ISSN: 1543-9518|Vol. 24

An application of means-end theory to analyze the college selection process of female athletes at an NCAA division II university

Submitted by: Peter Finley, Nova Southeastern University,
Jeffrey J. Fountain, Nova Southeastern University

Abstract

While considerable academic attention has been given to the college selection process of student athletes, it has typically relied strictly on survey responses to determine the relative importance of numerous factors. This research applied means-end theory to the problem of understanding college selection among female student athletes at an NCAA Division II university. Through interviews with participants (N=25), the researchers were able to utilize the laddering technique (Reynolds & Gutman, 1988) to identify not only attributes of the university that were salient to the participants as they made their college selection, but also to probe deeper to determine the underlying values that made the factors important. The values cited by participants were security, achievement, belonging, and fun and enjoyment. This study highlights the function of means-end analysis to investigate college selection among student athletes going beyond the superficial identification of important factors. Via means-end interviews, researchers can determine why varied factors are important to individuals.

Review of Literature

College selection is often a difficult process for students in general and is even more complicated for student athletes, particularly those who are recruited by numerous schools (Klenosky, Templin, & Troutman, 2001). To date, considerable academic attention has been paid to assessing the relative importance of factors student athletes consider during their college selection process. The traditionally used method has been to present student athletes with a survey through which various factors were rated. The factors receiving the highest mean scores were then considered to be the most important to the prospects at the time that they made their final college selection. Factors that were commonly cited as important in the college-selection literature in regard to student athletes were concisely detailed in Kankey and Quarterman (2007), and included: (a) opportunity to play (Forseth, 1987; Johnson, 1972; Konnert & Geise, 1987; Slabik, 1995); (b) academic factors (Bukowski, 1995; Cook, 1994; Forseth, 1987, Mathes & Gurney, 1985; Reynaud, 1998; Slabik, 1995); (c) amount of scholarship (Doyle & Gaeth, 1990; Ulferts, 1992); and (d) head coach (Cook, 1994; Mathes & Gurney, 1985; Slabik, 1995).

Recent studies in this area utilized the traditional method for college selection studies. In both studies, Finley (2005), and Kankey and Quarterman (2007), original surveys were constructed and tested for validity and reliability. Surveys were then distributed in packets to coaches with an accompanying cover letter, instructions for administering the survey, and an addressed and stamped return packet. Both studies utilized five-point scales to elicit scores intended to reflect relative importance of numerous factors. Kankey and Quarterman (2007) elected to use a scale ranging from 5 (extremely important) to 1 (unimportant), while the scale used by Finley (2005) was a traditional Likert scale, ranging from 5 (very important) to 1 (very unimportant), with a neutral category.

Karney and Quarterman (2007) surveyed members of NCAA Division I softball teams in Ohio. Participants (N=196) represented 10 of the 11 programs in the state. The descriptive analysis demonstrated that this population considered availability of major or academic program, head coach, career opportunities after graduation, and social atmosphere of the team to be the most important college choice factors, with the mean score for each being above 4 (very important).

Finley (2005) sought to determine the most salient aspects of college selection among NCAA Division III cross country runners (N=427) from around the country. Results indicated that academic reputation, major or degree program, atmosphere of the campus, and the success of the cross country program were the most important. Finley (2005) also determined that the importance of team-related factors was related to the gender and ability of the athletes. Finley split the sample by gender and then subdivided each gender-group into higher and lower ability groups based on the best cross country time each participant had recorded in high school. Several factors proved to be more important to higher ability males than the other groups: The team’s performance in the prior season, the team’s performance over the last several seasons, the performance of individuals on the team last year, and the number of award-winning athletes from the program were all more important to higher-ability males than to lower-ability males or female cross country runners in both the higher and lower ability groups.

While the aforementioned research was important and contributed to the understanding of the college selection of student athletes, it did not address the question of why these factors are important. Klenosky, Templin, and Troutman (2001) introduced a new strategy for assessing college selection criteria with an eye for understanding the underlying values of the student athletes at the time they selected a college. Specifically, the researchers sought to address the “why” question through interviews with 27 NCAA Division I football players at a single university. Their application of means-end theory (Gutman, 1982) demonstrated that college-selection research can move beyond the survey format to answer the more robust question of why particular factors are important to specific participants. The football players described such factors as facilities, the coach, schedule, and academics as important. Players linked these factors to such consequences as getting a good job, personal improvement as a player, playing on television, and feeling comfortable. In turn, these consequences supported the football players’ values of feeling secure, a sense of achievement, a sense of belonging, and having a fun and enjoyable experience. While Klenosky, Templin, and Troutman (2001) successfully introduced Gutman’s means-end theory to the study of college selection by student athletes, they acknowledged that further studies should explore other levels of competition, and female student athletes. This research sought to make that contribution to the college selection literature.

Means-End Theory

Developed by Gutman (1982), means-end theory allows researchers to explore consumer choice beyond the superficial level to understand the emotional underpinnings that drive consumers’ decisions. Through interviews, researchers guide participants through levels of abstraction, moving from the superficial factors that guide their choice, to the consequences that they perceive will arise (consumers seek to maximize positive outcomes) from their choice, and finally to the personal values they are attempting to reinforce. From each attribute of a program or school that an interviewee describes as important, a means-end chain is created to explore the interconnections between the attribute, the anticipated consequences that arise from the attribute, and finally to the personal value being reinforced. The defining aspect of an interview utilizing this theory is to present the participant with the simple question, “Why is that important to you?” After they name a factor or attribute that was important in their college selection, the researcher simply seeks to determine why that factor was important. This generally leads to a connection to a consequence. Asking why the consequence was important leads into further abstraction, to a statement of a value.

According to the theory, individuals base decisions on factors that are likely to lead to desired consequences (Gutman, 1982). The privileging of one consequence over another reflects the value set of the person empowered with the choice, and they will make selections that reinforce what they have deemed valuable (Klenosky, Templin, & Troutman, 2001). While two athletes might cite the location of a school as an important factor on a traditionally used survey format, it would be unclear whether they value location because of proximity to family, the effect of weather on their sport performance, preference for a rural or suburban lifestyle, or for myriad other reasons. Through the application of means-end theory, researchers can make this determination. As applied to college selection, for example, an athlete might rate facilities as an important factor (attribute) in her college selection. Further questioning (via the “why is that important” question) can elicit the response that facilities were import because she believed it would help her play better (consequence). Finally, she might describe that playing better would reinforce her desire for personal achievement (value). See Table 1 for an example of interview responses and the corresponding coding.

Table 1

Example of two interview ladders and the corresponding coding for each

Table 1

Research Goal

 

The present study sought to apply means-end theory to determine the attributes, consequences, and values that underpinned college selection for female student athletes at an NCAA Division II institution.

Method

Procedure

 

Semi-structured interviews were conducted with two researchers and individual student athletes. The participants were asked to recall the colleges that they seriously considered as they made their final college selection. Participants were then asked to list factors (attributes) that they relied on as they selected their college over their other finalists. The researchers then utilized the laddering technique as described by Reynolds and Gutman (1988) and later applied to student athletes and college selection by Klensoky, Templin, and Troutman (2001) to create means-end chains, in which each attribute was explored via the question, “Why is that important to you?” This would elicit a response suggesting how this attribute would benefit the participant (consequence). Then the “Why is that important to you?” question would be used to move the participant into deeper reflection, moving from the consequence to a personal value. Participants would create from two to four chains and interviews generally lasted ten to fifteen minutes.

To elicit the most thoughtful and honest answers possible, the researchers utilized the interview methods suggested by Reynolds & Gutman (1988). These included conducting interviews in a non threatening environment (a library area was used, which represented a more neutral site for participants than would a professor’s office or a classroom), making an effort to position the participant as the only expert regarding their college selection, with emphasis being placed on reassuring them that there was no right or wrong answer, and showing interest in responses while refraining from giving cues suggesting judgment. Following each interview, the researchers used interview notes to create means-end chains, which connected each attribute cited by the participants with the corresponding consequences and values stemming from it. Discrepancies were resolved jointly, relying as strictly as possible on key words and phrases used by the participants and recorded in the interview notes.

Participants

The participants in this study were 25 female student athletes at an NCAA Division II university in Florida during the 2005-2006 academic year. Participants represented a variety of sports, including basketball, soccer, softball, golf, tennis, rowing, and cross country.

Results

 

In total, 77 means-end chains were created, an average of 3.08 per participant. Coding of the means-end chains revealed eight attributes cited as important to the selection of the student athletes’ current college. These attributes led to eight potential consequences, which, in turn, led to four values.

