Chang Chia-Ming, Associate Professor, Department of Physical Education, National Chia-Yi University; Chen, Kuan-Chung, United States Sport Academy; Kelly E. Flanagan, D.S.M., Chair of Sport Studies, United States Sports Academy
Abstract
The purpose of this study was to explore the differences among the taekwondo training hall members’ demographic variables as they related to participative motivation, satisfaction, and loyalty. A secondary aim is to verify the cause and effect relationship of participative motivation, satisfaction, and loyalty. For this study, a total of 358 members were selected from 15 taekwondo training halls in Taipei County. The instruments utilized in this research include a participative motivation scale, a satisfaction scale, and a loyalty scale. The data were statistically analyzed utilizing descriptive statistics (including a frequency distribution percentage, the mean and the standard deviation), a t-test, a one-way ANOVA, the scheffe method and structural equation modeling. The results were as follows: (a) As it related to the demographics of the members at the taekwondo training halls in Taipei county, the descriptive statistics indicated that a majority of the members were males between 9-12 years old; their total family income was around NT 40,001~NT 60,000; and a majority of the members had practiced taekwondo for less than one year. (b) The results of the analysis of the member’s demographic variables showed that a member’s gender, age, and time spent learning taekwondo indicated statistically significant differences on his or her participative motivation and satisfaction. A member’s gender, age, family income, and time spent learning taekwondo also indicated statistically significant differences on his or her loyalty. (c) According to the analysis conducted by the structural equation modeling, participative motivation had a positive influence on satisfaction and loyalty, and satisfaction had a positive influence on loyalty. Based on these findings, the researchers have provided some suggestions for taekwondo training halls. (more…)
Nicos L. Kartakoullis and Andreas Theophanous,
University of Nicosia
Abstract
An in-depth study of the current football industry in Cyprus was undertaken to evaluate the financial situation of the first division football clubs, the competitive balance of the national league, the management practices of the football clubs and national league, and the negative effects of football hooliganism on the industry. Research involved both an extensive literature review of secondary sources from the Cyprus Sport Organization, the Cyprus Football Association, and the football clubs, as well as a qualitative data collection tool which included personal interviews and focus groups. Challenges and opportunities facing the football industry in Cyprus were identified.
Introduction
There is no doubt that football is the most popular sport worldwide. It is the king of sports. Because of the popularity of football all over the world on all continents, it is no surprise that on many occasions people address football as the “universal language.” According to Murphy, Williams, and Dunning (1992) “Soccer is, without any shadow of doubt, the world’s most popular sport.”
The hero of Liverpool FC, the late Bill Shankly, who managed to turn Liverpool Football Club into a big European football power, emphasized that football is a “more important matter than life or death.” It is true that “there appears to be something about the structure of soccer that gives it a very wide appeal in the modern world, an appeal that appears to be relatively independent to the level of development of countries, the socio-political character of the regimes by which they are ruled, their allegiances and the alliances that they are involved in” (Murphy, Williams, Dunning, 1992).
The Federation Internationale de Football Association (FIFA), the world governing body of football, commissioned the social research company in Zurich, Lamprecht and Stamm SE BAG, to conduct the FIFA Big Count 2006. A survey that was conducted through the 207 national football associations worldwide, in which data was gathered on the numbers of participating players in football at all levels. The results of the survey are impressive indicating how big football is worldwide. The president of FIFA, Joseph S. Blatter, in view of the published results of the survey stated, “Football’s popularity remains undiminished and is actually increasing.”
Some of the impressive findings of the 2006 survey as presented in a press release by FIFA on June 12, 2007, indicated the following:
· The overall number of 265 million male and female players is almost 10 percent higher than the number recorded six years ago (242 million). Of the 265 million, 26 million, or around 10 percent, are women.
· Since 2000, the number of registered male and female footballers has increased by around 23 percent to over 38 million.
· The growth in women’s football is particularly striking, with the number of registered players up 54 percent to 4.1 million, while the number of registered players in the men’s game has likewise seen an increase of 21 percent to 34.2 million.
· The number of unregistered occasional players, which was first recorded in the previous Big Count study, is up seven percent to 226 million.
· There are now a combined total of over one million futsal and beach soccer players (both male and female).
· The number of clubs (301,000) is similar to the figure recorded in 2000. That said, the total number of teams (1.7 million) has increased by approximately 200,000.
The FIFA president further noted, “If you count the relatives and close friends of active participants in football, who share in their passion for the game as fans and support them in other ways, the total number is even more impressive: Well over a billion people worldwide are involved in football at all levels of society and across all borders.” Based on the figures provided, FIFA stated that a grand total of 270 million people, male and female players, which represents four percent of the world’s population, are involved in one way or another in football. According to the FIFA press release, it is not only the television audiences and match attendances that are increasing but the number of people playing football on all continents. It is not only popular as a spectator sport but as a participant sport as well. It is worth noting that based on FIFA records, out of these 270 million people, 99.8% are amateur football players with 80% being youth players.
With all those figures available, the FIFA president is happy to state, “Football is truly the world’s game. It is played in every conceivable place, on every corner of the world by men, women, boys, and girls of all ages. It is played in narrow streets, in muddy fields, and in packed stadiums on grass, concrete, earth, and sand. Any differences between people fade away in its unifying light.”
The figures and all this related information display a picture of football’s development worldwide. However, besides this success in football’s development, which is proven by the increasing numbers, there are critics of the work of FIFA. Sugden and Tomlinson (2005) noted that FIFA has transformed itself from an international nongovernment organization into a business international nongovernment organization. FIFA has been increasingly profit driven and presents one of the leading examples of the professionalization and commercialization of modern sports. They define this as “sport’s emergence at the heart of the worldwide cultural industries” (Sugden and Tomlinson, 2005). Thus, Sugden and Tomlinson were willing to “… show what happens in an international nongovernmental organization when the pursuit of profit overwhelms an ethic of service” and in view of this they presented an analysis of the crisis in world football (Sugden & Tomlinson, 2005).
Along the same lines as this critical approach and perspective, Allison set a series of questions trying to set sports in the right perspective in this era of globalization; he emphasized, “… how worried should we be about the nature of power in international organizations?” (Allison, 2005).
There is no doubt that “football has been transformed over the years to a gigantic commercial operation” (Boyopoulos & Milakas, 2005). However, besides this truth, nobody can underestimate the cultural significance of football as elaborated by Norbert Elias in his civilizing process theory.
On the one hand, nobody can argue the fact that football has become commercialized and is big business now, as noted above; on the other, nobody should overemphasize the problems and challenges of the game by ignoring its power and what it can offer to different societies.
Sports generally, and football precisely, presents unique situations whereby we have the coexistence of profit making on the one hand, and nonprofit making and voluntary organizations on the other. In the football world, there is this uniqueness where profit making is an activity that is conducted in many instances by nonprofit or voluntary organizations where they all have common goals and objectives (Capling, 2004; Murphy et. al. 2001; Rachman, 2002).
In many instances, the financial dimensions of football are increasing without actually leading to profitability for the football clubs. In fact, all over the world, and in Cyprus too, many football clubs are facing severe financial problems. Although, there are occasions where the big football clubs in different nations are profitable (Capling, 2004; Deloitte, 2005; Booth, 2004; Rachman, 2002).
The finances of football clubs for many years and in many instances where not made public for many various reasons. In many situations, proper financial records were not kept, and in many countries, this presented a chaotic situation where records and information were not readily available (Kartakoullis, 2005). The introduction of the UEFA club licensing system by the Union des Associations Europeenes de football (UEFA), the European governing football body, assisted in many instances and actually contributed to the sorting of the finances of football clubs in Europe as clubs were forced to prepare financial statements, accounts, and budgets to be submitted to their national football associations; otherwise, they would not be granted permission to compete in national and European competitions.
Purpose of the Study
Football is an international cultural phenomenon which is currently characterized by two major challenges: professionalization and commercialization.
The purpose of this study was to examine specific parameters of the football industry in a small country, Cyprus, where there are certain unique characteristics. The specific parameters addressed were the financial situation of the first division football clubs, the competitive balance of the national league, and management practices in the football industry. What major challenges exist in the football industry of a small country such as Cyprus, away from this globalized form football is taking with the two major characteristics of professionalization and commercialization? What are the challenges facing such an industry away from huge contracts, profitable television rights, sponsorships, and so many vested interests, as one can see them in the international football arena?
The Republic of Cyprus became an independent state in 1960. It became a member of the United Nations in 1960, of the Council of Europe in 1961, and of the European Union in 2004. It has an area of 9,521 square kilometers and a population of approximately 800,000. Since 1974, it has been de facto divided. Efforts to solve this problem in Cyprus and reunify the island have not been successful yet. Nicosia (Lefkosia in Greek; Lefkosa in Turkish) is the capital city.
Three geographic characteristics of Cyprus have determined much of its fate: location, size, and the fact that it is an island. It is located at a strategic position in the eastern Mediterranean, at the crossroads of three continents. Its strategic location, long exposed coastline, and small size always made it an attractive and easy target for outsiders. Its history and demography reflect the ebb and flow of peoples and powers in the region. In the course of its long history, Cyprus has been controlled by most of the major powers that had interest in, or sought control of, the Middle East. The list of its successive rulers include the Egyptians, Greeks, Phoenicians, Asssy6rians, Persians, Ptolemies, Romans, Byzantines, Franks, Venetians, Ottoman Turks, and British. It gained its independence from Britain in 1960 (Joseph, 2000).
Cyprus has been considered a football-loving nation, arising from the fact that football competitions draw good attendance in Cyprus as well as from the fact that it is extensively covered in the media. It is not surprising for example that when the two big football teams of the country play against each other, they attract crowds of more than 25,000 people, which is indeed large, bearing in mind the small size of the country. This fact is further reinforced by the results of the football survey (2005-2006), conducted on behalf of the Cyprus Football Association by the Centre for Leisure, Tourism, and Sports Research and Development. The results of the research clearly indicated that Cyprus is a football-loving nation. For example, the fact that 77% of men aged between 21-70 years old support a football club, and another 20% who do not support a club, still follow football in Cyprus and are well informed about the results of the national league, clearly displays there is great interest. Additionally, the fact that 16,000 kids are registered and play football in football academies all over the island displays this love for the game.
Method
A combination of methods has been used to gather the material required to analyze the football industry in the country. Thus, as a first step, all related information was collected from the Cyprus Sport Organization, the Cyprus Football Association, and the first division football clubs in Cyprus. The task of collecting information for the football clubs was not as hard and difficult as initially predicted, as this was already done by the National Football Association, who collected all related material for the UEFA club licensing scheme. However, a review of available material was definitely not enough for such a purpose. That was only one aspect of this research.
Participants
In view of this, personal interviews and focus groups were conducted in the attempt to collect as complete and as accurate information as possible. Interviews were conducted with the presidents or secretaries general of all 14 footballs clubs in the first division of the national league, the professional clubs in Cyprus. This was done in order to collect qualitative data which was going to complement the material already collected in the first phase of the research. Qualitative data was useful in this respect in gaining additional information in relation to the issue under investigation. Qualitative data according to Straus and Corbin (1990) is “any kind of research that produces findings not arrived at by means of statistical procedures or other means of quantification.” Qualitative interview studies are usually conducted with small samples (14 in this case) and the “aim is usually to gather an authentic” understanding of people’s experiences (attitudes, knowledge, beliefs about football in Cyprus in this case) and it is believed that open ended questions are the most effective route towards this end” (Silverman, 1993). Thus, this method involved an open ended interview study which encouraged the top decision makers of the football clubs in Cyprus to offer their own attitudes, knowledge, definitions and understanding of the football industry.
Design and Procedure
Two focus groups were utilized as the means to collect data for the analysis of the football industry. For Morgan (1988), focus groups are basically group-oriented discussions that rely on interaction within the group based on the topic that the moderator supplies. The advantage is that through focus groups, the moderator assists, especially at the first stages of the interaction, by providing information that could be helpful to participants in placing the focus group in context.
According to Morgan (1988) focus groups are basically group interviews; they rely on interaction within the group, based on the topic that the researcher supplies; with the researcher taking the role of a moderator. Furthermore, Morgan (1988) notes that focus groups can be used as a supplement for collecting data when using either qualitative or quantitative methods. Additionally, focus groups can be used as follow-up research to clarify findings in the other data collected, but more importantly, according to Morgan (1988) the goal in using focus groups is to get closer to participants’ understandings of the researcher’s topic. In view of this, the use of the focus groups in this case provided a valuable insight into the variables examined for the football industry. Focus groups are thus helpful in investigating what participants think, uncovering why participants think as they do, crucial in the attempt being made to investigate the perspectives analyzed above. There are both strengths and weaknesses of focus groups as a setting in which to collect qualitative data; in this particular case the use of focus groups was considered appropriate in supplementing the data already collected. Additionally, focus groups were useful to conduct as they produced valuable data from group interaction on the specific topic under examination; a focus group can delve deeper as participant’s contributions can trigger further comments of other participants. Two focus groups were conducted; each group consisted of six persons (members of executive committees of football clubs, football players, referees, coaches, sports journalists, sponsors, supporter’s clubs, and representatives of the Cyprus Football Association) under the moderation of Dr. Andreas Theophanous, who has experience of more than 20 years in qualitative research. The focus was on obtaining a good representative sample of persons associated with the football industry in Cyprus. The focus group sessions lasted for almost two hours each, and the data collected was then analyzed using the coding technique of content analysis. Thus, a series of categories or coding frames have been developed in relation to the finances of the clubs, the governance and management of the clubs, the competitive balance of the league, and the major problems that the industry is facing today.
