ISSN: 1543-9518|Vol. 24

Educating Sports Entrepreneurs: Matching Theory to Practice

Anthony Borgese

Abstract

Sports entrepreneurship courses are part of sports management programs because some students hope to own their own sports-oriented business, and major sports conglomerates look to hire employees with entrepreneurial skills. Sports management instructors prepare students for these challenges. However, not all sports entrepreneurship instructors have owned their own businesses nor worked for large sports corporations. As a result, this study was conducted to determine if sports entrepreneurship instructors and sports entrepreneurs agree on the content that should be taught in sports entrepreneurship courses in order to prepare students for the real-world.

Results of the study indicate that sports entrepreneurship instructors do agree on a set of content standards for sports entrepreneurship courses, specifically, the Consortium for Entrepreneurship Education National Content Standards (1). Additionally, when ranking the content skills, sports entrepreneurship instructors and sports entrepreneurs agreed on four of the five top skills students should be taught in order to be successful sports entrepreneurs.

Key Words: Sports Entrepreneurship, Entrepreneurs, Sports Education, Sports Entrepreneurship Courses

Introduction

Sport management programs continue to grow in number. Since the first sport management program was developed at Ohio University in 1966, programs continue to spread across the United States and the world. According to the North American Society for Sport Management, there are more than 200 sport management programs in the United States alone (6). This growth has prompted a need for innovation within sport management curricula and the development of courses that are high quality, content-rich, and flexible.

The sports industry is the third largest industry in the United States, accounting for more than $213 billion dollars a year in revenues (3). Kurtzman (4) outlined the importance of sports tourism as the impetus for the pursuit of business entrepreneurship, economic impact, and profitability. He categorized sports tourism jobs into categories of events, resorts, cruises, tours and attractions – along with listed subgroups in those categories. These subgroups, such as sports events planning and sports tour operators, are areas that are ripe for entrepreneurial endeavors.

An industry as large as the sports industry requires educated people to run a variety of sports related businesses. However, it should not be assumed that sports entrepreneurs are only owners of professional sports franchises. The sports industry entails a variety of sub-businesses, both large and small. For example, there are owners of health club facilities, sports arena and facility operators, league owner/operators, sporting goods store owners, sports ticket agencies, and sport physical therapists – just to name a few. Sport management students take sport entrepreneurship courses in order to learn the skills that are necessary to operate these types of sport-related businesses.

On the other hand, sport management instructors are entrusted with preparing their students for jobs in sport-oriented businesses. It is up to them to develop effective curriculum that prepares students for careers in an industry that is constantly changing and evolving. However, not all sport entrepreneurship instructors have owned their own businesses nor worked for large sports corporations. Research into what type of content and skills sport entrepreneurship instructors are teaching was sorely needed.

This study was conducted to compare what sport entrepreneurship instructors and practicing sport entrepreneurs believe are the important skills necessary to teach sport entrepreneurship students in order to be successful in running sport-oriented businesses. It is relevant to sports entrepreneurship educators as well as students of sports management programs – in regards to gauging what is currently being taught in sports entrepreneurship courses.

Methods

There were two research populations for this study. The research populations included: 1) NASPE/NASSM instructors of sport entrepreneurship courses in college level sport management programs that are accredited by the National Association for Sport and Physical Education (NASPE) and the North American Society for Sport Management (NASSM). 2) Sport entrepreneurs located throughout the United States in a variety of sports oriented businesses.

Two hundred and seventeen (217) sport management instructors were identified through their faculty web pages. However, it should be noted that this was not a complete list of sport entrepreneurship instructors, because there is no way to determine how many of these sport management instructors actually taught sport entrepreneurship courses. The instructors that were contacted, were all members of sport management programs, and taught sports management related courses at the time the data was gathered. However, all sport management programs do not have sport entrepreneurship courses, nor do all sport management professors teach sport entrepreneurship. Therefore, it was impossible to get an exact count of how many sport entrepreneurship instructors exist in NASPE/NASSM accredited sport management programs. Ultimately, 43 (N = 43) sport entrepreneurship instructors participated in the study.

The second research population consisted of 250 sport-oriented businesses. The researcher randomly selected four sport-oriented businesses in each of the fifty states in the United States of America. Small sport-oriented businesses were chosen, as opposed to utilizing owners of large sports conglomerates. This is because they represented a good mix of sport-oriented businesses and they were more indicative of the types of businesses that would have been opened by recently graduating sports management students. Ultimately 67 (N = 67) sport entrepreneurs participated in the study.

The research instruments that were used to conduct this study were two questionnaires that were developed and piloted by the researcher and reviewed by a panel of experts to achieve validity and reliability.

The questionnaires were administered via email and regular mail for both research populations. The questionnaires were made available over the Internet to maximize participation. The researcher created electronic versions of the questionnaires and administered them on the Internet using www.surveymonkey.com.

Results

The Instructor Group was comprised of 88.4% males and 11.6% females, with 60.4% of the overall population between the ages of 36 and 55. A doctorate or master’s degree was held by 72.1% of the population. 60.4% were associate or full professors. 88.4% had 5+ years of general teaching experience. 90.7% had some type of online teaching experience. 93% had some type of blended teaching experience. 81.4% taught in 4-year colleges or universities or in graduate programs. Finally, 79.1% had sports entrepreneurship courses as an elective at their respective institutions.

An analysis of the descriptive data of the Sport Entrepreneur Group was as follows. 85.1% of the Sport Entrepreneur Group were males whereas 14.9% were female. 68.6% were between the ages of 36 and 55. 82.1% had some type of college degree. Sporting goods store owners were the largest type of business represented by this group at 37%. 25.4% of the Sport Entrepreneur respondents were relatively new businesses that had been in existence less than five years. On the opposite end, 20.9% of the group had been in business for over 25 years. The largest legal structure was a sole proprietorship at 34.3%. 38.8% of the business had over $500,000 in revenues. 17.9% only had themselves as the only employee whereas 83.6% had anywhere up to 14 employees.

To address the question of whether there is a universal set of content standards in sports entrepreneurship courses, both groups were asked if they thought that CEE’s National Content Standards (1) (Appendix A) were a complete list of all of the skills and traits necessary for sports entrepreneurship students to learn in order to become successful business owners. The results were as follows:

Table 1.1 Are CEE’s National Content Standards Complete? (Instructors)

Yes or No Frequency Percent
Yes 41 95.3
No 2 4.7

Table 1.2 Are CEE’s National Content Standards Complete? (Sports Entrepreneurs)

Yes or No Frequency Percent
Yes 65 97.0
No 2 3.0

For further analysis, a Mann-Whitney U Test was conducted to see if there were any differences between the two groups with regard to the whether they believed CEE’s National Content Standards were a complete list of the skills and traits necessary for sports entrepreneurship students to learn in order to become successful business owners. This test was administered with a .05 significance level. As the results indicated, the two tailed, significance was .650 – representing that there was no significant difference between the two groups. Table 1.3 demonstrates the results of the Mann-Whiney U Test.

Table 1.3 CEE’s National Content Standards Both Groups

Is the CEE National Content Standards List Complete?
Mann-Whitney U 1416.500
Wilcoxon W 3694.500
Z -.453
Asymp. Sig. (2-tailed) .650

Grouping Variable: Instructor or Entrepreneur

Because the Consortium for Entrepreneurship Education’s 15 National Content Standards might be too ambitious to cover in just one sports management course, both groups were asked to rank the top five of the fifteen National Content Standards (1). This question is necessary because despite the course delivery mechanism (online, face-to-face), the top five content standards should be feasible to teach in any one course.

