ISSN: 1543-9518

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

Tim B. Swartz, Adriano Arce and Mohan Parameswaran

 

Abstract

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

INTRODUCTION

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

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

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

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

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

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

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

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

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

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

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

CAREER TRAJECTORIES IN SOCCER

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

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

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

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

 

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

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

Formula

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

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

Figure 1

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

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

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

ASSESSING VALUE  OF  DRAFT POSITION

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Figure 2

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

DISCUSSION

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

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

Figure 3

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

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

APPENDIX

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

 

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

 

 

REFERENCES

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

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

2017-11-02T13:56:36-05:00June 13th, 2013|Contemporary Sports Issues, Sports Management|Comments Off on Assessing Value of the Draft Positions in Major League Soccer’s SuperDraft
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An Analysis of Weight Management and Motivation of Former and Present High School and College Football Players

Mark Still, Ed.D

 

ABSTRACT

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

Introduction

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

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

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

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

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

Weight Management

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

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

Motivation

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

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

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

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

Methods

Selection of Participants

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

Instrumentation

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

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

Procedures

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

Statistical Analysis of Data

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

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

RESULTS

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

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

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

DISCUSSION

Research Discussion One

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

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

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

Research Discussion Two

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

Research Discussion Three

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

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

Research Discussion Four

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

Research Discussion Five and Six

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

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

CONCLUSION

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

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

APPLICATIONS IN SPORT

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

Tables

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Conrad L. Woolsey, Joe Mannion, Ron D. Williams Jr, William Steffen, Mara S. Aruguete, Marion W. Evans, Brandon D. Spradley, Bert H. Jacobson, William W. Edwards, Weston S. Kensinger, Niels C. Beck

 

ABSTRACT

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

Introduction

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

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

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

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

Neuropsychological Mechanisms

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

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

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

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

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

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

Eating Disorders among Athletes

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

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

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

Understanding Health Behavior Change

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

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

Diagnostic Statistical Manual-V (DSM-V) updates

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

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

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

Treatment options

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

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

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

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

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

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

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

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2015-01-31T01:09:00-06:00May 8th, 2013|Contemporary Sports Issues, Sports Exercise Science, Sports Studies and Sports Psychology|Comments Off on Understanding Emotional and Binge Eating: From Sports Training to Tailgating
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Student-Athlete Participation in Intercollegiate Athletic Decision-Making: Inclusion through Different Domains of Governance

Eric Snyder

 

ABSTRACT

This investigation focused on literature related to student-athlete involvement and input in intercollegiate athletic governance.  The aim was to develop support for understanding and justifying differences in the level of involvement a student-athlete may have when considering multiple areas of governance. Results revealed that the various claims for and against student involvement should not been seen as mutually exclusive when seeking to understand and justify formal student-athlete involvement in intercollegiate athletic decision-making.  Rather, together they provide a complex lens for analyzing and changing the contributions of student-athletes in different domains of intercollegiate athletic governance.  Athletic administrators and other stakeholders should consider each domain and incorporate student-athletes into their governance process appropriately.

INTRODUCTION

The economic activity produced from consumer interests in intercollegiate athletic contests in America is profound. Schnaars, C., Upton, J., Mosemak, J, & DeRamus, K. (2012) report published in USA Today identified the largest intercollegiate athletic budget for a single institution surpassed 150 million in 2011. Currently, CBS network and Time Warner are paying over 10.8 billion for rights to broadcast the National Collegiate Athletic Association (NCAA) men’s basketball tournament through the year 2024 (Kramer, 2010). As the financial stakes increase within intercollegiate sport, the NCAA and individual institutions continue to create bylaws and policies which will undoubtedly impact a student-athletes experience in higher education.

Because of the power that athletic departments exert on campuses and within their surrounding communities, there is potential for concern by individuals associated with intercollegiate athletics and the way in which the programs operate.  The purpose of this paper is to focus on those persons for whom the universities, corporate entities, the NCAA and sports networks are indebted to for providing entertainment to fans since the first documented intercollegiate athletic event in 1827. Beginning in the early 20th century, the NCAA and other stakeholders have continued to deny student-athletes a voice or place in the governance of college sports in the United States (Branch, 2011).  This investigation will focus on literature related to student-athlete involvement and input in intercollegiate athletic governance.  Moreover, the aim is to develop support for understanding and justifying differences in the level of involvement a student-athlete may have when considering multiple areas of governance.

Initially, the researcher will provide a brief introduction into the historical origins of student-athlete involvement in intercollegiate athletic governance and then present an integrative review and discussion of the literature, with specific focus on the various reasons for and against student involvement in athletic decision-making.  In order to elaborate on this point, one must realize that different perceptions of student-athletes may represent a justification into certain perceptions of existing power holders; (1) student-athletes can be viewed as stakeholders (2) student-athletes can be viwed as consumers, and (3) student-athletes can be viewed as members of the athletic community. The argument will be made that different perceptions of student-athletes and related claims regarding their involvement in intercollegiate athletics do not have to be treated as mutually exclusive.  Instead, researchers, university administrators, corporate sponsors, and athletic personnel should envision through an intricate lens the nature and extent of student-athlete involvement in different domains of intercollegiate athletic governance.

For instance, the notion of a student-athlete as an athletic community member applies more readily to matters of the CHAMPS/Lifeskills program, while claims arguing they are consumers of higher education gain prominence in academic support services. The final portion of the article reveals that student-athlete involvement in intercollegiate athletic governance can be included in different areas of athletic governance (i.e., academic affairs, policy, finance), thus providing a new lens for understanding and/or justifying an increased involvement of student-athletes in intercollegiate athletic decision-making.

Historical View of Student Athlete Involvement in Governance
The student role in governance of sport can be traced historically to the birth of Oxford in 1167 (Smith, 1988). Here, the organizational nature and governance reflected the elite status of the study body.  Sport participation was valued and organized by the affluent. Sports such as boating, cricket, horse racing, hunting, and tennis were all popular as institutions continued to develop well into the sixteenth, seventeenth, and eighteenth centuries.  According to Smith (1988) these sporting events were rarely well-organized and often drew the scorn of university officials. The governance of these early college sporting events resembled Bologna University and their “student university” model where students would organize in a group and control the curriculum and organization of their studies.  However, the difference between Bologna and organized sport was the intention to participate in sport activities rather than scholarship.

