among spectators, and such timing agreement could be comfortable.

To ensure the safety and enjoyment of all spectators at the Olympics, spectators carrying forbidden items will be asked to either return them, or to dispose them immediately. Prohibited items at security gates cause the delay in entrance and may involve the customer into extra security procedures. That is why, the factor information before the games makes a smoother security-spectator contact. Journalists insisted that they were vaguely informed about the regulations regarding the entrance of the venue. Part of this position is due to the frequency of dealing with such events. Journalists are professionals who are used to attending conferences and events within the same security circumstances, so their jobs expose them to a large experience dealing with security in portals daily and maybe dozens of times. On the contrary, spectators are amateurs, usually with little previous experience in mega events, and sometimes, the excitement to the event makes the spectator forget about the instructions related to the security procedures and even if EMs did spread the information via the media, in the ticket, and by postings around the venues. It is understandable that all spectators took some necessary precautions before coming to the venue. Thanks to this cooperation, their waiting time and the security maneuver took less time. Precautions regarding security procedures for journalists are part of their duties, thus no special focus was required. The study data sustained the first part of our hypothesis that offering the spectators’ service excellence depends on the time spent at the portal before entering the venue, the quality of communication, the staff serving them, and the information previously provided regarding the security measures. Both journalists and spectators were equally satisfied with the event as a whole. Moreover, satisfaction is often evaluated by the joy felt by the event customer; indeed, customers declared not being bothered by any delays and receiving a special warm welcome.

Security agencies attempt to stay out of sight by using an array of surveillance technologies. This approach creates different security belts (layers) around the venues. The sporting event customer prefers to feel secure without seeing too much security people. The study results gave us an idea about the assortment of security people at security portals. It was very important that respondents noticed that the security people they met are mostly mixed corps, or “not official,” that is to say corresponding to the objective of recent “security model,” ensuring utter safety while respecting spectators’ dignity and meeting with civilians in all phases of venue services.

It was obvious for event spectators and journalists that the security filter is strong and they feel very secure. Regarding service quality, many authors highlight that such a feeling is satisfactory enough to judge the event successful. “Technical challenges, among these, the first concern is to ensure the safety and security of competitors and of the public”(Johnson, 2008). Respondents also pointed out that any security failures are the responsibility of the Local Police or Mounted Police, then the City Head gave special importance to Politicians in the Government, because the concept of CI has been removed from the technical and scientific and introduced to the political agenda.

The data supported our full hypothesis, and a security model in sport events should respect both the entire protection of the venue and the value of human rights when welcoming spectators. Vancouver Olympic security was one of the most talked about and most important factors in having a successful event.“After the purpose of a law has ceased to exist, or after coming to realize that some measures are ineffective, freedom’s rights then can regain full validity. This will prevent freedom’s rights from being limited longer than is absolutely necessary” (Meyer, 2004).

Eventually, it is important to stress through Vancouver 2010 how our study has contributed to theory. Whereas most previous research about security in Mega Sport Events merely displayed the problem vaguely, our study attempts to give concrete standards that will pave the way for future events and research.

Kelly and Turley (2001) never mentioned the timing as a major criterion among many that determine the quality and the outcome of the Games. Beis et al.(2006) suggested multiplying mag-and-bag security gates to a venue entry, because a person queuing for security checking should not wait longer than three minutes, and our data categorized all respondents in their range of the real time spent for security measures. Lehtinen and Lehtinen (1991) analyzed the quality of service from many dimensions whereas Chelladurai and Chang(2000) built the service quality on three criteria and failed to specify how this was measured. Greenwell et al. (2002) associated customers’perceptions with customer satisfaction. Our classifications conduct us to match the timing with the comfort level according to each range of the timing spent at the gates.

In sport tourism, Kouthouris and Alexandris (2005) considered the quality service as an event planner’s ability to coordinate with visitors. Our study differentiated the journalists from the spectators in terms of how they cooperated by taking actions that helped in the security context before appearing in the venue. Earlier, most authors merely classified service quality from different perspectives, but mainly focused on the outcome quality (Brandy& Cronin, 2001; Ko & Pastore, 2004). Dwyer and Fredline in 2008 noticed that a sport event could be differentiated from another just by its quality of service. Our study quantified the satisfaction and the dissatisfaction about the service for both journalists and spectators.

May (2004) witnessed that athletes could be negatively influenced by an excessive security presence to the point that they get scared. Tsoukala (2007) noticed that human rights defenders refuse the domination of security fields on people. Thus, our study scanned visitors’ opinions about security people and the types of visible corps nearby and at portals.

The concept of liberty, as perceived by Ericson and Doyle (2004) and Botha(2010), is that terrorists keep entire populations in fear and in security, which precipitates the urge for more severe security measures. The 2010 Olympic Games testified that journalists and spectators equally felt secure and serene, and judged the security filter at the portal as ‘hard to very strong’. Therefore, our data demonstrated that attendees were not terrorized or destabilized thanks to the tougher security standards adopted by the organizers. Our data, then, further support Toohey and Taylor’s(2008) findings.

Whereas Owen’s conceptualization (2004) of security responsibility proved to be vague, Coaffee and Wood (2006) made different agencies and governments share security rather than restricting it to organizing committees. Our data specifically ranked the “local police or mounted police”and the “local city head” as the first ones responsible for preventing, or delaying any potential terrorist attack on a well-defined sporting event, but also highlighted the differences in rank ratio between journalists and spectators.

Ashworth (1998) and Waldron (2003) cleared the notion of balance between security and liberty, Tsoukala (2007) defined the protection of civil rights and liberties vis-à-vis of public order and Johnson (2008) confirmed that successful security operations must be proportionate with the level of threat. This study provided a final report about the different attitudes of journalists and spectators in terms of comfort and service quality and also confirmed that these respondents felt secure during V2010. “In general terms, for social scientists, the contemporary security processes at sport mega-events have very strong social, political, and geographical dimensions, as reflected through social relationships, the everyday politics of the “war on terror,”and urban redevelopment” (Giulianotti & Klauser, 2010).

LIMITATIONS and DIRECTIONS for FUTURE RESEARCH

Using event service volunteers to conduct the survey was helpful. With their accreditation passes, they were easily moving between portals and had greater access to diverse spectators in different areas. However, we did not use this advantage to touch intensely other details in the questionnaire. It was the work of experts who validated the survey as they trimmed the questionnaire to avoid falling in the discomfort of respondents!

An attractive area for further research is to excavate deeply the data and find the divergence between indoor and outdoor venues. Moreover, integrating the difference between Olympics and Paralympics may be an addition to testing the proposed model. London was awarded the right to host the 2012 Olympic and Paralympic Games, and the United Kingdom suffered from recent terrorist attacks. “The 2012 Olympics will see further security legacies intechnological terms, including microphones attached to CCTV cameras and a massive extension of the national DNA database” (Giulianotti &Klauser, 2010). Then, which security model should they adopt in these Olympic Games? Contacts were made to scope a similar questionnaire with the games’ specification.

REFERENCES

1. Ahlert, G. (2006). Hosting the FIFA World Cup, Germany 2006: Macroeconomic and regional economic impacts. Journal of Convention and Event Tourism, 8(2), 57-77.

2. Ashworth, A. (1998). The Criminal Process: An Evaluative Study, Oxford: Oxford University Press.

3. Atkinson, M., & Young, K. (2002). Terror games: Media treatment of security issues at the 2002 Winter Olympic Games. OLYMPIKA: The International Journal of Olympic Studies, XI, 53−78.

4. Beis, D. A.; Loucopoulos, P. ; Pyrgiotis, Y.; & Zografos, K. G. (2006). PLATO Helps Athens Win Gold: Olympic Games Knowledge Modeling for Organizational Change and Resource Management; Interfaces: Vol. 36, No. 1, January–February 2006, pp. 26–42.

5. Black, D. R. & Bezanson, S. (2004). The Olympic Games, human rights and democratisation: lessons from Seoul and implications for Beijing. Third World Quarterly, 25 (7), 1245-1261.

6. Black, D. R. & van der Westhuizen, J. (2004). The allure of global games for ‘semi-peripheral’ polities and spaces: a research agenda. Third World Quarterly, 25(7), 1195-1214.

7. Botha, A. (2010). Preparations for the 2010 FIFA World Cup: Vulnerability and Threat of Terrorism; Elcano Royal Institute of International and Strategic Studies, Madrid, Spain; Issue: 14.

