Disordered Eating, Eating Attitudes, and Reasons for Exercise among Male High School Cross Country Runners

Submitted by Guy Wadas, MS, Southern Utah University and Mark DeBeliso, PhD, Southern Utah University


PURPOSE:  This study investigated the prevalence of disordered eating behaviors among male high school cross country runners.  The study identified behaviors and feelings about being an athlete, and determined relationships between motivations to exercise and disordered eating behaviors.  METHODS:  Sixty-eight male high school cross country runners from 12 high schools in one urban school district completed three questionnaire packets on one occasion pre-season.  The EAT-26 questionnaire was used to determine prevalence of disordered eating.  The ATHLETE questionnaire was used to determine psychological factors for relationships with disordered eating.  The EMI-2 was used to determine motivations to exercise and the relationship to disordered eating.  EAT-26 scores and data from the EMI-2 and ATHLETE questionnaires were analyzed via a Pearson Correlation Coefficient.  RESULTS:  A modest positive relationship existed between exercising for disordered eating behaviors versus exercising for weight management (r = 0.31: p < 0.05), the Your Body in Sports subscale (which measured drive for thinness and performance) (r = 0.36: p < 0.05), and the Feelings about Performance subscale (or Performance Perfectionism) (r = 0.26: p < 0.05).  CONCLUSIONS:  Risk factors associated with eating disorders exist in high school male cross country runners.  Underreporting and lack of recognition of disordered eating may affect prevalence rates.  Recommendations include a longitudinal study of male high school runners across the school year to determine relationships with the timing of questionnaire administration.  APPLICATIONS IN SPORT:  Disordered eating behaviors should be acknowledged as more than a “female only” issue.  Parents, teachers, coaches, and athletic trainers may be better able to understand and help male athletes with disordered eating behaviors or an active eating disorder.


2016-10-12T15:13:04+00:00April 28th, 2014|Contemporary Sports Issues, General, Sports Exercise Science|Comments Off on Disordered Eating, Eating Attitudes, and Reasons for Exercise among Male High School Cross Country Runners

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


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.


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).


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.


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’.


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


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.


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.


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).


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).


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.


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+00:00August 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



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.


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.


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


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.


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.


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.


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.




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+00:00June 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



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.


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).


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.


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.


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).


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.


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.


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.


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.


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.


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
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
Other than linemen 3.09 .56 3.01 .55 2.83 .54
Linemen 2.87 .46 2.86 .51 2.76 .46
Other than linemen 2.99 .73 2.82 .69 2.48 .64
Linemen 2.84 .65 2.63 .58 2.68 .62
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
df Mean
F p
Between groups 2.56 2 1.28 4.77 .009
Within groups 103.05 384 .27    
Total 105.61 386      
Between groups 6.83 2 3.42 7.98 < .001
Within groups 164.39 384 .43    
Total 171.22 386      
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
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
Linemen 3.54 1.55 3.30 1.61 2.84 1.35
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      
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


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+00:00May 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

Understanding Emotional and Binge Eating: From Sports Training to Tailgating



Many athletes are asked to gain weight and even overeat to “bulk up” for their respective sport(s). In addictive behaviors, early exposure and habit formation during the brain’s developing years are highly predictive of continued problems later in life. As with commonly abused drugs, research indicates foods high in sugars and fat also cause large increases in dopamine, serotonin, and, possibly the most important for those who struggle with food dependency, opioids/endorphins. Due to the brain’s hardwired limbic system circuitry and the naturally reinforcing biochemical mechanisms of eating, there are many physical and psychological factors that influence eating behaviors. Psychological eating factors include stress, depression, anxiety, body dissatisfaction, low self-esteem/self-efficacy, and a preoccupation with food, weight, and body shape. Interpersonal factors stem from social interactions and psychosocial variables such as cultural and ecological influences. For drugs of abuse, abstinence only programs are often the only effective method of eliminating dependency; however, these programs are not a possible with eating. Therefore, this review introduces research on mindfulness, which has been shown to be an effective impulse-control strategy for behaviors, such as eating, that are also a basic part of life. Any intervention plan for treating binge and emotional eating should include methods to help increase awareness and emotional resilience. Client-centered positive health behavior change techniques such as Motivational interviewing (MI) also appear to be highly effective in the treatment of emotional and binge eating.