A combination of the ease of access to participants within the university and the authority to govern sporting events made way for increased growth and interest in athletic competition.  Student leaders of sporting events were able to name the time, place, stakes, and rules of the contest (Smith, 1988). For this reason, the enthusiasm generated from early competitions in Europe eventually made their way across the pond to both Yale and Harvard.  By the 1840’s Yale and Harvard had established bona fide rowing clubs, the first organized sports clubs in American colleges (Lewis, 1970; Smith, 1988).

Much like their English counterparts, the American college students were the leaders of the intercollegiate athletic movement. As early as the 1780’s participation in horse races, betting on cock-fights, and hunting of wild game were known to exist between students at the College of William and Mary (Smith, 1988). The student culture of the American college was organized with athletic teams and clubs that were beyond the control of university presidents, deans, and faculty (Smith, 1988; Miller, 1987; Watterson, 1988; Thelin, 1996). However, as spectators and interests in sporting events continued, the dominance of students and marginalization of faculty, alumni, and collegiate leaders in sporting decisions began to decline (Smith, 1988). For example: Horse racing and betting at the College of William and Mary was so strong and so much at cross purposes with the goals of the institution that college officials banned students from keeping horses, making races, or betting on those made by others (p. 9).

Later, college presidents within national magazines began to influence the public view of college football through emotive inscriptions of the injuries and abuses of the game (Thelin, 1996). In 1904, it was documented that 20 players were killed during intercollegiate football games (Sack & Staurowsky, 1998). The public outcry over the violence and the addition of Theodore Roosevelt’s concern provoked the first successful of many previously attempted reform efforts (e.g., 1898 Brown University Conference, 1892 Charles Eliot Institutional Control Effort, 1884 Intercollegiate Association of Amateur Athletics of America).  In 1905, the Intercollegiate Athletic Association of the United States formed (IAAUS).  It was not until five years later that this group adopted its current name the National Collegiate Athletic Association.

As important as the creation of the NCAA was to the development of specific sporting rules, the ability to actually govern and gain administrative control of the structure and fiscal portions was not obtained until the 1930’s (Lawrence, 1987).  Prior to this many alumni, athletic directors, and coaches had attempted to garner much of the administrative power from the student body (Thelin, 1996).  An example can be found in 1909 within Yale’s Athletic Association (YAA) which was run by students and alumni: Undergraduate Robert Moses sought to break Walter Camp’s hegemony by creating the Yale Minor Sports Association—an effort that at first bemused, then angered, Camp. To thwart the renegade student movement headed by Moses, Camp called in chips owed to him by campus administrators; the dean of the college tried unsuccessfully to dissuade Moses from his new endeavor (p. 20).

Over the decades, however, continued struggles for power existed.  The commercialized nature of intercollegiate sport had become too profitable for the NCAA, universities, and corporate entities to allow the student body to remain in control.  The addition of academic eligibility, amateurism, and competition rules by the NCAA expanded the lack of student involvement in athletic governance (Thelin, 1996).  Subsequently, much like history of higher education, where the pre-modern experience of the student university in Bologna gradually faded into distant memory with the adoption of the Parisian model, the pre-modern student athletic organizations faded into distant memory with the adoption of the NCAA and its increased membership (Perkin, 2006).

Since the decrease in student-athlete involvement in intercollegiate athletic governance, five significant national studies have been published: (1) the 1929 Carnegie Foundation Study; (2) the 1952 Presidents’ Report for the American Council on Education; (3) George Hanford’s 1974 study for the American Council on Education; and (4) the 1991 Knight Foundation Commission Study (5) 2007 Knight Foundation Commission Study (Thelin, 1996, Knorr, 2004).  Occurring in different decades, each study focused on a specific issue related to intercollegiate athletics. Most important in regards to student-athlete involvement in intercollegiate governance was the 1929 Carnegie Foundation Study which called for restoration of student control (Savage, 1953). Specific issues within the other remaining studies included low graduation rates, lowering of academic entrance requirements for athletes; uncontrolled spending for facilities, escalating compensation for coaches, the manipulation of schedules to accommodate television, and the big-business element continues to drive athletic departments to acquire corporate sponsorships (Knorr, 2004).  Telander (1989) may have been most accurate when he explained that coaches are concerned with winning, athletic directors are concerned with generating revenue, and presidents are concerned with the prestige of the institution. The lack of mention or emphasis on student-athlete development or involvement in governance seems to have been disregarded and besieged by the concern and growth of commercialism.

NCAA and Student Involvement
Prior to the 1980’s the NCAA governed only male sports (Crowley, Joseph, Pickle, & Clarkson, 2006).  The NCAA differed from The Association for Intercollegiate Athletics for Women (AIAW), which was at one time the largest governing organization for intercollegiate athletics in the United States, because the AIAW included student-athletes in its governance process from its inception (Willey, 1996).  Student-athletes were able to serve on committees which were recognized at both the national and regional levels. Voting status concerning competition, eligibility, and financial aid was granted to student-athletes. In addition, student-athletes were allowed to serve on appeal committees to review student-athletes complaints or issues (Hendricks, 2011). In order to stay competitive, the AIAW moved away from these ideals, and, by its demise in 1982, appeared to be strikingly similar to the commercial professional model of the men (Smith, 2010).

Given the lack of regard for student involvement in the reform studies and the collapse of the AIAW; it is not surprising that it was not until eight decades after its inception that the NCAA adopted the first formal inclusion of student-athletes into their governance structure with the association wide formation of the Student Athletic Advisory Committees (SAAC) (Hendricks, 2011). Prior to the SAAC, areas such as academic eligibility, amateurism, health and safety and competition rules had been the regulation purview of the NCAA (Braziel, 1997). The SAAC was formed to review and offer student-athlete input of NCAA activities and legislation.  Its purpose is to ensure that the student-athlete voice was accounted for at all NCAA member institutions (NCAA, 2012).

Eventually the idea of allowing student-athlete representation at the national level led to the creation of SAAC at each NCAA division institution. This suggests that the NCAA recognizes that student-athletes deserve a voice in intercollegiate athletics. However, the limited power of the SAAC is obvious.  In 1995, the National SAAC expressed concern over a proposal set forth by the Oversight Committee of the NCAA Membership Structure (Braziel, 1997). Under the new restructuring model, the NCAA adopted a new voting system. The proposed plan was designed to increase university accountability and simplify the governing process.  However, the SAAC argued that the change destroyed the already restricted voice student-athletes had in the governing process.  Today, the national SAAC consists of 80 members serving on the national Division I, II and III committees (NCAA, 2012). The committee continues to push for an increase in student-athlete involvement as described in a letter written during the late 2000’s by the chair of the Division-I national SAAC (Piscetelli, 2006).