8. Bourdieu, P. (1990). In other words: Essays towards a reflexive sociology. Stanford, CA: Stanford University Press.

9. Bourdieu, P. (1993). Sociology in question. London: SAGE.

10. Boyne, R. (2003). Risk. Buckingham, UK: Open University Press.

11. Brady, M. K., & Cronin, J. J. (2001). Some new thoughts on conceptualizing perceived service quality: A hierarchical approach. Journal of Marketing, 65 (July 2001), 34-49.

12. Burns, R. C., Graefe, A. R., & Absher, J. D. (2003). Alternate measurement approaches to recreational customer satisfaction: Satisfaction-only versus gaps scores. Leisure Sciences, 25 (363-380).

13. Chelladurai, P., & Chang, K. (2000). Targets and standards of quality in sport services. Sport Management Review, 3, 1-22.

14. Clark, K. (2004, June 14). Targeting the Olympics. U.S. News and World Report, p. 34.

15. Close, P., Askew, D., & Xin, X. (2006). The Beijing Olympiad: The political economy of a sporting mega-event. London: Routledge.

16. Coaffee, J., & Wood, D. (2006). Security is coming home: Rethinking scale and constructing resilience in the global urban response to terrorist risk. International Relations, 20, 503−517.

17. Cronin, J.J., Brady, M.K., & Hult, G.T.M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193–218.

18. Cronin, J.J., & Taylor, S.A. (1992). Measuring service quality: Are-examination and extension. Journal of Marketing, 56(3), 56–68.

19. Crossley, N. (2002). Global anti-corporate struggle: A preliminary analysis. British Journal of Sociology, 53, 667-691.

20. [CTC] Counter-Terrorism Committee (2003). Security Council resolution, Human Rights, United Nations; resolution 1456.

21. Dabholkar, P.A., Shepherd, C.D., & Thorpe, D.I. (2000). Acomprehensive framework for service quality: An investigation of critical conceptual and measurement issues through a longitudinal study. Journal of Retailing, 76(2), 139–173.

22. Degen, M. (2004). Barcelona’s Games: The Olympics, urban design, and global tourism. In M. Sheller & J. Urry (Eds.), Tourism mobilities: Places to play, places in play (pp. 131-142). London: Routledge.

23. Dwyer, L. & Fredline, L. (2008). Special Sport Events – Part II; Journal of Sport Management, 22 / 495-500.

24. Eisenhauer, S. (2005). Sports Events and Risk Management in New Zealand: How safe is safe enough? e degree of Master in Tourism at the University of Otago, Dunedin, New Zealand (non published).

25. Ericson, R.V., & Doyle, A. (2004). Uncertain business: Risk, insurance and the limits of knowledge. Toronto: Toronto University Press, p. 141.

26. Euchner, C. C. (1999). Tourism and sports: The serious competition for play. In D. R. Judd & S. S. Fainstein (Eds.), The tourist city (pp. 215-232). London: Yale University Press.

27. Forest, J. (2004). Homeland Security: Critical infrastructure, Volume 3; Library of Congress Cataloging-in-Publication Data.

28. Foucault, M. (1991). Governmentality (1978), in G. Burchell, C. Gordon, P. Miller (eds.) The Foucault Effect: Studies in Governmentality, London: Harvester Wheatsheaf, pp. 87–104.

29. Foucault, M. (1997). Security, Territory, and Population, in Ethics: The Essential Works, Vol. 1, London: Penguin, pp. 67–72.

30. Foucault, M. (2000a). Omnes and Singulatim: Toward a Critique of Political Reason, in Power: The Essential Works, Vol. 3, London: Penguin, pp.298–325.

31. Foucault, M. (2000b). The Risks of Security, in Power: The Essential Works, Vol. 3, London: Penguin, pp. 365–381.

32. Gibson, H. (1998). The wide world of sport tourism. Parks &Recreation, 33(9), 108-114.

33. Gill, A. &Worden, M. (2009). Sochi Games and Murders of Russia’s Rights Defenders, Human Rights Watch; retrieved from: http://www.hrw.org/en/news/2009/08/28/letter-international-olympic-committee-regarding-sochi-games-and-murders-russia-s-ri, on Nov. 1, 2010.

34. Giulianotti, R. & Klauser, F. (2010). Security Governance and Sport Mega-events: Toward an Interdisciplinary Research Agenda; Journal of Sport and Social Issues, 34(1) 49 – 61, SAGE Publications.

35. Greenwell, T. C., Fink, J., & Pastore, D. (2002). Assessing the influence of the physical sports facility on customer satisfaction within the context of the service experience. Sport Management Review, 5, 129-148.

36. Grönroos, C. (1984). A service quality model and its marketing implications. European Journal of Marketing, 18(4), 36-44.

37. Johnson, C. W. (2008) Using Evacuation Simulations for Contingency Planning to Enhance the Security and Safety of the 2012 Olympic Venues. Safety Science, 46 (2). pp. 302-322.

38. Kandampully, J. (2002). Services management: The new paradigm in hospitality. Frenchs Forest NSW: Pearson Education Australia.

39. Kelley, S. W. & Turley, L. W. (2001). Consumer perceptions of service quality attributes at sporting events; Journal of Business Research, Volume 54, Issue 2, November 2001, Pages 161-166.

40. Kennelly, M. (2005). ‘Business as usual’: How elite Australian athletes frame terrorism post 9/11. Unpublished bachelor honors thesis, University of Technology, Sydney: Sydney: New South Wales.

41. Ko, Y. J., & Pastore, D. (2004). Current issues and conceptualizations of service quality in the recreation and sport industry. Sport Marketing Quarterly, 13(2), 159-167.

42. Kouthouris, C., & Alexandris, K. (2005). Can service quality predict customer satisfaction and behavioral intentions in the sport tourism industry? An application of the SERVQUAL model in an outdoor setting. Journal of Sport& Tourism, 10, 101–111.

43. Kwon, H.H., Trail, G.T., & Anderson, D. (2005). Are points of attachment necessary in predicting cognitive, affective, conative, or behavioral loyalty? A case analysis. Sport Management Review, 8(3), 255–270.

44. Lash, S., Szerszynski, B., & Wynne, B. (Eds.). (1996). Risk,environment and modernity. London: SAGE.

45. Lehtinen, U., & Lehtinen, J. R. (1991). Two approaches to service quality dimensions. The Services Industries Journal, 11(3), 287-303.

46. Lupton, D. (1999). Risk and sociocultural theory. Cambridge, UK: Cambridge University Press. 47. Marivoet, S. (2006). UEFA Euro 2004, Portugal: The social construction of a sports mega event and spectacle. Sociological Review, 54(2), 127-143.

48. May, M. (2004). Police Outnumber Athletes 7-1 at Olympics: Safety isname of the Games; San Fransico Chronicle, 12th August.

49. Meyer, B. (2004). Fighting Terrorism – A Narrow Path between Saving Security and Losing Liberty; Military Centre of Strategic Studies, Roma, p: 227-338.

50. Moteff, J., & Parfomak, P. (2004). Critical Infrastructure and Key Assets: Definition and Identification; CRS Report for Congress, Congressional Research Service, The Library of Congress.

51. Neocleous, M. (2007). Security, Liberty and the Myth of Balance: Towards a Critique of Security Politics, Contemporary Political Theory; Issue: 6,131–149.

52. [OG & HR] Olympic Games 2008 and Human Rights (2008). Positions within the IOC concerning the question of human rights, Beijing Hutong School; retrieved from: http://www.chinaorbit.com/2008-olympics-china/2008-olympics-human-rights.html ,on Oct 27, 2010.

53. Oliver, R.L. (1997). Satisfaction: A behavioral perspective on the consumer. New York: McGraw-Hill.

54. O’ Malley, P. (2004). Risk, uncertainty and government. London: Glasshouse.

55. Owen, T. (2004). Challenges and opportunities for defining and measuring human security, Disarmament Forum; Human Rights, Human Security and Disarmament, Issue: 3, pp. 15 – 23.

56. Parasuraman, A., Zeithaml, V.A., & Berry, L.L. (1994). Reassessment of expectations as a comparison standard in measuring service quality: Implications for future research. Journal of Marketing, 58(1), 111–124.