Table 2

Summary of all attributes, consequences, and values identified throughout the interview process

Table 2

Using the coded data, an implication matrix was constructed (Table 3) as a summary of the connections between attributes, consequences, and values. In addition to showing the number of participants that mentioned a concept (under N), the matrix also lists the number of total times the concept was mentioned. Each cell reflects the number of times the concept was mentioned. For example, location linked to the consequence of feel comfort (C1), three times and connected to the consequence of adventure (C3) twelve times. Location also connected to the value fun and enjoyment (V1) fifteen times. The implication matrix was then used to construct a Hierarchical Value Map (HVM).

table 3

Implication Matrix for female student athletes’ college selection

N Chains C1 C2 C3 C4 C5 C6 C7 C8 V1 V2 V3 V4
Attributes
A1 Location 22 30 3 1 12 1 5 8 15 5 8 2
A2 Scholarship 16 16 13 3 7 9
A3 Academics 7 7 7 3 1 3
A4 Coach 7 7 5 2 3 2 3 2
A5 Facilities 6 6 1 5 1 5
A6 Friend
on the team		 4 4 4 3 1
A7 School
Size		 4 4 3 1 2 2
A8 Open Spot 3 3 3 2 1
Consequences
C1 Feel Comfort 15 16 8 1 2 5
C2 Financial Comfort 14 14 4 10
C3 Adventure 12 12 12
C4 Get a Good Job 9 9 3 1 5
C5 Can Improve 8 10 10
C6 Friend & Family 7 8 2 5 1
C7 Feel
Valued		 5 5 4 1
C8 Playing
Time		 3 3 2 1
Values
V1 Fun
& Enjoyment		 20 27
V2 Achievement 14 21
V3 Security 13 22
V4 Belonging 5 7

As information from the implication matrix was transferred into the HVM, the researchers selected a cutoff level of two. A cutoff level establishes how frequently a connection had to be made to be depicted in the HVM. Thus, only connections made two or more times are illustrated with a line. Eliminating connections made only one time reducing clutter in the HVM. To assist the reader in interpreting the HVM, an illustrative example is presented (Figure 1). The complete HVM follows (Figure 2). Consistent with the literature (Klenosky, Templin, & Troutman, 2001), values are presented at the top of the map to represent their abstract nature in college selection (they appear within triangles and are spelled with all capital letters). Consequences are represented across the middle (within circles and beginning with a capital letter), and attributes appear at the bottom (within rectangles and all lower case letters) to reflect that they were merely the beginning point in each chain and are the most superficial level of information gathered. Further, the lines between attributes, consequences, and values represent the frequency of the connection between these concepts (more frequent associations depicted with thicker lines). The size of each shape also reflects the number of participants mentioning it, with more frequently mentioned concepts dominating more space. Finally, the first number in each shape reflects the number of participants that mentioned the concept, while the number in parenthesis is the number of times the concept was mentioned in total, reflecting that some concepts would be mentioned multiple times by a single participant.

Figure 1

Figure 1. An illustrative example of an HVM section

Figure 2

Figure 2. Hierarchical Value Map for female student athletes’ college selection

Discussion

 

Analysis of the HVM revealed several noteworthy findings. First, location was a primary attribute for the selection of this university over other universities the athletes considered as they made a final decision. In fact, 39% of all the chains created in this study began with the attribute of location. While it might not be surprising that a university in the state of Florida is selected for its location, this fact underscores the importance of a means-end analysis. While a college selection survey would also reveal that location was important, it would not discover the true reason for the importance of this attribute. The means-end analysis demonstrated that the attribute of location was important for several different reasons. Of the 30 chains beginning with location, 12 went to the consequence of adventure and then continued on to the value of fun and enjoyment. Other participants indicated that location was important because it kept them close to friends and family, which had a strong connection to the value of security. Others expressed that they simply are comfortable here, which largely connected with fun and enjoyment. Finally, some participants (in outdoor sports) noted that the weather in Florida would allow them to improve their sport performance (largely due to an extended season), which supported the value of achievement.

The different values that underpinned the importance of location supported the belief that college selection is a complicated process and that a single attribute of a campus can be important to prospective student athletes for a wide variety of reasons. This fact should be particularly interesting to coaches who spend considerable time and effort in the recruitment process and could misinterpret a prospects’ motivation for selecting a particular university. For example, coaches might feel confident that a student athlete selected a college because of location and may even presume to know that it is related to a consequence, such as improving sport performance, whereas in the mind of the student athlete, lying on the beach might be the true motivator because she is more driven by her value of fun and enjoyment than by the value of achievement.

Second, the attribute of receiving an athletic scholarship was also frequently mentioned. It was important to 16 of the 25 participants (64%). Predominantly it led to the consequence of financial comfort, which, in turn led to the value of security. For a few participants, however, the consequence of financial comfort led to the value of achievement, which reflected their belief that financial comfort was essentially earned through their years of dedication to sport participation. Comments made during the interviews suggested that the participants viewed the scholarship as a literal indication that they had achieved within their sport and that their achievement became measurable and worthwhile through the scholarship offer. Participants reported being offered scholarship packages of widely varying values and thus scholarship became an important attribute in differentiating between schools. The Klenosky, Templin and Troutman (2001) study did not reveal scholarship as an important attribute among the Division I football players because each participant in the sample reported being recruited by over 20 schools and thus scholarship was likely a non-issue in differentiating between schools.

Third, the attributes of the coach and academics were mentioned by surprisingly few participants. These attributes were seldom used by participants to differentiate their school from others at the time they made their final selection. Still, it is interesting to see that these attributes trailed location and scholarship by a wide margin. For the seven participants who mentioned academics, all of them linked it to the consequence of getting a good job, as opposed to more altruistic notions such as gaining knowledge or growing as a person.

Fourth, the consequence of feeling comfort was frequently mentioned and stemmed from a variety of attributes. School size, location, a friend on the team, and the coach were all attributes that seemed to assure the participants that this school would be a good fit for them and provide a place in which they would feel comfort. This information is valuable for coaches who actively recruit prospects. It is possible that a key to securing recruits is in convincing them that the attributes of the college, team, and campus will help the prospect feel comfort.

Fifth, the value of fun and enjoyment underpinned the college selection for many participants (it was mentioned by 20 of the 25 participants (80%), and several participants had multiple chains end with this value). However, the source of fun and enjoyment was extremely varied. At the time the college selection was made, participants believed that playing time, adventure (from location), proximity to friends and family, a comfortable atmosphere, and opportunity to get a good job all led to the possibility of fulfilling the value of fun and enjoyment.

This study contributes to the college selection literature and furthered the work of Klenosky, Templin, and Troutman (2001) to utilize means-end theory to determine the values that student athletes rely on in this process. However, there were limits to the study. Most notably, it only represented student athletes from one university and results do not generalize to female student athletes overall. Different results could occur among student athletes at other schools based on such traits as school size, region of the country, and NCAA division.

Conclusion

 

College selection is a complicated and difficult process for student athletes, which is often made even more confusing by the recruitment process. While traditionally researchers have sought to understand college selection by drawing from sizable data sets gathered via surveys, that method fails to explore fully the complexity of any given attribute (such as location). By applying means-end theory researchers can probe further and determine the values on which prospects are basing their selection. Further, a general understanding of means-end theory could be important for coaches to improve the process of attracting prospects in an increasingly competitive college sports climate. It also can assist coaches in understanding what is important to the student athletes once they matriculate to campus.

For the participants in this study, security, achievement, belonging, and fun and enjoyment were the guiding values for college selection. Future research should extend the use of means-end analysis to student athletes in other contexts, for example by sport, NCAA division, and region of the country.

References

 

Bukowski, B. J. (1995). Influences on student college choice for minority and non minority athletes at a Division III institution (Doctoral dissertation, University of Wisconsin, Madison, WI). Dissertation Abstracts International, 56(7), 126.

Cook, T. (1994). Factors female freshmen student-athletes use in deciding between a NJCAA college and a NAIA college. Unpublished master’s thesis, University of Kansas, Lawrence, KS.

Doyle, C. A. & Gaeth, G. J. (1990). Assessing the institutional choice process of student athletes. Research Quarterly for Exercise and Sport, 61(1), 85-92.

Finley, P. S. (2005). An analysis of team Web site content and college choice factors of NCAA Division III cross country runners (Doctoral dissertation, University of Northern Colorado, Greeley, CO). Dissertation Abstracts International, 66(04), 1291.

Forseth, E. (1987). Factors influencing student-athletes’ college choice at evangelical, church-supported NAIA institutions in Ohio (Doctoral dissertation, The Ohio State Univesity, Columbus, OH). Dissertation Abstracts International, 48(01), 172.