Table 1.4 Ranking of Top 5 Content Standards

Standards Group Rank #1 Rank #2 Rank #3 Rank #4 Rank #5 TOTAL %
Entrepreneurial Processes Instructors 11.6% 4.7% 2.3% 2.3% 4.7% 25.6%
Entrepreneurs 14.9% 6% 1.5% 1.5% 23.9%
Entrepreneurial Traits/Behaviors Instructors 7% 2.3% 2.3% 2.3% 14%
Entrepreneurs 3% 13.4% 4.5% 1.5% 22.4%
Business Foundations Instructors 9.3% 9.3% 11.6% 4.7% 7% 41.9%
Entrepreneurs 17.9% 7.5% 11.9% 1.5% 4.5% 43.3%
Communication/Interpersonal Skills Instructors 37.2% 14% 4.7% 7% 2.3% 65.1%
Entrepreneurs 38.8% 13.4% 14.9% 4.5% 4.5% 76.1%
Digital Skills Instructors 2.3% 2.3% 7% 4.7% 2.3% 18.6%
Entrepreneurs 1.5% 3% 7.5% 11.9%
Economics Instructors 2.3% 2.3% 4.7%
Entrepreneurs 3% 3% 1.5% 7.5%
Financial Literacy Instructors 4.7% 7% 14% 2.3% 4.7% 32.6%
Entrepreneurs 1.5% 7.5% 9% 4.5% 6% 28.4%
Professional Development Instructors 2.3% 2.3% 2.3% 4.7% 11.6%
Entrepreneurs 1.5% 4.5% 6%
Financial Management Instructors 14% 32.6% 9.3% 2.3% 58.1%
Entrepreneurs 9% 28.4% 14.9% 10.4% 3% 65.7%
Human Resource Management Instructors 7% 7% 9.3% 18.6% 41.9%
Entrepreneurs 7.5% 4.5% 10.4% 10.4% 32.8%
Information Management Instructors 2.3% 18.6% 16.3% 2.3% 39.5%
Entrepreneurs 4.5% 14.9% 1.5% 4.5% 25.4%
Marketing Management Instructors 4.7% 2.3% 9.3% 18.6% 23.3% 58.1%
Entrepreneurs 3% 7.5% 25.4% 19.4% 55.2%
Operations Management Instructors 2.3% 7% 16.3% 11.6% 37.2%
Entrepreneurs 4.5% 1.5% 23.9% 17.9% 47.8%
Risk Management Instructors 2.3% 2.3% 14% 18.6%
Entrepreneurs 1.5% 1.5% 3% 10.4% 16.4%
Strategic Management Instructors 9.3% 2.3% 2.3% 2.3% 16.3%
Entrepreneurs 1.5% 3% 3% 6% 13.4%

Table 1.4 indicates the individual content standard, along with the responses for the two research groups. Table 1.4 also indicates the percentage rankings of each content standard. The top five from both groups were: communication and interpersonal skills, financial management, marketing management, and business foundations. The two groups only differed in one of the top five areas. The instructor group listed human resources management in their top five, whereas the sports entrepreneur group listed operations management in their top five.

It is also interesting to note that the bottom three standards that both research groups felt were the least needed skills and traits were: Professional Development, Economics, and Digital Skills.

An Independent Samples T-test was conducted to compare the Instructor Group and Sport Entrepreneur Group rankings of the National Content Standards on an individual basis (Table 1.5). The Independent Samples T-test illustrated Levene’s Test of Quality Variance, a significance level, and a significance level for a two tailed test. The results indicated that there was significance in three of the fifteen National Content Standards: Digital Skills, Financial Management, and Strategic Management. This was determined by looking at the Sig. (two-tailed) column and finding the results that are below the 0.05 alpha level. SPSS provides two different statistics to choose from, depending on whether or not equal variances are assumed. One must look at the Sig. column first in order to determine if the numbers under the equal variances assumed, or equal variances not assumed row is to be used. If the Sig. level is over 0.05, then equal variances are assumed – so one would use the results in that row under the Sig. (two tailed) column.

Table 1.5 Independent T-test for Individual Rankings for Both Groups

Levene’s Test for Equality of Variances t-test for Equality of Means
F Sig. t Df Sig. (2-tailed) Mean Diff. Std. Error Diff. 95% Confidence Interval of the Difference
Lower Upper
Entrepreneurial Processes Equal variances assumed 4.112 .053 1.417 25 .169 .74 .521 -.335 1.812
Equal variances not assumed 1.315 16.063 .207 .74 .561 -.451 1.929
Entrepreneurial Traits Equal variances assumed 2.768 .113 1.783 19 .091 .80 .449 -.139 1.739
Equal variances not assumed 1.445 6.560 .195 .80 .554 -.527 2.127
Business Foundation Equal variances assumed .014 .908 1.321 45 .193 .54 .406 -.282 1.354
Equal variances not assumed 1.305 34.784 .200 .54 .411 -.298 1.371
Communication/Interpersonal Skills Equal variances assumed .138 .712 -.558 77 .579 -.16 .285 -.727 .409
Equal variances not assumed -.563 57.181 .576 -.16 .283 -.725 .407
Digital Skills Equal variances assumed .855 .371 -2.668 14 .018 -1.38 .515 -2.480 -.270
Equal variances not assumed -2.668 11.536 .021 -1.38 .515 -2.503 -.247
Economics Equal variances assumed 2.959 .146 2.023 5 .099 2.10 1.038 -.569 4.769
Equal variances not assumed 2.689 3.921 .056 2.10 .781 -.086 4.286
Financial Literacy Equal variances assumed .167 .686 -.816 31 .421 -.35 .433 -1.237 .530
Equal variances not assumed -.816 28.129 .422 -.35 .433 -1.241 .534
Professional Development Equal variances assumed .036 .854 -.482 7 .644 -.45 .933 -2.657 1.757
Equal variances not assumed -.474 6.062 .652 -.45 .950 -2.769 1.869
Financial Management Equal variances assumed 8.228 .006 -2.248 67 .028 -.55 .243 -1.030 -.061
Equal variances not assumed -2.460 63.283 .017 -.55 .222 -.989 -.102
Human Resources Management Equal variances assumed .012 .914 .588 38 .560 .22 .369 -.530 .965
Equal variances not assumed .588 36.452 .560 .22 .369 -.531 .966
Information Management Equal variances assumed .311 .581 .804 32 .427 .24 .293 -.361 .831
Equal variances not assumed .804 29.471 .428 .24 .293 -.363 .833
Marketing Management Equal variances assumed 1.631 .207 -.474 60 .638 -.13 .283 -.700 .432
Equal variances not assumed -.455 44.500 .651 -.13 .294 -.727 .459
Operations Management Equal variances assumed .002 .967 -.575 46 .568 -.16 .272 -.703 .391
Equal variances not assumed -.573 29.788 .571 -.16 .273 -.714 .401
Risk Management Equal variances assumed .080 .780 .316 17 .756 .19 .612 -1.098 1.485
Equal variances not assumed .324 16.506 .750 .19 .596 -1.066 1.453
Strategic Management Equal variances assumed .459 .509 -3.031 14 .009 -2.00 .660 -3.415 -.585
Equal variances not assumed -2.910 10.654 .015 -2.00 .687 -3.518 -.482

As demonstrated by the Independent Samples T-test, there was significance in Digital Skills, Financial Management, and Strategic Management. The significance levels for these content standards were: 0.018, 0.017 and 0.009 respectively. When consulting Table 1.4, it revealed that a larger percentage of the Instructor Group respondents thought that Digital Skills and Strategic Management were more important than the Sports Entrepreneur Group did. Conversely, a larger percentage of the Sports Entrepreneur respondents believed that Financial Management was more important than the Instructor Group believed it to be.

In order to be able to analyze the data and come to any conclusions, one needs to take a closer look at the descriptive data of each research group. It is interesting that the percentages of the gender and ages were pretty close for both respondent groups. Another important figure to note was the high percentage of respondents who indicated that sports entrepreneurship was an elective within their programs. The hardest part of this study to get a handle on was just how many sports management programs offered sports entrepreneurship courses. This high percentage indicated that sports entrepreneurship courses are being offered, but are not required.

For the Sport Entrepreneur Group, it was interesting to see that they were highly educated with college degrees. This is indicative of many entrepreneurs despite what most people may think. Entrepreneurs are often seen as uneducated, risk takers that started businesses because they did not like school, and that was just not the case for the sports entrepreneurs in this study. The Sport Entrepreneur group had a good mix of relatively new businesses and businesses with over 25 years of experience. This makes the results even more interesting because new business owners often make mistakes, and seasoned business owners may have learned from their earlier mistakes.

The 17.9% of the respondents in the Sport Entrepreneur Group that had only one employee is significant. This was an important finding for future research because many of the National Content Standards had skills and traits listed that might not necessarily have corresponded to one employee businesses. For example, if a business only has one employee then a skill like Human Resources Management might not have been beneficial for that business owner to learn. Additionally, for the sport entrepreneurs who made higher revenues, perhaps skills like Financial Management or Economics were more important to them and their business then it was to the small, low-income business.

The results of this study indicate that instructors of sports entrepreneurship courses and sports entrepreneurs agreed on the type of content that should be addressed in a sports entrepreneurship course. The Mann-Whitney U Test performed on the two research groups indicated that there was no significant difference between the groups with regard to how they responded to whether or not CEE’s National Content Standards were all of the skills and traits necessary to be learned in order for sports entrepreneurship students to become successful sports entrepreneurs. This is important for sports entrepreneurship instructors to note when planning course content.