Analysis or coding of qualitative data represents the operations by which data are broken down, conceptualized, and put back together in new ways; it is the central process by which theories are built from data (Straus and Corbin, 1990). This technique entails defining a series of categories of answers in which the researcher is interested (Breakwell, 1990). In addition, according, to Breakwell (1990), if the researcher does not wish to push responses into categories because this loses some of the individuality of the original statements, then content analysis can be used in a different way whereby in the report produced of the findings there are lots of quotations which will show the depth of the opinions expressed. More precisely, for analyzing the data gathered in this section, a classification system or coding was used where responses were classified in schemes using coding frames.
Results
Based on the data collected, it is evident that football clubs in Cyprus have four major sources of revenue (M. Gavrielides, A. Michaelides, D. Seraphim, personal communications, April 10, 2007). This include the income from tickets sold for the home matches, the television rights, membership fees and financial support from friends of the clubs, and commercial activities including sponsorship. The expenses of the football clubs are usually more than their income, and this was actually identified as the major cause of the financial problems that football clubs are currently facing in Cyprus during the focus groups (A. Michaelides, personal communication, March 20, 2007).
The major expenses of the football clubs involve salaries to the football players, coaches, and administrative staff, accommodation and board when the club is traveling for away games, transfer fees, and expenses for the organization of matches. (K. Koutsokoumnis, personal communication, April 6, 2007). This issue with the salaries of players and coaches is addressed extensively in the discussion section that follows.
For securing confidentially, the budgets of the different clubs discussed in the focus groups could not be presented separately, but Table 1 provides the total budgets of the 14 first division clubs for the 2004-2005 season in terms of their income and expenditures. For the purpose of analysis, the 14 teams are divided into two groups: the first group is comprised of the five largest teams in the country, and the second group includes the remaining nine teams. It became clear from diligent examination and discussion of the budgets submitted by all 14 first division clubs that most of the teams will have difficulty meeting the criteria of the UEFA club licensing scheme, which prescribes balanced income and expenditures of club members. From the study of the budgets submitted, as well as from the analysis of the data collected through the interviews and the focus groups, it appears that most of the budgets are over-ambitious. Additionally, the profit and loss accounts of the clubs were diligently studied. In most cases, it appeared that there was an over-estimation of expected income for the clubs.
Eight major points were identified by the research team in relation to the financial situation of the clubs in Cyprus.
· The 14 clubs of the first division submitted in their budgets their incomes for the period under examination, and total incomes for all clubs were calculated at Euro 17,530,250, which corresponds to Euro 1,252,404, for each club. The biggest income declared by any club was Euro 2,853,364, and the lowest income declared was Euro 744,319
· Total expenditure was calculated at Euro 17,629,349, which corresponds to Euro 1,259,239, for each club. The biggest expenditure declared by a club was Euro 2, 392,004 and the lowest was Euro 744,319.
· Six clubs declared that they were expecting losses in the period under investigation; while the other eight clubs expected to have a profit.
· The biggest profit to be made was estimated at Euro 640,725, and this was by a club which by the end of the season was relegated to the second division.
· Paying the salaries of players, foreign and domestic, and coaches consumed 75% of every club’s budget.
· From the data gathered, it was clear that foreign players were paid better salaries than the domestic players.
· Season tickets contributed an average of 10% of the total income for the clubs. The highest contribution from season tickets to total income was 20%, and the lowest was 1%.
· The television rights for the period under examination were calculated to Euro 934,177, which represented 5.3% of the total income of clubs.
The government of the Republic of Cyprus acknowledges the importance of football in Cypriot society. In view of this, the government has provided different forms of financial support to the sport. The Cyprus Sports Organization, which is the semi- governmental organization in charge of sports, has provided annual financial support to the Cyprus Football Association which comes to Euro 4,613,223 per year. However, in view of the financial problems of the football clubs in the country and in the attempt by the government to assist the clubs to get through this financial crisis, the government decided two years ago to provide a grant of Euro 10,251,608 over a four year period. Additionally, the Cyprus Sport Organization returns to the individual football clubs a total sum of Euro 717,612 per year, which represents taxes collected on gate income as well as community taxes (T. Christofides, personal communication, April 10, 2007). Furthermore, another amount of Euro 683,440 per year is given by the Sports Organization to pay the police forces in charge of security during the football matches (K. Papakosta, personal communication, March 15, 2007).
From the qualitative data gathered, it emerged that there was a consensus among the different parties involved in the football industry that there are three major challenges facing football in Cyprus. Football violence, bad governance and management of clubs, and prejudice against referees and officials are major challenges that the industry is facing, and although there is potential for further development, these problems do not allow the industry to grow to its full potential. (K. Zivanaris, personal communication, April 10, 2007). Peristianis, Kapardis, Loizou, Fakiolas, and Puloukas (2002) noted that the football industry in Cyprus is facing a major crisis in the face of football hooliganism, which can destroy the sport if this is not controlled. It is an ongoing problem that has not been controlled for years now and can lead to the financial collapse of the industry (Peristianis et al, 2002; Aristotelous & Pouloucas, 1996).
Another major issue that was addressed in the focus groups was the fact that there is no competitive balance in the national league, which poses a serious threat to the football industry. (T. Antoniou, K. Malekkos, C. Constantinou, C. Theodotou, personal communications, 12 April, 2007). The clubs are split into two groups: the five large ones in the first group and the other nine in the second group, which represent the weak teams struggling for survival. Out of the five clubs in the first group, three of those, namely APOEL, OMONIA and ANORTHOSIS, are the only ones that compete for the national championship each year. This has been the case for years now, and this competitive imbalance leads to a reduction of interest in the football industry (L. Kyriakou, personal communication, March 6, 2007). The results show, for example, that in the 2005-2006 season a total of 507,000 tickets were sold with 337,661, which represents 66% of the total, being utilized by the big five group. Table 2 shows the distribution of tickets during this season between the big and the weak teams of the league.
As Figure 1 identifies, the gap between the big and the weak teams in the sale of tickets is growing larger, which clearly presents the problematic situation existing because of this competitive imbalance in the national league.
Clubs are recruiting increasing numbers of foreign players, which increases their expenditures considerably, and this is causing Cypriot players to become a scarce commodity. (A. Michaelides, personal communication, April 10, 2007). Over a typical weekend with seven games on the national league calendar, approximately 190 players were used including substitutes during the 2005-06 seasons. Out of those 190 players, only 75 were Cypriots. This is a trend which is increasing every year; whereby last season, there was a point where there were teams starting without a single Cypriot player in the first eleven. Back in the 1992-1993 season, for example, the clubs in Cyprus used to have eight Cypriot players and only three foreigners in the starting eleven. (M. Gavrielides, personal communication, March 22, 2007). It is not surprising then that during that period, clubs were in a much better financial situation. In many countries, this is the trend, but in large developed countries, the football industry is big enough to cope with such expenses. In England, for example, the figures show that in the 1992-1993 season, only 10% of the players starting the games were not British. Conversely though, during this current season, only 37% of the players starting in the first eleven were British.
This is the issue actually. Clubs in small countries, like Cyprus, should not try to copy what is happening in other countries where the football industry is huge. The clubs’ officials need to be very realistic and down to earth when trying to build their teams. However, it is sad to identify that things are getting out of control according to the discussions held in the focus groups (L. Kyriakou, M. Gavrielides, T. Antreou, personal communications, April 10, 2007).
Discussion
Due to the popularity of football worldwide, the game has grown into a huge industry. Gratton and Henry (2001) estimated that in the big European countries, the football industry contributes 3% of the gross domestic product of those countries. According to Theophanous and Kartakoullis (2004), in Cyprus, the football industry contributes only 1.84% of the gross domestic product. This was actually expected as Cyprus is a small country. However, something which is alarming and risky as well is the fact that out of this 1.84%, which totals an amount of Euro 223,826,788, a great percentage of this, which comes to Euro 153,774,130, derives from the betting industry. Thus, the betting industry forms a substantial part of the football industry in the country, and this is something that for some years now is leading to various forms of problems and issues, the major of which is prejudice. In certain instances, rumors are spread concerning fixed matches and for referees that have been influenced by officials and players betting huge amounts of money on specific fixtures. This is a major issue for the football industry as the huge amounts of money spent in the betting industry have led to prejudice against the sport and, in turn, is destroying the image of the game in Cyprus. Similar sorts of problems with betting and fixed games have been identified in other countries all over the world.
In relation to the above issue, there are some additional complications and issues that are raised because of the betting situation. As noted in the results section, the clubs in the first division are split into two categories: the big five and the remaining small or weaker clubs. In view of the fact that 66% of the total income from games derives from the big five, a series of other questions are generated having to do with the influence that these clubs have in the decision-making processes, in the appointment of referees and in the allocation of television rights among the clubs. Television rights are handled by the Cyprus Football Association, which has developed a scheme for allocating income to the clubs. Again, in relation to this scheme of allocation, there are issues and concerns as it seems that the big five at some stage will start handling their own rights with television stations. The big five will secure good deals with the stations in the country, and the small ones will remain financially exposed, as they will lose a good portion of their incomes from the rights. The television rights totaled a sum of Euro 934,177, which represents almost 6% of the total income of the clubs. This is expected to rise to almost 12% of the total income of the clubs in the next two years, based on the new deals to be signed.
In relation to the distribution of income for football clubs, Back et al. (2004) estimated that the three major sources of income for football clubs should deliver roughly the same amounts. That comes to approximately 33% contribution to total income from each of the three categories of income: tickets, television rights, and commercial activities. For example, for Manchester United in the period of 1992-2002, this was calculated to 40% from tickets, 34% from television rights, and 26% from other commercial activities. When considering the distribution of income for the clubs in Cyprus, this is far from this equal distribution.
It should be noted that this issue of big and weak football clubs is not only a problem in Cyprus but a challenge for European football as well. In the Friedlander Report (2001) by the Centre for Research into Sport and Society of the University of Leicester, it is stated that the gap between the big clubs and the rest is ever growing bigger, so this is something that needs to be addressed.
Another major concern that is leading to great controversy has to do with the contracts and salaries of players. As can be deduced from the expenditures of the clubs (Table 1), 75% of the total expenses of the clubs were on salaries for players, coaches, and the support staff. The football players’ salaries came to 65% of expenditures. Each club in the first division has 25 registered professional players plus another six to ten persons in the support team (fitness trainer, physiotherapist, medical doctor, or administrators). The salaries of foreign players playing in Cyprus are considerably higher to those paid to Cypriot players; however, there is a great concern as to whether the contribution of foreign players to the team is greater than that of the Cypriots, thus justifying their bigger salaries. There are cases of foreign players in Cyprus who signed yearly contracts of Euro 341,720, which is really surprising for such a small industry. Along the same lines, there are coaches in Cyprus coming from Europe with contracts of Euro 256,290 per year, which is again on the very high side bearing in mind the size of the football industry in the country.
In relation to the above, Deloite (2004, 2005), in the annual review of football finances, noted that there is a tendency for decreasing the percentage of salaries on total expenditures. In the premier league, for example, in England, salaries represented 62% of total expenditures in 2001-2002, 61% in 2002-2003, and a further reduction to 60% in the following season. The same tendency for reducing salaries could be observed in other European countries. On the contrary, in Cyprus, the exact opposite is happening; there is an increasing tendency in this respect which is very dangerous indeed, when realizing that most of the clubs, if not all, are in a very bad financial situation. Thus, on the one hand, the clubs, due to their difficult financial situation, are seeking government support, but on the other, they are spending on salaries and contracts amounts with which the size of the industry in Cyprus cannot cope. The financial dimensions of the football industry in Cyprus are getting too big for such a small country, which is an alarming and dangerous trend for the future of the industry.
When all the financial statements and budgets of the clubs were examined from the documents submitted for the UEFA club licensing system, it was again obvious that clubs were in a bad financial situation. The great majority of clubs had big debts, and in order for them to meet the club licensing criteria, they postponed payments for years to come. For example, if a club had agreed to pay a player Euro 200,000 for a salary, they signed an agreement with the player stating that he is going to receive this money in the years to come. However, this is not solving the problem, but the problem is just postponed to the next few years.