Gutman, J. (1982). A means-end chain model based on consumer categorization processes. Journal of Marketing, 46(2), 60-72.

Johnson, E. A. (1972). Football players’ selection of a university. Unpublished master’s thesis, University of Utah, Salt Lake City, UT.

Kankey, K., & Quarterman J. (2007). Factors influencing the university choice of NCAA Division I softball players. The SMART Journal, 3(2), 35-49.

Klenosky, D. B., Templin, T. J. & Troutman, J. A. (2001). Recruiting student athletes: A means-end investigation of school-choice decision making. Journal of Sport Management, 15, 95-106.

Konnert, W., & Geise, R. (1987). College choice factors of male athletics at private NCAA Division III institutions. College and University, 63(1), 33-44.

Mathes, S., & Gurney, G. (1985). Factors in student-athletes’ choice of colleges. Journal of College Student Personnel, 26(4), 327-333.

Reynaud, C. (1998). Factors influencing prospective female volleyball student-athletes’ selection of an NCAA Division I university: Towards a more informed recruitment process (Doctoral dissertation, Florida State University, Tallahassee, FL). Dissertation Abstracts International, 59(02), 445.

Reynolds, T. J., & Gutman, J. (1988). Laddering theory, method, analysis and interpretation. Journal of Advertising Research, 28(1), 11-31.

Slabik, S. L. (1995). Influences on college choice of student-athletes at National Collegiate Athletic Association Division III institutions. Unpublished doctoral dissertation, Temple University, Philadelphia, PA.

Ulferts, L. (1992). Factors influencing recruitment of collegiate basketball players in institutions of higher education in the upper Midwest (Doctoral dissertation, University of North Dakota, Grand Forks, ND). Dissertation Abstracts International, 54(03), 770.

Authors Note:
Correspondence for this article should go to Peter Finley, H. Wayne Huizenga School of Business and Entrepreneurship, 3301 College Avenue, Fort Lauderdale-Davie, Florida 33314, (954) 262-8115, [email protected].

2016-10-20T10:36:52-05:00April 2nd, 2008|Sports Coaching, Sports Exercise Science, Women and Sports|Comments Off on An application of means-end theory to analyze the college selection process of female athletes at an NCAA division II university
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Competitive Balance in Men’s and Women’s Basketball: The Cast of the Missouri Valley Conference

Submitted by: Martin M. Perline, Ph.D. & G. Clayton Stoldt, Ed.D.

Abstract:

Competitive balance typically fosters fan interest. Since revenue associated with men’s sports is typically greater than with women’s, one might expect to find greater levels of competitive balance in men’s sport than women’s sport. The purpose of this research was to test this hypothesis by comparing the competitive balance in a high revenue intercollegiate sport, basketball, for both men and women over a 10-year period in the Missouri Valley Conference.  Three measures of competitive balance were employed. In each case, competitive balance was found to be greater among the men’s teams than the women’s. The findings support the hypothesis that where there is greater revenue potential, there should be greater competitive balance.

Introduction:

One of the important differences between sports organizations and other industrial organizations is the issue of competitive balance.  Whereas most industrial enterprises attempt to keep competition to a minimum, a lack of competition in the case of sport teams makes for boring games and ultimately fans lose interest (Depken & Wilson, 2006; El Hodiri & Quirk, 1971; Kesenne, 2006; Quirk & Fort, 1992; Sanderson & Siegfried, 2003).  This lack of interest would lead to a loss of revenue, as fewer fans would attend games or listen to or watch media presentations. While fans certainly prefer to see their teams win, they want them to at least have a chance of losing.  Economists refer to this as the uncertainty of outcome hypothesis (Leeds & Von Allmen, 2005).

In professional sports some teams, frequently those in large markets, normally receive more revenue than their competitors. Those teams are in a position to sign better players and win more frequently, leading to the problem of competitive imbalance.  Efforts to alleviate this problem have included salary caps, luxury taxes, revenue sharing, and reverse order of finish drafts.  In intercollegiate athletics, attempts to alleviate competitive imbalance are undertaken by the NCAA through its various rules and regulations (National Collegiate Athletics Association, 2006). Likewise, various intercollegiate athletic conferences do this through budgeting and scheduling requirements and the selection of institutional membership (Rhoads, 2004).

In order to maintain fan interest, competitive balance is important in all sports. From the viewpoint of program administrators, it would appear to be particularly important in sports such as basketball and football, in which there are potentially large sources of revenue involved.  Similarly, because revenue is typically so much greater for men’s than for women’s sports, one might expect to find greater efforts being made to bring about competitive balance in men’s sports than in sports for women.   This might be singularly true where there was a post-season tournament, thus a need to keep fan interest intense throughout the season to help insure interest for post-season play.

The purpose of this study is to test the hypothesis that one would expect to find more competitive balance in men’s than in women’s basketball.  More specifically, the researchers compared the degree of competitive balance in both men’s and women’s basketball in the Missouri Valley Conference (MVC) for the 10-year period 1996-97 through 2005-06. The MVC was selected because it annually holds a post-season tournament, and the authors had access to financial data indicating that there was significantly larger revenue associated with men’s basketball than women’s basketball (Missouri Valley Conference, 2006a). The particular time frame was selected as a period of stable membership within the conference.

The Missouri Valley Conference

Established in 1907 as the Missouri Valley Intercollegiate Athletic Association, the MVC is the oldest collegiate athletic conference west of the Mississippi River and the fourth oldest league in the nation (Markus, 1982).  The league has been comprised of 32 member institutions at varying times through its history, and it has seen members win national titles on 25 occasions (Missouri Valley Conference, 2006b).

The MVC now features 10 league members:  Bradley University, Creighton University, Drake University, the University of Evansville, Illinois State University (ILSU), Indiana State University (INSU), Missouri State University (MSU), the University of Northern Iowa (UNI), Southern Illinois University (SIU), and Wichita State University (WSU).

While the conference’s membership has changed on several occasions since its founding, the most recent changes occurred in the early and mid 1990s.  The MVC and the Gateway Collegiate Athletic Conference merged in 1992 (Benson, 2006; Markus, 1982; Missouri Valley Conference, 2006b; Richardson, 2006).  The merger resulted in the addition of UNI to bring total league membership to 10 institutions (Carter, 1991; Richardson, 2006).  It also resulted in the establishment of MVC championship programs in women’s sports for the first time in conference history.

In 1994, Evansville joined the conference, giving the conference an all-time high 11 league members (Richardson, 2006).  Conference membership dropped back to 10 institutions in 1996, when the University of Tulsa left the MVC to join the Western Athletic Conference (Bailey, 2005; Richardson, 2006)

Measuring Competitive Balance

There are several ways of measuring competitive balance, and there is some debate as to which approach is best.  Each method attempts to measure something different.  Which is best often depends on what the parties to the debate find most useful for their purposes (Humphreys, 2002).  Among the more popular measures are the standard deviations of winning percentages of the various teams in the conference or league, the Hirfindahl-Hirschman Index, and the range of winning percentages.

Winning Percentage Imbalance

One popular measure of competitive balance calculates each team’s winning percentage in the conference in a given season.  Since there will, outside of a tie, always be one winner and one loser for each game, the average winning percentage for the conference will be .500.

In order to get some idea of competitive balance, the researchers needed to measure the dispersion of winning percentages around this average.  To do this, they measured the standard deviation.  This statistic measures the average distance the observations lie from the mean of the observations in the data set.
_________________
σ = √ Σ (WPCT – .500)2
N

The larger the standard deviation, the greater the dispersion of winning percentages around the mean, and thus the less the competitive balance.  (If all teams had a winning percentage of .500, there would be a standard deviation of zero, and there would be perfect competitive balance.)

Championship Imbalance

Whereas the standard deviation as a measure of competitive balance provides a good picture of the variation among the winners, it does not indicate whether it is the same teams winning every season or if there is considerable turnover among the winners from one season to the next.

Therefore, another method economists use to measure competitive imbalance is the Hirfindahl-Hirschman Index (HHI), which was originally used to measure concentration among firms within an industry (Leeds & Von Allmen, 2005).  Since the standard deviation is used to measure percentage winning imbalance, the HHI is used to measure championship imbalance – how the championship or first place finish is spread amongst the various teams.  Using this method, the greater the number of teams that achieve championship status over a specific time period, the greater the competitive balance.

The HHI can be calculated by measuring the number of times that each team wins the championship, squaring that number, adding the numbers together, and dividing by the number of years under consideration.  Using this measure, it can be concluded that the lower the HHI, the more competitive balance among the teams.