The ranking of the content standards was necessary to show how each group felt about the importance of teaching or learning each individual content standard. Oftentimes, the amount of time it takes to administer an entire sports entrepreneurship course varied. For example, a three credit sports entrepreneurship course at a community college may have been thirty six hours long, whereas a four-year institution may have met for forty-five hours. If both research groups agreed to the top five content standards, then the rankings could have been used by instructors to guarantee that they covered the most important content standards, regardless of the amount of hours required to administer a course.

The results from the ranking of the National Content Standards indicated that each respondent group agreed on four of the five most important content standards: Communication and Interpersonal Skills, Financial Management, Marketing Management, and Business Foundations. The respondent groups did not agree on the fifth most important skill or trait. The Sports Entrepreneurs indicated that Operations Management was the fifth most important skill or trait, whereas the Instructor Group indicated that Human Resource Management was on of the top five most important skills or traits.

Despite the lack of agreement on the fifth most important content standard the results indicated that four of CEE’s National Content Standards were very important to both of these research groups. These results should also aid sports entrepreneurship instructors in planning their course content, especially when limited to teaching only one sports entrepreneurship course and not multiple courses. Although instructors should have no problem teaching more than five topics in one particular sports entrepreneurship course, these results also indicated that all of CEE’s National Content Standards do not have to be taught in order to prepare students to become sports entrepreneurs.

The Independent Samples T-test indicated that there were significant differences between the two research groups in the content areas of: Digital Skills, Financial Management, and Strategic Management. A further analysis of these results indicated that a larger percentage of the Instructor Group thought that Digital Skills and Strategic Management were worthy enough to be included in the top five most important content standards. This was consistent with their wanting to teach more of CEE’s National Content Standards than the Sports Entrepreneurs Group felt was necessary.

The differences between the two research groups in the Financial Management content standard simply indicated that a larger percentage of the Sports Entrepreneurs believed that Financial Management was more important than the Instructor Group believed it to be. It should be noted that 58.1% of the Instructor Group did have Financial Management as a top five most important content standard and that was good enough for that group to be the second most important content standard.

Applications in Sport

This study is relevant to all sports management educators that teach sports entrepreneurship courses. If you are a sports entrepreneurship instructor, then it is up to you to review this study in order to better understand what sports entrepreneurs do on a daily basis. Not every sports entrepreneurship instructor has had the opportunity to be a sports entrepreneur, so one might not be exactly sure of the content that should be taught future sports entrepreneurs. However, this study shows the relevant content sports entrepreneurship instructors should be teaching their students on a daily basis. This study focused on the practice of sports entrepreneurs and identified what skills and traits are needed in the field. All sports entrepreneurship instructors should look at this study and utilize the results for the benefit of their students.

Acknowledgments

The author would like to acknowledge all of the participants, both sports management professors and sports entrepreneurs, for taking the time out of their busy schedules to participate in this study.

References

Consortium for Entrepreneurship Education, National Content Standards for Entrepreneurship Education. Retrieved October 30, 2009, from http://www.entre-ed.org/Standards_Toolkit/standards_summary.htm

Consortium for Entrepreneurship Education, (2001). Entrepreneurship everywhere: A guide to resources and models for entrepreneurship education. Consortium for Entrepreneurship Education, Columbus, OH.

Howard, D., & Crompton, J. (2004). Financing sport, Fitness Information Technology, Morgantown, WV.

Kurtzman, J. (2005). Sports tourism categories, Journal of Sport Tourism, Vol. 10, No.1, p. 15-20.

Sport Management Program Review Council, (2000) Sport management program standards and review protocol, Reston, VA: National Association for Sport and Physical Education.

The North American Society for Sports Management website. All data retrieved on November 20, 2009 from: www.nassm.com.

Corresponding Author

Dr. Anthony Borgese: aborgese@kingsborough.edu

2013-11-25T17:42:32-06:00July 9th, 2010|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off on Educating Sports Entrepreneurs: Matching Theory to Practice
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Training to Improve Bone Density in Adults: A Review and Recommendations

Ed McNeely

Abstract

The loss of bone density is becoming a major health concern in industrialized societies. Increasing bone density during puberty and young adulthood is considered the best option for preventing the negative health consequences associated with osteoporosis, even in middle aged and older adults an exercise program can increase bone density. While low volume impact oriented aerobic activities like running have been shown to be effective at increasing bone density excessive endurance training has been linked to low bone density. Strength training remains the best option for adults wishing to increase bone density. A regular program of high load (60-85% 1RM) training three or more times per week using a variety of exercises that challenge all major muscles has been shown to significantly increase bone density even in elderly adults.

Key Words: Bone Density, Exercise, Osteoporosis, Training

Introduction

Osteoporosis, which has been defined as bone mineral density (BMD) more than 2.5 standard deviations below the young adult mean value (14), is a growing health problem for both men and women. In developed and developing countries, the incidence of osteoporosis is increasing at a rate faster than what would be predicted by the aging of the population alone (15). In the U.S., it has been estimated that by 2025 the number of hip fractures attributed to osteoporosis will double to nearly 2.6 million with a greater percentage increase in men than in women (12).

Epidemiological evidence suggests that genetic factors are the most important cause of osteoporosis (20) and can account for as much as 80% of the variability in bone density in the population (6), but a variety of environmental factors have been linked to bone density including: negative energy balance, low calcium intake, lack of fruit and vegetable consumption, low body mass index, strength, and hormone levels (13,22,9,7,23) – all of which may influence the ability to develop or maintain bone density.

A well designed exercise can have a tremendous impact on bone, increasing density, size, and mechanical strength (23) and may be one of the keys to preventing complications associated with osteoporosis. If bone density and maximum tensile strength are increased before osteoporosis sets in, subsequent complications could be minimized (21). Unfortunately many adults wait to start an exercise program once they are diagnosed with low bone density.

For middle aged and older adults one of the primary health goals of an exercise program is to maintain bone density. Without an exercise intervention, after the age of 40, bone mass decreases by about 0.5% per year, regardless of sex or ethnicity (15). Whether appreciable increases in bone density can occur for this age group is equivocal (15) and dependant on the duration of the exercise program, age, dietary factors, and history of physical activity. A variety of different types of exercise have been used in bone building programs middle aged or older adults.

Training Techniques

Strength training

Although not all studies have shown improvement in bone density with strength training (15), strength training, if done with a high enough intensity for a prolonged period of time, seems to be effective for improving bone density in middle aged and older women who have low bone density (16). Programs that have been successful at increasing bone density have several common characteristics; training intensity above 70% 1RM, programs that last more than 12 months, and training frequency greater than two times per week.

Endurance Training

Endurance training can be an acceptable form of exercise for maintaining or increasing bone density in middle aged or older adults provided there is sufficient impact. Stuart and Hannan (2000) examined the effects of cycling, running, or both on bone density in recreational male athletes. They found that runners had greater total and leg BMD than controls and that those athletes participating in both cycling and running had greater total and arm BMD – whereas the cyclists had decreased spine BMD compared to controls. The lack of impact involved in cycling may explain the lack of change in BMD even though all groups performed equal volumes of work throughout the study period. Walking programs, because of their low impact, tend to show only modest or no effects on BMD (3,18). Rowing, because of the high compressive and shear forces placed on the spine (4.6 times body weight) has been shown to increase lumbar spine BMD but not at other areas (17). Moderate training volumes seem to be more effective for increasing bone density. Running mileage of 20-30 km per week has a positive effect on bone, particularly lower leg and distal femur, but training volumes greater than this may cause a chronic increase in cortisol that negatively impacts bone (4) as running 92 km per week has been shown to result in bone density lower than sedentary controls (2).

Jump training

Although effective and popular in school based programs for increasing bone density in younger people jump training does not appear to be as effective in middle aged and older women. In a study comparing the effects of 12 months of vertical jumping on spine and proximal femur BMD in a group of pre and post menopausal women, Bassey, Rothwell, Littlewood and Pye (1998) found that 50 jumps six days per week increased BMD in the pre-menopausal group but not in the post menopausal group compared to group specific controls. Interestingly, the lack of change occurred even though the ground reaction forces and rate of force development on landing were higher in the post menopausal group resulting in a greater strain overload than in the pre menopausal group.

While a variety of exercise modalities have proven to be effective at maintaining bone density in adults, there are some basic principles that should be considered when designing a long-term program for people with osteoporosis:

Exercise Considerations

Use a Progressive Program

Increase resistance and intensity progressively. This is necessary because for bone to form it requires a minimum amount of strain. Once a bone adapts to a given strain level, the stimulus for bone to form is removed and a higher strain level becomes necessary for it to adapt further (10).

Use Dynamic Movements

Mechanical loading of bone has an osteogenic effect only if the loading is dynamic and variable, as static loading of bone does not trigger an adaptive response (23). Impact and rapid changes of direction can be particularly effective because ground reaction forces tend to be highest during these activities. Jumps, running, and more explosive or dynamic strength training activities should make up the majority of exercise in a bone-building program. In adults with advanced osteoporosis, more explosive exercises should be phased in gradually as their conditioning and bone strength improves.