The data from the qualitative analysis was enlightening in discovering the beliefs and opinions of the officials involved, top decision makers of the football clubs. It was indeed very interesting on the one hand, and very contradictory on the other, to identify from this research the commonly felt concern of all officials involved in football in Cyprus, and especially of the clubs’ top decision makers. There was a consensus that the expenditures of the clubs are growing, and the football industry is not currently ready to afford such a burden. However, beside this issue, which was overwhelmingly accepted, the club officials are doing absolutely nothing to resolve the problem. They clearly know the facts, they understand that football is in crisis, and still each year there is an average increase of 10% in the expenditures of the teams. This is indeed contradictory and illogical. The officials of the clubs, when asked why this happens, could not provide an answer. “There is no logic in football,” said one of the representatives of the big clubs. It should be noted that there are certain things that clubs can do to reduce their budgets, but the managers are still doing nothing about it. Actually, they are moving in the exact opposite direction.
The issue of overspending is something that can be observed in football clubs all over the world. Williams and Neatrour (2002) noted that clubs engage in this overspending practice by taking excess risks in view of the tough competition in football, and then, when things do not go the way they expect, in terms of performance, they cannot meet their financial obligations.
Football clubs in Cyprus are in crisis. This is proven by the results of this research, and it is justified in every respect. Clubs are currently in a struggle for survival as they have big debts that they need to repay. However, the situation is even more alarming considering the fact that clubs, despite this financial crisis, annually increase their budgets, with the result that the football industry is becoming too big and too risky for the country as well. Although clubs are operating on considerably big budgets, the structure they have still relies mostly on voluntary work without good governance or responsible management. Bad management and bad governance are major characteristics of clubs, and this was made clear in the qualitative data gathered. The clubs’ governing boards are comprised of volunteers, who for many different reasons become involved in the game. They are not always involved for the good of the Game but for many other different reasons. In view of this, when people become involved in the running of a club, they want immediate results, and they are not willing to plan for the future, as they wish to get the credit when they are on board. Thus, there is no strategic direction in the clubs, and, in view of this, no future plans for development. It is more of a day-to-day struggle for survival than anything else. There is an urgent need for better management of the football clubs and, additionally, a need for professionals to become involved in the football industry. The football industry in the country is getting too big for volunteers to run it. There is urgency for professionalism at all levels. Professionalization of the game is only happening with increasing numbers of professional players arriving from abroad; apart from this, there is no professionalization in any other respect.
Competitive balance refers to the ability of any of the football clubs in the national league to win the championship at the end of the season. Where there is competitive balance, clubs have equal chances to winning the league, and this makes the league very interesting as the outcome is not known. However, this is not the case in Cyprus, where at the beginning of each season, for years now, only three clubs are competing for the championship title. Thus, there are three favorites for the title and inevitably this leads to reduced interest on behalf of the fans, both for attending the matches as well as for watching them on TV. Additionally, it leads to a series of related problems with the remaining clubs that can not compete with the three favorites on equal terms; thus, the clubs are facing both competition and financial challenges. This limited interest at some stage during the football season by the indifferent clubs leads to problems and concerns with fixed matches and other related controversies. In view of this competitive imbalance, it is no surprise that out of 66 leagues organized in Cyprus, 50 were won by the three favorites. Nobody can question this issue, which was again extensively addressed by participants in the focus groups.
The issue of competitive balance in the national leagues is a major issue of concern for the football industry, as this is a critical success factor for the industry. In view of this, extensive work on the competitive balance of national leagues has been conducted by Holt et al. (2004), Michie and Oughton (2004 and 2005), Michie et al. (2004) and Forrest et al. (2005).
Despite the problems and issues identified, the club officials and top decision makers were still quite optimistic in relation to certain issues or opportunities that they identified. For instance, they identified the fact that an increasing number of big organizations and companies are interested in becoming involved in the industry as sponsors. This is quite true as there is a kind of new sponsorship culture that is developing lately on the island. The club officials emphasized this fact as they considered that this is a golden opportunity for the clubs to capitalize on. However, again this is an opportunity and a challenge. Sponsors are willing to join the football industry as long as they are going to get a good return. Gone are the days when companies donated money to football clubs in the form of charity (Kartakoullis, 2007). Consequently, the message is clear. On the one hand, there is potential in this area, but in order for the football clubs and the industry to utilize this, there is the need for expertise in the area.
Conclusion
The aim of the study was to gather data and examine important parameters of the football industry in Cyprus. This was the very first time that such an attempt has been made in Cyprus, which is indeed a football-loving nation. The research team approached the analysis from a purely critical perspective for the good of the game in Cyprus and for no other reason.
The football industry in Cyprus is facing a series of challenges that need to be addressed urgently. Bad management and governance are major characteristics in the industry, and it is no surprise that the football clubs, the major stakeholders in the industry, are in severe financial crisis. They have huge debts that they cannot pay; they have very high payrolls, which the industry can not handle in such a small country, and no strategy for development. Football hooliganism and the lack of competitive balance in the national league complete this picture of football in crisis in the small country of Cyprus. The financial dimensions, as denoted by the different parameters studied of the football industry, are growing, and the country cannot cope with it for the time being, as all football clubs are experiencing losses based on their profit and loss accounts studied. It is obvious that sports authorities need to invest in developing football and, precisely, in the management and structure of football; otherwise, the future of the game will be very gloomy and without hope.
Government support is good as provided, but this will not do much in saving the game, unless good management, governance, professionalism, and accountability are introduced at all levels of the game. In view of this, all those involved in the football industry need to realize the new opportunities and challenges in the world of sports and should introduce innovations at all levels of the game (Westerbeek & Smith, 2003). There is no doubt that all stakeholders in the football industry of Cyprus wish to upgrade football in this country, bringing it up to European standards. On the other hand, they should definitely have in mind all related concepts and issues in relation to this “Europeanization” of elite football (Martin, 2005). Above all, they need to be very realistic and down to earth, always having in mind the size of the football industry and the country as well.
Acknowledgments
The authors gratefully acknowledge the support of the Cyprus Football Association, the Football Clubs, and their officials in conducting this research. Additionally, the financial support of the Cyprus Football Association was greatly appreciated in conducting this research.
Table 1
Total Budgets for the Football Clubs 2005-2006
Income
€ 5 Big Clubs
€ 9 Weak Clubs
Total
€
% of
Budget
Tickets
4.421.957
2.184.865
6.606.823
37.69%
Commercial Activities
1.940.964
2.115.351
4.056.315
23.14%
Television Rights
452.779
481.398
934.177
5.33%
Funding
1.021.726
1.608.198
2.629.925
15.00%
Other
1.403.371
1.898.915
3.302.287
18.84%
Total
9.240.800
8.288.729
17.529.529
100.00%cmunisteri2009-03-13T14:37:00
Thousands & hundreds should be separated by commas not periods
Expenditure
€ 5 Big Clubs
€ 9 Weak Clubs
Total
€
% of
Budget
Foreign Players
2.843.174
2.709.558
5.552.732
31.50%
Cypriot Players
2.931.119
2.702.899
5.634.019
31.96%
Coaches
860.458
884.255
1.744.714
9.90%
Field Expenses
106.753
292.751
399.505
2.27%
Sports Equipment and Materials
29.046
230.046
259.092
1.47%
Transport
32.036
49.737
81.773
0.46%
Hotel Accommodation and Board
123.873
144.530
268.404
1.52%
Medical Expenses
90.555
160.523
251.078
1.42%
Field Security
12.643
59.288
71.932
0.41%
Transfer fees
3.417
321.217
324.634
1.84%
Expenses for European Competition
34.172
15.377
49.549
0.28%
Expenses for pre-season training abroad
129.853
203.569
333.423
1.89%
Complementary tickets
17.940
0
17.940
0.10%
Soccer Academies/Development Programmes
61.509
184.101
245.611
1.39%
Miscellaneous
1.475.777
919.724
2.395.501
13.59%
Total
8.752.331
8.877.582
17.629.913
100.00%
Table 2
Tickets Sold by the Big and the Weak Teams
Competition Season
Average no. of tickets
Average of the big teams
Average of the weak teams
Average of tickets sold without the big five
1996/97
1.387
5.065
882
541
1997/98
1.815
6.216
970
539
1998/99
1.911
6.581
955
414
1999/2000
1.813
6.130
941
454
2000/01
2.502
7.208
1.291
584
2001/02
2.553
7.720
1.258
491
2002/2003
3.091
8.458
1.624
707
2003/04
2.943
8.721
1.332
406
2004/05
2.790
7.655
1.563
652
Total
2.311
7.087
1.202cmunisteri2009-03-13T14:42:00
Thousands & hundreds separated by commas not periods
532
References
Allison, L. (2005). The global politics of sport – The role of global institutions
in sport. London and New York: Routledge.
Aristotelous, K. & Pulokas S. (1996). Fan violence and football attendance in Cyprus.
Journal of Business and Society. 9, 104-109.
Back, T. V., Blatter, P., & Burgin, J. R. (2004). Playing to win in the business of
sports the pressure is on. Making money – not just popularity – is the name of
the game. McKinsey Quarterly. web exclusive. Retrieved __________from
By: Andrew Bosak, Philip Bishop, J. Matthew Green, G Hawver, and Mike Iosia
Abstract
Recovery from a hard running effort determines when a runner can run at an intense level again. Overtraining is often caused by insufficient recovery, which ultimately hurts endurance performance. The number of recovery hours needed to sufficiently restore the body back to peak racing condition is unknown. The purpose of this study was to compare 5km running performance after 24 hours and 72 hours of recovery. Twelve well-trained runners (9 males and 3 females) completed two successive 5km performance trials on two separate occasions. Immediately following the baseline 5km trial, runners recovered passively for 24 hrs (R24) and 72 hrs of passive recovery (R72), and then performed a second 5km trial. The 5km time trial sessions were separated by 6-7 days of normal training and performed in a counterbalanced order. R24 (19:59 + 1.9 min) was significantly (p = 0.03) slower than baseline (19:49 + 1.9 min). However, no significant differences (p = 0.21) were found between R72 (19:30 + 1.5 min) and baseline (19:34 + 1.6 min). HRave for R24 (177.3 + 6.3 b/min) was the same as baseline (177.3 + 7.3 b/min), yet R72 HRave (177.9 + 6.3 b/min) was significantly higher (p = 0.04) than baseline (175.4 + 6.5 b/min). RPEend for R24 (19.5 + 0.8) was not significantly different (p = 0.39) than baseline (19.6 + 0.8), but R72 RPEend (19.8 + 0.6) was significantly (p = 0.01) greater than baseline (19.3 + 0.9). For the R24 trials, 9 participants ran a mean 17.4 + 12.1 secs slower and 3 participants ran a mean of 13.3 + 6.8 secs faster than baseline. During R72, three individuals ran a mean 10.3 + 5.7 secs slower, five individuals ran a mean 17.4 + 12.9 secs faster, and four individuals ran within 3.3 + 1.8 secs of their first run. Results indicate that 72 hrs of passive recovery, on average, permits maintenance of successive 5km time trial performance, yet individual variability existed regarding rate of decline of 2nd trial performance. Future research is needed to determine if a longer or shorter recovery time will maintain or improve 5km racing performance.
Introduction
Coaches and runners constantly strive to identify legal methods to improve runners’ performances. Factors such as tempo runs, hill repeats, long-slow distance days, striders and build-ups, intervals and repeats, dietary intake, and sleep patterns, are continually tested and adjusted to produce better performance. However, one factor often overlooked is recovery. Many runners feel that to race faster, they should have longer daily runs, run more miles per week, or train faster and harder. This often leads to overtraining, which hurts performance. Recovery from hard running efforts plays a vital role in determining when a runner can run at an intense level again (Fitzgerald, 2007).
Previous studies have focused on recovery from long endurance races such as marathons and ultra-marathons (Gomez et al., 2002; Martin & Coe, 1997; Noakes, 2003). Recovery from these endurance efforts revolves around repairing of damaged muscle fibers and replenishing glycogen stores (Fitzgerald, 2007; Gomez et al., 2002; Nicholas et al., 1997). In shorter duration endurance activities, such as a 5km (3.1 miles), 10km (6.2 miles) race, or hard training runs, Foss and Keteyian (1998) indicate that muscle and liver glycogen levels may be normalized 24 hrs after exercise, but muscle function may not be fully recovered and performance measures may be sub-optimal.
Former University of Oregon track coach Bill Bowerman first popularized the concept of hard/easy training, indicating that intense workouts such as an interval session, tempo run, or long run, should be followed the next day by an easy run (Dellinger & Freeman, 1984). Using Bowerman’s method, a runner would have an intense workout every 48 hrs to allow muscle function to be restored to normal (O’Conner & Wilder, 2001). Also, New Zealander Jack Foster indicated a runner should take one recovery day for every mile completed in a race [Brown & Henderson, 2002; Galloway, 1984; Henderson, 2000; Higdon, 1998; Sinclair, Olgesby, & Piepenburg, 2003). However, Henderson indicated that it may be better to take one easy day per kilometer (Brown & Henderson, 2002; Henderson, 2000). Although, Bowerman, Henderson, & Foster’s statements about recovery days after a race or hard effort seem reasonable, the appropriate recovery duration as well as what is considered “easy” has not been previously studied.