57. Roche, M. (2000). Mega-events and modernity: Olympics and expos in the growth of global culture. London: Routledge.

58. Roche, M. (2003). Mega-events, time and modernity: On time structures in global society. Time and Society, 12(1), 99-126.

59. Rothschild, E. (1995). What is Security?, Daedalus, vol. 124, no. 43, pp. 53–90. 60. Rubin, A. (2004). Safety, security, and preparing fordisaster at sporting events. Current sports medicine reports [1537-890X] 3(3),141−145.

61. Slovic, P. (Ed.). (2000). The perception of risk. London: Earth scan.

62. Taylor, T., & Toohey, K. (2006). Impacts of terrorism related safety and security measures at a major sport event, Event Management, 9(4), 199−209.

63. Toohey, K., & Taylor. T. (2008). Mega Events, Fear, and Risk: Terrorism at the Olympic Games; Journal of Sport Management 22 (4).

64. Tsoukala, A. (2007). Security Policies & Human Rights in European Football Stadia; Challenge, Centre for European Policy Studies, RP N° 5.

65. Tulloch, J. (2006). One day in July: Experiencing 7/7. London: Little Brown.

66. Ullman, R. (1983). Redefining Security; International Security, vol. 8,no. 1, pp. 129–53.

67. Wacquant, L. (1989). Towards a reflexive sociology: A workshop with Pierre Bourdieu. Sociological Theory, 7, 26-63.

68. Wakefield, K.L., & Blodgett, J.G. (1996). The effect of servicescape on customers’ behavioral intentions in leisure service settings. Journal of Services Marketing, 10(6), 45–61.

69. Waldron, J. (2003). Security and liberty: the image of balance, Journal of Political Philosophy 11(2): 191–210.

70. Whisenant, W. (2003). Using biometrics for sport management in a post 9/11 era. Facilities, 21, 134−141.

71. Whitson, D., & Horne, J. (2006). Underestimated costs and overestimated benefits? Comparing the outcomes of sports mega-events in Canada and Japan. Sociological Review, 54(2), 73-89.

72. Zedner, L. (2003). Too much security? International Journal of the Sociology of Law 31: 155–184.

 

2016-10-21T09:09:50-05:00August 21st, 2013|Contemporary Sports Issues, Sports Facilities, Sports Management|Comments Off on Security Models in Mega Sport Events between Safety and Human Rights (Case of Vancouver 2010)

Assessing Value of the Draft Positions in Major League Soccer’s SuperDraft

 

Abstract

This paper assigns various performance  measures to players who have been drafted in the SuperDraft of Major League Soccer. These measures are then used to assess the value of draft position. As a by-product of the analysis, we provide an estimate of the trajectory of player performance in a soccer career. Both the valuation of draft position and the career trajectory analysis may be important tools for general managers in Major League Soccer.

INTRODUCTION

By all measures, soccer (or football as it is more commonly known) is the most popular sport in the world (The Economist 2011). In the United States and Canada, the highest level of soccer is played in Major League Soccer (MLS). As of 2012, MLS consisted of 19 clubs divided into the Eastern Conference (10 teams) and the Western Conference (9 teams). Unlike the traditional European fall-to-spring schedule, the MLS season begins in March and ends in November. The MLS team with the best regular  season record is the recipient of the Supporters Shield and the winner of the MLS playoffs receives the MLS Cup.

There are various ways that  MLS teams acquire players for their rosters. One such mechanism is the annual SuperDraft  whereby players are placed on the draft-eligible list via nomination from MLS clubs. Most of these players are US college players. Players are then drafted by MLS teams in the inverse order of team performance from the previous  season. The ordering is an attempt to improve competitive balance within the league. The number of players drafted has varied since the inception of the SuperDraft in 2000. In the most recent draft of 2012, 38 players were drafted (two rounds involving the 19 MLS clubs).

The primary problem considered in this paper is the valuation of draft order in the SuperDraft. This is a fundamental problem for general managers in MLS. Consider the following hypothetical scenarios where the knowledge of draft value would be useful:

Your team has a glaring weakness at fullback and you have the 20th pick in the draft. What are the chances that the draftee can satisfy your needs at fullback? Would it be a better strategy to fill this position via a trade or via a designated player?

Your team is facing salary cap constraints and you have the 10th pick in the draft. What is the salary expectation for the player?

Your team has the draft rights for both the 10th and 11th picks. Would it be in your interest to trade both of these picks for the first draft pick?

The valuation of draft order was first considered in the context of the annual draft of the National Football League (NFL). Armed with a draft value chart, Jimmy Johnson (coach of the Dallas Cowboys) made informed trades on draft day in 1991, acquiring a whopping 19 players for the Dallas Cowboys. These informed trades eventually turned the team’s fortunes around as Dallas won three Superbowls within the next five years. Moskowitz and Wertheim (2011) provide an entertaining account of the use of draft value charts in the NFL.

The early chart was constructed according to the value of draft picks based on actual trades that took place. Massey and Thaler (2010) investigated the chart, and using data based on future salary contracts, determined that the early chart overvalued high draft picks. For example, although the first draft pick is valuable, the early chart suggested that the first pick is more valuable than is actually the case. Shuckers (2011) corroborated the overvaluation associated with the early draft chart via alternative measures of player performance. Shuckers (2011) subsequently proposed an alternative draft value chart. In other sports with drafts, Berry (2001) has looked at the success of first round picks. However, it does not appear that there has been any published investigation of the value of draft order in the MLS SuperDraft.

One of the complicating factors in assessing the value of draft order in the SuperDraft is that many of the players who have been drafted have not yet reached their peak level of play. Although some players when drafted in their early 20’s are unable to make an immediate contribution, through training and experience, they eventually become serviceable MLS players. We therefore want to be able to assess the future value of draft picks.

In section 2, we address this problem by estimating career trajectories of soccer players. Common sense dictates that players generally improve early in their career, then peak, and finally experience a decline in performance. The age at which they peak, and the extent of their improvement/deterioration  around the peak is the focus of section 2. Careful data collection is required to assess player productivity. Although the estimation of career trajectories is a necessary step in assessing draft order value, the problem itself is one of considerable interest to general managers. For example, what length and value of a contract should be offered to a player who is two years past his peak?

In section 3, we assess the value of draft position. The primary difficulty in the exercise is the determination and collection of performance measures. Clearly, a common metric such as “goals scored” is not relevant to all positional players. For example, defenders are not expected to score goals. The end product of our analysis are graphs of value plotted against draft position. Various graphs are provided based on various performance measures. With such graphs, one can assess for example, the relative value of the 20th draft pick to the first draft pick. We conclude with a short discussion in section 4.

CAREER TRAJECTORIES IN SOCCER

Assessing performance in soccer is not a straightforward task. For example, although goals scored is a popular and important statistic, it is not relevant to all positional players, especially defenders. Also, imagine a player who changes teams and experiences a surge in productivity. This may have more to do with circumstances surrounding his new team than an improvement in his personal play. In this section we make a number of subjective and hopefully reasonable decisions with respect to assessing player performance. Yearly performance data coupled with age data will help us to evaluate career trajectories  in soccer.

We began by considering players who have played on top flight clubs for a period of at least five consecutive seasons. We have chosen 12 teams from Europe which have been traditional footballing powers. The rationale is that these clubs are of the highest quality and consistency. Therefore an observed change in performance when competing for these clubs is assumed to convey a change due to the player. We have restricted our analysis to the “modern” era of soccer beginning with the 1992/1993 season when the English Premier League was formed. We have excluded goalkeepers from the analysis as it is well known that keepers can remain competitive at more advanced ages. For example, Edwin van der Sar retired as keeper from Manchester United following the 2010/11 season at 40 years of age. Although players from the 12 chosen clubs are of exceptional quality, we assume that the average career trajectory for players at these clubs is not unusual.For example, this implies that the average peak age for players at the elite clubs should be the same as the average peak age for all professional soccer players.

From the websites www.footballdatabase.eu  and www.bdfutbol.com/en/e/e.html we identified 232 players who met our criteria. These players played a total of 1791 seasons. We were also able to collect seasonal performance data on each of the players in terms of minutes played. Although minutes played does not capture all of the elements of performance, it is clearly a sensible measure of worth. The data are summarized in Table 1.