Over the course of history, there has been considerable variability regarding student involvement and input in intercollegiate athletic decision-making. From the early 1700’s when students exercised complete autonomy in regards to sporting events; to the failed reform attempts by administrators, alumni, and faculty during the 19th century; to the development of the NCAA; to the Carnegie Report of 1929 calling for presidents and alumni to return power to the student body; to our current day model with the SAAC.
This historical overview can be used as a source for understanding variations in student-athlete involvement in intercollegiate athletic decision-making.  The literature provides no secure grounds on which to establish a reason or justification for student-athlete inclusion in intercollegiate athletic governance. In the following sections, the paper therefore considers different reason for and against student athlete involvement in intercollegiate athletic governance articulated from a variety of perspectives.

METHODOLOGY

According to Mouton (2001), philosophical analysis is concerned with ‘questions of meaning, explanation, and understanding and such studies are typically aimed at analyzing arguments in favor of or against a particular position. The core of this paper is based on an extensive review of scholarly books and publications via searches of academic literature.  Multiple searches and search strategies were employed addressing the question of student-athlete involvement in intercollegiate athletic decision-making.  This includes searches through; university libraries, database searches included ERIC, Academic Search Premier, and Google Scholar.  Keywords included student-athlete governance, student-athlete participation, student-athlete involvement, student-athlete protests, and student-athlete government. The various searches provided a plethora of resources covering over fifty years of scholarship.

The final selection of sources was driven by theoretical considerations and the aim of the study, whereby only a fraction of the original sources could be utilized.  Preference was given to peer-reviewed journal articles and chapters in books that showcase the debate within the intercollegiate athletic community and directly engage with the question; how student athlete involvement in athletic department decision-making may be justified? The result is a historical-philosophical analysis and discussion of key arguments for and against the involvement of student-athletes in intercollegiate athletic decision making.

Reasons for and against student-athlete involvement in university decision-making will be articulated from a variety of perspectives: (1) student-athletes as stakeholders (2) students-athletes as consumers; (3) student-athletes as members of a community.  This section discusses the various ways in which the case for the formal inclusion of student-athletes in intercollegiate athletic decision-making has been made in the literature.

RESULTS

The power of student-athletes as a political member has been illustrated most recently in the extensive pressures provided through a non-NCAA sponsored organization known as the National College Players Association (NCPA).  The NCPA has been on the front line fighting for student-athlete concerns ranging from: increases in scholarships monies, holding universities responsible for player’s sport-related medical expenses, increased graduation rates, protected educational opportunities for student athletes in good academic standing, elimination of restrictions on legitimate employment, and modification to current transfer rules (NCPA, 2012).  Over the course of 3 years, the NCPA has expanded to include over 15,000 members consisting of both current and former NCAA student-athletes (NCPA, 2012)

The NCPA has successfully collaborated with other external organization (i.e., Knight Commission, Coalition of Intercollegiate Athletics) to pressure the NCAA and its constituents into making reforms by publishing research and exposing issues to media outlets such as CBS, 60 minutes, ESPN, Fox Sports, Sports Illustrated, The Wall Street Journal, the Chronicle of Higher Education, and numerous radio programs (NCPA, 2012).  More recently, the organization collected over 300 Division I football and basketball student-athlete signatures petitioning for a share in NCAA revenues (Zagier, 2011).  While the NCPA continues to support the student-athlete, historical accounts of student-athletes on campus advocating for increased involvement in intercollegiate athletic decision-making has been masked and needs to be revealed.

One of the first documented organized efforts by student-athletes to battle big-time college athletics occurred in the mid 1930’s. The lack of jobs for players, healthy food, and insufficient medical goods influenced the Howard University Bison’s to boycott participation in football games (Fram & Frampton, 2012). In 1937, the University of Pittsburgh undefeated football season resulted in uncertainty and unrest between players and the university (Oriard, 2001).  In this instance, the players organized and demanded compensation of $200 dollars for their participation in the season culminating Rose Bowl. The university disagreed to the terms resulting in players increasing their demands of the institution the following season.  The players believed they should be provided four-year athletic scholarships, accommodations for missed classes, and collective bargaining rights (Fram & Frampton, 2012).

Fast forwarding to the 1992-93 academic year, unified student-athletes at University of Oklahoma demonstrated their power to facilitate change by refusing to practice (Blum, 1993). The collective strategy required the coaches to cancel practice and provide the players a platform to vocalize their dissatisfaction with the team and its coaching staff.   Furthermore, a similar event occurred at Morgan State where school officials canceled the last scheduled football game because they feared that the team would stage a half-time protest to show its disgust of the head coach. In this instance, the team demanded the removal of the head coach, whom they accused of being verbally and physically abusive (Blum, 1993).  The issue was resolved with the firing of the head coach.

A more recent event occurred at University of California, Davis in 2010 where student-athletes silently marched into the institutions gymnasium in order to protest the possible elimination of funding for certain sports teams.  The silent sit-in protest included the gathering of signatures and occupying of the first floor lobby where the Office of Student Affairs was located (Tsan, 2010).  The petition was presented to the Chancellor with hopes to influence the administrations decision. The results were not in favor of the student-athlete when they received news that four of the 27 university sports teams would be cut.  However, a positive of the outcome was those student-athletes who were provided grant-in-aid were still able to receive funding for their remaining years at the institution.

These examples illustrate that student-athletes are cognizant of the potential for collective action on and off the playing fields. Although their efforts have been confined primarily to athletic issues, the precedent for successful collective action has been shown to include a variety of student-athlete concerns. Therefore, the political argument for student-athlete involvement in intercollegiate athletic decision-making exists.

The political argument is centered on the idea that student-athletes are internal stakeholders (i.e., politically significant constituents of intercollegiate athletics).  “Stakeholders are persons or groups that have or claim, ownership, rights, or interests in a business and its activities, past, present, or future (Clarkson, 1995, p 106).”  According to Harrison & Freeman, (1999) addressing the perspective of various stakeholders is socially responsible organizational behavior. Therefore, with democratic governance by stakeholders being commonplace in universities (Morrow, 1998), it remains troubling to think that the NCAA seems to have adopted a more monolithic approach. The NCAA’s influences along with other stakeholders (i.e., sports networks, faculty, corporations, and conference commissioners) have continued to deny student-athletes a legitimate place at the table.  Those stakeholders who currently have a voice must recognize that the athletic culture is composed of competing, internal stakeholders, all of which must be heard and accommodated (Boland, 2005).