Gomez et al. (2002) determined that strength and power capabilities of distance runners after a 10km race normalized after 48 hrs of passive recovery. Thus, it is likely that participants would be fully recovered, which would allow them to maximize performance during another 10km race. Because 5km is half the distance of 10km, it may be logical to presume only 24 hrs of passive recovery may be needed, instead of the required 48 hrs for 10km. However, this hypothesis was not supported when we tested two distance runners of above average abilities in a pilot study as the participants were not able to achieve similar 5km performance after 24 hrs of passive recovery. Twenty-four hours may not be a sufficient amount of time for the dissipation of muscle fatigue or soreness (Brown & Henderson, 2002). Therefore, the purpose of this study was to compare 5km running performance after 24 hrs of passive recovery versus 72 hrs of passive recovery.
Methods
Participants
Participants for the study were 12 well trained male (n = 9) and female (n = 3) runners currently engaged in rigorous training. Runners from the local road running and track club, local triathlon competitors, and former competitive high school and college runners, were recruited by word of mouth. Participant inclusion criteria included: (a) Subjects must have been currently involved in a distance running training program, (b) Had previously run 16-22 min for male runners or 18-24 min for a female runner for 5km, (c) Currently averaging at least 20-30 miles (running) per week, (d) Have previously completed at least five 5km road or track races, (e) Have a VO2max of at least 45 ml/kg/min (females) or 55 ml/kg/min (males), and (f) Provided sufficient data (from running history questionnaires, Physical Activity Readiness Questionnaires, and Health Readiness Questionnaires) that reflected good health.
Participants completed a short questionnaire regarding their running background, racing history, and current training mileage. All participants were volunteers and signed a written informed consent outlining requirements and potential risks and benefits resulting from participating.
Procedures
Participants were assessed for age, height, body weight, and body fat percent using a 3-site skinfold technique (Brozek & Hanschel, 1961; Pollock, Schmidt, & Jackson, 1980). Participants were fitted with a Polar Heart Rate Monitor and then completed a graded exercise test (GXT) to exhaustion lasting approximately 12-18 minutes. VO2max, heart rate (HR), and Ratings of Perceived Exertion (RPE) were collected every minute.
All GXTs were completed on a Quinton 640 motorized treadmill. The test began with a 2 min warm-up at 2.5 mph. Speed was increased to 5 mph for 2 min, followed by 2 min at 6 mph, 2 min at 7 mph, and 2 min at 7.5 mph. At this point, incline was increased two percent every 2 min thereafter until the participant reached volitional exhaustion (ie., the felt like they could no longer continue running at the required speed and grade). Once the participant reached volitional exhaustion, they were instructed to cool down until they felt recovered.
Approximately five days later, participants performed their first 5km race between the hours of 6:30 am and 7:30 am. The time of day for each performance trial was consistent throughout the study. All performance trials were completed on a flat hard-surfaced 0.73 mile loop. Prior to each trial, participants completed visual analog scales pre and post a 1.5 mile warm-up run, regarding their feelings of fatigue and soreness within the quadriceps, hamstrings, gastrocnemius, lower body, and total body muscle groups. Visual analog scales were 15 cm lines where participants placed an “X” on the line indicating their feelings (with 0 = no fatigue or soreness and 15 = extreme fatigue or soreness). The visual analog scales evaluated participants’ status before the start of every time trial. Participants were also required to rate their perceived exertion (RPE) after the warm-up, prior to the start and during each 5km, to see if feelings of effort remained consistent between each trial, as well as during each lap and after each performance trial.
Participants underwent a 1.5 mile warm-up prior to every 5km performance trial (Kaufman & Ware, 1997). Participants completed successive 5km performance trials on two separate occasions. Immediately following a baseline 5km trial, runners recovered passively for 24 hrs (R24) or 72 hrs of passive recovery (R72) and then performed a second 5km trial. The 5km time trial sessions were in a counterbalanced order and were separated by 6-7 days of normal training. All participants were required to have 24 hrs of passive recovery prior to each baseline. Passive recovery was deemed as no exercise or extensive physical activity during the allotted recovery hours. During each time trial, average HR (HRave) and ending RPE (RPEend) were recorded to determine if effort for each 5km trial was consistent. All runners competed with runners of equal ability to simulate race day and hard training conditions with verbal encouragement provided often and equally to each participant. At the end of every performance trial, each runner was instructed to complete a low intensity 1.5 mile cool-down. Each testing session required approximately 60 min.
Statistical Analysis
Basic descriptive statistics were computed along with Repeated Measures of Analysis of Variance (MANOVA) for making comparisons between R72 and R24 performance trials regarding finishing times, HRave, RPEend, and fatigue/soreness responses. All statistical comparisons were made at an a priori p < 0.05 level of significance. Data was expressed as group mean + standard deviation and individual results.
In order to evaluate individual responses, data from each participant’s first 5km trial was compared to their second 5km trial using a paired T-test. The least significance group mean difference (p < 0.05) was determined and group mean finishing time was adjusted to determine the amount of change in seconds, between baseline and treatment trials, needed for significance. The time change between the first trial run and the adjusted baseline run was divided by the first trial run and expressed as a mean number of seconds and as a percent for both the R24 (9.5 secs or 0.8%) and R72 (7.0 secs or 0.6%) trials. The percent values were applied to each individual baseline time in order to determine how many seconds (positive or negative) the second performance trial time had to be over or under the first performance trial, in both R24 and R72 conditions, to quantify as a response. Participants were then labeled as non-responders, positive-responders (faster during successive trial), and negative-responders (slower during successive trial).
Results
Descriptive characteristics are found in Table 1. The participants were between the ages of 18 and 35 (majority of subjects were between ages of 20-28) years. All participants were trained runners or triathletes (where running was their specialty event).
Mean finishing times, HRave, and RPEend for 1) R24 vs baseline and 2) R72 vs baseline are found in Table 2. R24 was significantly (p = 0.03) slower (10 secs) than baseline, where as R72 was not significantly (p = 0.21) different from baseline. Regarding HRave, no significant differences (p = 1.00) were found between R24 and baseline, yet R72HRave was significantly (p = 0.04) greater than baseline. Significance (p = 0.39) was not found between R24 RPEend and baseline, but R72 RPEend was significantly (p = 0.01) higher than baseline.
R24 trials = 24 hrs of passive recovery between baseline and R24
R72 trials = 72 hrs of passive recovery between baseline and R72
*indicates significant difference between respective baseline trial.
Figure 1 displays individual differences between R24 and R72 performance trials. To be considered a non-responder, the individual time change had to fall within 0.8% of baseline performance for R24 and 0.6% of baseline performance for R72.
Figure 1. Changes in Individual Finishing Times (R72 vs R24)
Positive and negative responders (Table 3) were identified when individual time change was greater than 0.8% for R24 trials and 0.6% for R72 trials, with a positive responder being one whose 2nd performance trial time improved (expressed as a negative value) and a negative responder being one whose 2nd performance trial time slowed (expressed as a positive value).
Table 3
Comparison of Individual R24 and R72 Performance Trials
________________________________________________________________________
R24 trials = 24 hrs of passive recovery between R24 and baseline
R72 trials = 72 hrs of passive recovery between R72 and baseline
* = responder
– = faster
+ = slower
@ = significance
Three individuals responded negatively to R72 by running a mean 10.3 + 5.7 secs slower during R72. Five individuals responded positively to R72 by running a mean 17.4 + 22.9 secs faster than baseline. Four individuals were considered non-responders to R72 with a mean time change of 3.3 + 1.8 secs.
Nine individuals responded negatively to R24 by running a mean 17.4 + 12.1 secs slower than baseline. Three individuals responded positively to R24 by running a mean 13.3 + 6.8 secs faster. There were no non-responders to the R24 trials. It is important to note that only two (participants 3 and 10) of three individuals who were negative responders to R72 also responded negatively to R24. Also, there were no individuals who positively responded to both R72 and R24.
There were no significant differences between R24 and baseline trials vs R72 and baseline trials for soreness and fatigue regarding pre and post warm-up scores on the fatigue/soreness visual analog scales (Table 4).
No significant differences were found between trials
Subjects appeared to be fully recovered before each trial
Discussion
The primary purpose of this study was to compare 5km racing performance after 24 hrs of passive recovery versus 72 hrs of passive recovery. Other than a few somewhat related studies by Bosak et al. (2008 & 2009), the necessary duration of passive recovery from 5km time trials has not previously been studied. Results indicate that 72 hrs of passive recovery, on average, permits maintenance of second 5km time trial performance, yet individual variability existed regarding rate of decline of 2nd trial performance. Individuals must therefore test themselves or coaches must test their athletes to determine optimal recovery time that allows for improved performance during successive 5km efforts.
R24 was significantly (p = 0.03) slower (10 secs) than baseline. However, no significant differences (p = 0.21) occurred between R72 and baseline (Table 2). Due to the catabolic nature of the running process, pain results from microtears and swelling (edema) within the muscle, which require sufficient passive recovery time prior to undergoing another intense running effort (Brown & Henderson, 2002). Increased passive recovery time can also be used to reduce the reflex muscle spasm and spastic conditions that accompany pain. Thus, it is logical to assume longer hours of passive recovery following a 5km race, may attenuate soreness and fatigue prior to the next race or hard running effort, which would potentially allow performance to be maintained or at least minimize impairment (Fitzgerald, 2007). Therefore, in this study, it is hypothesized that 72 hrs of passive recovery facilitated a more effective recovery allowing participants to actually run a few seconds faster than baseline. Since, subjects were required to have 24 hrs of passive recovery before each baseline it is likely that subjects were more fully recovered for R72 than for either baseline performance trial, thereby producing slight improvements during R72 performance trial.
There were no significant differences between R24 and baseline trials versus R72 and baseline trials for soreness and fatigue (Table 4) regarding pre and post warm-up scores on the fatigue/soreness visual analog scales. These results indicated that all runners tended to feel the same prior to each baseline and treatment trial. The assumption, therefore, is that each runner felt a similar level of preparedness before every trial. However, individual variability (Figure 1) existed among runners, which makes it important to focus on the effects of passive recovery (24 hrs and 72 hrs) on each individual.
Four individuals were considered non-responders to R72 with a mean time change of positive or negative 3.3 + 1.8 secs. It is possible that the intensity needed to complete the 5km performance trial was less than what was needed to fatigue these 4 non-responders.
Five individuals responded positively (Table 3) to R72 running a mean of 17.4 + 12.9 secs faster during the second trial. The potential reason for improved performance during R72 may be due to the fact that the 5 participants may have been in a more rested state as compared to their status prior to the first trial. Several of those subjects who did run faster during R72 verbally indicated that they “felt better” (regarding fatigue and muscle soreness) prior to the start of the second 5km as compared to how they were feeling before the baseline trial.
Despite the fact that as a group the participants ran a mean 10 seconds slower during R24 vs baseline, three individuals responded positively to R24 by running a mean 13.3 + 6.8 secs faster than baseline. The improvements during R24 could have been due to the fact that the 5km distance may not have been sufficient enough to fatigue these individuals from baseline, which allowed each runner to be recovered before the start of the second trial.
In terms of participants who ran slower (Table 3) during R24 and R72 performance trials, 9 individuals ran a mean time of 17.4 + 12.1 seconds slower after 24 hrs of passive recovery. Apparently, 24 hrs of passive recovery was not sufficient enough to allow muscle function to return to normal (Brown & Henderson, 2002). However, despite having 72 hrs of passive recovery, 3 participants still ran a mean of 10.3 + 5.7 secs slower than baseline. The decreased performance during R72 may have been a result of the runners having a “feeling of staleness” in their legs from completing no exercise for 72 hrs as explained by Mujika et al. (2001), where he suggested that many collegiate and post-collegiate runners often complain of feeling “stale” if they haven’t run in a few days. A potential loss of “feel” during exercise has been implied to occur in competitive athletes as a result of a reduction in training frequency (Mujika et al., 2001).
Despite R72 HRave being significantly (p = 0.04) greater than baseline and R24 HRave being the same as baseline, there were no consistent patterns of HRave and increased or decreased performance among participants during all R72 and R24 trials. It can be assumed that a lower HRave was associated with less effort since HR and intensity levels are related. However, only participant 7 ran faster and had a higher HRave during R24 and R72. During the R72 trials, only participants 4, 10, and 12 ran slower and had a lower HRave during second trial performance. During the R24 trials, only 1, 3, 5, 6, ran slower and had a lower HRave during second trial performance.
As for RPEend, no significant difference (p = 0.40) occurred between R24 and baseline, yet R72 was significantly (p = 0.01) greater than baseline. Also, scores on the pre and post warm-up fatigue/soreness visual analog scales were not significantly different between R24 and baseline trials vs R72 and baseline trials, indicating that all runners individually tended to feel the same prior to each 5km trial. Therefore, since inconsistencies exist between HRave, RPEend, and performance trials, while no significant differences occurred regarding fatigue/soreness responses, it is assumed that all participants displayed similar efforts during each 5km performance trial.