Range of Winning Percentage Imbalance

As suggested above, the standard deviation of winning percentages explains variation around the mean, but it does not specifically reveal if it is the same teams winning or losing from season to season.  Likewise, the HHI provides perspective on the number of teams which win the championship over a period of time, but it does not indicate what is happening to the other teams in the conference.  It is possible that a few teams could always finish first, but that the other teams could be moving up or down in the standings from one year to another.

One way of gaining some insight into the movement in the standings of all teams over time is to get the mean percentage wins for each team over a specific period.  The closer each team is to .500, the greater the competitive balance over this period.  If several teams had a very high winning percentage and others had a very low winning percentage, it would suggest that there was not strong competitive balance over time, but that the same teams were winning and the same teams losing year after year.

Results:
In order to arrive at conclusions concerning competitive balance in the MVC, the researchers employed each of the above measures and compared the results for men’s and women’s basketball over the selected period.

Standard Deviation of Winning Percentages

Tables 1 and 2 display the winning percentages for the women’s and men’s basketball teams. Table 3 displays the standard deviations for both the women’s and men’s winning percentages each season.  As indicated in Table 3, the men had a mean standard deviation of .2184 compared to a .2404 for the women.  This is approximately a 10% difference favoring competitive balance among the men.  It can also be noted that the men had a lower standard deviation than the women in seven of the 10 years studied.  Likewise, it can be seen that the highest standard deviation for women .2644 (2004-95) exceeded the highest for men, which was .2551 (2002-03).  Similarly, the lowest standard deviation for women .2010 (2002-03) was considerably higher than a comparable figure for the men, which was a very low .1527 (1998-99).

Table 1. Winning Percentages- Missouri Valley Conference Women’s Basketball

  Bradley Creighton Drake Evansville ILSU INSU MSU SIU UNI WSU
1996-97 0.5 0.389 0.778 0.111 0.722 0.5 0.722 0.5 0.278 0.5
1997-98 0.222 0.611 0.944 0.056 0.5 0.556 0.778 0.389 0.444 0.5
1998-99 0 0.5 0.778 0.611 0.222 0.556 0.833 0.278 0.667 0.556
1999-00 0.167 0.389 0.833 0.778 0.167 0.278 0.778 0.278 0.556 0.778
2000-01 0.278 0.611 0.889 0.444 0.167 0.389 0.889 0.222 0.667 0.444
2001-02 0.389 0.889 0.833 0.5 0.278 0.389 0.667 0.111 0.5 0.444
2002-03 0.5 0.722 0.611 0.278 0.278 0.722 0.611 0.167 0.667 0.444
2003-04 0.389 0.833 0.611 0.333 0.5 0.556 0.889 0.111 0.389 0.389
2004-05 0.444 0.722 0.444 0.556 0.389 0.722 0.833 0.056 0.722 0.111
2005-06 0.278 0.278 0.722 0.611 0.389 0.889 0.389 0.333 0.667 0.444
Mean 0.317 0.594 0.744 0.428 0.361 0.556 0.739 0.245 0.556 0.461

Source: Missouri Valley Conference 2005-06 Women’s Basketball Media Guide

Table 2. Winning Percentages- Missouri Valley Conference Men’s Basketball

  Bradley Creighton Drake Evansville ILSU INSU MSU SIU UNI WSU
1996-97 0.667 0.556 0 0.611 0.788 0.333 0.667 0.333 0.611 0.444
1997-98 0.5 0.667 0 0.5 0.888 0.556 0.611 0.444 0.222 0.611
1998-99 0.611 0.611 0.278 0.722 0.389 0.556 0.611 0.556 0.333 0.333
1999-00 0.556 0.611 0.222 0.5 0.278 0.788 0.722 0.667 0.389 0.278
2000-01 0.667 0.788 0.444 0.5 0.667 0.556 0.444 0.556 0.167 0.222
2001-02 0.278 0.788 0.5 0.222 0.667 0.222 0.611 0.788 0.444 0.5
2002-03 0.444 0.833 0.278 0.444 0.278 0.111 0.667 0.888 0.389 0.667
2003-04 0.389 0.667 0.389 0.278 0.222 0.278 0.5 0.944 0.667 0.667
2004-05 0.333 0.611 0.389 0.278 0.444 0.278 0.556 0.833 0.611 0.667
2005-06 0.611 0.667 0.278 0.278 0.222 0.222 0.667 0.667 0.611 0.778
Mean 0.506 0.68 0.278 0.433 0.484 0.39 0.606 0.668 0.444 0.517

Source: Missouri Valley Conference 2005-06 Men’s Basketball Media Guide

Championship Imbalance

Using the HHI to measure competitive balance for men’s and women’s basketball, the researchers found more competitive balance among the various institutions playing men’s basketball than among their counterparts playing women’s basketball.

Using the HHI for men’s basketball, the researchers found that six teams achieved an outright first place finish (SIU 3, ILSU 2, Evansville 1, Creighton 1, INSU 1, and WSU 1) over the 10-year period studied.  In one year, there was a tie for first place (SIU and Creighton in 2001-02).  If one point for each outright first place finish and .5 point for each two way tie is given:

HHI= 3.52+22+1.52+12+12+12 = 21.50/10 = 2.150

For women, over the 10-year period only four teams achieved an outright first place finish (Drake 3, MSU 3, Creighton 1, and INSU 1).  In 2 years, there was a tie for first place 2000-01 MSU and Drake, and 2002-03 Creighton and INSU).  Using the same point distribution as above:

HHI= 3.52+3.52+1.52+1.52 = 29/10= 2.9

In this case, the HHI showed considerably more competitive balance among the men’s basketball teams, than among the women’s.  Indeed, the HHI is about 33% higher for the women than for the men.  As indicated above this competitive balance advantage for the men can also be seen by the fact that over the 10-year period six different men’s teams achieved a first-place finish, while in the case of the women only four teams finished first.

Range of Winning Percentage Imbalance

If one arbitrarily sets .100 plus or minus the perfect balance, i.e., .500 as a range, which would suggest a high degree of competitive balance over the ten-year period, one once again finds more competitive balance among the men’s teams than among the women’s.

Table 2 suggests that, using this approach, five teams (50%) fit this range.  Those teams were Bradley, Evansville, ILSU, UNI, and WSU. Among the others, Creighton, MSU, and SIU seemed to be more consistent winners, while Drake and INSU were at the bottom.  But even among the latter, INSU had a winning percentage in 4 of the 10 years.  Indeed only one team—Creighton had a winning season each of the ten years. When viewing the range from top to bottom, a variation of .680 (Creighton) to .278 (Drake) a range of .402 is found.

Table 1 indicates that among the women’s teams over this 10-year period a similar five teams fit this range.  Those teams were Creighton, Evansville, INSU, NIU, and WSU.  Drake and Missouri State were consistent winners, each having only one losing season over the period studied. Meanwhile Bradley, ILSU, and SIU were on the lower end, none of which had an actual winning season over the last 9 years.

While both the men and women had five teams fitting our defined range for a high degree of competitive balance, it should be noted that the range from top to bottom was .499 for the women as compared to .402 for the men.  This range is almost 25% greater for women, which again suggests less competitive balance among the women’s teams

Table 3. Standard Deviations of Winning Percentages in Women’s and Men’s Basketball

Year Women Men
1996-97 0.2078 0.2298
1997-98 0.2538 0.2442
1998-99 0.2606 0.1527
1999-00 0.2746 0.201
2000-01 0.258 0.1942
2001-02 0.24 0.2142
2002-03 0.201 0.2551
2003-04 0.2342 0.2313
2004-05 0.2644 0.1851
2005-06 0.2095 0.2208
Mean 0.2404 0.2184

Source: Authors’ calculations based on data in Tables 1 and 2.

Conclusions:

The uncertainty of outcome hypothesis suggests that a lack of competitive balance among teams in a league or conference can lead to a lack of interest in the games outcome and thus a loss of revenue to teams sponsoring the games.  If this were indeed the case, it should follow that the greater the potential revenue possible, the more likely there would be an attempt to bring about competitive balance.

The purpose of this research was to test this hypothesis by comparing the competitive balance in a high revenue intercollegiate sport, basketball, for both men and women over a period of time.  Expectations were that, because of the greater revenue associated with men’s basketball, there would be greater competitive balance.

Using the standard deviation of winning percentages, the Hirfindahl-Hirschman Index, and the range of winning percentage imbalance to measure competitive balance, the researchers found in each case that there was greater competitive balance among the men’s basketball teams than for the women’s teams.  These findings would support the hypothesis that where there is greater revenue potential, there should be greater competitive balance.