Team League No. Players
Arsenal English Premier League 25
Chelsea English Premier League 11
Liverpool English Premier League 23
Manchester United English Premier League 25
Bayern Munich German Bundesliga 26
AC Milan AS Italian Serie A 20
Roma Italian Serie A 18
Internazionale Italian Serie A 14
Juventus Italian Serie A 18
Barcelona Spanish La Liga 20
Real Madrid Spanish La Liga 16
Valencia Spanish La Liga 16
Overall 232

 

Table 1: Summary data for players who have played at least five consecutive years with a top flight club sometime during the 1992/93 through 2011/12 seasons.

Recall that our objective in this section is the evaluation of career trajectories. Therefore, we want to assess individual player performance at different ages where player performance is measured against himself. Accordingly, let xij denote the minutes played for the ith player at age j in the season where the player was j years old on January 1. The beginning of January is roughly halfway through the traditional fall-spring soccer season. Corresponding to xij, let wij be the number of available minutes during the season where wijis the product of 90 minutes and the number of games  that his team played in the season. We then define zij= xij/wij as a performance statistic for the i the player in the given season as it represents his proportion of available minutes on the field. To provide a personal measure of performance for the ith player at age j, we define

Formula

where the maximum is taken over all of his active seasons at the club. Therefore the personal performance measure ppij for the i player has a maximum value of 100% in at least one of his seasons. Note that we only considered matches played in the domestic  season. Our rationale for this choice is that other matches (e.g. friendlies, FA Cup, Europa League, Champions League, etc) may not have a consistent level of competition. Also, it is well known that players are often given rest when matches are scheduled in frequent succession.

In Figure 1, we provide a scatterplot of the personal performance measure ppij versus age j based on minutes played for all players over all seasons. The plot consists of 1791 points. Although there is considerable variability in the scatterplot, the lowess function describes the overall trend. The shape of the lowess plot corresponds to our intuition where performance improves early in a career, then peaks, and concludes with a period of decline. We observe that typical player performance peaks at roughly 24-27 years of age. Also, the drop off is minimal for roughly two years surrounding the peak period. The improvement early in a career is more rapid than the decline at the end of a career. We note that although the peak period of 24-27 years appears to be in rough agreement with common opinion (www.forum.ea.com/uk/posts/list/802432.page), we know of no quantitative study that has provided  such an interval. A miscalculation by even a couple of years can have dire consequences for general managers when deciding upon long term contracts. The parameters of the lowess function were set according to span=0.5 and degree=2 which is consistent with the analyses of Shuckers (2011). The choice of the span parameter appears reasonable as we do not want large fractions of the data to fit local segments of the trajectory curve. For example, the trajectory at young ages does not likely have much to do with longevity. The degree parameter  should also take a value exceeding 1 since we do not expect linear segments in the trajectory curve. Setting degree=2 provides more curvature.

Figure 1

Figure 1:  Scatterplot of the personal performance  measure ppij based on minutes played versus age. A lowess fit is included to help assess the overall trend.

Recall that each player has at least one plotted value of 100%. Accordingly, there is an inherent assumption that data are collected over a period that includes each player’s peak years of play. The assumption is valid for most players since it is unlikely that a player had five consecutive years of form that were all below peak performance, yet he managed to play on one of these top flight teams. However, to check the robustness of the assumption, we have repeated the analysis based on a restricted subset of 129 players  who played at least seven consecutive seasons with one of the 12 top flight clubs. These players played a total of 1229 seasons. A greater period of seasons improves the chance of capturing a player’s peak year. We found no meaningful difference in the resultant plot when compared to Figure 1. Related to the assumption, we encountered 9 players (e.g. Zinedine Zidane) who played at least five years on each of two teams from our list. In these cases, we only retained the years at the club where the player was 26 years of age. In the case of Zidane, we used his Juventus years instead of his years at Real Madrid.

How do we interpret the vertical scale in Figure 1? From 24-27 years of age, an average player operates at roughly 75% of top performance. Similarly, an average 34 year old operates at roughly 50% of top performance. Therefore, we might view the 35 year old as being able to contribute 50/75 two thirds of what he was able to contribute at his peak. Here, the measure of contribution can be interpreted in minutes played.

ASSESSING VALUE  OF  DRAFT POSITION

In this section we investigate the relationship between player value and draft position in the MLS SuperDraft. To facilitate the investigation, www.wikipedia.org/wiki/MLS  SuperDraft provides the entire history of the MLS SuperDraft going back to the inaugural draft on February 6, 2000. The list consists of a total of 745 players chosen in the 13 drafts from 2000 through 2012. The number of players drafted per year ranges from 72 (2001) to 38 (2012).

Whereas obtaining the draft position of each player is uncontroversial and routine, the determination of player value is far from straightforward. As in section 2, we first consider value measures based on minutes played. Another indicator of player value which we consider is yearly salary. Although players can be underpaid or overpaid in a given contract, subsequent player contracts tend to adjust to reality. A difficulty  with using salary as a proxy for performance is that there are time lags between observed performance and contract. Fortunately, for the MLS, there are good sources of data. For minutes played, we made use of http://socceroutsider.com/ and player’s personal Wikipedia sites. For salary information, data are available for the six seasons 2007 through 2012 at www.mlsplayers.org/salary info.html. We had to dig deeper for earlier seasons, referring to www.washingtonpost.com/wp-srv/sports/mls/longterm/2006/mls.salaries.html for the 2006 season, www.bigapplesoccer.com/article.php?article id=3103 for the 2005 season and http://sportsillustrated.cnn.com/2004/soccer/01/06/mls.salaries.sa/  for the 2004 season.

Before the various value metrics are introduced, we indicate some general problems that need to be addressed with respect to player valuation:

A spectacular  season is valuable to a club. There is also value in a longstanding career. How do we balance short term performance with longevity?

How do we assess a player who was drafted in the SuperDraft but went on to play in some other league? For example, Clint Dempsey was drafted 8th in the 2004 SuperDraft by the New England Revolution. However, since 2006/07, Dempsey has played in the English Premier League for both Fulham and Tottenham. Clearly, Dempsey is a valuable player although he has only limited MLS data.

In our current list of drafted players, some players are still young and have not yet reached their full potential. Should we assess their value on some combination of current performance and future performance? The career trajectory plot Figure 1 may be helpful in this regard.

With the growth of the MLS, there has been an escalation in salaries over time. How do we compare a salary from the early years to recent salaries?

To facilitate a comparison of various metrics, we define each metric on a scale of 0 to 100. We begin by considering minutes played in regular season MLS matches. The restriction to regular season matches levels the comparison amongst players since each team has the same number of games of comparable importance. For each player, we calculated his percentage of total minutes played relative to available minutes in a season. This was done for each year over all of his MLS seasons. We then defined the player performance metric y1 for a given player as his maximum percentage over his MLS career. We also defined the player performance metric y2 for a given player as his average percentage over his three best MLS seasons. Therefore, the measure y2 favours career longevity over y1.

In the case of players who have gone on to play in ldquo;superior” leagues, we arbitrarily assign a percentile rank of 90% in seasons where they played in superior leagues. We define a superior  league as any of the four famous leagues listed in Table 1. Players who have made it to one of these four top flight leagues have typically developed in the MLS before making their jump to the big time. Although there are other leagues that many football fans would agree are better than the MLS (e.g. Liga Portuguese (Portugal), Ligo Do Brasil (Brasil), Ligue One (France), Primera Liga (Argentina), Eredivisie (Holland)), very few MLS drafted players have gone on to play in these professional leagues. When an MLS draftee plays in leagues other than the MLS or one of the four top flight leagues, we assign a percentile rank of 0% for those seasons. A 0% score is also assigned to players who discontinue playing. A rationale for the 0% performance score is that it was a mistake to draft such a player as they did not contribute to the MLS team that drafted them. In our list of MLS drafted players, only 12 played in superior leagues. Of the 339 that played in other leagues, 277 played in the NASL (North American Soccer League) or the USL (United Soccer Leagues) which can truly be viewed as lower quality leagues compared to the MLS. When a player belonged to multiple leagues in a year, we used the league where he played most of his games.

To account for young players who have not yet reached their top level of performance (i.e. less than 24 years of age), we imputed values for their unobserved seasons. For example, suppose that we have a 21 year old player in the MLS who has just completed a season. We take his minutes played as a 21 year old and multiply by l(22)/l(21) to obtain his predicted minutes as a 22 year old where l(x) is the value of the lowess function at age x in Figure 1. We do not allow predicted percentages to exceed 100%. The determination of player ages was not as straightforward as we had hoped; there were at least six additional websites that we accessed to collect birthdates.