Additional research was completed by Thompson (1972) analyzing the political functions and consequences of formally including the general student population into university governance. Thompson (1972) found that when general students are incorporated into the governance process as stakeholders, they are quickly exposed to the complexity of issues, the recognition of the consequences of decisions, and the development of personal commitments.  Consequently, loyalties develop through the inclusion of the governed and in return major impulses are deflated (i.e., student athlete protests or revolts will not occur).

As a result, formal student-athlete involvement in intercollegiate athletic decision-making would provide, on the one hand, an alternative to tactics of coercion through organizations like the NCPA and future disruption or protests by student-athletes.   On the other hand, the inclusions might also moderate the partisan views of other member of the intercollegiate athletic community and thus create less adversarial relationships between the current intercollegiate athletic powers.

Student-Athletes as Consumers
As opposed to the political argument for the involvement of all stakeholders through democratic governance, an additional argument for student-athlete involvement in intercollegiate athletic decision-making can be made with reference to the role and function of student-athletes as consumers of higher education. This case involves different viewpoints of student-athletes as well as intercollegiate athletic departments.  The student-athlete is viewed as a consumer of higher education, whereas, the athletic department and university are viewed as a service provider in a contractual relationship with the student-athlete.  As the service provider makes decisions, the student-athletes experience the consequences.  For that reason, it seems the student athletes should be provided the right to partake in decision-making.

However, student athletes are a diverse group and diversity can be both a strength and weakness to the consumer argument.  Besides gender, student-athletes are diverse economically, racially, socially, and geographically.  These differences can create distinct issues for the internal structure and goals of student-athlete involvement in governance. For example, what do student-athletes desire from the NCAA and athletic departments?  Student-athletes in revenue-producing sports may want increased profit or revenue sharing.  Student-athletes in nonrevenue-producing sports may want increased scholarships.  Women athletics may want equal funding. The diverse individual interests of student-athletes could potentially destroy the consumer argument because the variety of goals associated with the consumer.

Therefore, it is critical that student-athletes in terms of political influence determine at least one common goal in their involvement in governance. As consumers, it seems education would be the most appropriate choice because it remains a commonality among the student-athlete population.

Student Athletes as Members of the Athletic Community
An additional argument first explored by Wolff (1969) argues general student participation in decision making can be justified by virtue of students being members of a community. Without a doubt, the notion of students as full members of the academic community still carries currency in studies that seek to make a case for general student rights to involvement in university decision making (Bergan, 2004; Lizzio, A. & Wilson, K, 2009).  According to Wolff (1969) ‘a community of persons united by collective understandings, by common goals, by bonds of reciprocal obligation, and by a flow of sentiment makes the preservation of the community an object of desire, not merely a matter of prudence.’ This communitarian view of the university can be easily transferred to a communitarian view of intercollegiate athletic departments. Consequently, an argument for inclusion of student-athletes involvement in athletic decision-making through the community domain exists.

However, an argument may exist against student-athletes as full members of an athletic department’s community.  One could argue that student-athletes by definition and in practice are only temporary members of this community, whose commitment to intercollegiate athletics mission may be diminutive. Thus, students are not likely to be personally affected when decisions they have been partial to actually take effect since they will have left campus by then (Zuo and Ratsoy, 1999). Others could point out that characteristically intercollegiate athletic departments are not democratic communities but rather are structured in a fairly rigid professional hierarchy of athletic expertise and seniority.  Therefore, student-athletes are at best, novices and junior members of the intercollegiate athletic community.

Is it appropriate for student-athletes to claims to having an equal voice and equal authority in intercollegiate athletic governance or should their voice be tempered in view of their limited knowledge and experience?  Many of the stakeholders today would argue the student-athletes authority should be weighed against the competencies of other groups within the intercollegiate athletics community; in particular, those of the faculty, coaches, administrators, and corporate entities.  Therefore, the argument is that authority should reside with the credentialed rather than the less expert.  However, Thompson (1972) argues that the involvement by all major groups in governing the university has important benefits, such as a better quality of decisions. In the case of students-athletes, the potential educational benefit of participating in decision-making of intercollegiate athletics should be seen as a means to pursue the educational purposes of the university.

The argument for formal student involvement in intercollegiate athletic decision-making as a means to instill democratic norms and values in students as future citizens carries a strong message.  Active citizenship is one of a number of potentially positive consequences of student inclusion.  Thompson (1972) notes that by widening the circle of participants in decision-making to include others (i.e., student-athletes), the results may reveal positive educational effects in different respects. Student-athlete involvement is not only for the benefit of the student athletes themselves, but it is also likely to improve the quality of decisions and acceptance of decisions. In these regards, the inclusion of students in intercollegiate decision-making contributes to the pursuit of the institutions and the NCAA mission.

DISCUSSION AND APPLICATION

The historical-philosophical debate analyzed in the previous section shows that the meaning and justification of student-athlete involvement in intercollegiate athletic decision-making can be understood with reference to different views of the student-athlete.  These different conceptions provide a means for understanding the nature and extent of student-athlete involvement in different contexts and domains of intercollegiate athletic decision-making. When considering formal student-athlete involvement in the various domains of intercollegiate athletic governance student athletes as stakeholders, consumers, and members of the athletic community claims come to play in various combinations.

Governance of Policy
The involvement of students in intercollegiate athletic decisions dealing with policy involves considerations of students’ expertise both as low-ranking members of the athletic community and users of athletic department and institutional services.  The nature and extent of student-athlete involvement will vary with regard to the setting (academic policy, team policy, department policy, and NCAA policy).  Additionally, the nature of the issues under considerations must be evaluated (e.g., staffing, marketing, compliance, academic affairs).

Governance of Academic and Student Affairs
Extra-curricular involvement in intercollegiate athletics dealing with matters of the Champs/Lifeskills programs, fundraisers, and so forth, offers extensive opportunity for student involvement in decision-making.  Here students are clearly the most interested and affected members of the community; as users of services and facilities for student development, their lived experience offers invaluable expertise in decision-making.  Moreover, as student athletes they have certain rights and responsibilities associated with governing their own lives.  Students acceptance of and support for decisions taken in this domain of governance is particularly crucial and students collective power to demand or reject certain decisions must be seriously taken into account.