Eating pathologies are common among athletes where body image and size are emphasized due to the nature of their respective sports (8, 15, 25, 28). Long-term eating behaviors are reinforced and hard to change because of complex interactions between physical, psychological, and psychosocial factors. This critical research review addresses the often unrecognized issues associated with emotional and binge eating. Highly effective treatment options such as mindfulness-based therapies and Motivational Interviewing (MI) are introduced to help coaches and sport psychology consultants recognize and get even better at supporting the athletes they serve.

Emotional eating (EE) is characterized by episodes of binge eating to cope with unwanted feelings or serve as a positive reward, and the binges are often followed by feelings of guilt or loss of control. Binge eating is defined as“eating in a discrete period of time an amount of food that is definitely larger than most individuals would eat under similar circumstances” (2, p. 589). Whereas binge eating disorder (BED) is defined as “recurrent episodes of binge eating in the absence of the regular use of inappropriate compensatory behaviors characteristic of Bulimia Nervosa” (2, p. 595).

Kemp, Bui, & Grier (2011) describe EE as the “invisible plague” and as eating (often over consuming) linked to an individual’s emotional states, characterized by episodes of binging,grazing, and/or eating when not hungry in an effort to change feelings. Therefore, the function of emotional eating is to change one’s emotional state (whether to reduce perceived stress or pain, or to enhance positive emotions), or to experience instant gratification by using food as a coping mechanism/reward (31). Binge eating is characterized by significant reoccurring disturbances or episodes of overeating followed by feelings of lack of control over food and distress about body shape and weight. Consequently, it may also be associated with depression, low self-esteem, and decreased quality of life (10, 14, 36, 41, 50). Emotional and binge eating are common behaviors that plausibly contribute to the growing obesity endemic with over half of U.S. adults being classified as overweight or obese (31, 36). Because we must consume food to live, it is difficult for some to find the balance between healthy consumption and over or under consumption.

Many athletes are asked to gain weight and even overeat in an attempt to bulk up for their sports (e.g., football). In all addictive behaviors, early exposure and habit development alters the mesolimbic system during the brain’s developing years. Such changes are highly predictive of continued problems later in life (11). Additionally, cultural obsessions with body image and the use of food for entertainment or celebrating social events (e.g., overcoming boredom, football tailgates, Superbowl parties, and weddings) further confound the developmental issues related to the formation of eating habits. Social norms and fast-paced lifestyles contribute to the obesity pandemic and the etiology of emotional and binge eating disorders. Eating disorders such as anorexia, bulimia, and binge eating can be characterized by food and body image causing distress and issues with emotions, attitudes, and behaviors (44). Furthermore, EE may be a major predisposing factor to the development of eating disorders along with other predisposing factors such as depression, stress, anxiety, body dissatisfaction, poor coping skills, low self-esteem and self-efficacy, low emotional awareness, a preoccupation with weight, body shape, and food intake (20, 36, 41, 48, 52, 57).

Neuropsychological Mechanisms

Many factors influence food consumption: physiological needs, psychological and emotional connections, and psychosocial elements. Water and food are essential for survival (i.e., metabolic requirements). To differentiate the critical need versus desire to eat, hunger is the biological craving for food based on survival needs whereas appetite describes the psychological desire for food (21). The neuro-physiologic response to hunger and control of food intake is regulated by the hypothalamus which stimulates the release of hormones such as leptin and ghrelin. The functions of leptin and ghrelin are mainly to stimulate hunger/satiety and regulate metabolism (21, 31).

Ghrelin has emerged as the first circulating hunger hormone and has been shown to increase food intake and fat mass in humans (33). Ghrelin is a fast acting hormone produced mainly by the lining of the stomach and the pancreas to stimulate hunger. Ghrelin levels increase rapidly before meals causing cravings for food and eating behavior initiation. Conversely, fat cells produce the hormone leptin which is responsible for causing full feelings and appetite suppression. Ghrelin-responsiveness is both leptin and insulin-sensitive. In relation to food addiction, ghrelin activates the mesolimbic cholinergic-dopaminergic reward link, which is a circuit that communicates the hedonistic and reinforcing aspects of natural rewards, (e.g., food) as well as of addictive drugs (27). Understanding the strength of this addictive mechanism helps to understand why people continue to eat despite the negative consequences of obesity. It has been established that obese individuals are leptin-resistant, but the role of leptin and ghrelin in the development or maintenance of obesity is still unclear (21, 31). Although physiological needs regulate “true” hunger, there are also psychological, emotional, psychosocial, and environmental factors that influence this complicated process.