Vary the Exercises

Bone adaptations occur primarily at insertion and origin points where muscles attach to the bones. Ryan et al. (1994) suggest that increased BMD from strength training and explosive activities is related to the load placed on the muscles that act as prime movers. A wide variety of exercises, which change every 2-4 weeks, exercising the whole body will help ensure that all bones receive stimulus to increase BMC or BMD.

Minimum Intensity

As with most training, there is a minimum level of intensity that is needed to stimulate increase in BMD. For strength training activities there is a linear relationship between weight lifted and improvements in bone density (5). Chilibeck, Sale and Webber (1995) suggest that for strength training intensities of at least 60%, 1RM are needed to increase BMD, with faster and greater increases in bone density coming as intensity climbs (16). For impact activities like running and jumping, ground reaction forces of greater than two times body weight can increase bone density with higher forces having a greater effect.

Training Frequency

Improvements in BMD can occur with relatively short training sessions if high impact activities like jumping are the core of the program. However, there is a need to perform these sessions frequently. Studies of jump training have found that where three or more sessions per week are sufficient to increase bone – two sessions per week has negligible effect on bone density (11).

Program Duration

Consistency is one of the keys to long term bone health. Like other tissues, bone undergoes both adaptation to training and detraining during periods of decreased activity. The bone remodelling cycle lasts four to six months (8); this is the minimum period of time needed for BMD to change significantly. Training programs need to be designed so that they offer the variety and adaptability for people to make them a year round part of lifelong fitness regime.

Conclusion

Decreased bone density is a growing problem in modern societies. Exercise remains one of the most potent alternatives to drug treatments for maintaining or improving bone density. An intensive program, three or more times per week featuring a variety of exercises that considers the individual needs of each person and promotes long term compliance can have a positive impact on bone density.

Applications in Sport

Over the past years, adults have become more and more active in age group sports, particularly in the endurance sports like running, cycling, and triathlon. The inclusion of an intensive strength training program will not only improve their performance, but will help offset the decrease in bone density that often accompanies aging and higher volumes of aerobic training.

References

Bassey, E. J., Rothwell, M.C., Littlewood, J.J., & Pye, D.W. (1998). Pre- and postmenopausal women have different BMD responses to the same high-impact exercise. J. Bone Miner. Res., 13, 1805– 1813.

Bilanin, J., Blanchard, M., & Russek-Cohen, E. (1989). Lower vertebral bone density in male long distance runners. Med Sci Sports Exerc., 21, 66-70.

Cavanaugh, D. J., & Cann, C.E. (1988) Brisk walking does not stop bone loss in postmenopausal women. Bone, 9, 201–204.

Chilibeck, P., Sale, D., & Webber, C. (1995). Exercise and bone mineral density. Sports Medicine, 19, 103-122.

Cussler, E. C., Lohman, T.G. Going, S.B., Houtkooper, L. B., Metcalfe, L.L., Flint-Wagner, H.G., Harris, R.B., & Teixeira, P.J. (2003). Weight lifted in strength training predicts bone change in postmenopausal women. Med. Sci. Sports Exerc., 35, 10 –17.

Dequeker, J., Nijs, J., Verstraeten, A., Geusens, P., & Gevers, G. (1987). Genetic determinants of BMC at the spine and radius: a twin study. Bone, 8, 207–209.

Duncan, C. S., Blimkie, C., Cowell, C.T., Burke, S., Briody, J.N., & Howman-Giles, R. (2002). Bone mineral density (BMD) in adolescent female athletes: relationship to exercise type and muscle strength. Med. Sci. Sports Exerc., 34(2), 286–294, 2002.

Epstein, S. (1988). Serum and urinary markers of bone remodelling: assessment of bone turnover. Endocrine Review, 9, 437-449.

Fisher, J.O., Mitchell, D.C., Smiciklas-Wright, H., Mannino, M.L.& Birch, L.L. (2004). Meeting calcium recommendations during middle childhood reflects mother-daughter beverage choices and predicts bone mineral status Am. J. Clin. Nutr.,79, 698 –706.

Frost, H. (1987). Bone mass and the mechanostat: a proposal. Anat. Rec., 219, 1-9.

Fuchs, R., Bauer, J., & Snow, C.(2001) Jumping improves hip and lumbar spine bone mass in prepubescent children: A randomized controlled trial. J. Bone Miner. Res., 16,148–156.

Gullberg, B., Johnell, O., & Kanis, J.A. (1997). World wide projections for hip fracture. Osteoporosis. Int. 7, 407-413.

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Ryan, A., Treuth, M., Rubin, M., Miller, J., Nicklas, B., Landis, D., Pratley, R., Libanati, C., Gundberg, C., and Hurley, B. (1994). Effects of strength training on bone mineral density: hormonal and bone turnover relationships. Journal of Applied Physiology. 77: 1678-1684.

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Author Profile

Ed McNeely

Ed McNeely is the senior physiologist at the Peak Centre for Human Performance and a partner in StrengthPro Inc. a Las Vegas based sport and fitness consulting company he is also a National Faculty member of the United States Sports Academy

Corresponding Author

Ed McNeely, MS: e.mcneely@rogers.com

2013-11-25T17:43:12-06:00July 9th, 2010|Contemporary Sports Issues, Sports Exercise Science, Sports Management, Sports Studies and Sports Psychology|Comments Off on Training to Improve Bone Density in Adults: A Review and Recommendations
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An Analysis of Leadership Qualities That Influence Male and Female Athletes in Middle School Interscholastic Team Sports

Dr. Raymond Tucker, United States Sports Academy doctoral graduate

Abstract

The purpose of this study was to determine what behavior styles of leadership male and female athletes in middle school interscholastic team sports prefer their coaches use. The study compares those behavior styles of leadership used by coaches on male and female athletes at three different middle schools. The study compares males and females to determine if the preferred behavior styles of leadership are similar.

Results of this study detected a statistically significant difference in the leadership behavior styles by male and female coaches among the middle schools between the following dimensions: (1) democratic behavior and training and instruction, (2) autocratic behavior and training and instruction, (3) social support and training and instruction, (4) positive feedback and democratic behavior, (5) positive feedback and autocratic behavior, (6) positive feedback and social support. The study did detect a statistically significant difference in the behavior styles of leadership used at the different middle schools in the dimensions of autocratic behavior, training and instruction, and positive feedback. This study did not reveal a statistically significant difference between the middle schools in the dimensions of democratic behavior and social support. Finally, the study detected the only statistically significant difference between male and female coaches in middle school interscholastic team sports in the five dimensions of leadership behavior was in training and instruction.

Results of this study indicate that male and female coaches use different leadership behavior styles to deal with male and female athletes in middle school interscholastic team sports. The study reveals that female coaches place more emphasis on the training and instruction behavior style of leadership than male coaches.

This study does not examine which behavior style of leadership is superior for the overall success of an interscholastic middle school athletic program. What follows is the basis for this study, procedures used to conduct the research, an analysis of the data, conclusions, and finally, recommendations for further research on this topic.

Research Questions

This research study entitled An Analysis of Leadership Qualities That Influence Male and Female Athletes in Middle School Interscholastic Team Sports was conducted to answer the following research questions:

  1. Was there a difference in the median scores of the five Leadership Scale of Sports dimensions among eighth grade females in middle school interscholastic team sports?
  2. Was there a difference in the median scores of the five Leadership Scale of Sports dimensions among eighth grade males in middle school interscholastic team sports?
  3. Was there a difference between eighth grade males and eighth grade females who participate in middle school interscholastic team sports in the median scores of the five Leadership Scale of Sports dimensions?
  4. Was there a difference among the three middle schools in the median scores of the five Leadership Scale of Sports dimensions?

Subjects

Subjects for this study were male and female athletes who participated in interscholastic
team sports at their middle schools during their seventh and eighth grade years. The schools selected for this study were three different middle schools from Central Texas which include Bastrop, Cedar Creek, and Elgin middle schools.