Governance of Finance and Planning
A complex combination of different reasons for and against formal student involvement comes into play when considering the nature and extent of student-athlete involvement in  financial decision making. In certain contexts, student-athletes may have been able to carve a niche historically as a political constituency that needs to be consulted and formally involved.  Student-athlete involvement in this domain may engross the recognition of certain participatory rights of students as adults and citizens. However, the increasingly dominant view of student athletes as transient users and consumers indicates that such high-level participation can be only marginal. An example of one scenario where student-athletes may successfully lobby for a seat at the decision-making table would be an issue such as social media monitoring or banning for student-athletes.

CONCLUSION

This illustrative application of different claims and related views of student-athletes proves that they are not exclusive to a specific domain of governance.  Rather, the goal was to provide in combination a heuristic lens for considering student-athlete involvement.  The researcher has outlined the history of student-athlete involvement in university governance and analyzed multiple arguments for and against formal student-athlete involvement.  The task involved a review of the literature and has yielded reasons for and against the consideration of increased student-athlete involvement in intercollegiate athletic decision-making. It has been argued that the various claims for and against student involvement, and related perceptions of students, should not been seen as mutually exclusive when seeking to understand and justify formal student-athlete involvement in intercollegiate athletic decision-making. Athletic administrators, faculty, and other current stakeholders should consider each domain and incorporate student-athletes into their governance process appropriately.

REFERENCES

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Crowley, Joseph N., David Pickle, and Rich Clarkson. 2006. In the Arena: The NCAA’s First Century. Indianapolis, IN: NCAA.

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Knight Commission on Intercollegiate Athletics. (2001). A call to action: Reconnecting college sports and higher education. Miami: Knight Foundation.

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2013-11-22T22:33:55-06:00April 2nd, 2013|Contemporary Sports Issues, Sports Exercise Science, Sports Management, Sports Studies and Sports Psychology|Comments Off on Student-Athlete Participation in Intercollegiate Athletic Decision-Making: Inclusion through Different Domains of Governance
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A Preliminary Investigation of NCAA Division II Compliance Officers

Lance P. Kaltenbaugh, Jennifer Parsons, and Bryce Winters

 

NCAA DII Compliance Officers

 

ABSTRACT
This study examined the position of Compliance Officer at NCAA Division II institutions in the Upper Midwest of the United States. A perceptual and attitudinal scale was used to measure the participants’ responses to the structure that supports their job of NCAA compliance. Results indicated that having an experienced person responsible for compliance was essential. Overall, respondents reported that hiring professionals who have experience in law or a degree in law, such as a Juris Doctorate, was beneficial. Although the respondents reported that the introduction of new or innovative initiatives were welcomed and that their compliance efforts were better than the previous year, more than half of the participants agreed that the athletic department still should use more resources and strategies in fulfilling NCAA requirements. The majority of the Division II Compliance Officers’ surveyed suggested that limited staff and work load were factors which might hinder compliance efforts.  The findings from this study could benefit individuals responsible for maintaining a fair competitive playing field in sport organizations.

INTRODUCTION
The tenuous balance between academics and athletics in higher education has created controversies that date back to the late 1800s (2). Early intercollegiate athletics became so aggressive and dangerous that during the 1905 season, 18 athletes died while numerous others were seriously injured in football alone.  Demonstrating how popular college sport had become, President Theodore Roosevelt demanded reform leading to a set of established rules and the precursor of the modern National Collegiate Athletic Association (19).

The NCAA is a multipurpose organization that governs intercollegiate athletic departments and their student-athletes.  From its inception in 1905, the NCAA has adopted thousands of rules and regulations to protect the student-athlete and prevent unethical advantages (4). Today, the NCAA Manual (2010-2011) continues to have distinct functions that strive to meet specific goals and objectives that directly involve student-athletes and their institutions.

The NCAA monitors three divisions (I, II, III) of athletic competition. Regardless of the type and size of the institution, the NCAA is responsible for addressing issues relating anywhere from academic issues like “Progress Towards Degree” and “Graduation Success Rate” to infractions and eligibility for each sport’s championship segment (21). NCAA rules must be monitored at each member institution and this multifaceted responsibility is handled by the Compliance Officer(s). The most publicized infractions tend to be associated with major revenue producing programs within NCAA Division I institutions (14, 26). Little research has been conducted at either the NCAA Division II or III level examining the role and duties of Compliance Officers. Therefore, a study investigating NCAA Division II Compliance Officers is warranted.

Compliance Issues
NCAA athletic compliance is a complex and often challenging aspect of intercollegiate athletics that all governed Division I, II, and II institutions must follow. Institutions must monitor and enforce athletic habits of student-athletes, coaches and administrators. If a school is held responsible for a violation, it most likely involves a lack of institutional control and monitoring of standards on behalf of the compliance department and athletic administrators (3, 8).

Violations of NCAA bylaws and regulations are varied and can occur in all sports (12).  The aftermath from breaking NCAA rules not only affects the athletic program, but can also tarnish the overall reputation of the institution (5). A study examining NCAA infractions at all divisions between 2005 and 2008 identified the seven most common violations that can occur at an institution or to their student-athletes (22). The most frequent institutional violation was a failure to monitor athletic programs. This type of infraction can be considered the worst to commit because it represents failure for the entire athletic department on all fronts. Furthermore, it shows that the institution as a whole, even beyond the athletic department, has failed to put a proper monitoring system in place (8).

Another frequently reported compliance issue pertains to academic fraud and academic progress. In 2003, the NCAA started collecting data for the Graduation Success Rate (GSR) (21), a measure calculated annually by Division I member institutions to determine athlete graduation rates.  Division II institutions followed a similar methodology, the Academic Success Rate (ASR), but also gave unique consideration to athletes who entered their first year without receiving athletic-based aid. The NCAA also instituted an Academic Progress Rate (APR) to measure academic achievement by teams each term (1).  The goal of the APR is to hold schools accountable for educating athletes throughout their athletic career.  NCAA sanctions can occur if a team’s APR score falls below a certain threshold.  As a condition of NCAA membership, institutions are accountable for reporting these measures of the academic records for their athletic teams (12).