Conclusion
The results of the study indicate that 72 hrs of passive recovery, on average, permits maintenance of second day 5km performance. The study displays evidence that in most runners, 24 hrs of passive recovery did not provide sufficient recovery time for restoration of proper muscle function in agreement with Foss and Keteyian (1998) and Sinclair, Olgesby, & Pierpenburg (2003). For most runners, performance after 24 hrs of passive recovery may be impaired due to the inability to recruit sufficient muscle fibers in active muscles, as a result of residual muscle fatigue (Noakes, 2003). On average, more than 24 hrs of passive recovery is necessary for most runners to achieve optimal 5km race performance (Bosak et al., 2008). Since it was apparent that individual variability in recovery occurred in our study, individuals and coaches must therefore test themselves and their athletes to determine optimal recovery time, which may vary even within individuals depending upon other factors.
References
Bosak, A., Bishop, P., & Green, M. (2008). Active vs passive recovery in the 72 hours after a 5km race. The Sport Journal, 11 (3).
Bosak, A., Bishop, P., Green, M., & Hawver, G. (2009). Impact of cold water immersion on 5km racing performance. The Sport Journal, 12 (2).
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Mujika, I., Goya, A., Ruiz, E., Grijalba, A., Santisteban, J., & Padilla, S. (2001). Physiological and performance responses to a 6-day taper in middle-distance runners: influence of training frequency. International Journal of Sports Medicine, 23, 367-373.
Nicholas, C. W., Green, P. A., Hawkins, R. D., & Williams, C. (1997). Carbohydrate intake and recovery of intermittent running capacity. International Journal of Sport Nutrition, 7, 251-260.
Noakes, T. (2003). Lore of Running (4th ed.). Champaign, IL: Human Kinetics.
O’Conner, F. G. & Wilder, R. P. (2001). Textbook of Running Medicine. New York, NY: McGraw-Hill.
Pollock, M. L., Schmidt, D. H., & Jackson, A. S. (1980). Measurement of cardiorespiratory fitness and body composition in the clinical setting. Comprehensive Therapy, 6, 12-27.
Sinclair, J., Olgesby, K., & Piepenburg, C. (2003). Training to Achieve Peak Running Performance. Boulder, CO: Road Runner Sports Inc.
Authors’ References:
Dept. of Sport Health Science, Life University, Marietta, GA 30060
Dept. of Kinesiology, University of Alabama, Tuscaloosa, AL 35401
Dept. of Health, PE, and Recreation, University of North Alabama, Florence, AL 35632
Dept. of Health and Human Performance, Georgia Southwestern State University, Americus, GA 31709
Dept. of Health, Exercise Science, and Secondary Education, Lee University, Cleveland, TN 37320
Oğuz Özbek, Ankara University, School of Physical Education and Sports, Ankara, Turkey
Abstract
The purpose of this study was to determine the levels by which the students in Departments of Physical Education agree with the professional codes of ethics for physical education teachers. One hundred twenty-two students receiving education in Departments of Physical Education and Sports in three universities participated in the research. A questionnaire consisting of 32 items was used as the data collection tool. Physical education teacher candidates studying in different universities stated that they fully agreed with the professional codes of ethics for physical education teachers. However, they were observed to have different opinions regarding some ethics codes depending on gender, class, and school variables.
Introduction
Ethics lies on the basis of all relationships established by humans. There are such values as love, respect, gratitude, and trust in a relationship between two persons. (Kuçuradi, 1996). Ethical behavior considers the rights and interests, as well as the existence of others (Haynes, 2002). The goal of an ethical relationship is being able to show that ethical action is a basic characteristic of human existence; that is being able to teach to love people (Pieper, 1999). Studies on ethics deal with the standards used in the rightfulness or wrongfulness of human behavior. They seek answers to such questions as to which behaviors are good, desirable, and acceptable (Gözütok, 1999).
Professional ethics resulted from an increase in ethical problems in certain professions or from the awareness of these increasing problems. Ethics of medicine, law, sports, press, and education are some examples of professional ethics (Tepe, 2000). Professional ethics are a set of general rules that look at the work performed by the members of the profession from an ethical point of view and that are complied with by the majority of these members (Sockett, 1990; Kultgen, 1988). Ethical codes laid down by professional organizations and supported by sanctions will guide the person who applies them and help him/her to decide in potential dilemmas (Fain, 1992). Even though professional codes of ethics are regulated separately for every profession, such codes as honesty, legality, reliability, professional loyalty, and respect apply to all professions (Wiley 2000).
When education was taken up as a multidimensional system, ethical conduct came to be one of these dimensions (Barcena & Gıl, 1993). Ethics of education interests all of society. Behaviors related to students are central to the ethics of education. It is the duty of all educators to provide the student with humane living conditions within the environment of education. The relationship between the teacher and the student must be based on love and respect (Bilgen, 1994).
Ethical relationships are expected to be experienced within the environment of education. For this reason, ethics codes that are determined for education must have compliance by educators. Universal values such as honesty, fairness, loyalty, and respect are taken as basis when determining ethics codes. The basic purpose of ethics codes is to make application most beneficial, to provide public benefit, to protect the profession, to discipline the members, and to guide the teachers in solving ethical dilemmas they may encounter during daily applications (Campbell, 2000).
Physical education teachers are faced with making ethical decisions while they are fulfilling their duties in schools and sports facilities (Harrison and Blakemore, 1992). Physical education teachers must act in compliance with professional ethics while they are performing their duties in order to protect service ideals, regulate competition within the profession, and raise the quality of the service provided. The first known codes of ethics in literature for physical education teachers were proposed in 1950 by the American Alliance for Health, Physical Education and Recreation (AAHPER) professional ethic board, and published in the Journal of Physical Education and Recreation in 1950 (Resick, Seidel, & Mason, 1975). A major part of these professional codes of ethics regulate the relationship between the teacher and the student. Other ethics codes are concerned with the relationship of teachers and their colleagues, their responsibilities towards the society, participation in professional organizations, and professional development.
It was observed that the definitions made related to ethical dilemmas were more successful, their theoretical and practical knowledge concerning ethical dilemmas increased, and their solutions and recommendations for ethical problems became more successful at the end of their education (Bergem, 1993). In a study conducted by Priest, Krause, and Becah (1999), ethical value choices of students were discovered to have changed positively at the end of a four years higher education.
The pre-service education received by teachers will have an influence on the decisions to be made by them in ethical incidents they encounter during the course of their professional lives. In research conducted by Tirri (1999), teachers stated that they encountered ethical dilemmas in matters related to passing courses, education, lessons and success, moral dimensions of student behavior, cheating, negative student behavior, and general rules in school. Some very sensitive situations were expressed by some of the teachers who took part in the research. For instance, if a teacher has to touch his/her student as required by his/her profession, s/he is faced with a dilemma. The teacher must decide on the limits of the help s/he will provide to his/her students. Such dilemmas are mostly encountered by special education and physical education teachers (Tirri, 1999).
Physical education teachers in Turkey are educated in Schools of Physical Education and Sports in universities and Departments of Physical Education and Sports connected education faculties. Students take special skill examinations in order to be admitted to these departments. Physical education teacher candidates receive four years of higher education consisting of general knowledge, professional knowledge for teaching, and field education knowledge. The physical education teacher training program, which was prepared centrally by the Higher Education Council in 1997, is applied in all universities. All physical education teacher candidates graduate from programs consisting of the same courses and contents. With a recent amendment made to the program, optional courses have been proposed to be introduced for the students to acquire professional ethics (YÖK, 2007).
The education received by physical education teachers has a major influence on their behavior inside the school and the classroom. Therefore, physical education teacher candidates should acquire the qualifications of being able to act in compliance with the professional ethics along with professional knowledge and skills during their pre-service education.
The basic aim of this study was to determine the levels by which the students in departments of physical education agree with the professional codes of ethics for physical education. With this aim was an intent to determine whether or not the opinions of students in Departments of Physical Education regarding the levels of agreement with the professional codes of ethics displayed differences depending on gender, class, and school variables.
Method
The survey method was used in this research. The scale developed by Özbek (2003) was used in order to measure the levels by which physical education teacher candidates agreed with of professional codes of ethics for physical education teachers. The validity and reliability of the measuring tool, was studied again. Factor analysis was carried out for the structural validity of the measuring tool and total correlation analysis of items was evaluated. Before conducting factor analysis, the Kaiser-Meyer-Olkin (KMO) value was observed in order to determine the suitability of the size of sampling to factor analysis and the KMO value was found to be .90. The minimum KMO value must be .60 in order for a factor analysis to be realized on the data (Pallant, 2005). The .90 KMO value, which was observed in this case, showed that the data were suitable for factor analysis. On the other hand, the Barlett test result for the factor analysis of 32 items was found to be 2837.291, (p < 0.001). The KMO and Barlett test results indicated that a factor analysis could be conducted on these data. As a result of the factor analysis, the scale was decided to be one-dimensional. The total declared variance was calculated as 46.4 %. A declared variance of 30 % or more is considered sufficient in single-factor scales (Büyüköztürk, 2002). The factor load values of the items included in the scale ranged between .37 and .83. A factor load value of .30 or more was taken as basis while deciding on including an item in the scale. None of the items was excluded from the scale in this case (see Table 1). The correlation coefficient of the items included in the scale, on the other hand, ranged between .37 and .81 (See Table 1). The total correlation coefficient of items is required to be at least .30 (Pallant, 2005). According to this, no items were excluded from the scale. All of the 32 items in the original scale were kept without any change. The internal consistency coefficient Alpha, which is calculated for the reliability of the scale, was found as .95. Therefore, the scale was considered valid and reliable.
Table 1.
Factor Load of the Items in the Scale and Their Total Correlation Values
Item
No
Factor Load
Item
Total r
Item
No
Factor Load
Item
Total r
1
.41
.39
17
.75
.71
2
.37
.37
18
.71
.69
3
.41
.40
19
.69
.65
4
.72
.68
20
.73
.69
5
.78
.75
21
.78
.74
6
.69
.68
22
.68
.64
7
.60
.57
23
.81
.76
8
.66
.62
24
.75
.71
9
.53
.50
25
.66
.63
10
.73
.71
26
.56
.53
11
.62
.59
27
.77
.74
12
.64
.63
28
.83
.81
13
.52
.51
29
.76
.73
14
.62
.60
30
.82
.78
15
.48
.46
31
.79
.76
16
.60
.60
32
.83
.80
The scale contained the 32 professional codes of ethics given chart 2 along with personal information. The options of the scale and their points were determined as, Fully disagree (1 point), Somewhat agree (2 points), Moderately agree (3 points), Mostly agree (4 points), and Fully agree (5 points). The formula (5-1 = 4; 4/5 = 0.80) was used in determining the range coefficient of the scale. According to this the option ranges were determined as Fully disagree (1.00-1.79), Somewhat agree (1.80-2.59), Moderately agree (2.60-3.39), Mostly agree (3.40-4.19), and Fully agree (4.20-5.00). Whether or not there was a difference between the opinions of physical education teacher candidates based on class and gender was tested with the unrelated t test. Whether the opinions displayed differences based on the school variable, on the other hand, was tested with the unilateral variance analysis and the LSD test.
A Physical Education Teacher must,
A Physical Education Teacher must,
C1 – take the mental, emotional, and social developments of students into
consideration along with their physical skills while evaluating their success.
C2 – attach importance on education and health rather than being a champion or winning a
competition.
C3 – accept losing in competitions as natural as winning.
C4 – work in cooperation and solidarity with his/her colleagues.
C5 – help those who are new in the profession gain professional knowledge and experience.
C6 – not display an action based on violence towards his/her students.
C7 – approach the students who do not succeed in competitions with understanding.
C8 – take the necessary measures in conditions that might arise in students such as physical
discomfort, dehydration, or fatigue.
C9 – include activities by which all students take part in sports activities rather than providing a
group of students with the school’s facilities.
C10 – ensure that all students benefit from the tools, equipment, and facilities of the school.
C11 – not use grades as an instrument of pressure.
C12 – prefer honesty over winning in sports.
C13 – prefer discipline over winning in sports.
C14 – act with tolerance towards his/her students in their lessons.
C15 – reward proper behavior of students.
C16 – evaluate the success of students objectively.
C17 – take care to ensure that both s/he and his/her students conform to the lesson and training
hours.
C18 – attach more importance on the health and security of his/her students than sportive
success.
C19 – not intervene with the transfers of athlete students by following his/her own interest.
C 20 – show special attention to disabled students in order to ensure their participation in the
lesson.
C21 – consider the course of physical education as an integral and complementary part of
general education.
C22 – value the opinions of students during the lesson.C23 – not talk in a way to humiliate his/her athlete students.
C24 – not allow tests, measurements, or drug testing that would endanger the health of his/her
athlete students.
C25 – keep confidential the private information concerning his/her students.
C26 – keep confidential the religious, political, and ethnical matters discussed within the
classroom environment.
C27 – not conduct training exercises that would endanger the health of athlete students.
C28 – take the education and health of the athlete students into consideration during club
transfers.
C29 – avoid applications that would hold back other lessons of the students who will
participate in competitions.
C30 – not insult his/her students.
C31 – not talk in a way to humiliate the athletes and coaches of the competitor school team.