An obvious difficulty with the minutes played variables y1 and y2 is that they do not account for team strength. For example, it is easier to play extended minutes on a poorer performing club than at a stronger club. Another difficulty with these measures is that there are a number of players who represent their club in nearly all of the regular season matches. Therefore minutes played does not adequately distinguish these players in terms of performance.

Our preferred performance metrics are based on salary data. Varying team strength is less of an issue when dealing with salary data since league-wide  salary caps exist. Salary caps help to impose a realism on salaries so that players are paid what they are worth. An exception are the salaries paid to designated players who are not MLS draftees. For each player, we calculated his percentile rank for a given year based on his salary relative to all MLS players in that year. Thus the comparison sensibly involves the performance of draftees against the population of MLS players. This was done for each year over all of his MLS seasons. We then defined the player performance metric y3 for a given player as his maximum percentile rank over his MLS career. We also defined the player performance metric y4 for a given player as his average percentile rank over his three best MLS seasons. We used the same rules as above in handling players who have gone on to play at superior clubs and for young players who have not yet reached their full potential. In the case of multi-year contracts, the amount that a player received in a year is used as his yearly salary.

In Figure 2, we provide a scatterplot of the preferred y4 metric versus draft position. To assess the overall trend, a lowess plot is superimposed. We observe the anticipated pattern that early draft picks have more value. The plot decreases rapidly during the early picks and then levels off. It is interesting that there is little additional value beyond draft position 25. What this suggests is that whereas general managers have good intuition of value early in the draft, late draft picks are more or less a crapshoot. It also suggests for example that managers should value a 50th draft pick as about equal to a 25th draft pick. If this sort of information is not well understood, a savvy manager may be able to trade a 25th draft choice for a 50th draft choice plus additional assets. We observe from the variability in the plot that it is still possible to draft a productive player late in the draft but the probability of doing so is much decreased. Moreover, the variability is greater for early draft picks. This suggests that that there may be great pressure for teams drafting early as an early draft choice can turn out to be either a star or a bust. With less expected of late draft picks, there may only be upside for a general manager. How might we interpret the vertical scale of the plot? According to the salary metric, the first draft pick provides you with a player who on average ranks in the top 85.6% of players in the MLS. The first draft pick is about 1.7 times as valuable as the 10th draft pick and is about 5.3 times as valuable as the 20th draft pick in terms of salary. Finally, we note that we obtain a very similar plot if y4 is based on the best four seasons rather than the best three seasons. For ease of reference, the values of the loess curve in Figure 2 are provided in the pick value chart given in Table 2 of the Appendix.

In Figure 3, we provide a comparison of the lowess plots using each of the four proposed metrics. We observe that each plot conveys similar information and this provides assurance that the valuations are meaningful. For example, all four plots indicate that the first draft pick injects a team with a player who on average will rank roughly in the top 80% of MLS players. The level of agreement in the four curves was a bit of a surprise to us as we were aware of the flaws in assessing value based on minutes played. For the most part, we also note that y1 dominates y2 and that y3 dominates y4. This suggests that the consideration of a single season (y1 and y3) tends to inflate a player’s value when compared to their performance over multiple seasons (y2 and y4). Finally, we note that the preferred metric y4 lies amongst the middle of the four lowess curves.

Figure 2

Figure 2: Scatterplot of the value metric y4 versus draft position. A lowess fit is included to help assess the overall trend.

DISCUSSION

The major contribution of the paper is the construction of Figure 1 and Figure 2. In Figure 1, we have estimated the performance trajectory of soccer players (excluding  keepers). The plot may be of value to general managers in planning team rosters and offering contracts. In Figure 2, we have estimated  the value of draft picks in the MLS SuperDraft. This may also be of value to general managers when planning rosters and assessing trades.

The major difficulty in both the construction of Figure 1 and Figure 2 is the determination of player value. Value is a subjective quantity and involves many factors including player age, the assessment of the importance of longevity, positional characteristics, the confounding of individual and team characteristics, changes in league salaries and missing data. We have attempted to handle these issues sensibly and we note that various value metrics have lead to similar results (see Figure 3). Data collection and data management also proved to be a substantial exercise in obtaining our results. It may be interesting to extend the work by restricting analyses to various positions (e.g. defenders, midfielders,  forwards) although this reduces the sizes of data sets and often introduces uncertainties with respect to the categorization of players.

Figure 3

Figure 3: Lowess plots for each of the value metrics.

Finally, a relatively new change may affect the future of the MLS SuperDraft. In 2006, the Home Grown player criteria was established in the MLS to nurture promising young players living in the vicinity of an MLS team. The designation requires commitment by players to practice/play sufficiently under the club’s development system. Teams may then sign a player to their first professional contract if the player has trained for at least one year in the club’s youth development program and has met the league’s Home Grown player criteria. The important implication is that such players do not participate in the SuperDraft. Therefore, although the Home Grown player program is currently in flux, should it gain widespread popularity, it may eventually dilute the quality of the SuperDraft.

APPENDIX

Pick    Value Pick    Value Pick    Value Pick    Value
01       85.6
02       81.5
03       77.5
04       73.5
05       69.5
06       65.6
07       61.7
08       57.9
09       54.2
10       50.5
11       46.8
12       43.2
13       39.7
14       36.1
15       32.7
16       29.2
17       25.4
18       21.9
19      18.8
20      16.1
21      13.5
22      11.3
23      09.6
24      08.3
25      07.3
26      06.3
27      05.7
28      05.4
29      05.1
30      04.8
31      04.7
32      04.6
33      04.3
34      04.1
35      04.0
36      03.8
37      03.6
38      03.5
39      03.5
40      03.4
41      03.3
42      03.3
43      03.3
44      03.2
45      03.1
46      03.1
47      03.1
48      03.0
49      02.9
50      02.7
51      02.6
52      02.5
53      02.3
54      02.2
55      02.0
56      01.9
57      01.7
58      01.6
59      01.4
60      01.2
61      01.1
62      00.9
63      00.7
64      00.6
65      00.4
66      00.2
67      0.00
68      0.00
69      0.00
70      0.00
71      0.00
72      0.00

 

Table 2: Pick value chart corresponding to the lowess curve in Figure 2.

 

 

REFERENCES

Berry, S.M. (2001). “Do you feel a draft in here?”, In the column, “A Statistician Reads the Sports Pages”, Chance, 14(2): 53-57.
Massey, C. and Thaler, R.H. (2010). “The loser’s curse: overconfi dence vs. market efficiency in the National Football League draft”, http://ssrn.com/abstract=697121.

Moskowitz, T.J. and Wertheim, L.J. (2011). Scorecasting: The Hidden Influences Behind how Sports are Played and Games are Won, Crown Archetype: New York.
Shuckers, M. (2011). “An alternative to the NFL draft pick value chart based upon player performance”, Journal of Quantitative Analysis in Sports, 7(2): Article 10.1
The Economist (2011). Game Theory blog post under “Ranking sports’ popularity: And the silver goes to …”, www.economist.com/blogs18

2017-11-02T13:56:36-05:00June 13th, 2013|Contemporary Sports Issues, Sports Management|Comments Off on Assessing Value of the Draft Positions in Major League Soccer’s SuperDraft

An Analysis of Weight Management and Motivation of Former and Present High School and College Football Players

 

ABSTRACT

The purpose of this study was to analyze the weight management practices and motivational orientation for participating in the sport of football from former and present high school and college aged football players. The study included an in-depth analysis of the practices of offensive and defensive linemen, because of the likelihood of these individuals having the most abnormal eating practices. The researcher also attempted to determine if there was a significant relationship between the eating patterns of all the players and their motivation to participate in football. The sample for the study consisted of former and present football players (N = 387) from three target populations: high school, college, and former players. The study was conducted over a period of 30 days in the month of June 2011. Surveys were returned at a rate of 95%. The results indicated differences in eating pattern and motivation among the four groups: former players, college players, high school players, and offensive and defensive linemen. Offensive and defensive linemen did not differ from other players on any of the motivation scales. The results also revealed correlations among the eating pattern and sport motivation scales.