Lustig’s (2006) biochemical model of obesity provides a clear application of the research on hormonal and biochemical influences to obesity prevention and intervention programs. His model illustrates how an obese individual’s hormonal signaling may inappropriately be triggering a hunger response. This process causes the body to store more energy as fat and to reduce energy expenditure while, at the same time, increasing appetite and biochemical motivations for overeating. Thus, a child may be gaining weight due to a biochemical imbalance that is causing him/her to experience hunger and sluggishness even though he/she is ingesting more calories than required (51).

Psychological and emotional factors that may predict or impact eating disorders are (a) varying levels of emotional awareness and regulation, (b) negative emotional states, (c) negative core beliefs and low self-efficacy, and (d) fundamental emotional dysfunction. Barchard et al. (2010) explain that emotional awareness is essential for an individual to have the ability to self-reflect and regulate emotional states. People with eating disorders may have difficulty identifying emotions and utilizing adaptive coping strategies to resolve negative feelings (31, 52). Without access to these coping strategies, some individuals use food as a solution to alleviate aversive emotional states. This often results in a learned behavior or conditioned response that over/under eating will soothe their problems or reduce negative affect (31, 52). The learned behavior may originate from childhood rewards consisting of food-related treats to encourage emotional regulation (19). This continued practice frequently breeds more disordered eating among adults later in life.

Likewise, negative self-beliefs play a causal role in both eating behaviors and depressed moods (48). The effects of low self-esteem in relation to body dissatisfaction and body disturbance have been extensively researched creating a reliable paradigm for accurately predicting disordered eating (20). Sim and Zeman (2006) consider body dissatisfaction as “normative discontent” because it is common among adolescent girls. Body dissatisfaction also appears to sustain a cyclic relationship with negative affect as it contributes to increased negative affect, and negative affect can contribute to increased feelings of body dissatisfaction (52).

There are numerous rudimentary elements that affect emotional states and well-being, which ultimately influence and can be used to predict eating disorders. Emotional dysfunction can encompass a multitude of feelings related to disordered eating such as anger, anxiety, depression, fear, loneliness, tiredness, sadness, and stress (7, 19, 36, 41, 52). Stress, specifically, can be quite influential to food intake. Stress is defined as the occurrence of an imbalance between demands (stressors) and coping resources (psychosocial resources) with the mediating factor of cognitive control in connection with“stress-eating” (57). Stress-induced eating typically occurs with a desire to escape from the negative emotion and can cause individuals to either engage in EE or restrictive eating (57). Other predisposing characteristics may include high levels of insecurity, submissive behaviors, social phobias, negative self-evaluation and low self-esteem, poor coping skills, neuroticism, maladaptive perfectionism, restrictive emotional expression, difficulty regulating intensity/duration of emotional states, internalization of behaviors, and/or ruminating thoughts about food items (7, 20, 23, 31). These personal variables interact with psychosocial and physiological variables to create a complex interaction of issues contributing to EE and BED.

Eating Disorders among Athletes

Multiple studies show that athletes report a higher incidence of eating disorders than comparable non-athlete populations (8, 15, 25, 28). Even among athletes with subclinical symptoms, there exists an increased risk of disordered attitudes or behaviors related to dietary practices. Sundgot-Borgenand Torstveit (2004) estimated that 13.5% of Norwegian elite athletes demonstrated clinical or subclinical eating disorders compared to only 4.6% of control groups. While rates of disordered eating are generally higher among females (16, 26), male athletes also exhibit risky eating behaviors related to body image (47). Furthermore, the type of competition is known to correlate with increased risk of eating disorders. Athletes in appearance-based sports such as gymnastics, figure skating, and diving, as well as weight-sensitive sports such as wrestling, jumping events, and endurance running have long been the focus of prevention and intervention efforts because of their demonstrated risk of disordered eating (12, 17, 55). More specifically, prevalence of eating disorders among sport types differs for males and females. Males participating in jumping sports and females in aesthetic sports have higher prevalence of eating disorders than other types of sport participation (55). Multiple influential factors have been linked to increased risk of eating disorders among athletes. Important risk factors include social pressures to adhere to the ideal body, perceived norm of sport body appearance, and perceived performance gains from weight control (56). Considering the associated problems related to both physical (e.g., body mass impact, fatigue, insomnia) and mental health (e.g., depression, anxiety, substance abuse), disordered eating represents a significant health concern among athletes (43).