Methods

Data for this study was collected using the Leadership Scale of Sports (LSS) questionnaire with the permission of Dr. Packianthan Chelladurai Ph.D at Ohio State University. Athletic coordinators at each school were given verbal directions in person prior to the questionnaires being mailed. The data was analyzed quantitatively using the 15.0 version of Statistical Package for Social Sciences. Several statistical tests were used to analyze the data. The Freidman test is a test used for two-way repeated measures analysis of variance by ranks. This test was used to determine the statistically significant difference based on gender among the three middle schools in at least one of the five dimensions of leadership behavior. The Wilcoxon signed-rank test is a non-parametric statistical hypothesis test used for two related samples or repeated measures on a single sample. In order to determine the location of the difference, a series of Wilcoxon signed-ranks tests using the Bonferroni adjustment to the p-value were administered. Because there are ten comparisons to be measured, 0.05 was divided 10, rendering a new p-value of 0.005 The Kruskal-Wallis test is the non-analog test, an ANOVA; this test was used to compare three or more medians among schools based on gender. In order to determine if there were differences between males and females concerning the median scores on the (LSS), the Mann-Whitney U statistical test was used.

Results

The first research question in this study asked whether there was a difference in the
median scores of the five leadership scale of sports dimensions among eighth grade females in middle school interscholastic team sports. This question can be answered by the results of the Friedman test in Table 1.13, which clearly shows a statistically significant difference among females athletes in at least one of the five leadership scale of sports dimensions of leadership behavior from Bastrop, Cedar Creek, and Elgin middle schools. Based on this data, a series of pair wise comparisons was made to determine where the differences lie by using Wilcoxon signed Rank Test and a Bonferroni adjustment to the p-value. Because ten comparisons were made, 0.05 was divided by by10, to get a new p-value of.005.
The results of the Wilcoxon signed-rank Test in Table 4.13 show a statistically
significant difference at the 0.005 alpha level among the females athletes between
between the following dimensions: (1) democratic behavior and training and instruction, (2) between autocratic behavior and training and instruction, (3) between social support and training and instruction, (4) between positive feedback and democratic behavior, (5) between positive feedback and autocratic behavior, and (6) between positive feedback and social support.
The data in Table 3.13 reveals the first statistically significant difference between the dimensions of democratic behavior and training and instruction among female coaches at the respective middle schools. Female coaches at Bastrop Middle School had a mean score of 3.13 for democratic behavior, and a mean score of 2.1 for training and instruction. Female coaches at Cedar Creek Middle School had a mean score of 2.60 for democratic behavior and a mean score of 2.3 for training and instruction. Female coaches at Elgin Middle School had a mean score of 3.07 for democratic behavior and a mean score of 2.3 for training and instruction. This data clearly shows that female coaches at Bastrop Middle School and Elgin Middle School have a higher regard for the democratic behavior style of leadership compared to the training and instruction style of leadership. Female coaches at Bastrop Middle School ranked the highest in utilizing the democratic behavior style of leadership over training and instruction.

The second statistically significant difference occurred between the dimensions of autocratic behavior and training and instruction. The data in Table 3.13 reveals that female coaches at Bastrop Middle School show a mean score of 2.7 for autocratic behavior and a mean score of 2.1 for training and instruction. Female coaches at Cedar Creek Middle School had a mean score of 2.65 for autocratic behavior and a mean score of 2.3 for training and instruction. Female coaches at Elgin Middle School show a mean score of 3.15 for autocratic behavior and a mean score 2.3 for training and instruction. This data reveals that female coaches at all three middle schools placed a greater emphasis on the autocratic behavior style of leadership compared to training and instruction. Female coaches at Elgin Middle School ranked highest in utilizing the autocratic behavior style of leadership over training and instruction.

The third statistically significant difference occurred between the dimensions of
social support and training and instruction. Table 3.13 reveals that female coaches at Bastrop Middle School had a mean score of 2.88 for social support and a mean score of 2.1 for training and instruction. Female coaches at Cedar Creek Middle School had a mean score of 2.67 for social support and a mean score of 2.3 for training and instruction. Female coaches at Elgin Middle School had a mean score 3.29 for social support and a mean score of 2.3 for training and instruction. This data reveals that female coaches at all three schools have a higher regard for the social support behavior style of leadership compared to training and instruction. Female coaches at Elgin Middle School ranked the highest in utilizing the social support behavior style of leadership compared to training and instruction.

The fourth statistically significant difference occurred between the dimensions of positive feedback and democratic behavior. Table 3.13 reveals that female coaches at Bastrop Middle School have a mean score of 2.06 for positive feedback and a mean score of 3.13 for the democratic behavior style of leadership. Female coaches at Cedar Creek Middle School had a mean score of 2.24 for positive feedback and a mean score of 2.60 for the democratic behavior style of leadership. Female coaches at Elgin Middle School had a mean score of 2.29 for positive feedback and mean score of 3.07 for democratic behavior. The result of this data indicate that female coaches at Bastrop and Elgin middle schools have a higher regard for the democratic behavior style of leadership than positive feedback. Female coaches at Bastrop Middle School showed the highest regard for the democratic behavior style of leadership over positive feedback.

The fifth statistically significant difference occurred between the dimensions of
positive feedback and autocratic behavior. Table 3.13 reveals that female coaches at Bastrop Middle School had a mean score of 2.06 for positive feedback and a mean score of 2.77 for the autocratic behavior style of leadership. Female coaches at Cedar Creek Middle School had a mean score of 2.24 for positive feedback and a mean score of 2.65 for the autocratic behavior style of leadership. Female coaches at Elgin Middle School had a mean score of 2.29 for positive feedback and a mean score of 3.15 for the autocratic behavior style of leadership. This data reveals that female coaches place more emphasis on the autocratic behavior style of leadership compared to positive feedback. Female coaches at Elgin Middle School had the highest regard for using positive feedback over the autocratic behavior style of leadership.

The sixth statistically significant difference occurred between the dimensions of positive feedback and social support. Table 3.13 reveals that female coaches at Bastrop Middle School had a mean score of 2.06 for positive feedback and a mean score of 2.8 for the social support behavior style of leadership. Female coaches at Cedar Creek Middle School had a mean score of 2.24 for positive feedback and a mean score of 2.67 for the social support behavior styles of leadership. Female coaches at Elgin Middle School had a mean score of 2.29 for positive feedback and a mean score of 3.29 for the social support behavior style of leadership. This data reveals that female coaches at the three middle schools have a higher regard for the social support behavior style of leadership compared to positive feedback. Female coaches at Elgin Middle School had the highest score in the social support behavior style of leadership compared to positive feedback.

The second research question of this study asked whether there was a difference in the median scores of the five LSS dimensions among eighth grade males in middle school interscholastic team sports. The results of the Freidman test in Table 5.13 show that among male athletes in the study, there was a statistically significant difference in at least one of the five leadership scale of sports dimensions of leadership behavior. In order to determine the location of the difference, a series of Wilcoxon signed-rank test using the Bonferroni adjustment to the p-value were conducted. Once again, since there were ten comparisons to be measured, 0.05 was divided by 10, rendering a new p-value of 0.005.

The data from the Wilcoxon signed-rank test in Table 8.13 detected a statistically significant difference in leadership styles among male coaches at Bastrop, Cedar Creek, and Elgin middle schools between the following dimensions: (1) between democratic behavior and training and instruction, (2) between the autocratic behavior and training and instruction, (3) between social support and training and instruction, (4) between positive feedback and democratic behavior, (5) between positive feedback and autocratic behavior, and (6) between positive feedback and social support.

The first statistically significant difference between male coaches at the middle schools occurred between the dimensions of democratic behavior and training and instruction. The data in Table 7.13 shows that male coaches at Cedar Creek Middle School had a high mean score of 3.43 for the democratic behavior style of leadership and a mean score of 2.2 for training and instruction. Male coaches at Bastrop Middle School had a mean score of 2.72 for the democratic behavior style of leadership and a mean score of 2.0 for training and instruction. Male coaches at Elgin Middle School had a mean score of 2.95 for democratic behavior and a mean score of 1.6 for training and instruction. The data reveals that the male coaches at three middle schools have a higher regard for the democratic behavior style of leadership than training and instruction. Male coaches at Cedar Creek Middle School showed the highest regard for the democratic behavior style of leadership compared to training and instruction.

The second statistically significant difference occurred between the dimensions of
autocratic behavior and training and instruction. The data in Table 7.13 reveals that male
coaches at Cedar Creek Middle School had a mean score of 3.01 for the dimension of autocratic behavior and a mean score of 2.2 for training and instruction. Male coaches at Elgin Middle School had a mean score of 3.07 for autocratic behavior and a mean score of 1.6 for training and instruction. Male coaches at Bastrop Middle School had a mean score of 2.69 for autocratic behavior and a mean score of 2.0 for training and instruction. The data reveals that male coaches at all three middle schools have a higher regard for the autocratic behavior style of leadership compared to training and instruction. Male coaches at Elgin Middle School ranked highest in utilizing the autocratic behavior style of leadership over training and instruction.