Introduction

The research concerning weight management and motivation of former and present high school and college football players is a worthy subject for extensive research analysis. A 2003 study, conducted at the University of North Carolina, found that professional football players have a 52% greater risk of dying of heart disease than the general American population (7); it was noted that offensive and defensive linemen are three times more likely to die from heart disease than teammates who play other positions. Hargrove (6) conducted a study investigating the death of former NFL players (N = 3,850) who had died since 1955. The study reported the following findings:

•The average weight of National Football League (NFL) players had grown10% since 1985.

•The average weight of offensive tackles, the heaviest football players, had increased from 281 pounds in 1985 to 318 pounds in 2005.

•Compared to Major League Baseball (MLB) players, the rate of death before the age of 50 for NFL players was double that of the MLB players.

When college football players’ weights were compared to a cross section of similarly aged males, overweight and obesity were more prevalent amongst players (13). The average varsity high school lineman is expected to gain more than 50 pounds in 3 years to compete on the collegiate level (3). The 300-pound lineman is now common at the high-school level (11). An analysis of a 1985 Indiana State high school football championship game found that 7 players weighed more than 250 pounds; in a follow-up study in 2004, 50 players weighed more than 250 pounds, representing an increase of 43 players (16).

Weight Management

The National Strength and Conditioning Association (12) reported that football players need to increase the number of calories they eat a day to gain muscular mass, aiming for 18 to 20 times their maintenance calorie intake. To increase power and to fuel muscles football players often engage in binge eating behaviors. Binge eating disorder (BED) is exhibited through frequent binge eating episodes, combined with impaired control over eating, followed by remorse about the binge eating episodes within a 2-hour period (1). BED eventually leads to obesity and visceral abdominal fat, which is an essential factor to examine in football players because of its relation to metabolic syndrome, sleep apnea and high blood pressure (5).

Jonnalagadda, Rosenbloom, and Skinner (10) conducted a study to investigate the eating practices, attitudes, and physiology of 31 Division I college freshman football players. Results from the study revealed that players ate 3.6 times per day and ate out 4.8 times per week. Fast food was the most popular choice for eating out (55%). In a study on the prevalence of metabolic syndrome of 69 Division I college football players, the mean BMI of offensive and defensive linemen was categorized as obese, with a significant amount of fat in the abdominal area (13).

Motivation

Researchers have asserted that family members encourage athletes to perform well more than coaches do (2). Thompson and Sherman (21) stated that coaching style along with positive feedback can play a significant role in a player’s weight management practices and motivation player’s weight management behaviors and self-perception. Pressures from teammates, either real or imagined, can cause an athlete to accept the notion that extreme weight management practices as necessary to participate in the sport (41).

The self-determination theory (SDT) is a general theory for assessing an individual’s personality and motivational orientation. The objective of the SDT is to determine if an individual’s motivational behavior is non self-determined or self-determined (4). Non self-determined behavior is behavior that is controlled by external factors in which the individual experiences an obligation to behave in a specific way and feels controlled by a reward or by constraints (10). Self-determined behavior is described as an individual’s understanding and fulfillment of his or her needs by being able to make psychologically free choices (10).

Ryan (38) examined the effects of scholarship on a variety of male and female, scholarship and non scholarship athletes. Results indicated that scholarship football players had lower levels of IM than non scholarship athletes. Conversely, male wrestlers and female athletes on scholarship reported higher IM than non scholarship athletes. Sloan and Wiggins (39)conducted a study using the SMS to assess the motivational differences between61 college football players and 60 professional football players. Results revealed that, overall, players scored higher on IM subscales than on EM subscales (39). Professional football players scored higher on IM subscales than college players (39).

The purpose of this study was to analyze the weight management practices and motivational orientation for participating in the sport of football from former and present high school and college football players. The study included an in-depth analysis of the practices of offensive and defensive linemen, because of the likelihood of these individuals having the most abnormal eating practices. The researcher also attempted to determine if there was a significant relationship between the eating patterns of all the players and their motivation to participate in football.

Methods

Selection of Participants

Participants were selected from a convenience sample of 387 former and present football players. Emphasis was placed on the participation of offensive and defensive linemen because they were more likely to have the most extreme eating behaviors.

Instrumentation

The Yale Eating Pattern Questionnaire (YEPQ) is designed to diagnose a wide variety of eating behaviors of nonclinical populations (23). The scale consists of eight subscales: (a) uninhibited, (b) over snacking, (c) bingeing, (d)dieting, (e) satiation–full, (f) satiation–nausea, (g)satiation– guilty, (h) attributions to physical and emotional causes of weight problems. For the purpose of this study the uninhibited, over snacking,and bingeing scales were used to assess football player eating behaviors.

The Sport Motivation Scale Revised (SMSR) consists of six, 3-item subscales that measure three types of motivation: Intrinsic Motivation (IM), External Motivation, and A motivation (AMO) The IM subscale identifies athletes who practice sport to experience personal pleasure. The scale identifies EM-athletes who participate in sport for external purpose such as a prize (17). AMO identifies athletes who do not know why they practice, sport (17).

Procedures

The researcher obtained permission to conduct the study through a local university’s Institutional Review Board. Upon confirmation the researcher made initial contact with football camp administrators at the college and high school age level to explain the nature of the research and to obtain permission to administer the survey to players. Former football players were contacted by the researcher via telephone to explain the nature of the study and to answer any questions about consent.

Statistical Analysis of Data

Data for this study were analyzed using the Statistical Package for the Social Sciences software program (SPSS) version 17.0. (IBM, Chicago, IL). An alpha level of .05 was used for all statistical analyses. Demographic profile was analyzed through the use of descriptive statistics. The research design included three analyses. A Multivariate Analysis of Variance (MANOVA) was performed with the three eating habits scales from the YEPQ as the dependent variables and player group (high school, college, and former) and position group (linemen versus others) as the independent variables. To follow up a statistically significant main effect for player groups, three one-way Analysis of Variance (ANOVA) were performed (one for each eating habits scale) to determine where the differences between the player groups occurred. A follow-up honest significance test, Tukey’s honestly significant difference (THSD),was used to find which means were significantly different from one another.

MANOVA was used to analyze the differences in motivational orientation among the groups (types of football players and player positions). To follow up a statistically significant main effect for player group, six one-way ANOVAs were conducted: one for each of the six sports motivation dependent variables. These analyses were performed to determine which of the six dependent variables differed as a function of player group. A follow-up THSD was used to find which means were significantly different from one another. Pearson product-moment correlation coefficients were calculated to investigate the relationship between the YEPQ and SMSR subscale.

RESULTS

A total of 387 valid survey questionnaires were collected from former and present football players with a return rate of 95%. The study participants were equally distributed among the three player groups: 35.1% former players, 35.1%college players, and 29.7% high school players. Similarly, there were approximately equal numbers of offensive or defensive line players (50.6%) and players in other positions (49.4%). Most (69.3%) of the participants reported eating to maintain an ideal body weight for their position. The majority(73.4%) of participants also believed that unhealthy weight management practices pose a potential risk for football players. Most (72.9%) of the participants reported that receiving a scholarship or playing professional football was a career goal.

Coaches were the most likely individuals to influence a participant’s current weight management practices (47.3%), with parents and family also representing a significant influence (20.9%). Nearly all (85.3%) of the participants indicated that they would consider a weight management program after completing their football career, and very few (2.1%) had been diagnosed with an eating disorder.

Six of the scores in the SMSR scales had adequate reliability in this sample, whereas three did not. The internal consistency reliability coefficients for the intrinsic regulation (α = .74), extrinsic integrated regulation (α = .70), extrinsic identified regulation(α = .71), and a motivation (α = .72) scales from the SMSR were adequate, as were the reliability coefficients for the over snacking (α = .82) and bingeing (α = .81)scales from the YEPQ. The reliability coefficients for the extrinsic introjected regulation (α = .58) and extrinsic external regulation (α = .54) scales from the SMSR and the uninhibited scale (α = .48) from the YEPQ, however, were lower than the conventional criterion of .70. This finding represents a substantial limitation of this study, and the results related to these scales should be interpreted with caution.

DISCUSSION

Research Discussion One

The first research question asked if there were significant eating pattern differences among all groups of football players. The results indicate significant differences between high school, college, and former players on the eating pattern scales. High school players had higher scores on the uninhibited, over snacking, and bingeing scales than college and former players.The findings suggest that high school football players have more abnormaleating patterns than college and former football players. The findings support Henderson’s (8) examination of California’s Mater Dei high school football championship team in 2006; revealed that their starting offensive line outweighed the 1972 undefeated NFL Miami Dolphins’ Super Bowl championship team by 118 pound.