C32 – act aggressively and offensively in his/her relationships with his/her colleagues.
Figure 1. Professional Codes of Ethics for Physical Education Teachers
Participants
The research covered the students, who were receiving education in the Departments of Physical Education and Sports in the Gazi University School of Physical Education and Sports, Hacettepe University, School of Sport Sciences and Technology, and Ankara University School of Physical Education and Sports during the 2005 – 2006 academic year. There were 278 students in the freshman and senior classes of the three universities. The study aimed to reach the relevant segment of students fully. However, the data collection tool could only be applied to a study group consisting of 122 students. Twenty-five percent (n = 26), 53 percent (n = 64), and 26 percent (n = 32) of the students participating in the survey consisted of the students of Hacettepe University, Gazi University, and Ankara University, respectively. When the gender distribution was examined, 60 percent (n = 73) of the students were observed to be male and 40 percent (n = 49) female. 62 percent (n = 76) of the students participating in the survey were freshmen while 38 percent (n = 46) consisted of senior class students. Personal information regarding the study group of the survey has been provided in Chart 3.
Table 2
Personal Information Regarding the Study Group
Personal Information
Sub categories
f
%
School
Hacettepe U.
26
21
Gazi U.
64
53
Ankara U.
32
26
Total
122
100
Class
Freshman
76
62
Senior
46
38
Total
122
100
Gender
Male
73
60
Female
49
40
Total
122
100
Results
Findings regarding the opinions of physical education teacher candidates about their agreement with the professional codes of ethics were interpreted based on gender, class, and school variables.
The mean averages of the levels by which the physical education teacher candidates agreed with the professional codes of ethics based on gender, class, and school variables have been given in Table 3. As seen in Table 3, it was observed that the teacher candidates receiving education in three universities fully agreed with the professional codes of ethics [Hacettepe University ( = 4.66), Gazi University ( = 4.64), Ankara University ( = 4.66)]. The mean average of the levels by which the students in freshman and senior classes agreed with the professional codes of ethics [freshman ( = 4.63), senior ( = 4.69)] was realized as “full.” The mean average of the levels by which the male and female students agreed with the professional codes of ethics, on the other hand [male ( = 4.62), female ( = 4.71)], was again realized as “full”.
Table 3
The Mean averages of the Levels by which the Physical Education Teacher Candidates Agreed with the Professional Codes of Ethics based on Gender, Class, and School Variables
School
N
Mean
Class
N
Mean
Gender
N
Mean
Hacettepe U.
26
4.66
Freshman
76
4.63
Male
73
4.62
Gazi U.
64
4.64
Senior
46
4.69
Female
49
4.71
Ankara U.
32
4.66
The averages of the opinions of physical education teacher candidates concerning the professional codes of ethics based on their genders have been provided in Table 4. As seen in Table 4, a noteworthy difference was observed in three items as a result of the unrelated t test conducted among the averages regarding the opinions of physical education teacher candidates based on their genders, while no significant differences were seen in other items.
Male teacher candidates agreed at the level of ( = 4.61), and female teacher candidates at the level of ( = 4.87) with the principle stating “a physical education teacher must value the opinions of students during the lesson” (C22). There was a significant statistical difference between the averages of the opinions of male and female physical education teacher candidates [ t (120) = 2.15, p<.05]. More female teacher candidates agreed with the principle that a physical education teacher should value the opinions of students during the lesson compared to male teacher candidates.
While male student candidates agreed with the principle stating “a physical education teacher must not allow tests, measurements, or drug testing that would endanger the health of his/her athlete students” (C24) at a level of = 4.75, the level of agreement by female teacher candidates was = 4.93. There was a significant statistical difference between the averages of the opinions of male and female physical education teacher candidates [t (120) = 2.11, p < .05]. More female teacher candidates agreed with the principle that a physical education teacher should not allow tests, measurements, or drug testing that would endanger the health of his/her athlete students, compared to male teacher candidates.
While male teacher candidates agreed with the principle stating “a physical education teacher must not insult his/her students” (C30) at a level of = 4.65, the level of agreement by female teacher candidates was = 4.85. There was a significant statistical difference between the averages of the opinions of male and female physical education teacher candidates [t (120) = 2.04, p < .05]. More female teacher candidates agreed with the principle that a physical education teacher should not insult his/her students, compared to male teacher candidates.
Table 4
Descriptive Statistics on the Opinions of Physical Education Teacher Candidates concerning the Professional Codes of Ethics based on their Genders
Item
No
Gender
Mean
s
t
p
Item
No
Gender
Mean
s
t
P
1
M
4.79
.525
.231
.817
17
M
4.78
.650
.342
.733
F
4.81
.486
F
4.81
.391
2
M
4.24
.909
.255
.799
18
M
4.47
.818
1.48
.141
F
4.20
.889
F
4.67
.625
3
M
4.49
1.04
1.29
.198
19
M
4.65
.767
.738
.462
F
4.24
1.03
F
4.75
.630
4
M
4.68
.664
.847
.399
20
M
4.68
.761
.368
.714
F
4.77
.421
F
4.63
.782
5
M
4.75
.547
.631
.529.
21
M
4.68
.642
.915
.362
F
4.81
.527
F
4.79
.676
6
M
4.71
.588
1.11
.266
22
M
4.61
.810
2.15
.033*
F
4.83
.624
F
4.87
.525
7
M
4.61
.637
.521
.603
23
M
4.71
.676
1.117
2.66
F
4.55
.737
F
4.83
.472
8
M
4.68
.598
.471
.639
24
M
4.75
.640
2.11
.037*
F
4.73
.531
F
4.93
.316
9
M
4.71
.513
.518
.605
25
M
4.65
.730
1.92
.056
F
4.65
.751
F
4.85
.408
10
M
4.82
.419
.299
.766
26
M
4.42
.848
1.23
.219
F
4.79
.539
F
4.59
.642
11
M
4.46
.958
1.43
.128
27
M
4.78
.583
.052
.959
F
4.69
.683
F
4.77
.510
12
M
4.45
.972
1.93
.055
28
M
4.57
.797
1.59
.113
F
4.73
.638
F
4.77
.586
13
M
4.41
.796
.861
.391
29
M
4.46
.851
1.28
.203
F
4.53
.680
F
4.65
.693
14
M
4.50
.728
.673
.502.
30
M
4.65
.671
2.04
.044*
F
4.59
.609
F
4.85
.408
15
M
4.39
.701
1.76
.097
31
M
4.76
.589
.295
.769
F
4.59
.574
F
4.73
.604
16
M
4.67
.727
1.36
.173
32
M
4.78
.671
.045
.964
F
4.81
.441
F
4.77
.586
df = 120 NMale = 73 NFemale = 49 N = 122 P* < .05
The averages regarding the opinions of physical education teacher candidates concerning the professional codes of ethics based on their classes have been given in Table 5. As seen in Table 5, a noteworthy difference was observed in three items as a result of the unrelated t test conducted among the averages regarding the opinions of physical education teacher candidates based on their classes, while no significant differences were seen in other items.
While freshman students agreed with the principle stating “a physical education teacher must take in consideration the mental, emotional, and social developments of students into consideration along with their physical skills while evaluating their success” (C1) at a level of ( = 4.73), the level of agreement by senior students was ( = 4.91). There was a significant statistical difference between the averages of the opinions of physical education teacher candidates in freshman and senior classes [t (120) = 2.09, p < .05]. More teacher candidates in senior classes agreed with the principle that a physical education teacher should take in consideration the mental, emotional, and social developments of students into consideration along with their physical skills while evaluating their success, compared to those in freshman classes.
While freshman students agreed with the principle stating “a physical education teacher must evaluate the success of students objectively” (C16) at a level of ( = 4.64), the level of agreement by senior students was ( = 4.86). There was a significant statistical difference between the averages of the opinions of physical education teacher candidates in freshman and senior classes [ t (120) = 2.27, p < .05]. More teacher candidates in senior classes agreed with the principle that a physical education teacher should evaluate the success of students objectively, compared to those in freshman classes.
While freshman students agreed with the principle stating “a physical education teacher must attach more importance on the health and security of his/her students than sportive success” (C18) at a level of ( = 4.46), the level of agreement by senior students was ( = 4.71) There was a significant statistical difference between the averages of the opinions of physical education teacher candidates in freshman and senior classes [ t (120) = 2.09, p < .05]. More teacher candidates in senior classes agreed with the principle that a physical education teacher should attach more importance on the health and security of his/her students than sportive success, compared to those in freshman classes.
Table 5
Descriptive Statistics on the Opinions of Physical Education Teacher Candidates concerning the Professional Codes of Ethics based on their Classes
Item
No
Class
Mean
s
t
p
Item
No
Class
Mean
s
t
p
1
Freshman
4.73
.574
2.09
.038*
17
Freshman
4.80
.632
.191
.849
Senior
4.91
.354
Senior
4.78
.417
2
Freshman
4.22
.946
.092
.927
18
Freshman
4.46
.855
2.09
.039*
Senior
4.23
.821
Senior
4.71
.501
3
Freshman
4.35
1.11
.519
.605
19
Freshman
4.73
.660
.796
.428
Senior
4.45
.911
Senior
4.63
.798
4
Freshman
4.71
.649
.264
.793
20
Freshman
4.59
.911
1.57
.119
Senior
4.73
.443
Senior
4.78
.417
5
Freshman
4.76
.585
.408
.684
21
Freshman
4.69
.748
.694
.489
Senior
4.80
.453
Senior
4.78
.467
6
Freshman
4.77
.665
.328
.743
22
Freshman
4.71
.745
.212
.832
Senior
4.73
.419
Senior
4.73
.681
7
Freshman
4.63
.689
.867
.388
23
Freshman
4.71
.689
1.36
.174
Senior
4.52
.657
Senior
4.84
.419
8
Freshman
4.67
.640
.924
.357
24
Freshman
4.77
.623
1.54
.125
Senior
4.76
.431
Senior
4.91
.354
9
Freshman
4.68
.657
.099
.921
25
Freshman
4.71
.708
.614
.541
Senior
4.69
.552
Senior
4.78
.467
10
Freshman
4.77
.531
1.18
.240
26
Freshman
4.46
.870
.572
.568
Senior
4.86
.340
Senior
4.54
.585
11
Freshman
4.56
.884
.138
.891
27
Freshman
4.73
.640
1.22
.224
Senior
4.54
.853
Senior
4.84
.363
12
Freshman
4.51
.901
.862
.390
28
Freshman
4.61
.815
.730
.467
Senior
4.65
.749
Senior
4.71
.544
13
Freshman
4.40
.751
.966
.336
29
Freshman
4.61
.815
1.39
.167
Senior
4.54
.751
Senior
4.41
.747
14
Freshman
4.53
.738
.031
.975
30
Freshman
4.75
.535
.297
.767
Senior
4.54
.585
Senior
4.71
.501
15
Freshman
4.39
.713
1.88
.063
31
Freshman
4.78
.617
.845
.400
Senior
4.60
.536
Senior
4.69
.552
16
Freshman
4.64
.743
2.27
.025*
32
Freshman
4.78
.717
.240
.811
Senior
4.86
.340
Senior
4.76
.480
df = 120 N Freshman = 76 N Senior = 46 N = 122 P* < .05
The averages regarding the opinions of the physical education teacher candidates based on their schools have been given in Chart 7. As seen in Chart 7, a noteworthy difference was observed in two items as a result of the unilateral variance analysis conducted among the averages regarding the opinions of physical education teacher candidates based on their schools, while no significant differences were seen in other items.
A difference of .05, which was worth noting, was found among the averages as a result of the variance analysis conducted on the averages of the points concerning agreement levels with the principle stating “a physical education teacher must not display an action based on violence towards his/her students” (C6) [F (2, 119) = 3.11, p < .05]. As a result of the LSD test, which was applied in order to find the group that created the difference, a significant difference was observed between the opinions of Hacettepe University and Gazi University students. While the students of Hacettepe University agreed with the principle stating “a physical education teacher must not display an action based on violence towards his/her students” (C6) at a level of = 4.96, those of Gazi University stated that they agreed with this principle at a level of = 4.64.
A difference of .05, which was worth noting, was found among the averages as a result of the variance analysis conducted on the averages of the points concerning agreement levels with the principle stating “a physical education teacher must reward proper behavior of students” (C15) [F (2, 119) = 5.51, p < .05]. As a result of the LSD test, which was applied in order to find the group that created the difference, a significant difference was observed between the opinions of Ankara University students and Hacettepe University and Gazi University students. While the students of Ankara University agreed with the principle stating “a physical education teacher must reward proper behavior of students” (C15) at a level of ( = 4.15), those of Hacettepe university and Gazi University stated that they agreed with this principle at levels of ( = 4.61) and ( = 4.57), respectively.