In conclusion, the usual caveats are in order.  It is possible that if the researchers analyzed a different time frame within the MVC, or if a different intercollegiate conference was chosen for analysis, a different conclusion may have been reached.  It may also be that as women’s basketball continues to grow and generate greater amounts of revenue from ticket sales, media rights fees, and corporate sponsorship, levels of competitive balance may also change.  These possibilities provide further research opportunities to test the hypothesis.

References :

Bailey, E. (2005, June 26). Hurricane settled. The Tulsa World, B1.

Benson, J. (2006, October 30). Valley holds Centennial celebration. Knight Ridder Business News. Retrieved April 12, 2007 from http://proquest.umi.com/pqdweb?did=1170880621&Fmt=3&clientId=328&RQT=309&VName=PQD&cfc=1.

Carter, K. (1991, September 23). Schools jump starting future movement. The Sporting News, 212 (13), 57.

Depken, C.A., & Wilson, D.  (2006). The Uncertainty of Outcome Hypothesis in Division I-A College Football. Manuscript submitted for publication.

El Hodiri, M. & Quirk, J. (1971). An economic model of a professional sports league. Journal of Political Economy, 79, 1302-19.

Humpreys, B. (2002). Alternative measures of competitive balance.  Journal of Sports Economics, 3, (2), 133-148.

Kesenne, S. (2006). Competitive balance in team sports and the impact of revenue sharing. Journal of Sport Management, 20, 39-51.

Leeds, M. & vonAllmen, P. (2005). The Economics of Sports. Boston: Pearson-Addison Wesley.

Markus, D. (1982, February) The best little conference in the country. Sport. 73, 31.

Missouri Valley Conference. (2006a). Finance committee report. St. Louis: Author.

Missouri Valley Conference. (2006b). This is the Missouri Valley Conference. Retrieved April 27, 2007 from http://www.mvc-sports.com/ViewArticle.dbml?DB_OEM_ID=7600&KEY=&ATCLID=271380.

National Collegiate Athletics Association (2006). 2006-07 NCAA Division I manual. Indianapolis, IN: Author.

Quirk, J. & Fort, R.D.  (1992). Pay Dirt: The Business of Professional Team Sports. Princeton, NJ: Princeton University Press.

Rhoads, T.A. (2004). Competitive Balance and Conference Realignment in the NCAA. Paper presented at the 74th Annual Meeting of Southern Economic Association, New Orleans, LA.

Richardson, S. (2006). A Century of Sports: Missouri Valley Conference. St. Louis: Missouri Valley Publications.

Sanderson, A.R., & Siegfried, J.J. (2003). Thinking about Competitive Balance. Unpublished manuscript. Vanderbilt University.

2016-10-20T10:19:13-05:00March 14th, 2008|Sports Management, Sports Studies and Sports Psychology, Women and Sports|Comments Off on Competitive Balance in Men’s and Women’s Basketball: The Cast of the Missouri Valley Conference
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Book Review: Senda Berenson: The Unlikely Founder of Women’s Basketball

Reviewed by: Jeffrey Chamberlin

Senda Berenson: The Unlikely Founder of Women’s Basketball is author Ralph Melnick’s biographical account of Senda Berenson (1868-1954), considered by many to be the founder of women’s basketball. She pioneered gender-specific rules and emphasized skill development and team play. She transformed the sport of women’s basketball from a physical education class for female underclassmen at Smith College to a nationwide, standardized-women’s game with rules formally approved by the American Association for the Advancement of Physical Education and published by Spaulding’s Athletic Library.

Senda Berenson: The Unlikely Founder of Women’s Basketball is a “portrait” of Senda Berenson’s life. In sixteen chapters, the author describes Berenson’s modest upbringing as a sickly, young Jewish immigrant from Lithuania, her aspirations to be an artist, her revolutionary and practical applications towards women’s physical education, and her commitment to making exercise and games social and enjoyable. Berenson believed the new age of women dictated that women’s athletics could be used as catalysts for social change. She believed competition created moral bankruptcy. Berenson condemned personal glory, corporate profit, individualism, and the entrepreneurial spirit reflected in men’s athletics. In qualifying his portrait of Berenson, Ralph Melnick writes:

[T]his book is neither a history of an advancing feminist wave nor a history of early women’s basketball; these stories have been told elsewhere, as has the history of women’s physical education. Rather, it is a step back more than a century, even to those moments before the first ball was tossed at center court, in an attempt to create a portrait of the remarkable women who sent it upward.

Nothing summarizes her better words to her nephew shortly before her death, “Old age is creeping up on me…I suppose that at our age we resign ourselves to the fact that our energy gets weaker and weaker – although I cannot do it with resignation.”

Millions of females throughout the country are reaping the benefits of Berenson’s foresight and fortitude. Her contributions to basketball have solidified her place in the Basketball Hall of Fame.

This book is an ideal text for those interested in the history of women’s sport or in the life of a remarkable American figure.

Author: Ralph Melnick
Published in 2007 by University of Massachusetts Press
(221 pages, ISBN: 1-55849-568-1)

2016-10-12T14:53:53-05:00March 14th, 2008|Sports Coaching, Sports Exercise Science, Sports Management, Women and Sports|Comments Off on Book Review: Senda Berenson: The Unlikely Founder of Women’s Basketball
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A History of Women in Sport Prior to Title IX

Submitted by: Richard C. Bell, Ed.D., J.D.

Abstract:

Women’s opportunities for competitive physical activity were limited in America until Federal Legislation, commonly referred to as Title IX, became law. It required American society to recognize a woman’s right to participate in sports on a plane equal to that of men. Prior to 1870, activities for women were recreational rather than sport-specific in nature. They were noncompetitive, informal, rule-less; they emphasized physical activity rather than competition. In the late 1800’s and early 1900’s, women began to form clubs that were athletic in nature. Efforts to limit women’s sport activity continued as they became more involved in competitive sports. This paper will present a history of women’s involvement in sport prior to the federal legislation enacted to eliminate sexual discrimination in education and sport.

Early Women’s Sports

Certainly, women engaged in sport three millennia ago. Homer, c 800 B.C., relates the story of Princess Nausicaa playing ball with her handmaidens next to a riverbank on the island of Scheria. “When she and her handmaids were satisfied with their delightful food, each set aside the veil she wore: the young girls now played ball; and as they tossed the ball…” (Homer, lines 98-102). Odysseus was awakened by the shouts of the girls engaged in their sport. Thousands of years later, the shouts of girls playing ball finally awoke the United States to the need for sport-specific opportunities for women.

Prior to 1870, sports for women existed in the form of play activities that were recreational rather than competitive and, being informal and without rules, emphasized physical activity (Gerber, Felshin, Berlin, & Wyrick, 1974). A dominant belief in the 1800s was that each human had a fixed amount of energy. If this energy were used for physical and intellectual tasks at the same time, it could be hazardous (Park & Hult, 1993). Horseback riding for pleasure, showboating, and swimming became fashionable, but women were not encouraged to exert themselves. Such physical activity for a woman was thought to be especially hazardous because during menstruation she was “periodically weakened” (Clarke, 1874, p. 100). In 1874, as women were beginning to gain access to higher education, Dr. Edward Clarke published Sex in Education; or, A Fair Chance for Girls, which sparked a tenacious and acrimonious debate about the capacity of women for physical activity. He stated that, “both muscular and brain labor must be reduced at the onset of menstruation” ( p. 102). Manipulating science to reinforce established dogma prevailed for many years in spite of repeated examples of women who were perfectly capable of performing physical feats and intellectual tasks. Many early opportunities for women to engage in physical activity were thwarted as a result of this dogma (Park & Hult).

As more women sought to become involved in physical activity, they became more competitive. In the late 1800s and early 1900s, women began to form informal athletic clubs. Tennis, croquet, bowling, and archery were popular in clubs from New York to New Orleans. Many men’s clubs allowed women to become associates and to participate in separate activities, though without according them full status. Parallel clubs in colleges began to appear during this time, but a major difference between the social metropolitan clubs and the college clubs was that the latter frequently sponsored coed competition as occasions for social gatherings (Gerber, et al., 1974).

College Sports for Women Prior to Title IX

Early college sports for women have been largely unrecognized by historians because competition was within college between students (intramural) rather than between the institutions (extramural). Competitions included intramural, club, and sorority matches, in addition to ‘play days’. These were special dates when women competed in sports and activities against students and teams from their schools. By 1936, 70% of colleges surveyed used this as a predominant form of sport participation for women (Hult, 1994).