The third statistically significant difference occurred between the dimensions of social support and training and instruction. The data in Table 7.13 reveals that male coaches at Cedar Creek Middle School had the highest regard for the social support leadership style, with a mean score of 3.2, whereas they had a mean score of 2.2 for training and instruction. Male coaches at both Bastrop and Elgin middle schools scored high in the dimension of social support, with means scores of 2.66 and 2.65, respectively. Male coaches at Bastrop Middle School had a mean score of 2.2 for training and instruction and male coaches at Elgin Middle School had a mean score of 1.6. The data reveals that male coaches at the middle schools have a higher regard for the social support behavior style of leadership compared to training and instruction. The data also shows that male coaches at Cedar Creek Middle School have a high regard for the use of the social support behavior style of leadership compared to training and instruction.

The fourth statistically significant difference occurred between the dimensions of positive feedback and democratic behavior. The data in Table 7.13 shows that male coaches at Cedar Creek Middle School had a mean score of 2.26 for positive feedback and a mean score of 3.43 for the democratic behavior style of leadership. Male coaches at Bastrop Middle School had a mean score of 2.0 for positive feedback and a mean score of 2.72 for the democratic behavior style of leadership. Male coaches at Elgin Middle School had a mean score of 1.70 for positive feedback and a mean score of 2.95 for the democratic behavior style of leadership. Male coaches at all three middle schools showed a higher regard for the democratic behavior style of leadership compared to positive feedback.

The fifth statistically significant difference occurred between the dimensions of positive feedback and autocratic behavior. Table 7.13 shows that male coaches at Cedar Creek Middle School had a mean score of 2.26 for positive feedback and a mean score of 3.01 for autocratic behavior style of leadership. Male coaches at Bastrop Middle School had a mean score of 2.01 for positive feedback and a mean score of 2.69 for the autocratic behavior style of leadership. Male coaches at Elgin Middle School had a mean score of 1.70 for positive feedback and a mean score of 3.15 for the autocratic behavior style of leadership. The data reveals that male coaches at the three middle schools have a higher regard for the autocratic behavior style of leadership compared to positive feedback. Male coaches at Elgin Middle School ranked the highest in utilizing the autocratic behavior style of leadership over the positive feedback behavior style of leadership.

The sixth statistically significant difference occurred between the dimensions of positive feedback and social support. The data in Table 7.13 reveals that male coaches at Cedar Creek Middle School had a mean score of 2.26 for positive feedback and a mean score of 3.21 for the social support behavior style of leadership. Male coaches at Bastrop Middle School had a mean score of 2.01 for positive feedback and mean score of 2.66 for social support. Male coaches at Elgin Middle School had a mean score of 1.7 for positive feedback and a mean score of 2.65 for the social support behavior style of leadership. The data indicates that male coaches at the three middle schools place a higher regard on using the social support behavior style of leadership over positive feedback.

The third research question in this study asked whether there was a statistically significant difference between eighth grade males and females in middle school interscholastic sports in the median score of the five leadership scale of sports dimensions. This question was answered using the Mann-Whitney U test to compare the median scores between male and female student athletes and the unpaired t-test. The data in Table 9.13 reveals the only statistically significant difference in means between male and female students was for the training and instruction behavior style of leadership. The difference was not statistically significant for any of the other four dimensions of leadership behavior styles preferred by males and females at any of the three middle schools. The data in Table 10.13 shows a mean score of 1.99 for males, and a mean score of 2.22 for females at Bastrop, Cedar Creek, and Elgin middle schools for the dimension of training and instruction. The data also shows female coaches have a higher regard for the training and instruction behavior style of leadership than male coaches.

The fourth research question asked whether there was a difference among the three
middle schools in the median scores of the five leadership scale of sports dimensions. The data in Table 11.13 reveals the first statistically significant difference occurred within the dimension of autocratic behavior between Bastrop Middle School and Elgin Middle School. The data in Table 12.13 displays the second statistically significant difference within the dimension of training and instruction between Cedar Creek Middle School and Elgin Middle School. The data in table 13.13 detects the third statistically significant difference within the dimension of positive feedback between Cedar Creek Middle School and Elgin Middle School. This difference was determined by the Bonferroni adjustment, which gave a new p-value of 0.017. The data did not reveal a statistical difference for the dimensions of social support and the democratic behavior styles of leadership among the three middle schools.

Discussion and Implications

In answering the first research question, the researcher will discuss the statistically significant differences among female coaches between the following dimensions: (1) democratic behavior and training and instruction, (2) autocratic behavior and training and instruction, (3) social support and training and instruction. Female coaches at all three middle schools did not place much emphasis on the training and instruction behavior style of leadership. Instead more emphasis was placed on the democratic and autocratic behavior styles of leadership. These behavior styles of leadership do not enhance athletic performance or improve athletic ability. The data in Table 2.13 reveals a high mean score of 2.88 for the dimension of democratic behavior among female coaches at the middle schools in this study. The data also shows a high mean score of 2.79 for the dimension of the autocratic behavior style of leadership among the female coaches at the three middle schools in this study. The social support behavior style of leadership had a mean score of 2.87. The data indicates female coaches at the three middle schools use the social support behavior style of leadership in their daily interaction with athletes. The data reveals the training and instruction behavior style of leadership has the lowest mean scores among the female coaches at the three middle schools with a mean of 2.23.

In the dimensions of (4) positive feedback and democratic behavior, (5) positive feedback and autocratic behavior, and (6) positive behavior and social support, female coaches at the three middle schools did not place much emphasis on the positive feedback behavior style of leadership. Instead, they placed more emphasis on the democratic and autocratic behavior styles of leadership. This means the coaches place more emphasis on controlling an athlete, giving them the opportunity to express their opinions, and helping an athlete through problems, than encouraging and reinforcing good behavior in athletes.

In order to discuss the second research question, the researcher will discuss the statistically significant differences among male coaches: (1) democratic behavior and training and instruction, (2) autocratic behavior and training and instruction, (3) social support and training and instruction. According to the data in Table 6.13 male coaches at the three middle schools did not place much emphasis in the training and instruction behavior style of leadership compared to the democratic, autocratic and social support behavior styles of leadership. Male coaches had a mean score of 2.98 for democratic; 2.87 for autocratic and a 1.98 for training and instruction. In the dimensions of (4) positive feedback and democratic behavior, (5) positive feedback and autocratic behavior, (6) positive feedback and social support, male coaches did not place much emphasis in the positive feedback behavior style of leadership compared to democratic behavior, autocratic behavior and social support. As with female coaches, male coaches placed more emphasis on the democratic and autocratic behavior styles of leadership. According to the date more emphasis was placed on controlling an athlete, giving them the opportunity to express their opinions, and helping an athlete through problems, than encouraging and reinforcing good behavior in athletes.

In looking at the third research question, the data in Table 10.13 reveals a statistically significant difference for the dimension of training and instruction between male and female coaches at the three middle schools for this study. Male coaches had a mean score of 1.99, and female coaches had a mean score of 2.22. According to the data, female coaches scored higher than male coaches in utilizing the training and instruction behavior style of leadership in their daily interaction with athletes. Furthermore, female coaches at Cedar Creek and Elgin Middle Schools had a mean score of 2.3. The data shows for training and instruction, male coaches at Cedar Creek Middle School had a mean score of 2.2. This data also reveals that between male and female coaches at Bastrop Middle School, Cedar Creek Middle School, and Elgin Middle School, female and male coaches at Cedar Creek Middle School and female coaches at Elgin Middle School have a high regard for the dimensions of training and instruction behavior style of leadership.

In discussing the fourth research question, the data reveals a statistically significant difference among male and female coaches at the three respective middle schools for this study. The results of the Kruskal-Wallis test show that for autocratic behavior, there was a statistically significant difference between Bastrop and Elgin middle schools. The data reveals that both male and female coaches at Elgin Middle School have a higher regard for the autocratic behavior style of leadership in their daily interaction with their athletes.

The second statistically significant difference among male and female coaches at the middle schools was for the dimension of training and instruction between Cedar Creek and Elgin middle schools. This data reveals the training and instruction behavior style of leadership is the style preferred by male and female coaches at Cedar Creek Middle School. The third statistically significant difference was for the dimension of positive feedback among male and female coaches at Cedar Creek, and Elgin Middle Schools. The data indicates that male and female coaches at Cedar Creek Middle School have a high regard for the positive feedback behavior style of leadership when interacting with their athletes.