Table 6
Descriptive Statistics on the Opinions of Physical Education Teacher Candidates concerning the Professional Codes of Ethics based on their Schools
Item
No
School Averages
F
P
Item
No
School Averages
F
P
1
2
3
1
2
3
1
4.76
4.82
4.78
.162
.850
17
4.73
4.84
4.75
.514
.600
2
4.26
4.14
4.37
.756
.472
18
4.61
4.57
4.46
.322
.725
3
4.26
4.40
4.46
.270
.764
19
4.69
4.70
4.68
.006
.994
4
4.73
4.71
4.71
.004
.996
20
4.53
4.67
4.75
.548
.579
5
4.76
4.78
4.78
.005
.995
21
4.80
4.70
4.71
.238
.789
6
4.96
4.64
4.84
3.11
.048*
22
4.92
4.60
4.78
1.94
.148
7
4.53
4.59
4.62
.117
.889
23
4.69
4.73
4.87
.798
.453
8
4.69
4.68
4.75
.134
.875
24
4.80
4.82
4.84
.031
.969
9
4.65
4.70
4.68
.058
.944
25
4.73
4.70
4.81
.323
.725
10
4.80
4.79
4.84
.106
.900
26
4.46
4.56
4.37
.647
.525
11
4.65
4.50
4.59
.329
.721
27
4.69
4.82
4.75
.612
.54
12
4.62
4.50
4.65
.401
.670
28
4.69
4.65
4.62
.061
.941
13
4.50
4.39
4.56
.603
.549
29
4.61
4.56
4.43
.405
.668
14
4.57
4.53
4.53
.045
.956
30
4.73
4.70
4.81
.379
.692
15
4.61
4.57
4.15
5.51
.005*
31
4.76
4.78
4.68
.274
.761
16
4.65
4.71
4.81
.470
.626
32
4.84
4.78
4.71
.285
.753
df (Between groups: 2, Within groups: 119, Total: 121) P* < .05
N1 = 26 N2 = 64 N3 = 32 N = 122
1 = Hacettepe University 2 = Gazi University 3 = Ankara University.
Discussion and Conclusion
According to the results of the survey, it was determined that physical education teacher candidates in different universities fully agreed with the professional codes of ethics for physical education teachers based on school, gender, and class averages. However, it was observed that they thought differently in some codes of ethics according to these variables.
More female teacher candidates agreed with the principles that a physical education teacher should value the opinions of students during the lesson and should not insult his/her students, compared to male teacher candidates. Again, female teacher candidates agree with the principle that a physical education teacher should not allow tests, measurements, or drug testing that would endanger the health of his/her athlete students, more than male teacher candidates. It may be said that the female teacher candidates approached their students with more tolerance and compassion. Training applications that would ensure that the male teacher candidates think as the female teacher candidates should be included during pre-service education.
Teacher candidates in senior classes agreed with the principles that a physical education teacher should take the mental, emotional, and social developments of students into consideration along with their physical skills while evaluating their success, and that s/he should evaluate the success of students objectively, more than those in freshman classes. In addition, more teacher candidates in senior classes agreed with the principle that a physical education teacher should attach more importance to the health and security of his/her students than sportive success, compared to those in freshman classes. According to this result, it is possible to say that the physical education teacher training program has resulted in positive changes in the opinions of teacher candidates.
The teacher candidates in Hacettepe University agreed with the principle that a physical education teacher should not display an action based on violence towards his/her students, more than those in Gazi University. Applications of these findings would ensure that the teacher candidates in Gazi University become more sensitive with regard to application of violence towards students.
The teacher candidates in Gazi and Hacettepe Universities agreed with the principle that a physical education teacher should reward proper behavior of students, more than those in Ankara University. Activities that would strengthen the knowledge of teacher candidates in Ankara University that rewards constitute an important and useful instrument in education.
The fact that a difference exists among the opinions of physical education teacher candidates concerning some codes of ethics makes us think that training programs for physical education teachers are not effective enough in ensuring that students acquire behaviors related to professional codes of ethics. Physical education teacher candidates are expected to be more sensitive about the professional codes of ethics. Techniques such as case study analysis and role playing may be used in order to provide higher quality training on professional codes of ethics.
It is known that theoretical and practical information concerning ethical dilemmas are increasing and solutions and recommendations for ethical problems are becoming more successful in the formal education received by teacher candidates (Bergem, 1993). Therefore, more efficient ethical training must be included in pre-service education (Fain & Gillespie, 1990; Priest, Krause & Becah, 1999). Some problems may be encountered in applying ethical principles. It is always possible for a teacher to find himself/herself in an ethical dilemma and experience conflicts with the roles s/he has undertaken. In this context, ethical behavior is a hard job. This difficulty will be alleviated if teachers acquire the characteristics that constitute ethical conduct, such as doing the right thing and being fair, honest, and helpful, during the pre-service education (Frank, 1996; Oser & Althof, 1993).
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Author’s note:
Correspondence for this article can be sent by email to oozbek@sports.ankara.edu.tr, by telephone at: +90-312- 221-16-01 or by fax: +90-312-212-29-86;
Submitted by: Scott J. Callan and Janet M. Thomas – Bentley College
Abstract
Salaries paid to high school coaches and team managers have recently generated media and public debate over their justifiability. This research represents an earnings function estimation designed to identify salary determinants for high school football coaches. The theoretical model supporting the analysis builds on models presented in the sports economics literature. To conduct the empirical estimation, we used salary, human capital, performance, and institutional data for coaches of Class 4A and Class 5A 11-man high school football programs in Texas (N = 95). Our results indicate that the determination of overall coaching compensation is significantly affected by human capital investment, measured through experience; by job performance, captured in winning percentage; and by school characteristics, such as location and stadium size.
Pay and Performance: An Examination of Texas High School Football Coaches
Over the past decade, economic investigations of professional sports teams—particularly pay-for-performance studies—have become increasingly prevalent. This emerging research trend has evolved in part because of the broad applicability of economic principles to sporting contexts and also because of the increasing availability of performance and salary data for professional sports participants. Although it has not always been the case, reliable data for selected amateur sports, such as NCAA golf, are also starting to become available, allowing researchers to apply economic reasoning to these varied and important sports environments. (Examples are Callan and Thomas, 2004, 2006, which are investigations of the determinants of success in amateur golf that employed two different samples of NCAA golfers.)
From a theoretical perspective, economic research on sports salaries and performance builds on human capital theory, as first suggested by Becker (1964). Critical to this theory is the belief that education and experience play a significant role in the determination of a worker’s performance and earnings. Simply stated, investments in human capital, such as education, training, and work-related experience, are expected to positively influence compensation.
As for the empirical testing of these theoretical models, most salary investigations within the professional sports literature have focused on individual players as opposed to coaches or managers. It is also the case that most used an earnings function model similar to the one developed by Scully (1974), who studied salary determinants for Major League Baseball players. Consistent with Becker’s (1964) fundamental hypothesis, Scully’s model assumes that a professional baseball player’s development of human capital and skill are critical determinants of his earnings. Since Scully’s original work, numerous studies have adapted his model to other sports settings. For example, Jones and Walsh (1988) examined salary determination for players in the National Hockey League, and Hamilton (1997) did the same for players in the National Basketball Association.
Despite the accumulating research on players’ salaries in various sports, we know of only two papers that adapted Scully’s (1974) original model to an examination of the earnings of team managers or coaches. One is a study by Kahn (1993), and the other is an investigation conducted by Humphreys (2000). A brief overview of each follows.
Kahn (1993) used 1987 data for professional baseball teams to estimate an earnings function for team managers, which in turn was used to analyze managerial quality. Following human capital theory, Kahn’s model specifies earnings as the natural log of manager salary and includes the following as explanatory variables: years of managerial experience; lifetime winning percentage; and a binary variable to control for league (i.e., American or National). Kahn asserts that there are at least two reasons why experience is expected to have a positive effect on earnings. Specifically, more years of experience should reflect (a) greater skills, developed through on-the-job training, and (b) longevity, based on relatively high-quality management ability exhibited over time. Winning percentage captures team performance or success, which also should positively affect earnings, and the binary league variable controls for any league-specific differences in the demand for managerial quality. As expected, Kahn’s results showed that a manager’s experience level and career winning percentage have significant and positive effects on salary, although the league variable was not found to be statistically significant.
Humphreys (2000) used Division I NCAA basketball program data for the 1990–1991 academic year to test for possible gender-based differences in compensation among head basketball coaches. Similar to Kahn’s model, Humphreys’s earnings function defines the dependent variable as the log of annual base salary. Two groups of hypothesized salary determinants are specified: a set of coach characteristics and several control variables to represent the institution where each coach is employed. For the coach characteristics, Humphreys included a dummy variable for gender; experience, in years, to represent investment in human capital; and career winning percentage to measure job performance. In accordance with conventional human capital theory, both experience and winning percentage were assumed to have a positive effect on salary. The institution-specific control variables were intended to capture potential demand-side influences on a coach’s earnings. Included among these were total student enrollment, ticket revenues, and school location. The underlying hypothesis was that greater demand for basketball entertainment, which can be proxied by higher enrollment and larger revenues, should positively influence a coach’s salary.
Humphreys’s empirical estimation across several variations of his model found neither gender nor experience to be significant. However, the results did suggest that performance (measured through career winning percentage) positively affects earnings. Humphreys believed that a high correlation between performance and experience in his sample likely explained the lack of significance found for the experience parameter. Among the institutional control variables, Humphreys found that total enrollment, participation in Division IA games, and ticket revenues exhibited consistently positive effects on collegiate basketball coaches’ salaries.
Clearly, the studies by Kahn (1993) and Humphreys (2000) have helped to identify some of the factors responsible for manager or coach salaries at the professional and collegiate level, respectively. However, to our knowledge, no analogous earnings function estimations exist for noncollegiate amateur coaches, leaving many questions unanswered.
At least until recently, the primary reason for this lack of research on noncollegiate school sports was, apparently, limited or nonexistent data. However, reliable data on high school football in some regions of the United States have now become available. That such a turn of events is timely is evidenced in part by recent media attention to high school coaches’ salaries, particularly in comparison to teachers’ and other school administrators’ salaries. Some journalists report on the relatively high salaries earned by high school football coaches, particularly in the southern and western United States, where high school football is markedly more important to local communities than in other regions (Jacob, 2006; Associated Press, 2006). Others, such as Abramson (2006), counter with a different perspective about coaches’ earnings, referring to long hours worked, particularly in so-called football states like Texas, Florida, and Georgia.
A related issue raised by the media is the extraordinary level of monetary investments made in some high school football programs, an observation that some find particularly striking in the face of funding cuts for educational resources and programs. In a recent issue of a national newspaper, Wieberg (2004) reported on multimillion-dollar projects in Texas, Georgia, and Indiana to build state-of-the art high school football stadiums. This trend, he argued, arises from a competitive race involving high-end facilities and highly paid coaches that has trickled down from the college level. In some states, such competition arises from open enrollment policies, under which schools literally compete for students to preserve their state funding (which is linked to enrollment). Schools also compete for a strong fan base to generate revenues to help support the costs of football programs—including elevated salaries for coaches, some reportedly reaching six figures. Such activity, which is consistent with the demand-side effects on salary suggested by Humphreys (2000), identifies another motivation for exploring the issue empirically.
The present research addressed the critical issues by empirically examining salary determinants for a sample of high school football coaches in Texas. There were a number of reasons for using Texas as the context of the analysis. First, high school football is enormously popular in Texas, and schools there invest heavily in football programs. These observations translate to a favorable opportunity to study demand-side salary determinants for coaches along with the usual human capital factors. Second, and perhaps not unrelated to the first reason, the necessary sample data to conduct an empirical estimation of earnings have become available for the state. Third, because Texas high school football is nationally recognized, we anticipated that our findings concerning Texas coaches would both call attention to underlying issues and stimulate new research on salary determination for those who coach in other parts of the country and in other high school sports.
Method
Sample
Reflecting both data availability and our motivation to capture possible demand-side factors in our model, the sample for this study was 95 head coaches at Class 4A and Class 5A Texas high schools during the 2005–2006 football season. Oversight of high school football in Texas is provided by the University Interscholastic League (UIL). The UIL is a nonprofit organization with a purpose to “organize and properly supervise contests that assist in preparing students for citizenship” (About the UIL, n.d., ¶3); extracurricular activities outside athletics also fall within UIL’s purview. The UIL organizes Texas high school football contests based on schools’ geographic locations and enrollments. It divides football programs into 6-man and 11-man classifications. Most small schools (i.e., those with fewer than 100 enrolled students) participate in 6-man football, but the majority of Texas high school football programs are 11-man programs. The sample for this study was drawn from 11-man programs only.
Giving greater context for our analysis, table 1 presents the breakdown by classification of the 1,033 11-man high school football programs in Texas. The UIL identifies 32 geographic districts within Texas. The average number of football teams within each district ranges from 5.13 in Class 1A, to 7.53 and 7.69, respectively, in the larger 4A and 5A classes. The data indicate that significant enrollment differences exist across these various conferences. Classes 4A and 5A comprise the largest schools, those with enrollments as high as 2,084 and 5,852, respectively.