Women’s physical educators were aware of the problems and criticism surrounding men’s intercollegiate athletics. They were determined to keep athletics in an educational environment for women. In the early 1900s, the Committee on Women’s Athletics (CWA) and the American Physical Education Association (APEA) endorsed programs of broad participation for women (Park & Hult, 1993). This occurred just as the Carnegie Foundation for the Advancement of Teaching produced its 1929 report, American College Athletics, reporting that amateurism was being eliminated or modified from athletics at the college level as colleges turned athletics into big business. The report argued that there should be a way to give “athletics back to the boys” (Thelin, 1994). These views were uppermost in the minds of many women’s physical educators as they met to organize a governing organization for women’s sports. In the 1920s, the Women’s Division-National Amateur Athletic Federation (NAAF) was formed to organize intercollegiate competition among women (Park & Hult).

Women were not active in intercollegiate sport until basketball was introduced at Smith College in 1892 (Gerber, et al., 1974). Basketball quickly spread to other colleges, and students began to clamor for intercollegiate play. Women’s physical educators opposed such competition because they were not ready to lose control over their programs (as they perceived the men had) (Gerber, et al.). The first intercollegiate competition among women was a scheduled tennis tournament between Bryn Mawr and Vassar. It was canceled because the Vassar faculty did not allow their women’s athletes to participate in competition between colleges (Hult, 1994). The honor of being the first teams to compete in women’s intercollegiate athletics belongs to the basketball teams of the University of California, Berkeley vs. Stanford and the University of Washington vs. Ellensburg Normal School; they played in 1896 (Gerber, et al.).

Competitive events for college women increased in the early 1900s. The nature of varsity competition was in conflict with the philosophy of women’s physical educators in the 1920s and 1930s, so these events were still uncommon. This philosophical conflict contributed to a lack of support for women’s varsity athletics. The NAAF provided a forum for women’s physical educators and leaders of women’s sports to formalize their beliefs regarding competition for girls and women by issuing a policy statement of the organizations goals for women. The goals were established to “play for play’s sake,” limit awards and travel, protect the participant from exploitation, discourage “sensational” publicity, and place qualified women in immediate charge of athletics and other physical activities (Gerber, et al., 1974). The motto was “every girl in a sport and a sport for every girl.” This position was interpreted by many as negative to competition and, as a consequence, virtually all forms of competitive sport for college women decreased in the early 1900s (Gerber, et al.).

The women’s suffrage movement in the late nineteenth and twentieth century resulted in the passage of the Nineteenth Amendment in 1920. The right to vote for women renewed emphasis on women’s freedoms. The first feminist movement resulted in modest gains for women in sports and intercollegiate competition, but these gains were negated by the depression in the 1930s. They would remain dormant for almost fifty years (Gelb & Palley, 1987). The depression left millions of Americans out of work, and the resulting campaign to keep women home and out of the work force left the women’s movement for broadened equal rights stagnating. The expectations of society were that a woman’s place was ‘in the home,’ which pushed aside the idea that there were psychological and physiological benefits to be gained from involvement in sport. This view remained largely unchanged until the events of the 1940s (Lucas & Smith, 1982).

The 1940s brought war to the United States and millions of men entered the military. Many women joined the military service or left their positions as homemakers to fill the void left in the work force, earning the moniker, “Rosie the Riveter.” They demonstrated that they were equal to the task. The self-esteem and self-confidence gained by women during these critical times propelled the movement for women’s equal rights. Many women believed that if they could compete successfully in the work force, then they could certainly compete on the athletic fields (Chafe, 1972). World War II also saw the advent of the first woman’s professional athletic team. The All-American Girls Baseball League was started in 1943 as an attempt to replace Major League Baseball, which had been canceled due to the war. When World War II ended, organizations for women in sport began to increase as sport became more competitive and intercollegiate and interscholastic competition spread (Gerber, et al., 1974).

In the 1950s and 1960s, the social conscience of America was changing. The push for Civil Rights, which culminated in the passage of the Civil Rights Act of 1964, helped increase the status of women and minorities. A wave of feminist activism was born (Gelb & Palley, 1996). Feminist activism propelled the movement for women’s rights forward. The United States became embroiled in the debate for an Equal Rights Amendment. This debate raised the consciousness of those involved in women’s sport. Collegiate women seeking greater athletic opportunities moved closer to their goals in 1957, when the long-entrenched official position statement of the Division for Girls and Women in Sport (DGWS) was amended to state that intercollegiate programs “may” exist. In 1963, the DGWS view of women in sport evolved further to state that it was “desirable” that intercollegiate programs for women exist (Gerber, et al., 1974).

In 1966, the DGWS appointed a Commission on Intercollegiate Sports for Women (CISW) to assist in conducting intercollegiate competitions. In 1967, it was renamed the Commission on Intercollegiate Athletics for Women (CIAW). The women’s movement in sport was rapidly moving toward a status more in line with men’s athletics. In 1969, a schedule of national championships for women’s sports was announced that included gymnastics and track and field. Swimming, badminton, and volleyball followed in 1970 and in 1972, basketball was added. Women wanted an institutional membership organization similar to the NCAA. The CIAW was replaced by the Association for Intercollegiate Athletics for Women (AIAW) in 1971. This set the stage for the struggle to control women’s athletics in the 1970s between the AIAW and the NCAA (Gerber, et al., 1974).

The increasingly positive attitude toward women in sport carried over into the 1970s (Hult, 1994). The AIAW began the 1971-1972 academic year with 278 charter institutions. By 1981, their membership exceeded 800. Their mission was to “lead and conduct” programs at the collegiate level that were competitive for women (Hulstrand, 1993). The AIWA focused on the female student-athlete’s education, not on athletic performance, and thus rejected the ‘win or die’ attitude of the NCAA. Instead, the AIAW emphasized participation in sport as the most important aspect and de-emphasized winning (Sperber, 1990).

The Evolution of Title IX

The new wave of feminism within the larger social reforms sought by the Civil Rights movement moved women closer to legislative action for greater equal treatment in athletics. The concept that federal legislation was to eliminate sexual discrimination was the main focus of women’s groups in the late 1960s and early 1970s. At their first national conference in 1967, the National Organization for Women (NOW) adopted a platform that read in part “…the right of women to be educated to their full potential equally with men be secured by Federal and State legislation” (Boles, 1989, p.643).

Title IX of the Education Amendments of 1972 was paid little attention in the early legislative efforts to codify these rights. Court-ordered busing in the other Titles of the Omnibus Education Amendments took the spotlight (Palley & Preston, 1978). It was only after Title IX was passed, when the question surrounding implementation arose, that opposition to Title IX took place (Gelb & Palley, 1987). After the passage of Title IX, Congress built in a six-year period for secondary and post-secondary schools to achieve compliance. The date for compliance by colleges and universities was 1978. Interpretation and enforcement were vested in the Department of Health, Education, and Welfare (Carpenter, 1993).

The critical element lacking after the passage of Title IX was the implementation legislation that would specify how it was to be applied and to whom. Passage of the implementation legislation was not easy; many self-interest groups sought to erode the legislation. In 1974, approximately sixty women’s and feminist groups formed a coalition called the Education Task Force (which would later becme the National Coalition for Women and Girls in Education) (Gelb & Palley). It was largely as a result of their persistent and dedicated efforts through lobbying that Title IX was successful.

The NCAA became concerned by what it perceived to be the potential weakening of its position as the dominant and controlling body of intercollegiate athletics. If Title IX was to apply to intercollegiate sports at all levels and women were to be elevated to a status equal to the men, its financial assets and political power were threatened. The first approach of the NCAA, when faced with the threat of equality in intercollegiate athletics, was to attempt to limit Title IX’s application. The NCAA tried to offer its interpretation of Title IX (Acosta & Carpenter, 1985). It encouraged a narrow interpretation of the law, excluding athletic departments from the scope of Title IX. The NCAA argued that because athletic departments did not receive federal funds, they should be excluded from compliance. Nonetheless, when the NCAA sought to limit the application of Title IX, it began to address the issue of control of women’s athletics in earnest.

The NCAA observed the growth of women’s athletics and looked to the increased financial base and political power to be gained from exerting control over women’s intercollegiate athletics. It set out to force the AIAW out of control (Hult, 1994). The strategy was to absorb the AIAW into its current structure while offering women’s championships outside the AIAW to effectively link schools to the NCAA. Because there was no alternative mechanism for determining college-level champions, this strategy could have been successful (Stern, 1979). The NCAA decided to form its own NCAA Women’s Committee and exclude the AIAW (Carpenter, 1993). The NCAA had never shown an interest in women’s athletics before Title IX because there was nothing that required female participation at a national level. Thus, it chose not to pursue women’s athletics. “The formation of this committee was politically significant because prior to this time the NCAA had demonstrated no interest whatever in taking responsibility for women’s sports” (Carpenter, 1993, p. 83).