Recommendations

The author of this study makes the following recommendations for further research. First, further research is needed on the leadership behavior styles used by coaches in athletics today and the effect these behavior styles have on athletes. Future research should focus on how the various leadership styles contribute to a successful and winning athletic team. The second recommendation is for future researchers to focus the study on male and female athletes who participate in middle school interscholastic athletics and then conduct another study high school interscholastic athletics in the same school district during their senior year to determine if there was a change in their preferred behavior style of leadership. In addition, if there is a change, research should examine the factors behind the change from middle school to high school intercollegiate athletic programs. The third recommendation is to have other researchers conduct the same study at middle school intercollegiate athletic programs in other school districts, and then compare the school districts results to determine if there is difference between school districts. The last recommendation concerns the methodology used in this study. Future studies should allow for participation from all subjects, regardless of whether or not they participated in athletics during their seventh grade year or more then one sport during their eight grade year.

Finally, it is important to note that a factor that contributed to the researcher’s success in this study was having a strong relationship with the head coaches at the middle schools used in the study. This made it very easy to collect the data. The coaches had an interest in this study and were eager to find out the results.

It is the goal of this study that coaches consider the data in this study and use it to improve on the leadership behavior styles they use in their daily interaction with athletes. Researchers should pursue additional studies on this topic and coaches should look into this and similar studies to improve their interaction with athletes in interscholastic middle school athletic programs.

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2013-11-25T19:24:46-06:00April 8th, 2010|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off on An Analysis of Leadership Qualities That Influence Male and Female Athletes in Middle School Interscholastic Team Sports
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Making the Grade: Academic Success in Today’s Athlete

Jennifer Dilley-Knoles, North Central Texas College; Jeffrey S. Burnett, Fort Hays State University; Kayla W. Peak, Tarleton State University

Abstract

The overall importance placed on an athlete’s academic eligibility can be extremely stressful for both the coach and the student-athlete. In order to compete the athlete must remain academically eligible; thus, various academic support programs have been implemented by athletic departments as a means of maintaining eligibility and ensuring academic progress. Although these programs are vital to assisting student-athletes in accomplishing the goal of academic success, the question remains ‘Are they successful?’ This study found that academic support programs were successful as they related to female student-athlete’s overall GPA. Yet, male student-athletes were not as successful. In fact, a significant difference was found between intercollegiate sports teams and overall GPA; interestingly, all of the female sports teams had significantly higher GPAs than did their male counterparts. It appears that academic support programs are not a ‘one size fits all;’ male student-athletes may need a different type of program in order to achieve academic success. A standard format for study hall may not be an appropriate method for helping today’s athlete to ‘make the grade’.

Keywords

Academic success, academic support programs, athletics, student-athletes

Introduction

Athletics has a history of importance in American society. Across the country, newspapers have devoted entire sections and televisions have created entire channels dedicated to covering the latest updates on sports. Attention has not always been solely about games and competitions; the spotlight has recently been redirected to academics. This is quite a change since 1983, when only 25 (out of more than 16,000) high school districts had even minimal academic standards as a condition of high school sports (Edwards, 1984). Today, athletes wanting to participate in intercollegiate athletics must meet specific academic criteria before being added to a sport’s roster.

Over the last few years, the National Collegiate Athletic Association (NCAA) has intervened and created firm standards for academic performance among member institutions. Programs with incentive and disincentives have been created to reward sport teams that do well academically, while penalizing those that do not. Their goal is to encourage improvement of academic performance of all student-athletes on all sports teams (Meyer, 2005).

The NCAA requires member institutions to distribute graduation rates to prospective student-athletes and/or their parent(s) or guardian(s) to ensure athletes and their families are made aware of the academic reputation of the institutions they are considering. Recruits considering various universities should answer two important questions: which institution will provide the best athletic experience, and second, which will provide the best academic experience (Lucas & Lovaglia, 2005). In a 2006 report aimed to assist high school students in choosing a college, reporter Carolyn Thornton interviewed David DeBloise of the College Planning Center in Rhode Island. In Thornton’s interview, DeBloise stated that the key to choosing the right college is to find one that offers a balance of both academics and athletics. DeBloise offered a long list of questions for students preparing themselves for college. Among them: What is the school’s academic reputation, and does the school offer support services, such as a writing center, academic advising center, and computer facilities? In the conclusion of the interview, “DeBlois’ parting advice to anyone working through this process: maintain the perspective that you are a ‘student-athlete,’ not an ‘athlete-student’” (Thornton, 2006, p.13).

With academic importance and expectations increasing, universities across the country have launched a variety of academic services for their athletes. According to Foltz (1992):

Data have shown the individual student-athlete has suffered from an educational system that has not prepared him or her well for institutions of higher learning. Their training through the educational system has left a number of student-athletes with inadequate skills necessary for academic success in college. (p. 4)

In an attempt to remedy problems associated with participating in intercollegiate athletics, many institutions offer services to assist and monitor their student-athlete’s academic progress. Shining light on the area of academics may not only increase the number of athletic departments offering specialized academic support services and monitoring strategies, but may also increase the academic success of student-athletes.

Pressure placed on athletes to win may have a detrimental effect on the student’s commitment to be successful in the classroom (Lance, 2004). Although it does not justify poor or absent course work, it does illustrate the importance behind increased monitoring strategies. Role conflict may hinder a student-athlete’s ability to reconcile this dual status as both student and athlete (Sack & Thiel, 1985). While academic support services may help member institutions solve the academic problems many colleges and universities face (Hobneck, Mudge, & Turchi, 2003), the intent is to exchange the athletic performance for a quality education (Edwards, 1984).

There is a need for interference of athletic participation and academic performance (Akker, 1995). Faculty, coaches, and athletic administrators must be knowledgeable and responsive regarding the student-athlete’s academic performance. According to Peak (1995), “the student-athlete must remain academically eligible in order to participate in intercollegiate athletics” (p. 2); thus, study halls are often developed to assist struggling student-athletes.

The ability to identify possible contributing factors of academic success might be valuable in providing a basis for academic support or required study halls. Knowing a generalized history of the most rigorous academic year for students may be useful in deciding a target population to assist. In addition, athletes in some sports may rarely struggle, while some may be notorious for their academic shortcomings. Identifying whether or not there is a difference in the academic performance of female athletes and male athletes, or between freshmen/sophomores and juniors/seniors could be beneficial in creating the most advantageous academic services. Recognizing areas of potential struggle might be valuable in helping facilitate academic services for student-athletes.

During February 2005, the NCAA released its first Academic Progress Rate (APR) for Division I football and basketball programs (NCAA, 2005). The desired outcome behind the APR was to motivate athletic programs to become more involved with the academic success of their athletes, thus peaking the student’s interest in attending institutions with a higher APR. APRs are based on the eligibility and retention of student-athletes. Recruits and their parent(s) or guardian(s) find it important to know which institutions are likely to not only keep students academically eligible, but also retain the student-athletes through graduation (Lucas & Lovaglia, 2005). Distributing APRs may help prospective student-athletes become more interested in pursuing not only a successful athletic career, but also a successful academic career. The NCAA (2005) believed that, over time, the best athletes would then begin attending the successful academic schools, ultimately increasing athletic and academic success. Once the desired transition takes place, it is assumed the negative perceived relationships between athletics and academics will become positive.

Using cumulative college grade point averages (GPA) as a measure of academic performance (Foltz, 1992), studies have indicated that athletic participation has had a positive impact on academic achievement, despite the additional responsibility athletic participation requires (Sack & Thiel, 1985; Lance, 2004; Hobneck, Mudge, & Turchi, 2003). Research by Foltz (1992) found that athletes performed at a higher academic level in-season than out-of-season. Gender has become a major influence on the predictor of academic performance possibly due to the reported role conflict being greater among males versus female (Sack & Thiel, 1985). Foltz (1992) reported female athletes’ college GPAs were found to be higher than their male student-athlete counterparts. Although gender may be a predictor of possible academic stress, student-athlete classification was not. Average GPAs of freshmen were identical to the GPAs of seniors-while sophomore and junior GPAs were identical. However, Foltz (1992) found no link between type of sport participation and GPA.

A great deal of importance has been placed on academic services and there has been a strong demand for quality student-athlete support services in terms of tutorial services, academic advising, and teaching study skills (Pope & Miller, 1999). Over the last several years, the NCAA has taken many actions to strengthen its academic requirements and to provide better outcome measures. Nationwide, universities are grasping the idea behind this action and more support services and more ways to monitor academic progress are being provided to help athletes succeed. In order to assist student-athletes in accomplishing the goals of academic success and graduation, it is essential to identify areas for improvement.

Statement of the Problem

The purpose of the study was to investigate academic success, via grade point average among baseball, men/women basketball, men/women cross-country, football, men/women golf, softball, women’s tennis, men/women track and field, volleyball, and wrestling at a small NCAA Division II institution. Academic success was defined as earning a GPA of 3.0 or above. The following research questions were posed:

  1. Would there be a significant difference in grade point averages among the intercollegiate sports teams?
  2. Would there be a significant difference in grade point averages between the male and female student-athletes?