Table 1
2008–2009 Season Data for Texas High School 11-Man Football Teams, by Class
Class
Number of districts with football programs in the class
Number of schools with football programs
Average number of schools per district
Minimum enrollment
Mid-point enrollment
Maximum enrollment
1A
32
164
5.13
69.00
134.00
199.00
2A
31
205
6.61
201.00
314.75
428.50
3A
32
177
5.53
222.00
599.00
976.00
4A
32
241
7.53
533.00
1,308.50
2,084.00
5A
32
246
7.69
1,515.00
3,684.00
5,852.00
Note. Conference 2A spans 32 districts, but no school in District 24 has an 11-man football program. From “Alignments (updated for 2008–2010),” n.d., retrieved June 14, 2008, from http://www.uil.utexas.edu/athletics/football/
Measures
For each coach in our sample, we collected earnings data for the 2005–2006 academic year from a Dallas Morning News article, creating our empirical model’s dependent variable, SALARY (Jacob, 2006). According to a recent article in the popular press, a Class 4A or Class 5A head coach typically works 70–100 hr per week and is under contract for a 226-day work year (Texas Twist, 2006). Some coaches also teach, and some hold administrative positions such as athletic coordinator or athletic director. Our empirical model defined the variable ADMIN as a binary variable equal to 1 for a coach having administrative responsibilities or to 0 otherwise. We expected that coaches with administrative positions in addition to coaching responsibilities would earn higher salaries than those with coaching responsibilities only. Hence, we anticipated that the estimated parameter associated with ADMIN would be positive.
To capture each coach’s investment in human capital, we defined two distinct measures, GAMES and ROOKIE. Because the number of contests each team plays annually is fairly consistent, the GAMES variable was allowed to serve as a proxy for each coach’s cumulative head coaching experience in years (the data we would have preferred as our measure of human capital investment, had they been available). The GAMES variable actually measured the cumulative number of games for which an individual had acted as a head coach. Increases in this human capital variable were expected to have a positive influence on coaches’ salaries. The binary variable ROOKIE equaled 1 for a coach who was a rookie head coach (i.e., had no more than one year’s experience) and 0 for more experienced coaches. We anticipated that the parameter on this variable would be negative, reflecting the market’s ability to pay a rookie coach a lower salary than a veteran coach.
The sports economics literature suggests that in addition to experience level, how able a coach is, reflected in job performance, is an important determinant of compensation. Both Kahn (1993) and Humphreys (2000) used a coach’s career winning percentage to capture job performance. Following their approach, we defined a variable, WP, to measure the overall career winning percentage for each coach in our sample. If a coach’s winning percentage increased, we hypothesized, his salary will be higher, holding all other factors constant.
We further theorized that a coach’s salary would be influenced by demand-side characteristics (Humphreys, 2000), which would be linked to attributes of the high school employing the coach. One such characteristic was student enrollment, which we measured in the ENROLL variable, obtaining data from PigskinPrep.com, a website devoted to Texas high school football. (PigskinPrep.com’s Class 4A data was found at www.texasfootballratings.com/4ADistEnrollmentRealign.html and its Class 5A data at www.texasfootballratings.com/5ADistEnrollmentRealign.html). Schools with larger enrollments are expected to pay their coaches higher salaries, so we expected to find a positive relationship between ENROLL and SALARY.
Moreover, because Texas football has a following that extends beyond the student body, it was important to include some measure of community demand for the sport. Indeed, H. G. Bissinger (1990) suggests, in his best-selling book Friday Night Lights, that football in Texas is a community event. Therefore, we included the variable STADIUM in our empirical model to measure seating capacity at the facility where each coach’s school played its home games; the Texas High School Stadium Database (www.texasbob.com/stadium) provided the measures for each stadium. STADIUM was intended to capture a community’s market demand for high school football. Adapting Humphreys’s (2000) logic to our model, we expected that high school teams playing in larger stadiums would generate more revenue than those playing in smaller facilities, yielding more funds with which to compensate their head coaches, and hence we expected STADIUM to be positively related to SALARY. While we viewed stadium capacity as a reasonable proxy, we would have preferred including ticket revenues directly in our model, as Humphreys did, had such data been available for the individual Texas high schools. UIL does track football gate receipts for Texas high schools as a group. They totaled $1,102,798 for the 2005–2006 season, more than any other high school sport in Texas generated (West, Davis, and Company, 2008).
Lastly, following Humphreys (2000) we included a location-specific variable, DALLAS, in our model. The measure is a binary variable equal to 1 for a school located in the Dallas school district or to 0 otherwise. The variable controls any salary differences associated with location in the Dallas urban district. Earnings levels in urban districts may differ from those in other districts, due to differences in cost of living and/or population. However, since the relative magnitude of any such effect was not known a priori, the qualitative relationship between SALARY and DALLAS could not be predicted.
Procedures
To estimate the earnings function for each head coach in the sample, we used multiple regression analysis to examine the relationship between earnings and the defined human capital investment measures, job performance, and demand-side characteristics. As the literature suggests is typical, we transformed the dependent variable, SALARY, by natural logs. This transformation meant that the effect of each explanatory variable on earnings could be interpreted as a percentage change.
Results and Discussion
Fundamental statistical analysis was used to describe the variables in our data set. Table 2 presents the basic descriptive statistics for the sample of 95 Class 4A and Class 5A head football coaches. Note that, on average, a coach in this sample earned slightly more than $82,000 per year, and that 9 out of 10 coaches performed some administrative duties. The average coach had participated in approximately 107 games and achieved an overall career winning percentage of 53.41. Because a typical season consists of approximately 10 games, the mean value of 106.8 for GAMES suggests that the average coach in our sample had over 10 years of head coaching experience. Only 7% of the coaches were rookies.
Regarding institution-specific characteristics, the mean value for school enrollment was 2,310 students, and the average high school stadium seated 10,963 fans. The difference between the two measures indicates that demand for Conference 4A and 5A football extends well beyond the student body to the larger community. We also observed that 20% of coaches in the sample were employed at schools in the Dallas school district.
Table 2
Basic Descriptive Statistics for Class 4A and Class 5A Head Coaches (N = 95)
VariableMeanStandard DeviationMinimumMaximum
SALARY
82,179.00
10,457.00
50,117.00
106,044.00
GAMES
106.80
89.67
10.00
401.00
ROOKIE
0.07
0.26
0.00
1.00
WP
53.41
17.30
5.00
84.00
ADMIN
0.91
0.29
0
1.00
STADIUM
10,963.00
3,795.00
3,500
21,193
ENROLL
2,310
849.12
1,076
5,652
DALLAS
0.20
0.40
0.00
1.00
Table 3 presents the multiple regression estimates for our hypothesized earnings function model. (Several model specifications were estimated; overall results for the alternative model specifications did not differ significantly from the results presented in table 3.) On the basis of the adjusted R-squared statistic, our regression model explains over 58% of the variability in the natural log of earnings. The overall fit of our model compares favorably with those presented by other researchers. Each regression model presented by Kahn (1993) and Humphreys (2000) explained less than 50% of the variability in, respectively, professional coaches’ salaries and collegiate coaches’ salaries.
Table 3
Regression Model Parameter Estimates (Dependent Variable = Natural Log of Salary)
Determinant
Parameter estimate
Intercept
11.11†
Human capital variables
GAMES
3.96 E-04†
ROOKIE
-0.09**
Job Performance variable
WP
8.88 E-04†
Institution-specific characteristics
ENROLL
2.94 E-05**
STADIUM
3.55 E-03†
DALLAS
-0.17†
Other factors
ADMIN
0.04
F-statistic
19.81 (p value < 0.001)
R-squared
61.45
Adjusted R-squared
58.34
* p < 0.05, assuming a one-tailed test of hypothesis for ENROLL and two-tailed tests elsewhere. ** p < 0.01, assuming a one-tailed test of hypothesis for GAMES and two-tailed tests elsewhere. † p < 0.10, assuming a one-tailed test of hypothesis for WP and STADIUM.
Turning attention next to the model’s individual parameter estimates, we made a series of important observations, starting with the two measures of human capital investment. First, as anticipated, the algebraic sign on the ROOKIE parameter was negative, meaning that a coach with no more than 1 year of experience received less compensation than veteran coaches. On average, the difference was approximately 9%. Second, the estimated directional effect for a coach’s level of experience, measured through the GAMES variable, was consistent with expectations. Specifically, we found that GAMES had a statistically significant positive effect on a coach’s salary. Holding all other factors constant, each additional year of coaching experience increased salary by, on average, approximately 0.4 percentage points. (We assumed that 10 games represented about 1 year of play; the GAMES parameter estimate hence indicates that each additional game coached translated to a salary increase of about 0.04%, a year’s worth of games thus representing 10 times that salary increase, or 0.4%.) In contrast Kahn’s (1993) investigation of Major League Baseball managers showed that each additional year of experience in professional ball increased a manager’s salary by 2.35%. Humphreys’s (2000) investigation of NCAA basketball coaches did not find the analogous effect on salary to be statistically significant. He argued that a high correlation (0.60) between career winning percentage and years of experience most likely produced the insignificant result for the latter variable. The correlation coefficient between GAMES and WP in our model was markedly lower (0.46).
Holding constant a coach’s investment in human capital, we obtained further results indicating that a coach’s job performance, measured by WP, has a statistically significant positive effect on compensation (a one-tailed test was used). Qualitatively, this result is consistent with those presented by Kahn (1993) and Humphreys (2000). The specific estimated value suggested that an increase of 10 percentage points for WP increased a coach’s salary by approximately 0.9%. Clearly, this finding suggests that winning is important in high school football. However, the common sports adage “Winning is everything” seems an overstatement, at least in the context of how high school football coaches’ salaries are determined.
Quite predictably, our results also indicate that demand-side factors are relevant to the determination of coaches’ overall compensation. For two of the demand-side, institution-specific variables, STADIUM and ENROLL, each of the obtained parameters had the predicted positive sign. Using a one-tailed test, the parameter on STADIUM was statistically significant at the 10% level. This suggests that coaches at schools with larger stadiums, and hence greater demand for high school football, receive higher compensation than those at schools with smaller stadiums. The parameter on ENROLL was positive and statistically significant on the basis of a two-tailed test. As expected, then, larger schools tend to compensate coaches at higher rates than do schools with relatively fewer students. The specific estimated value implies that for every additional 100 students enrolled in a school, its football coach’s salary is about 0.29% higher. The underlying premise is that demand for football games is greater when the student body is larger.
The algebraic sign of the parameter on the urban location variable, DALLAS, was negative and statistically significant at the 1% level. This finding differs from Humphreys (2000), who in his study of NCAA basketball coaches did not find the urban location variable to be significant. It might be the case that the result in our model is specific to the Dallas, Texas, area and cannot be generalized to other urban areas. In any case, we can say that the subsample of Texas high school coaches employed by the Dallas school district earned about 17% less than their counterparts in other districts. This negative effect might reflect a larger population of available coaches in the area, which would mean greater competition for available positions and hence lower salaries. It might also be a function of the relatively low cost of living in Dallas, suggested by consumer price index levels for Dallas versus other areas (U.S. Department of Labor, 2008).
Finally, while the parameter on ADMIN had the expected sign, the finding was not statistically significant. This result may be due to the fact that over 90% of the head coaches in our sample held some type of administrative position in addition to their regular coaching duties. The resulting lack of variability in this measure may be responsible for its insignificance in our earnings function.
Conclusion
It is well documented in the sports economics literature that, holding ability constant, a player’s investment in human capital and his overall performance contribute significantly to the determination of overall compensation. Building on these findings, recent research in sports economics has applied earnings function analysis to an examination of salaries paid to professional and collegiate team managers and coaches. Although this segment of the sports literature is still in its infancy, thus far the empirical findings are generally consistent with those for players. That is, investments in human capital and job performance seem to be significant determinants of managers’ and coaches’ salaries, just as they are of players’ salaries.
In this research study, we extended the analysis of sports managers’ and coaches’ salaries to the noncollegiate amateur level, using a sample of Texas high school football head coaches employed during the 2005–2006 season. Following the approach used in investigations of professional sports, we modeled and estimated an earnings function, using conventional regression analysis. Our model specified a series of potential salary determinants, including human capital measures, a performance variable, and institution-specific demand-side factors.
Our statistical findings indicate that coaches’ salary determinants at the high school level are qualitatively consistent with those identified in the literature for professional and collegiate coaches. Specifically, a high school coach’s development of human capital was shown to be a statistically significant determinant of his salary. Moreover, a coach’s performance or ability to win games, as measured by career winning percentage, also affected his earnings. Lastly, consistent with findings presented by Humphreys (2000), we found that demand-side, institution-specific influences such as the size of the fan base can affect a coach’s compensation.
Taken together, the results of this research, we believe, make an important contribution to the literature examining compensation paid to sports participants, because they broaden its scope to include coaches at the high school level. The findings are timely, as well, given recent media attention to coaching salaries and the associated debate about rising investments in high school sports programs concurrent with funding cuts for education. We are hopeful that, as new data become available, other researchers will seek to validate our findings in other locations and for other high school sports throughout the country. This in turn could help stimulate important dialogue about the level of compensation for coaches relative to other educational professionals and whether that compensation appropriately rewards experience and performance.
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