In the fall of 1974, the NCAA agreed to a meeting with the AIAW. The NCAA wanted the AIAW to affiliate itself with the NCAA; the AIAW hoped to form a joint committee to draw up rules. The NCAA did not consider the AIAW its equal and it would not agree to a 50-50 joint union and equal representation at all policy-making levels (Festle, 1996).

At its 1973 convention, the NCAA waived the regulation barring women from men’s events, thinking that the compromise of allowing a token female to compete in the NCAA championships would help avoid charges of sex discrimination and help avoid offending the AIAW while avoiding any real commitment to women’s athletics (Festle, 1996). The NCAA continued to be concerned about the loss of power and control over intercollegiate athletics as it began to sense that the idea of equal opportunity for women in intercollegiate athletics was the direct aim of the Federal Government. The NCAA needed to implement an acceptable policy without delay (Festle).

The NCAA was a powerful adversary for the AIAW because of its wealth, political influence, and long history. The NCAA decided to introduce women’s championships for intercollegiate sports by offering the institutions sponsoring women’s sports a proposition that ultimately led to the demise of the AIAW. The NCAA offered to: (a) pay all expenses for teams competing in a national championship, (b) charge no additional membership fees for schools to add women’s programs, (c) create financial aid, recruitment, and eligibility rules that were the same for women as for men, and finally, (d) guarantee women more television coverage. The NCAA had earmarked three million dollars to support women’s championships. The AIAW could not compete with the NCAA inducements and the loss of membership, income, championship sponsorship, and media rights forced the AIAW to cease operations on June 30, 1982 (Festle, 1996). The AIAW sued the NCAA for allegedly violating the Sherman Anti-Trust Act, but was unsuccessful when the courts ruled that the market for women’s athletics was open for competition, therefore no anti-trust laws had been violated (Schubert, Schubert, & Schubert-Madsen, 1991).

Subsequent to Title IX, women and girls have become much more involved in sports. College women’s athletic participation has increased from 15% in 1972 to 43% in 2001. High school girl’s athletic participation increased from 295,000 in 1971 to 2.8 million in 2002-2003, an increase of over 840%. In 2004, the average number of teams offered for females per college/university was 8.32, up from 2.50 per school in 1972 (Carpenter & Acosta, 2005). In 1981-82, women’s championships became a part of the NCAA program. Today, the NCAA sponsors forty women’s championships, thirty-eight men’s championships, and three combined championships in all three of its divisions (NCAA, 2005).

It can be seen that women’s involvement in sport was slow to develop. Opportunities for participation and recognition were almost non-existent for centuries. It was not until the advent of the equal rights movements and Title IX that women truly found a place as participants in the world of sport and in the public arena.

References

Acosta, R.V. & Carpenter, L.J. (1985). Women in sport. In Donald Chu, Jeffrey O. Segrave & Beverly J. Becker (Eds.), Sport and Higher Education (pp.313-325). Champaign, IL. Human Kinetics.

Boles, J.K. (1989). A policy of our own: Local feminist networks and social services for women and children. Policy Studies Review, 8(3), 638-647.

Carpenter, L.J. (1993). Letters home: My life with Title IX. In G.L. Cohen (Ed). Women in Sport: Issues and Controversies. (pp 133-155), Newberry Park, CA.: Sage Publishing.

Carpenter, L.J. & Acosta, R.V. (2005). Title IX. Champaign, IL: Human Kinetics.

Chafe, W.H. (1972). The American woman: Her changing social, economic and political roles, 1920-1970. New York: Oxford University Press.

Clarke, E. H. (1874). Sex in education; or, a fair chance for girls. Boston: James R. Osgood and Company.

Festle, M.J. (1996). Playing nice: Politics and apologies in women’s sports. New York: Columbia University Press.

Gelb, J., & Palley, M.L. (1996). Title IX: The politics of sex discrimination. Women and Public Policies: reassessing gender politics. Charlottesville: University of Virginia Press.

Gerber, E.W., Felshin, J., Berlin, P., & Wyrick, W. (Eds.). (1974). The American woman in sport. Reading, MA: Addison-Wesley.

Homer, The Odyssey of Homer (Allen Mandelbaum, trans.) Berkeley, CA: University of California Press (1990).

Hult, J.S. (1994). The story of women’s athletics: Manipulating a dream 1890-1985. In D.M. Costa & S.R. Guthrie (Eds.), Women and sport: Interdisciplinary perspectives. (pp. 83-107), Champaign, IL: Human Kinetics.

Hultstrand, B.J. (1993). The growth of collegiate women’s sports: The 1960s. The Journal of Physical Education, Recreation, and Dance, 64(3), 41-43.

Lucas, J.A., & Smith, R.A. (1982). Women’s sport: A trial of equality. In R. Howell (Ed.), Her Story in Sport: A Historical Anthology of Women in Sports (pp. 239-265). West Point, NY: Leisure Press.

NCAA Championships (2005).http://www.ncaa.org/about/champs.html

Palley, M.L., & Preston, M.B. (1978). Symposium on race, sex and policy studies. Policy Studies Journal, 7, 188.

Park, R.J., & Hult, J.S. (1993). Women as leaders in physical education and school-based sports, 1865 to the 1930s. The Journal of Physical Education, Recreation & Dance, 64(3), 35-40.

Schubert, A.F., Schubert, G.W., & Schubert-Madsen, D.L. (1991). Changes influenced by litigation in women’s intercollegiate athletics. Seton Hall Journal of Sport Law, 1, 237-268.

Sperber, M. (1990). College sports inc.: The athletic department vs. the university. New York, John Hopkins Press.

Stern, R.N. (1979, June). The development of an inter-organizational control network: the case of intercollegiate athletics. Administrative Science Quarterly, 24, 242-266.

Thelin, J. (1994). Games colleges play: Scandal and reform in intercollegiate athletics. Baltimore, MD: John Hopkins University Press.

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Gender-specific Aspects of Football Expertise: Implications of Two Prospective Observation Studies

Submitted by: Thomas Bobbert, K. Mai, A.F.H. Pfeiffer & J. Spranger

Abstract:

Women and men differ in many aspects of life; among these, their view of sport activities differ considerably. Thus, football (soccer) and the prediction of football results are recurrent sources of stress. Despite this, until now no study has investigated the parameters affecting football expertise in detail. We performed two prospective observation studies in health care employees to investigate whether football expertise, as a parameter combining behavioural, social, and physical aspects of life, is related to gender or anthropometric parameters.

The first study was performed in 2004 during the UEFA European Cup in Portugal. In order to confirm the results of the initial study, a second study was performed during the FIFA World Cup 2006 in Germany. A total of 307 persons were included in the studies. All volunteers had to predict the results of the preliminary round of the respective tournament. An evaluation of the results was done by scores, which were given for correct tendency and correct numbers of goals for each team.

In the first study, a significant difference between male and female participants was found (46.7 ± 1.3 pts, n=41 f: 42.7 ± 1.4 pts, n=42; p = 0.03). This was confirmed in the second study, which had a total of 224 participants. Here, male participants scored significantly higher than female participants (m: 113.9 ± 1.0 pts; f: 108.7 ± 1.3pts; p = 0.004). This difference remained significant in both studies after adjustment for age, profession, and BMI. Despite the fact that the majority of “couch potatoes” are supposed to be outstanding football experts, no relation between BMI and the ability to predict football results was found.

We demonstrated that men perform better in predicting football results than women. This finding was confirmed in a second independent cohort. The consequences of this apparent discrepancy between these gender specific realities on men’s health and the question of whether advertisement and television increasingly favour promoting women as football experts remain to be determined.

Introduction:

Football (soccer) expertise depends on psychological, social, and physiological factors. Despite the apparent impact of this topic on daily life, no study has investigated the parameters affecting football expertise in detail until now. In particular, the question of whether gender is important for individual football expertise is recurrent, due to a lack of valid studies and often irrational debate. Initially, football was dominated on and beside the football field by males. The classical roles were described; the male was the football expert, who rarely played football himself, watched football on TV, and liked to analyse previous games. On the other hand, women tried to avoid watching football games if possible and judged it simply as a sport with twenty-two men running for one ball. Therefore, discussions between males and females about this topic have been often dominated by males.