Descriptive statistics from this study’s demographic information sheet, support findings in the review of literature; statistics reveal that the coach (47.3%) was the most likely individual to influence players current weight management practices, followed by parents (20.9%). In relation, to parent and coach influence on high school football player’s weight management practices, peer pressure from teammates, either real or imagined,can cause athletes to accept the notion that extreme weight management practices as necessary to participate in the sport (21).

The findings also support body dissatisfaction research conducted by Pope(14). Adolescent males often feel pressure from social sources and the media to obtain the low body fat, “cut” or “ripped” muscular body (14). In relation, a significant amount of players from this study (69.3%)reported that they eat to maintain an ideal body weight for their position in football. In this case, high school football players eating patterns may express their desire to obtain the perceived prototype body they see in the media of football players.

Research Discussion Two

The second research question asked if there were significant eating pattern differences between all offensive or defensive linemen and other team players.Offensive and defensive linemen had lower scores on the uninhibited and bingeing scales compared to other players. The results indicate that smaller players who play positions other than offensive or defensive lineman have more abnormal eating patterns. The findings of the research support research conducted by Pope (15) on muscle dysmorphia. Males with muscle dysmorphia are obsessed with the idea that they are not muscular enough and see themselves as”skinny” or “too small” (15). In this case, smaller players who play position other than offensive/defensive line could be emulating perceived eating patterns of offensive/defensive linemen; in an attempt to obtain the prototype body to participate in football.

Research Discussion Three

Research question three asked if there were significant intrinsic or extrinsic motivational differences among all football players. High school and college players scored higher on the EM-introjected regulation and EM-external regulation scale than former players. The findings suggest that football players at the high school and college level have more non self-determined motivation than former players. The findings support research conducted by Hyman (9) on external influence student football players’ encounter in their participation in football. The findings are also supported by statistics in the demographic information sheet which show a large majority of players(72.9%) who reported that receiving a scholarship or playing professional football was a career goal.

A significant finding in the research was that college football players had higher mean scores on the EM-identified regulation, EM-integrated, and the IM-regulation scale than former and high school players. The finding suggests that college football players have more self-determined motivation than former and high school players. The findings are classic and supports Ryan’s(18) SDT which states, that intrinsic motivation can be improved with the introduction of performance-contingent rewards.

Research Discussion Four

The fourth research question asked if there were significant intrinsic or extrinsic motivational difference between all offensive and defensive linemen and other team players. The results indicate that offensive and defensive linemen did not differ from other players on any of the sports motivation scales. The findings suggest offensive/defensive linemen motivation to participate in football is no different in comparison to other team players. In this case, it was the researcher’s hypothesis that offensive/defensive linemen motivation to participate in football would be more non self-determined because they are routinely the heaviest players on a team. The results did not support the researcher’s hypothesis.

Research Discussion Five and Six

The fifth and sixth research questions asked if there was a significant correlation between eating patterns and motivation among all football players and if there was a significant correlation between extrinsic motivation and binge eating patterns among all football players. The results showed that there were significant correlations among the eating patterns and motivation scales.

Players with high scores on the YEPQ: uninhibited, overeating, and bingeing scale also had higher scores on the SMSR: EM-introjected regulation,EM-external regulation, AMO scales. The findings suggest that football players,who participate in football for non-self-determined reasons— to avoid criticism, to win a prize, or for no good reason, are also prone to abnormal eating patterns. Players with high scores on the YEPQ: bingeing scale and overeating scale tended to have lower scores on the SMSR: IM-regulation, EM-integrated regulation, and EM-identified regulation scales. The findings suggest that football players, who participate in football for self-determined reasons-to obtain personal goals, because its apart of you, to experience pleasure, do not show signs of abnormal eating patterns. In this sense performance contingent rewards in the form of food, can be introduced, for consistently adhering to the leisure activity or weight management plan.

CONCLUSION

The results indicate that there were significant eating pattern differences among the four independent groups. The results indicate that high school players had higher scores on the uninhibited, over snacking, and bingeing scales than did former players. College players-scores on all three scales were between high school and former players. Former players-had lower score on all three scales. The results also revealed that offensive/defensive linemen had lower mean scores on the uninhibited and bingeing scale compared to other player groups. Results indicate that high school and college players had higher scores on the EM-external regulation scale than former players. College players had higher IM-regulation, EM-identified regulation mean scores than high school and former players. Former players had lower EM-introjected regulation scores than high school and college players. Offensive and defensive linemen did not differ from other players on any of the sport motivation scales.

To investigate if there were correlations among the eating pattern and motivation scales, results revealed that individuals with higher scores on the uninhibited scale from the YEPQ tended to have higher scores on the SMSR, EM-introjected regulation, EM-external regulation, and the A motivation scale.Participants with higher on the over snacking scale tended to have lower scores on the IM-regulation, EM-integrated regulation, and EM-identified regulation,and higher scores on the EM-external regulation and A motivation scales.Participants with higher scores on the bingeing scale tended to have lower IM-regulation scores and higher EM- introjected regulation, EM-external regulation, and A motivation scores. A limitation is that this was a convenience sample and may not be representative of all players or former players.

APPLICATIONS IN SPORT

Because the coach was reported to have the most influence on players’weight management practices (47.3%); and players reported eating to maintain an ideal body weight for their position (69.3%); and because nearly all participants (85.3%) reported they would consider a reconditioning plan after their playing career is over; future research could investigate the role coaches can play in the establishment of reconditioning plans once a player’s football career ends. Future research also could focus on making players aware that BED is a diagnosed eating disorder.

Tables

Table 4.2. Descriptive Statistics for Demographic and Background Characteristics (N = 387)

Variable Frequency Percentage
Player group    
High school player 115 29.7
College player 136 35.1
Former player 136 35.1
     
Position group    
Not offensive or defensive line 191 49.4
Offensive or defensive line 196 50.6
     
Ethnicity    
African American 289 74.7
Caucasian 74 19.1
Hispanic 10 2.6
Other 14 3.6
     
Do you eat to maintain an ideal body weight for your position?
Yes 268 69.3
No 107 27.6
Missing 12 3.1
     
Do you feel that unhealthy weight management practices are a potential health risk for football players?
Yes 284 73.4
No 95 24.5
Missing 8 2.1
     
Do you have hereditary health issues that contribute to weight gain?
Yes 44 11.4
No 339 87.6
Missing 4 1.0
     
Is earning a scholarship or playing professional football a career goal?
Yes 282 72.9
No 99 25.6
Missing 6 1.6
     
The individual who has influenced your current weight management practices the most:
Teammates 16 4.1
Peers 26 6.7
Parents/Family 81 20.9
Coach 183 47.3
Nobody 77 19.9
Missing 4 1.0
     
Would you consider a weight management program after you football career?
Yes 330 85.3
No 43 11.1
Missing 14 3.6
     
Have you ever been diagnosed with an eating disorder?
Yes 8 2.1
No 373 96.4
Missing 6 1.6
     
Height in inches 71.44 3.36
     
Age in years 25.05 10.49
     
Weight in pounds 214.63 48.31

Table 4.3. Descriptive Statistics for Composite Scores (N = 387)

Variable Items Min. Max. M SD α
Sports Motivation (SMSR)            
Intrinsic regulation 3 1.33 7.00 5.53 1.30 .74
Extrinsic integrated regulation 3 1.00 7.00 5.34 1.29 .70
Extrinsic identified regulation 3 1.33 7.00 5.49 1.28 .71
             
Sports Motivation (SMSR)            
Extrinsic introjected regulation 3 1.00 7.00 4.24 1.53 .58
Extrinsic external regulation 3 1.00 7.00 3.20 1.52 .54
Amotivation 3 1.00 6.67 2.17 1.37 .72
             
Eating Patterns (YEPQ)            
Uninhibited 9 1.44 4.89 2.90 .52 .48
Oversnacking 12 1.17 5.00 2.74 .67 .82
Bingeing 13 1.00 4.54 2.61 .68 .81

Table 4.4. Descriptive Statistics for Eating Patterns Composite Scores as a Function of Player Group and Position Group (N = 387)