While much research has historically focused on eating disorders which result in low body mass (e.g., anorexia), more recent research on the high prevalence of overweight and obese athletes has revealed the need for more comprehensive approaches to disordered eating prevention. For example, the premium placed on size in American football often leads to unhealthy practices(e.g., anabolic steroid use, binge-eating) to increase size, with as many as 74% of college football players purposefully participating in regular binge-eating (3, 13, 16).

Increasing attention has been given to the weight-related health risks of professional football players in recent years (22). While binge eating increases the risk of health complications similar to those linked to obesity including hypertension, diabetes, and heart disease (43), there are other notable complications related to the increased size of football players. A recent study indicated that overweight, retired football players were more likely to suffer from decreased cognitive functioning and neurodegenerative disease than normal weight former players (58). While this study examined professional football players, the average size of football players has also increased at both the high school and college levels over the last several decades (40, 42, 45, 46). Given the assumption that binge-eating may be linked to increases in athletes’ size, the health risks may be even more significant. Because sport-related eating disorders often persist after sport participation has ceased, the importance of recognition, prevention, or early diagnosis and treatment of these conditions in essential (8).

Understanding Health Behavior Change

As explained in the Theory of Planned Behavior (TPB), intention is not the exclusive determinant of behavior, meaning that perceived behavioral control includes factors outside of the individual’s control that can affect both intention and behavior (31, 51). TPB supports the belief that psychosocial,environmental, and intrapersonal factors also influence disordered eating. The three overarching factors recognized by researchers are (a) food advertising,(b) sociocultural pressures, and (c) relational variables (20, 31). Kemp et al. (2011) suggest that exposure to food advertising heavily influences unhealthy food consumption and tendencies to overeat and snack, possibly serving as an external trigger to activate hedonic desires for food.

Sociocultural pressures include a variety of social norms (i.e., beliefs about a behavior that reflect the perceived social pressure to perform or not perform a behavior) such as the high value placed on a thin female body, the overall encouragement to eat more, and unfavorable social comparisons (20, 23, 31). Research indicates the drive to be thin among girls and women produces a negative emotional response and body dissatisfaction because of the feelings of failure to live up to perceptions of what is considered the ideal of beauty (20, 52). Markedly, many people who engage in EE have learned the behavior overtime and may be socially facilitated by family and friends who exhibit similar behaviors (31). The severity of eating disorders can be measured on a continuum and take into account all of the influential factors.

Diagnostic Statistical Manual-V (DSM-V) updates

To update older versions of the Diagnostic Statistical Manual (DSM), the American Psychiatric Association (APA) suggested that BED be included in the DSM-V because of several reliable predictive factors such as family history and its comorbid associations with mood disorders (1). In the DSM-V, BED is marked by recurrent episodes of binge eating and is characterized by both of the following:

1) eating, in a discrete period of time (e.g., within any 2-hour period), an amount of food that is definitely larger than most people would eat in a similar period of time under similar circumstances, and 2) a sense of lack of control over eating during the episode (e.g., a feeling that one cannot stop eating or control what or how much one is eating). The binge eating episodes are associated with three or more of the following: 1) eating much more rapidly than normal, 2) eating until feeling uncomfortably full, 3) eating large amounts of food when not feeling physically hungry, 4) eating alone because of feeling embarrassed by how much one is eating, 5) feeling disgusted with oneself, depressed, or very guilty afterwards. Marked distress regarding binge eating is also present. Additionally, the behavior occurs, on average, at least once a week for three months.

Binge eating is not associated with the recurrent use of inappropriate compensatory behavior such as purging and does not occur exclusively during the course of anorexia, bulimia, or restrictive food intake disorder.