The Position of Compliance Officer
The position of Compliance Officer has emerged to take responsibility for complying with NCAA rules and regulations. The duties of a Compliance Officer, at governed institutions are to educate, monitor, report, and enforce NCAA bylaws (13). A distinct aspect of an intercollegiate Compliance Officer’s position is the need to possess a thorough understanding of legal and NCAA regulations for an association, conference, and institution.

The Compliance Officer position covers a diverse subject area requiring a wide variety of skills and competencies. There is a constant dynamic that compliance officers must navigate as stated by (23) Pierce, Kaburakis, and Fielding (2008) “Coaches need to win, whereas Compliance Officers need coaches to abide by the rules” (p. 87). The compliance coordinator role within the athletics department has continued to expand and has gained the well-deserved respect of coaches, administrators, and student athletes.

Compliance efforts have become the cornerstone of maintaining institutional control within an athletics program. Institutions must be fully aware of what could happen to their well-being if and when an NCAA violation does occur. Therefore, Compliance Officers need to have more of a standard within the workplace including the ability to recognize and understand legal jargon, start a benchmark for the NCAA Divisions, and exercise their authority when appropriate (3, 8).

Purpose of Study
Research on the duties and roles of collegiate Compliance Officers is limited. Although the concept of compliance under the NCAA is not new, the little available research has been done almost exclusively at the Division I level. The purpose of this study is to provide a basic framework for research at the Division II level, thus establishing a justifiable need for this study.  Without research on compliance at the Division II level, it is difficult to advance the field of literature.

At the time this study was conducted, there were no studies addressing compliance issues or the accountability and level of support for Compliance Officers specifically at the NCAA Division II level. A more complete understanding of NCAA Division II Compliance Officers requires investigation. Research on compliance in particular at the Division II level would better represent the NCAA as a whole. Overall, this study has the potential to contribute to the lack of literature with NCAA Division II compliance efforts. This study will establish a basic foundational understanding of Division II Compliance Officers and their responses to the structure that support their job of NCAA compliance.

METHODS
Participants and Procedure
Participants for this study were 14 Compliance Officers from a Division II conference in the upper Midwest of the United States. A total of 11 surveys were returned. The conference has undergone significant expansion in member institutions within the time frame of this instrument’s distribution. Two of the 14 full time member institutions were in the midst of transitioning from affiliation within the National Association for Intercollegiate Athletics (NAIA) to the NCAA Division II.  This change may have affected their ability to respond to the survey.

Study participants completed a series of questions related to their opinions about the structure that supports their job as a NCAA Compliance Officer. Participants were asked  anonymously, and on a voluntary basis, to fill out an online questionnaire through Survey Monkey. The data-collection process was completed in 5 weeks within the 2010-2011 academic year.

Instrumentation
The questionnaire, which was specifically developed for this study, included a total of 15 questions. Responses were recorded on a 5-point Likert-type scale which included: 1 = strongly agree, 2 = somewhat agree, 3 = neither, 4 = somewhat disagree, and 5 = strongly disagree. Each question on the survey addressed NCAA compliance efforts within an athletic department. Face validity was established by asking two athletic department staff members and two graduate students working for the athletic department to judge language of the statements in the questionnaire. The staff members and students were deemed to be a representative of those chosen to participate in the study. To determine the reliability of the instrument, Chronbach’s alpha was employed. The reliability coefficient was determined to be .712, which is within the acceptable range for the interpretation of scores (7). Descriptive data by percentages were used to measure NCAA compliance efforts at Division II institutions.

RESULTS
Demographics
The participants surveyed were Compliance Officers from a NCAA Division II conference in the upper Midwest of the United States. Demographics of the respondents revealed that 64% identified themselves as male, and 36% as female. Participation by type of institution was 64% public and 36% private. Perhaps the greatest difference between NCAA Division I institutions and the Division II level is Compliance Officers often have responsibilities in addition to compliance. In this study, the current position of respondents was, 9% Marketing Directors; 18% Senior Women’s Administrator; 9% Faculty Athletic Representative; 9% Coach; 9% Associate Athletic Director; and 46% Assistant Athletic Director.  Regarding years in position, 64% reported they had been working for the organization for more than 6 years, 9% between 4 and 6 years, 9% subjects between 1 and 3 years, and the rest, 18%, had worked for the organization less than one year.  The total enrollment of the surveyed institutions was 27% had less than 2,500 students; 27% were between 2,501 and 5,000; 27% between 5,001 and 10,000; and 19% between 10,001 and 20,000. The average number of full-time professional staff employed in the athletic department were 18% (0 – 4); 9% (5 – 10); 9% (11 – 20); 64% (21 and more). Description of the participant demographic composition is presented in Table 1.
(Insert Table 1 here)

Descriptive Analysis
Descriptive analysis was conducted to examine Division II Compliance Officers and their responses to the structure that supports their job of NCAA compliance. Respondents were asked if their athletic department has an individual(s) specifically responsible for NCAA compliance. It was reported that 100% indicated that it would be beneficial to have an individual(s) designated full-time to be responsible for compliance within an athletic department.

An inquiry was made to examine what factors respondents thought were important to support their job of NCAA compliance. Of the 11 respondents, 80% indicated that their athletic department was doing a good job of letting the Compliance Officer introduce new, innovative strategies related to NCAA compliance and 100% agreed that NCAA compliance efforts are better today compared to a year ago. Regarding NCAA compliance efforts used within respondent’s athletic department, 50% agreed that an athletic department should be using more compliance resources, strategies, and initiatives and 80% indicate that the university has invested sufficient time and resources to adhere to NCAA compliance rules and regulations.

Overall, 100% of the respondents indicated that the leadership of the athletic department is fully committed to the long-term success of NCAA compliance and initiatives.  When asked if athletic departments should hire professionals who possess experience with NCAA compliance, 100% indicated that it was somewhat important. Although a vast majority of respondents revealed that professionals should possess experience with NCAA compliance, 60% agreed that professionals should possess experience in law (i.e. Juris Doctorate).

Respondents were asked specific questions related to factors that could hinder them from carrying out NCAA compliance rules and regulations. Overall, respondents agreed that operating constraints (67%), support from administration/supervisor (67%), budget (56%), and experience/expertise (68%), were not major factors that hindered them from carrying out NCAA compliance. Conversely, respondents indicated that limited staff (89%) and work load (78%) were key factors that stalled them from successfully carrying out NCAA compliance rules and regulations to the fullest extent. A summary of the results is presented in Table 2.
(Insert Table 2 here)

DISCUSSION
Compliance is an essential component of an athletic department. A Compliance Officer plays a key role for the institution in its efforts to achieve full compliance with all rules and regulations (18). Thus, athletic departments need to acknowledge the importance of evaluating a Compliance Officer’s work environment.  Trends emerged that provided insight into the work environment of a Division II Compliance Officer.