Variable High school College Former
  M SD M SD M SD
Uninhibited            
Other than linemen 3.09 .56 3.01 .55 2.83 .54
Linemen 2.87 .46 2.86 .51 2.76 .46
             
Oversnacking            
Other than linemen 2.99 .73 2.82 .69 2.48 .64
Linemen 2.84 .65 2.63 .58 2.68 .62
             
Bingeing            
Other than linemen 2.93 .79 2.65 .69 2.48 .58
Linemen 2.60 .77 2.51 .61 2.52 .56

Table 4.5 Results from ANOVAs for the Eating Habits Dependent Variables (N = 387)

Effect Sum of
squares
df Mean
squares
F p
           
Between groups 2.56 2 1.28 4.77 .009
Within groups 103.05 384 .27    
Total 105.61 386      
           
Oversnacking          
Between groups 6.83 2 3.42 7.98 < .001
Within groups 164.39 384 .43    
Total 171.22 386      
           
Bingeing          
Between groups 4.61 2 2.30 5.12 < .001
Within groups 172.70 384 .45    
Total 177.30 386      

Table 4.6. Descriptive Statistics for Sports Motivation Composite Scores as a Function of Player Group and Position Group (N = 387)

Variable High school College Former
  M SD M SD M SD
Intrinsic regulation            
Other than linemen 5.41 1.36 5.72 1.15 5.23 1.50
Linemen 5.51 1.25 5.88 1.24 5.41 1.24
Extrinsic integrated regulation            
Other than linemen 5.29 1.14 5.39 1.18 5.14 1.47
Linemen 5.22 1.29 5.51 1.26 5.44 1.37
Extrinsic identified regulation            
Other than linemen 5.21 1.32 5.67 1.09 5.08 1.71
Linemen 5.47 1.09 5.84 1.03 5.59 1.22
Extrinsic introjected regulation            
Other than linemen 4.49 1.41 4.45 1.41 3.80 1.57
Linemen 4.23 1.67 4.65 1.65 3.85 1.35
Extrinsic External Regulation
Other than linemen
 
 
3.60
 
 
1.48
 
 
3.60
 
 
1.44
 
 
    
2.40
 
 
1.34
Linemen 3.54 1.55 3.30 1.61 2.84 1.35
Amotivation            
Other than linemen 2.44 1.50 2.19 1.47 2.18 1.31
Linemen 2.39 1.55 2.06 1.34 1.86 1.02

Table 4.7. Results from ANOVAs for the Sports Participation Dependent Variables (N = 387)

Effect Sum of squares df Mean squares F p
Intrinsic regulation          
Between groups 15.56 2 7.78 4.71 .010
Within groups 634.38 384 1.65    
Total 649.94 386      
Extrinsic integrated regulation          
Between groups 2.58 2 1.29 .77 .462
Within groups 639.48 384 1.67    
Total 642.06 386      
Extrinsic identified regulation          
Between groups 14.11 2 7.06 4.41 .013
Within groups 613.88 384 1.60    
Total 628.00 386      
Extrinsic Introjected Regulation          
Between groups 37.57 2 18.78 8.31 < .001
Within groups 867.61 384 2.26    
Total 905.18 386      
Extrinsic External Regulation          
Between groups 67.57 2 33.78 15.79 < .001
Within groups 821.45 384 2.14    
Total 889.01 386      
Amotivation          
Between groups 10.80 2 5.40 2.91 .055
Within groups 711.75 384 1.85    
Total 722.55 386      

Table 4.8. Correlations Among Composite Scores (N = 387)

Variable 1. 2. 3. 4. 5. 6. 7. 8. 9.
Sports motivation (SMSR)                  
1. Intrinsic regulation 1.00                
2. Extrinsic integrated regulation .67*** 1.00              
3. Extrinsic identified regulation .73*** .73*** 1.00            
4. Extrinsic introjected Regulation .47*** .44*** .44*** 1.00          
5. Extrinsic external regulation .09 .11* .15** .46*** 1.00        
6. Amotivation -.29*** -.33*** -.30*** .07 .39*** 1.00      
Eating Patterns (YEPQ)                  
7. Uninhibited .01 .00 -.01 .21*** .23*** .13* 1.00    
8. Oversnacking -.13* -.10* -.10* .06 .29*** .24*** .60** 1.00  
9. Bingeing -.11* -.06 -.09 .13* .25*** .24*** .58** .75*** 1.00

*p < .05, **p < .01, ***p < .001

REFERENCES

American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC.

Brustad, R. J. (1988). Affective outcomes in competitive youth sport: The influence of interpersonal and socialization factors. Journal of Sport& Exercise Psychology, 10, 307-321.

Colaianni, R. (2005, December 1). Pounds of performance. The University Daily Kansan, Retrieved fromhttp://www.kansan.com/news/2005/dec/01/sp_football_health/

Deci, E. L., & Ryan, R. M. (2002). Handbook of self-determination research. Rochester, NY: University of Rochester Press.

George C. F., Kab V., & Levy A. M., (2003). Increased prevalence of sleep-disordered breathing among professional football players. New England Journal of Medicine. 348, 367-368.

Hargrove, T. (2006). Heavy NFL players twice as likely to die before 50. Scripps Howard News Service. Retrieved from http://sports.espn.go.com/nfl/news/story?id=2313476

Harp, J., & Hecht L. (2005). Obesity in the NFL. The Journal of the American Medical Association, 293, 2999-3002.

Henderson, M. (2006). Carrying a hefty amount of risk: Large young athletes face obesity problems after playing days end. The Los Angeles Times,p. A-25.

Hyman, M., (2009). The kids are n’t alright: They’re getting hurt more than ever, often because parents push them too hard. Sports Illustrated, 110(15), 4.

Jonnalagadda, S. S., Rosenbloom R., & Skinner, R. (2001). Dietary practices, attitudes, and physiological status of collegiate freshman football players. Journal of Strength and Conditioning,15, 507-513.

Mathews, M., & Wagner, D. (2008). Overweight and obesity among youth participants in American Football. Journal of American College Health,151(4), 378-382.

National Strength and Conditioning Association. (2011). NSCA sports nutrition education program, sponsored by EAS. Retrieved from: http://athletics.macalester.edu/custompages/Deno_Videos/nutrition nutrition_for_strength_and_power_athletes.pdf

Noel, M. B., Vanheest, J. L., Zanetas P., & Rogers, C. D. (2003). Body composition in Division I A football players. Journal of Strength and Conditioning, 17, 228-237.

Pope, H. G. Jr., Gruber, A. J., Choi, P., Olivardia, R., & Phillips, K.A. (1997). Muscle dysmorphia: An under recognized form of body dysmorphic disorder. Psychosomatics, 38, 548-557.

Pope, H. G., Phillips, K. A., & Olivardia, R. (2000). The Adoniscomplex: The secret crisis of male body obsession. American Journal of Psychiatry, 158, 1947-1948.

Pytel, B. (2008). Obese HS football players: High school linemen are far too heavy. Educational Issues. 4(23), 5-6.

Rocchi, M., Pelletier, L., Vallerand, R., Deci, E., & Ryan, R. (2007). Validation of the Revised Sport Motivation Scale. Psychology of Sport and Exercise, 14(3), 329-341.

Ryan, E. D. (1977). Attribution, intrinsic motivation, and athletics. In L.I. Gedvilas & M. E. Kneer (Eds.), National College Physical Education Association for Men/National Association for Physical Education of College Women. Champaign, IL: Human Kinetics.

Ryan, E. D. (1980). Attribution, intrinsic motivation, and athletics: A replication and extension. In C. H. Nadeau, W. R. Halliwell, K. M. Newell,& G. C. Roberts (Eds.), Psychology of Motor Behavior and Sport(pp. 19-26). Champaign, IL: Human Kinetics.

Sloan, R. B., & Wiggins, M. S. (2001). Motivational differences between American collegiate and professional football players. International Sports Journal, 5(1), 17-24.

Thompson, R., & Sherman, R. (1999). “Good” athlete traits and characteristics of anorexia nervosa: Are they similar? Eating Disorders: The Journal of Treatment & Prevention, 7(3), 181-190.

 

2016-10-21T08:35:51-05:00May 16th, 2013|Contemporary Sports Issues, Sports Exercise Science, Sports Studies and Sports Psychology|Comments Off on An Analysis of Weight Management and Motivation of Former and Present High School and College Football Players
Go to Top