Treatment options

Mindfulness has been described as an intentional, nonjudgmental awareness of one’s present-moment thoughts, feelings, sensations, and perceptions as they occur and fade away in an ongoing stream, without being swept away in preconceived expectations (5, 29, 30). Research evaluating mindfulness-based therapy has begun to proliferate in the health literature (32) and has demonstrated effectiveness in treating a variety of health concerns including addictive disorders (54), and emotional disorders due to HIV/AIDS (53). Several mindfulness-based therapies are commonly found in clinical and counseling psychology literature. Among these are dialectical behavior therapy (DBT; 37,38), acceptance and commitment therapy (ACT; 24), mindfulness-based eating awareness training (MB-EAT; 35), and mindfulness-based cognitive therapy (MBCT; 49). Researchers (6, 35) have found MBCT and MB-EAT to be effective in the treatment of eating disorders. MBCT and MB-EAT programs frequently consist of 8-10 sessions. The initial sessions serve to introduce the basic tenets of mindfulness, while subsequent sessions help participants address the thoughts (and feelings) associated with food and eating through mindful eating. Binge triggers, hunger cues, and taste and stomach satiety are identified. Participants, then, learn how to use mindful eating to reduce the frequency and severity of unhealthy eating episodes (e.g., binge eating).

The presence and influence of coaches (and, frequently, sport psychology consultants) in many sport environments, makes them well positioned to identify patterns or evidence of disordered eating among athletes. Furthermore, mindfulness-based approaches to athletic performance enhancement (e.g., 9, 18) are being increasingly adopted by coaches and sport psychology consultants. These interventions may provide an existing infrastructure and understanding in which other concerns such as EE and BED may be more readily addressed through MBCT and MB-EAT. The close relationship between the affected athlete and coach may allow the coach to be more aware of difficulties the athlete may be experiencing. Furthermore, MBCT and MB-EAT interventions may be enhanced and reinforced on a more regular basis, too, by including coaches in the training. Sport psychology consultants should be made aware that mindfulness-based interventions can serve much broader purposes than performance enhancement (4) and should at least be made aware of existing modalities (e.g., MBCT, MB-EAT) for such purposes.

A variety of treatment options have been associated with positive outcomes regarding eating disorders. Mental health interventions that increase emotional awareness are highly beneficial for emotional eaters, and because binge eating disorder and addictive disorders possess a number of overlapping symptoms, treatments that are successful in treating addictive disorders are also typically considered beneficial in treating binge eating (7, 10). Other assumptions for treating eating disorders include (a) education alone will not be sufficient; (b) goal orientation and coaching to better manage emotions and resist overeating temptations may positively impact behaviors; (c) engaging in stress management techniques (like meditation or relaxation) may help regulate emotions; and (d) parenting skills may help to model positive behavior for children, as explained by the social learning theory (31).

Cognitive-behavioral therapy (CBT) is still considered the treatment of choice for binge eating and is successful in reducing binging behaviors and improving psychosocial functioning (14). CBT in self-help programs and group settings provide positive outcomes, not only for BED, but also in treating depressive disorders, maladaptive body image, and social self-esteem by addressing negative self-beliefs and teaching effective coping strategies (14, 48, 50).

More recent advances in the treatment of eating disorders use the practice of motivational interviewing (MI), a client-centered directive method for enhancing intrinsic motivation for change (10, 14). MI is effective in treating substance use, diet, exercise, and other lifestyle behaviors including eating disorders, and is as effective as CBT in reducing the frequency of binge eating (10, 14). MI encourages reflection on the behavior and resolution of ambivalence towards changing the behavior Moreover, MI introduces/considers the idea of change, and may increase self-esteem, self-efficacy, and motivation for change, while decreasing depressive symptoms (10).

The positive psychological principles of MI can also be used by practitioners along with other therapeutic approaches and positive strategies when working with clients. Clinician behaviors may significantly influence a client’s motivation for change. Therefore, a strategic model could be integrated to help improve existing therapeutic practices. When working with clients who struggle with EE or BED, practitioners can use the following MI strategies to guide treatment/counseling sessions. First, express acceptance towards the client and maintain an empathetic manner. Also, affirm the client’s freedom of choice and self-direction. Elicit both the client’s concerns about the behavior as well as ideas for healthier alternative behaviors. Change talk should also be elicited from the client. Next, explore the client’s ambivalence towards changing the behavior while assessing their confidence and readiness for change (10, 14). It is also advisable to discuss the various stages of change (i.e., transtheoretical model) and assess the client’s current stage while eliciting self-motivational statements. These statements may then be reframed to amplify motivation and self-efficacy. Proceed by exploring the client’s values and encourage a written decisional balance of the pros and cons for changing the behavior. Strive to practice active listening with the client and work collaboratively on a change plan in which the client is vested. Similar treatment models for composure and coping may also be helpful in treating clients with eating pathologies.