Continuing Education
The NCAA requires that each member institution, regardless of division, have a designated Compliance Officer for its athletic program. In fact, more and more institutions are recognizing that compliance is a significant theme that needs qualified personnel to help manage the rules and regulations that the NCAA has established.  Therefore, Compliance Officers with little or no legal training are often required to interpret the legal language of a complex NCAA manual.

Overall, respondents reported that hiring professionals who have a degree in law, such as a Juris Doctorate (J.D.), is preferred.  This continued education (i.e. J.D.) leads to formal qualifications that provide compliance personnel with the adequate knowledge and skills pertaining to NCAA compliance. Likewise, previous research has shown that at Division I, conference commissioners and fellow administrators perceived potential candidates positively when possessing a J.D. (6). Furthermore, those Compliance Officers who obtained a J.D. to pursue athletic administration were most often hired as Associate Athletic Directors and other executive administrative positions (27).
To emphasize the importance of compliance officers having a J.D., the National Association of Athletics Compliance (NAAC) has developed important benchmarks to standardize the industry of compliance within athletics (3). The NAAC website supports its members by providing educational opportunities to increase their knowledge and skill set, establish opportunities to increase understanding of relevant industry issues, and initiate and disseminate industry research, data and trends to enable compliance personnel to perform better. (17). While athletic compliance efforts evolve and become multifaceted, this study revealed that one Division II conference supported continued education.

Nature of Work
Variables exist that penetrate the offices, meeting rooms, and operational facilities. Athletic departments must be able to identify those variables that should be addressed in any program to improve the work environment. Respondents indicated they had other job duties beyond that of a Compliance Officer.  Limited staff and the nature of the job were cited as factors that could hinder their ability to carry out NCAA compliance. (25) Robinson, Peterson, Tedrick and Carpenter (2003) suggest that excessive job demands due to multi-tasking can impact job satisfaction of NCAA athletic administrators. According to (16) Mueller and Wallace (1996), (28) Tyler and Cushway (1998), and (29) Zhang, DeMichele, and Connaughton (2004), the lack of resources, less rewarding work conditions, lack of support from supervisors and co-workers, and heavy workloads have an effect on an employee’s satisfaction toward their jobs. Thus, an employee’s level of satisfaction may be shaped by multiple features of a particular department and institution.

Although respondents suggested that their institutions were fully committed to the long-term success of NCAA compliance and initiatives, respondents indicated that they would like to see athletic departments use more compliance resources, strategies, and initiatives. Athletic administrators must acquaint themselves with compliance and institutional control and not solely place the responsibility on the Compliance Officer (6). It is imperative that all coaches and administrators work together with their Compliance Officer to manage and adhere to the rules and regulations that have been established by the NCAA.  Athletic departments must be prepared to offer expertly established, promoted, implemented, and evaluated compliance standards (8). But to do this, universities must realize that compliance is not just a component of the NCAA, but an important tool that helps develop the overall makeup of the institution.

CONCLUSION AND FUTURE IMPLICATIONS
The body of knowledge is limited with regard to NCAA Division II compliance positions.  Although this study attempted to provide a limited perspective of these Compliance Officers, broadening this area of research to include additional sport governing bodies would create a greater understanding of the role and job duties of this increasingly important position. With specific regard to NCAA compliance and the need to decipher an often-complicated NCAA manual, future studies might also examine the effectiveness of NCAA compliance training sessions that introduce new and existing strategies that can help all Compliance Officers be more productive and learn with their jobs.  Because the study used a perceptual and attitudinal scale to measure Compliance Officers’ responses to the structure that supports their job of NCAA compliance, answers may change with time as well as organizational structure, individual responsibilities, and positions. Finally, further investigation into the job satisfaction and job related stress related to monitoring NCAA rules and regulations at all divisions is warranted.

APPLICATIONS IN SPORT
Although this study focused on issues of compliance in NCAA Division II institutions, similar governance structures can be found in a variety sport organizations (11).  The need for such offices can be seen through well-publicized controversies that are not limited to any particular level of competition. In an attempt to monitor these issues, sport organizations often devote departments to attempt to regulate and control its member institutions. These structures are put in place to help maintain a fair competitive playing field and require constant monitoring and evaluation.

Policing such a wide array of rules and regulations can prove to be a challenge for sport organizations. The findings of this study suggest that to help meet and maintain NCAA regulations attention should be paid to the position and role of the institution’s Compliance Officer.  By offering avenues for continued education to broaden areas of expertise in compliance and by providing appropriate work related resources, NCAA compliance standards may be more easily met.  The participants in this initial study responded they often have job responsibilities in addition to Compliance Officer.  Not surprisingly, those who responded also suggested institutions might be well served to increase compliance staff in an effort to decrease workload.  Regardless, the qualifications and work environment of those charged with maintaining a balanced field of competition warrants further study.