In recent years, this picture has changed remarkably. Apart from a considerable number of female football players and increasing interest by the media for professional female football, an increasing number of female football supporters have been registered (Member Statistics 2005 German Football Association). This has resulted in changes in the typical behavioural roles in relation to football. Indeed, football discussions often result in quarrels. These discussions are often passionate and lack rational bases. Taking all this together, there is certainly a considerable chauvinism in terms of supposed football expertise. Whether this is justified is completely unclear.

Therefore, we performed the first study to investigate whether football expertise, as a parameter combining behavioural, social, and physical aspects of life, is related to gender. Since men and women are apparently different in aspects potentially influencing football expertise, among them anthropometry and social status, we included these parameters in our multivariate analysis.

Methods:

The first study was performed in 2004 during the UEFA European Cup in Portugal. Participants for this study were recruited by e-mail and personal communication at the Charité-University Medical School Berlin and the German Institute of Human Nutrition. A total of eighty-three volunteers were recruited. Apart from personal information, all participants had to predict the results of the preliminary round. In total, there were twenty-four games.

To confirm the results of the initial study, a second study (study II) was performed during the 2006 FIFA World Cup in Germany. Participants of this study were recruited by Internet and intranet from the Charité-Medical School Berlin. Two hundred and forty-one persons agreed to participate in this study. However, due to missing data, seventeen individuals had to be excluded from final analysis so that a total of 224 persons were ultimately included in this study. All volunteers had to predict the results of the preliminary round of the FIFA World Cup 2006. In total, there were forty-eight games. Baseline characteristics of the volunteers of both studies are presented in Table 1. Additional questions about profession and occupational localization were asked.

Table 1: Baseline characteristics of volunteers in Study I and Study II. P-values for reached points were adjusted for BMI, age, profession, and workplace.

A) Study I: UEFA EC 2004

Males Females p-value
Participants 41 42 –
Points 46.7 ± 1.3 42.7 ± 1.4 0.03
BMI (kg/m2) 23.3 ± 0.7 22.5 ± 0.5 0.34
Age (y) 32.2 ± 1.2 34.5 ± 1.6 0.25

B) Study II: FIFA WC 2006

Males Females p-value
Participants 132 92 –
Points 113.9 ± 1.0 108.7 ± 1.3 0.004
BMI (kg/m2) 23.7 ± 0.2 22.2 ± 0.4 0.001
Age (y) 35.0 ± 0.7 36.6 ± 1.0 0.18

A total of 307 persons were included. An evaluation of the results was done by scores given for correct tendency and correct numbers of goals for each team. For correct tendency, three points were given and for correct number of goals for one team, one point was given. In one game, a maximum of five points could be achieved.

Statistics:

Statistical calculations were performed with SPSS 12.0 (SPSS Inc., Chicago, IL, USA). All values are given as mean ± standard error. Unpaired T-test was applied if parameters were normally distributed, otherwise Mann-Whitney-U test was used. Multivariate analysis was performed by General Linear Model procedure. Correlations between variables were investigated by Pearsons coefficient of correlation. An alpha-error below 5% was considered to be statistically significant.

Results:

In Study I during the 2004 EC in Portugal, a significant difference between males and females was found in eighty-three individuals (m: 46.7 ± 1.3 pts, f: 42.7 ± 1.4 pts; p = 0.03). This result was confirmed in Study II, which had a total of 224 participants. Here, male participants scored significantly higher than female participants (m: 113.9 ± 1.0 pts; f: 108.7 ± 1.3 pts; p = 0.004).

We next speculated that differences in anthropometry might affect these results, given that “couch-potatoes” might score differently than lean and fit individuals. However, no significant correlation was found between BMI (2006: r = 0.061; p = 0.391; 2004: r = 0.001; p = 0.991) and football expertise (Figure 1) in either study. Correspondingly, the gender specific difference of football expertise remained significant in both studies after adjustment for age and BMI.

Figure 1: Males show higher football expertise compared to female participants in the studies. Results were adjusted for age, profession, and BMI.

Figure 1:

a) FIFA WC 2006 b) UEFA EC 2004
Figure 1 a Figure 1 b

While no significant differences between physicians and non-physicians could be observed in Study I, physicians had significantly more points than non-physicians in Study II (P: 114.3 ± 1.3 pts, N.P.: 110 ± 1.1 pts; p = 0.007, figure 2). In the WC 2006 study, a more detailed analysis on the influence of profession was performed. The analysis of working areas showed that neurologists and psychiatrists had the highest levels of football expertise, while the lowest results were achieved by the members of the departments of pediatrics (internal medicine: 111.1 ± 1.3 pts, neurology/psychiatry: 115.2 ± 2.6 pts, pediatrics: 109.8 ± 4.4 pts, surgical departments: 112.1 ± 3.2 pts, radiology: 112.1 ± 5.2 pts, others: 109.7 ± 2.3 pts, administration: 111.3 ± 3.2 pts). Although apparently of considerable interest, none of these differences reached statistical significance. We additionally tested whether profession or workplace affected the relation between gender and football expertise. Although profession had a significant influence in Study II (p = 0.03), the gender-specific difference remained significant in both cohorts.

Subsequently, the relation between professional experience and football experience was tested in physicians. Although senior registrars had significantly more points than all other groups, especially the directors of the clinics (directors: 111.5 ± 9.7 pts, senior registrars: 118.6 ± 2.6 pts, SHO: 113.0 ± 1.5 pts, care staff: 109.3 ± 2.3 pts, scientist: 110.6 ± 1.6 pts, administration: 108.8 ± 3.2 pts, technicians: 108.9 ± 3.3 pts, students: 113.8 ± 2.8 pts), these differences were not statistically significant.

Discussion:

We demonstrate that men predict football (soccer) results more accurately than women. Thus, the widespread chauvinism in terms of football expertise appears to be partially justified. However, it is important to note that gender accounts for only about 5% of the variability of football expertise. Thus, additional, not-yet identified factors are apparently predominantly responsible for the individual football expertise.

Differences in health care between genders were recently acknowledged as important neglected points; these are part of the ongoing competition between men and women (1). The gender confrontation can also be found in the field of sports, which is not exclusive to the sport itself but includes parasportive activities (2). Football is among the most discussed topics, especially during globally communicated events like the recent FIFA World Cup (3;4). The classical role, which is also often presented by the media, characterises men as football experts, while women are neglected in that context. In recent years, this picture has changed considerably. Women are increasingly recognised as a potential focus of advertisement in the environment of sport events. Consequently, more and more women are presented as experts, i.e. in television broadcasts, which clearly challanges the classical role of the man being the football expert.

Our results indicate that in the general population, men are still better qualified to predict football results than women. Thus, any overemphasis with respect to women in that context is in contrast to the existing reality. The health consequences of such undeserved discrimination are unclear, but may finally result in inferiority complexes or aggression in men, which remains to be determined. Some points of the study design should be mentioned. The presented data are based on healthcare workers and it is unclear whether they can be transferred to the general population. In addition, the ability to predict football results is unlikely to represent the whole spectrum of football expertise. Another important topic addressed here was the relation between anthropometry and football expertise. Although no direct association with BMI was found, a relation to abdominal obesity cannot be excluded. However, “couch potatoes,” who are likely to perform pretty well in football results prediction, are characterised by abdominal obesity, rather than simply elevated BMI. In addition, only about 20% of the cohorts had a BMI higher than 25 kg/m2. Thus, the study may have been underpowered to address this question sufficiently.

Figure 2: Physicians (P) in Study II (n=224) show a significantly higher football expertise than non-physicians (N.P.). Results are after adjustment for age, sex, and BMI.

Figure 2:

Figure 2

In summary, we demonstrated that men perform better in predicting football results than women. This finding was confirmed in a second independent cohort. The consequences on men’s health due to the apparent discrepancy between gender specific realities and the fact that advertisement and television increasingly favour women as football experts remain to be determined.

References:

Carroll D., S. Ebrahim, K. Tilling, J. Macleod, G.D. Smith. Admissions for myocardial infarction and World Cup football: Database survey. BMJ 2002; 325(7378):1439-1442.

Collin J., R. MacKenzie. The World Cup, sport sponsorship, and health. Lancet 2006; 367(9527):1964-1966.

Doyal L. Sex, gender, and health: The need for a new approach. BMJ 2001; 323(7320):1061-1063.

Tanaka H. The battle of the sexes in sports. Lancet 2002; 360(9326):92.

2016-10-19T10:11:08-05:00March 14th, 2008|Contemporary Sports Issues, Sports Studies and Sports Psychology, Women and Sports|Comments Off on Gender-specific Aspects of Football Expertise: Implications of Two Prospective Observation Studies
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