Ultimately, there are numerous physiological, intrapersonal (i.e., cognitive and affective), interpersonal (i.e., relational), and psychosocial (i.e., environmental and sociocultural) factors that influence behaviors associated with disordered emotional and binge eating. Similarly, there are also a range of therapies and treatments that can be used to positively affect the frequency and severity of these behaviors. Practitioners should stay abreast of this literature as treatment protocols continue to expand and become further refined and more efficacious.


1. American Psychiatric Association. (Jan. 31, 2011). Binge Eating Disorder. DSM-V revision. http://www.dsm5.org/ProposedRevisions/Pages/proposedrevision.aspx?rid=372

2. American Psychiatric Association. (June, 2000). Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR: Text Revision.

3. Anderson, A.E. (2004). Males with eating disorders: The gender factor.Eating Disorders Recovery Today, 2(3). Retrieved December 2, 2012 from http://www.eatingdisordersrecoverytoday.com/nl/nl_edt_2_3_2.html.

4. Andersen, M. B., & Mannion, J. (2011). If you meet the Buddha on the football field, tackle him! In D. Gilbourne & M. B. Andersen (Eds.), Critical essays in applied sport psychology (pp. 173-192). Champaign, IL: Human Kinetics.

5. Baer, R. A. (2003). Mindfulness training as a clinical intervention: A conceptual and empirical review. Clinical Psychology: Science and Practice, 10, 125-143.

6. Baer, R.A., Fischer, S., & Huss, D.B. (2005). Mindfulness and acceptance in the treatment of disordered eating. Journal of Rational-Emotive & Cognitive-Behavior Therapy, 23, 281-300

7. Barchard, K. A., Bajgar, J., Leaf, D. E., & Lane, R. D. (2010). Computer scoring of the levels of emotional awareness scale. Behavior Research Methods, 42(2), 586-595. doi: 10.3758/BRM.42.2.586

8. Baum, A. (2006). Eating disorders in the male athlete. Sports Medicine, 36(1), 1-6.

9. Birrer, D., Rothlin, P., & Morgan, G. (2012). Mindfulness to enhance athletic performance: Theoretical considerations and possible impact mechanisms. Mindfulness, 3, 235-246.

10. Cassin, S. E., Von Ranson, K. M., Heng, K., Brar, J., & Wojtowicz, A. E. (2008). Adapted motivational interviewing for women with binge eating disorder: A randomized controlled trial. Psychology of Addictive Behaviors, 22(3), 417-425. doi: 10.1037/0893-164X.22.3.417

11. Childress, A. R. (2006). What can human brain imaging tell us about vulnerability to addiction and relapse? In. Miller, W. R., & Carroll, K. M. Rethinking Substance Abuse: What the Science Shows, and What We Should Do About It. New York, NY: Guilford Press; 2006.

12. Currie, A. (2010). Sport and eating disorders: Understanding and managing the risks. Asian Journal of Sports Medicine, 1(2), 63-68.

13. DePalma, M. T., Koszewski, W. M., Case, J. G., Barile, R. J., DePalma, B. F.,& Oliaro, S.M. (1993). Weight control practices of lightweight football players. Medicine and Science in Sports and Exercise, 25(6), 694-701.

14. Dunn, E. C., Neighbors, C., & Larimer, M. E. (2006). Motivational enhancement therapy and self-help treatment for binge eaters. Psychology of Addictive Behaviors, 20(1), 44-52. doi: 10.1037/0893-164X.20.1.44

15. Fulkerson, J. A., Keel, P. K., Leon, G. R., & Door, T. (1999), Eating-disordered behaviors and personality characteristics of high schoolathletes and non-athletes. International Journal of Eating Disorders, 26(1), 73-79.

16. Galli, N., Reel, J. J., Petrie, T., Greenleaf, C., & Carter, J.(2011). Preliminary development of the weight pressures in sport scale for male athletes. Journal of Sport Behavior, 34(1), 47-68.

17. Garner, D. M., Rosen, L. W., & Barry, D. (1998). Eating disorders among athletes: Research and recommendations. Child and Adolescent Psychiatric Clinics of North America, 7(4), 839-857.

18. Gardner, F. E., & Moore, Z. E. (2004). A mindfulness-acceptance-commitment-based approach to athletic performance enhancement: Theoretical considerations. Behavior Therapy, 35, 707-723.