ACKNOWLEDGEMENTS
None

REFERENCES

  1. Behind the blue disk: Division I academic progress rate (APR). (2009). Retrieved April 4, 2009 from the National Collegiate Athletic Association website: http://www.ncaa.org/wps/ncaa?ContentID=45983&gclid=CKDCwd2P7JkCFSAhDQodMlKhRg
  2. Beyer, J., & Hannah, D. (2000). The cultural significance of athletics in U.S. higher education. Journal of Sport Management, 14(2), 105-132.
  3. Brutlag-Hosick, M. B. (2010). Many NCAA infractions cases move quickly, but complications can slow the process. Enforcement, Retrieved on December 4, 2010 from http://www.ncaa.org/wps/wcm/connect/public/NCAA/About+the+NCAA
  4. Covell, D., & Barr, C. A. (2001). The ties that bind: presidential involvement with the development of NCAA Division I initial eligibility legislation. Journal Of Higher Education, 72(4), 414-452.
  5. Dixon, M. A., Turner, B. A., Pastore, D. L., & Mahony, D. F. (2003). Rule violations in intercollegiate athletics: A qualitative investigation utilizing an organizational justice framework. Journal of Academic Ethics, 1, 59–90.
  6. Fielding, L., Kaburakis, A., & Pierce, D. (2008). Compliance officers’ guide to navigating NCAA student-athlete reinstatement cases involving amateurism violations. Journal of Issues in Intercollegiate Athletics, 1, 87-106.
  7. Fraenkel, J. R. & Wallen, N. E., (2003). How to design and evaluate research in education 4th ed;. United States of America: McGraw-Hill.
  8. Fuller, M. (2009-2010). Where’s the penalty flag? The unauthorized practice of law, the NCAA, and athletic compliance directors. New York Law School Law Review, 54.
  9. Glazier, M., & Jones, K. (1991). A sea of rules. College Athletic Management, 3(3), 14-18.
  10. Henne, K. (2010). WADA, the Promises of Law and the Landscapes of Antidoping Regulation. Polar: Political & Legal Anthropology Review, 33(2), 306-325. doi:10.1111/j.1555-2934.2010.01116.x
  11. Hums, M. & MacLean, J. (2009). Governance and policy in sport organizations, 2nd edition. Scottsdale, AZ: Holcomb Hathaway Publishers.
  12. LaForge, L. & Hodge, J. (2011). NCAA academic performance metrics: Implications for institutional policy and practice. Journal of Higher Education, 82(2), 217-235.
  13. Kihl, L. (2009). Pacific-10 compliance officers’ morality and moral reasoning. Journal of Issues in Intercollegiate Athletics, 2, 111-149.
  14. Knight Commission (1989). Retrieved on December 6, 2010 from the Knight Commission website:http://www.knightcommission.org
  15. Marsh, G. A. (2009). A call for dissent and further independence in the NCAA infractions process. Cardozo Arts and Entertainment Law Journal, 26, 696-717.
  16. Mueller, C. W., & Wallace, J. E. (1996). Justice and the paradox of the contented female worker. Social Psychology Quarterly, 59(4), 338-349.
  17. NACDA (2011). Overview. Retrieved January 15, 2011 from http://www.nacda.com/naacc/naacc-overview.html
  18. NCAA. (2010). Division I committees. Retrieved November 2, 2010 from http://www.ncaa.org/wps/wcm/connect/public/ncaa/about+the+ncaa/who+we+are/committees/division+i+committees
  19. NCAA. (2010). History. Retrieved on December 6, 2010 from http://www.ncaa.org/wps/portal/ncaahome?WCM_GLOBAL_CONTEXT=/ncaa/NCAA/About+The+NCAA/Overview/history.html
  20. NCAA. (2010). NCAA Division I manual 2010-2011. Retrieved December 4, 2010 from http://www.ncaapublications.com/productdownloads/D111.pdf
  21. NCAA Division I Graduation Success Rate / Division II Academic Success Rate. (2008). http://www.ncaa.org/wps/ncaa?ContentID=5652
  22. Note most common NCAA violations to stay in compliance (2008). College Athletics and The Law, 5(2), 5.
  23. Pierce, D., Kaburakis, A., & Fielding, L. (2008). Compliance Officers’ Guide to Navigating NCAA Student-Athlete Reinstatement Cases Involving Amateurism Violations. Journal of Issues in Intercollegiate Athletics, 87-106. Retrieved from EBSCOhost.
  24. Remington, F. (1984). NCAA enforcement procedures including the role of the committee on infractions. Journal of College and University Law, 10 (2), 181-196.
  25. Robinson, M. J., Peterson, M. M., Tedrick, T. T., & Carpenter, J. R. (2003). Job satisfaction on NCAA Division III athletic directors: impact of job design and time on task. International Sports Journal, 7(2), 46-57.
  26. Simon, R. L. (2008). Does athletics undermine academics? Examining some issues. Journal of Intercollegiate Sport, 1, 40-58.
  27. Tharrington, A.S. & Osborne, B. (2008). An analysis of the presence and perception of the Juris Doctorate degree in Division I college athletics administration. Journal of Legal Aspects in Sport, 18(2), 310-341.
  28. Tyler, P., & Cushway, D. (1998). Stress and well-being in health-care staff: The role of negative affectivity, and perceptions of job demand and discretion. Stress Medicine, 14, 99-107.
  29. Zhang, J. J., DeMichele, D. J., & Connaughton, D. P. (2004). Job satisfaction among mid-level collegiate campus recreation program administrators. Journal of Sport Behavior, 27(2), 184-212.

TABLE WITH CAPTIONS

Table 1     Demographic Characteristics of Division II Compliance Officer Sample (N = 11)

 

Characteristics

  

n

  

%
Gender
Male
Female

7
4

64
36
Type of Institution
Public
Private

7
4

64
36
Current Position
Marketing Director
Senior Women’s Administrator
Faculty Athletic Representative
Coach
Assistant Athletic Director
Associate Athletic Director		  

1
2
1
1
1
5

  

9
18
9
9
9
46
 Years in Position
More than 6 years
4 – 6 years
1 – 3 years
Less than 1 year		  

7
1
1
2

  

64
9
9
18

Table 2     Division II NCAA Compliance (N = 11)

NCAA Compliance

  

n

  

%
Compliance
Individual Responsible for NCAA Compliance		    
Yes

10

90.9
No

1

9.1
Beneficial to Have Individual Designated to Compliance

Agree

11

100
Disagree

0

0
 

Compliance Efforts
Ability to Introduce New, Innovative Strategies

  

9

  

80
Overall NCAA Compliance Efforts Today, Compared with a       Year Ago

11

100
Athletic Departments Should be Using More Compliance Resources, Strategies, and Initiatives

5

50
University Has Invested Sufficient Time and Resources to Adhere to Compliance Rules and Regulations

9

80
Leadership of Athletic Department is Fully Committed to the Long-Term Success of NCAA Compliance and Initiatives

11

100
Athletic Department Should Hire Professionals Who Possess Experience with NCAA Compliance

11

100
Professional Should Possess Experience in Law (i.e. Juris Doctorate)

6

60
   Factors That Could Hinder NCAA Compliance

Operating Constraints (Required NCAA Guidelines)

6

66.7
Support from Administration/Supervisor

6

66.7
Budget

5

55.5
Limited Staff

8

88.9
Nature of Work

7

77.8
Experience/Expertise

6

66.7

 

2016-10-12T15:05:44-05:00April 2nd, 2013|Contemporary Sports Issues, Sports Studies and Sports Psychology|Comments Off on A Preliminary Investigation of NCAA Division II Compliance Officers
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