19. Geliebter, A., & Aversa, A. (2003). Emotional eating in overweight, normal weight, and underweight individuals. Eating Behaviors, 3(4), 341-347. doi: 10.1016/S1471-0153(02)00100-9

20. Grabarek, C., & Cooper, S. (2008). Graduate students’ social and emotional functioning relative to characteristics of eating disorders. The Journal of General Psychology, 135(4), 425-452. doi:10.3200/GENP.135.4.425-452

21. Guyton, A. C., & Hall, J. E. (2006). Dietary balances; regulation of feeding; obesity and starvation; vitamins and minerals. In Textbook of medical physiology (11th ed., pp. 865-880). Philadelphia: Saunders.

22. Harp, J. & Hecht, L. (2005). Obesity in the National Football League. Journal of the American Medical Association, 293, 1061-1062.

23. Harrison, A., Sullivan, S., Tchanturia, K., & Treasure, J. (2010). Emotional functioning in eating disorders: Attentional bias, emotion recognition and emotion regulation. Psychological Medicine, 40, 1887-1897. doi: 10.1017/S0033291710000036

24. Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (1999). Acceptance and commitment therapy. New York, NY: Guilford Press.

25. Holm-Denoma, J. M., Scaringi, V., Gordon, K. H., Van Orden, K. A., & Joiner, T. E. (2009). Eating disorder symptoms among undergraduate varsity athletes, club athletes, independent exercisers, and nonexercisers. International Journal of Eating Disorders, 42(1), 47-53.

26. Hudson, J. I., Hiripi, E., Pope, H. G., & Kessler, R. C. (2007). The prevalence and correlates of eating disorders in the national comorbidity survey replication. Biological Psychiatry, 61(3), 348-358.

27. Jerlhag, E., Egecioglu, E. Dickson, S. L., & Engel, J. A. (2010). Ghrelin receptor antagonism attenuates cocaine- and amphetamine-induced locomotor stimulation, accumbal dopamine release, and conditioned place preference. Psychopharmacology Berlin, 211(4), 415-422. doi: 10.1007/s00213-010-1907-7

28. Johnson, C., Powers, P. S., & Dick, R. (1999). Athletes and eating disorders: The National Collegiate Athletic Association study. International Journal of Eating Disorders, 26(2), 179-188.

29. Kabat-Zinn, J. (1994). Wherever you go, there you are: Mindfulness meditation in everyday life. New York, NY: Hyperion.

30. Kabat-Zinn, J. (2005). Coming to our senses. New York, NY: Hyperion.

31. Kemp, E., Bui, M., & Grier, S. (2011). Eating their feelings: Examining emotional eating in at-risk groups in the United States. Journal of Consumer Policy, 34(2), 211-229.

32. Keng, S. L., Smoski, M. J., & Robins, C. J. (2011). Effects of mindfulness on psychological health: A review of empirical studies.Clinical Psychology Review, 31, 1041-1056.

33. Klok, M. D., Jakobsdottir, S., & Drent, M. L. (2007). The role of leptin and ghrelin in the regulation of food intake and body weight in humans: a review. Obesity Reviews, 8(1), 21-34.

34. Kristeller, J. L., Baer, R. A., & Quillian-Wolever, R. (2006). Mindfulness-based approaches to eating disorders. In Baer, R. (Ed.), Mindfulness-based treatment approaches: clinician’s guide to evidence base and applications (pp. 75-91). Boston, MA: Academic Press.

35. Kristeller, J. L., & Hallett, C. B. (1999). An exploratory study of a meditation-based intervention for binge eating disorder. Journal of Health Psychology, 4(3), 357-363.

36. Linde, J. A., Jeffery, R. W., Levy, R. L., Sherwood, N. E., Utter, J., Pronk, N. P., & Boyle, R. G. (2004). Binge eating disorder, weight control self-efficacy, and depression in overweight men and women. International Journal of Obesity, 28(3), 418-425. doi: 10.1038/sj.ijo.0802570.

37. Linehan, M. (1993a). Cognitive-behavioral treatment of borderline personality disorder. New York, NY: Guilford Press.

38. Linehan, M. (1993b). Skills training manual for treating borderline personality disorder. New York, NY: Guilford Press.

39. Lustig, R. H. (2006) Obesity: Metabolism: Childhood obesity: behavioral aberration or biochemical drive? Reinterpreting the First Law of Thermodynamics. Nature Reviews Endocrinology, 2, 447-458 doi: 10.1038/ncpendmet0220

40. Malina, R. M., Morano, P. J., Barron, M., Miller, S. J., Cumming, S. P.,Kontos, A. P., & Little, B. B. (2007). Overweight and obesity among youth participants in American football. Journal of Pediatrics, 151, 378-382.

41. Masheb, R. M., & Grilo, C. M. (2006). Emotional overeating and its associations with eating disorder psychopathology among overweight patients with binge eating disorder. International Journal of Eating Disorders, 39(2), 141-146.

42. Matthews, E. M. & Wagner, D. R. (2008). Prevalence of overweight and obesity in collegiate American football players, by position. Journal of American College Health, 57(1), 33-37.

43. Montenegro, S.O. (2006). Disordered eating in athletes. Athletic Therapy Today, 60-62.

44. NEDA: Terms and definitions. (2011). National Eating Disorders Association. Retrieved November 01, 2011, from http://www.nationaleatingdisorders.org/

45. Noel, M. B., VanHeest, J. L., Zaneteas, P., & Rodgers, C. D. (2003). Body composition in division 1 football players. Journal of Strength and Conditioning Research, 17, 228-237.

46. Perko, M. A., Williams, R. D., Gordon, B. C., & Tucker, T. (2007). Changes in body size of elite high school football players before and after anabolic steroid legislation [Abstract]. Research Quarterly for Exercise and Sport, 78¬(1), A95.

47. Petrie, T., Greenleaf, C., Reel, J. J., & Carter, J. E. (2008). Prevalence of eating disorders and disordered eating behaviors among male collegiate athletes. Psychology of Men and Masculinity, 9(4), 267-277.

48. Pringle, A., Harmer, C. J., & Cooper, M. J. (2010). Investigating vulnerability to eating disorders: Biases in emotional processing.Psychological Medicine, 40, 645-655. doi: 10.1017/S0033291709990778

49. Segal, Z. V., Williams, J. M. G., & Teasdale, J. D. (2002). Mindfulness-based cognitive therapy for depression: A new approach to preventing relapse. New York, NY: Guilford Press.

50. Shelley-Ummenhofer, J., & MacMillan, P. D. (2007). Cognitive-Behavioral treatment for women who binge eat. Canadian Journal of Dietetic Practice and Research, 68(3), 139-142.

51. Shumaker, S. A., Ockene, J. K., & Riekert, K. A. (2009). The handbook of health behavior change. New York, NY: Springer Pub.

52. Sim, L., & Zeman, J. (2006). The contribution of emotion regulation to body dissatisfaction and disordered eating in early adolescent girls. Journal of Youth and Adolescence, 35(2), 219-228. doi:10.1007/s10964-005-9003-8

53. Sinha, U. & Kumar, D. (2010). Mindfulness-based cognitive behavior therapy with emotionally disturbed adolescents affected by HIV/AIDS. Journal of Indian Association for Child Adolescent Mental Health, 6(1), 19-30.

54. Skanavi, S., Laquelle, X., & Aubin, H. (2011). Mindfulness based interventions for addictive disorders: A review. Encephale, 37(5), 379-387.

55. Sundgot-Borgen, J. & Torstveit, M.K. (2004). Prevalence of eating disorders in elite athletes is higher than in the general population. Clinical Journal of Sport Medicine. 14(1), 25-32.

56. Sundgot-Borgen, J. & Torstveit, M.K. (2010). Aspects of disordered eating continuum in elite high-intensity sports. Scandinavian Journal of Medicine and Science in Sports, 20(S2), 112-121.

57. Wallis, D., & Hetherington, M. (2004). Stress and eating: The effects of ego-threat and cognitive demand on food intake in restrained and emotional eaters. Appetite, 43(1), 39-46. doi: 10.1016/j.appet.2004.02.001

58. Willeumier, K., Taylor, D. V., & Amen, D. G. (2012). Elevated body mass in National Football League players linked to cognitive impairment and decreased prefrontal cortex and temporal pole activity. Translational Psychiatry, 2(e68). doi: 10.1038/tp.2011.67.

2015-01-31T01:09:00+00:00May 8th, 2013|Contemporary Sports Issues, Sports Exercise Science, Sports Studies and Sports Psychology|Comments Off on Understanding Emotional and Binge Eating: From Sports Training to Tailgating