Methodology

The participants for this study consisted of 379 male and female collegiate student-athletes who participated in any of the following sports during the 2006-2007 academic year at the institution being researched. Of the 379 participants, there were 266 males and 113 females who comprised the 14 sports teams (see Table 1).

Table 1
Subjects – By Gender and By Sport

Sport Male Female
Baseball 40 n/a
Basketball 16 16
Cross-Country 12 06
Football 90 n/a
Golf 06 06
Softball n/a 17
Tennis n/a 12
Track ∓ Field 60 40
Volleyball n/a 16
Wrestling 42 n/a
Total 266 113

The eligibility rosters were obtained through the University’s compliance coordinator and contained all student-athletes eligible or ineligible to compete during the 2006-2007 season. Only student-athletes who were on a team for the consecutive fall 2006 and spring 2007 semester were used for the study; all other participants were excluded. The participation statistics for each sport were obtained through the head coach and the compliance coordinator at the institution. As an additional criterion, only student-athletes who participated in a contest or match were used for the study; all other participants were excluded. Thus, reducing the total population for the study to 251 student-athletes (N=251).

A 4.0 scale was used as the measurement value of grade point average. The points per credit hour earned were assigned as follows: each credit of A = 4 points; each credit of B = 3 points; each credit of C = 2 points; each credit of D = 1 point; each credit of F = 0 points. Cumulative GPA was calculated by dividing the total points earned by the number of credit hours attempted.

The registrar’s office provided information related to each student-athletes’ academic status and GPA. The data was then analyzed to determine if there was a difference in academic success among intercollegiate sports teams and gender using GPA. Statistical Package for the Social Sciences 16.0 was used to calculate the statistics. For the purpose of this study, the alpha level was set at .05.

Results

Utilizing an ANOVA to analyze the data, the results of this study yielded that there was a significant difference in grade point averages between intercollegiate sports teams. Since the significance of the 2-tailed test was less than the alpha level at .05, there was a significant difference between grade point averages and sports (see Table 2).

Table 2
Grade Point Averages between Intercollegiate Sports Teams

Grade Point Averages Intercollegiate Sports Teams
Mean 2.9650 8.48
N 251 251
Standard Deviation .56963 4.179
Significance .000

In order to determine which sports teams had significantly different grade point averages, the researcher conducted a Between-Subjects Effects test (see Table 3). The results showed that there was a significant difference in grade point average among all of the female sports (basketball, cross-country, golf, tennis, track, softball, and volleyball) as compared to the other intercollegiate sports teams (see Table 4).

Table 3
Tests of Between-Subjects Effects

Source Type III
Sum of Squares		 df Mean Square F Sig.
Corrected Model 14.536 1 14.536 54.358 .000
Intercept 2069.314 1 2069.314 7738.47 .000
Gender 14.536 1 14.536 54.358 .000
Error 66.584 249 0.267
Total 2287.688 251
Corrected Total 81.120 250

Table 4
Means per Intercollegiate Sports Teams

Sport Mean Standard Deviation N
Baseball (M) 2.9276 0.43374 33
Basketball (F) 3.2773 0.47559 11
Basketball (M) 2.555 0.6663 12
Cross-Country (F) 3.4362 0.52196 13
Cross-Country (M) 2.7436 0.65531 11
Football(M) 2.7454 0.5336 50
Golf (F) 3.246 0.46231 5
Golf (M) 2.8986 0.4482 7
Softball (F) 3.1831 0.49035 13
Tennis (F) 3.33 0.56353 7
Track (F) 3.2465 0.45389 26
Track (M) 2.8295 0.63888 38
Volleyball (F) 3.5575 0.2307 8
Wrestling (M) 2.7747 0.33834 17
Total 2.965 0.56963 251

Lastly, the researcher concluded that the female student-athletes had a significantly higher grade point average than the male student-athletes (see Table 5).

Table 5
Gender (Dependent Variable: GPA)

95% Confidence Interval
Gender Mean Standard Error Lower Bound Upper Bound
Male 2.796 0.04 2.717 2.874
Female 3.307 0.057 3.196 3.419

Conclusion

Based upon the results of this study, the following conclusions were drawn:

  1. A significant difference was found between grade point averages and the various intercollegiate sports teams.
  2. A significant difference was found between male and female student-athletes as it related to their grade point averages.

Discussion

It is apparent that this research study affirms the trend of female student-athletes performing at significantly higher academic levels than their male counterparts. Yet, academic support programs, for both male and female student-athletes, have been a mainstay within most athletic departments since the mid-1980s. As professionals, we must ask ourselves why many male student-athletes continue to earn lower GPAs than their female peers. We must also ask ourselves how we may be able to close this academic gap. What programs can be implemented to ensure the overall success of both genders, yet concentrate on those athletes, mostly males, who may struggle academically? Perhaps it is not just a matter of academic support services and study halls; rather the trend is directly related to role conflicts and adjustments to collegiate life. Serious thought should be given to the long-term academic success of the student-athlete. The NCAA has been proactive in establishing programs to try to help ensure student-athlete success. These programs are vital in assisting student-athletes accomplish their goals of academic and athletic success. However, the formula for success is a dynamic and holistic concept and may require uniquely different approaches as it relates to each intercollegiate sports team as well as gender. The old adage “one size fits all” may not be an appropriate method for helping today’s athlete to make the grade.

Discussion

Akker, K.V. (1995). Athletic participation and the academic achievement of athletes. Unpublished master’s thesis, Ball State University, IN.

Edwards, H. (1984). The collegiate athletic arms race: Origins and implications of the ‘Rule 48’ controversy. Journal of Sport and Social Issues, 8, 4-22.

Foltz, R.A. (1992). Academic achievement of student-athletes. Unpublished master’s thesis, Fort Hays State University, KS.

Hobneck, C., Mudge, L., & Turchi, M. (2003). Improving student athlete academic success and retention. Saint Xavier University, Chicago, IL.

Lance, L.M. (2004). Gender differences in perceived role conflict among university student-athletes. College Student Journal, 38(2), 179-190.

Lucas, J.W., & Lovaglia, M.J. (2005). Can academic progress help collegiate football teams win? The Sport Journal, 8(3). Retrieved from http://www.thesportjournal.org/

Meyer, S.K. (2005). NCAA academic reforms: Maintaining the balance between academics and athletics. Phi Kappa Phi Forum, 85(3), 15-18.

National Collegiate Athletic Association. (2005, February). Academic progress rate data report information. Retrieved from http://web1.ncaa.org/web_files/Misc_Committees_DB/CAP/Membership%20Teleconference%20Materials/February%202005/APR_Data_Report_Information.pdf

Peak, K.W. (1995). An investigation of the academic progress of selected intercollegiate athletes involved in two types of academic support programs. Unpublished master’s thesis, East Texas State University, TX.

Pope, M.L., & Miller, M.T. (1999). Support services for student-athletes: Athletic department and student affairs officers perceptions. (ERIC Document, Reproductions Service No. ED437886).

Sack, A.L., & Thiel, R. (1985). College basketball and role conflict: A national survey. Sociology of Sport Journal, 2, 195-209.

Thornton, C. (2006, July 17). College-bound athletes need to assess ability. The Providence Journal. Retrieved May 4, 2009, from http://www.projo.com/sports/content/projo_200060618_spparent3.1f1d7724.html

2017-08-03T10:33:56-05:00January 8th, 2010|Contemporary Sports Issues, Sports Management, Sports Studies and Sports Psychology|Comments Off on Making the Grade: Academic Success in Today’s Athlete
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Making College Football’s Postseason Fair, Legal and Ethical While Preserving its Unique Traditions

By Dr. Kelly E. Flanagan, United States Sports Academy

Abstract

Controversy continues to surround college football bowl games, especially when official championship events became the norm in professionals sports, college sports, end even college football in the lower division levels. The public demand for a “national championship game” led to the formation what is now called the Bowl Championship Series (BCS). The issue is now more than just of fan popularity, but also legality. There are public officials that believe the fact that undefeated teams from smaller universities continue to be excluded from the BCS title game, makes it a violation of the letter, if not the spirit, of the Sherman Anti-Trust Act and that make advertising the BCS Championship Game as a “National Championship” is actually false advertising. The author, who has an educational background that specializes in college football bowl games, attempts to create a solution that preserves college football’s unique bowl tradition and resolves the legal and ethical issues surrounding the BCS.

The Every Bowl Counts (EBC 1-2-3) Plan

The National Collegiate Athletic Association (NCAA) recognizes an official national champion and national championship event in every sport at every level except football in the Football Bowl Subdivision (FBS) of Division One, which is the association’s marquis product, made up of 120 Division One athletic programs.

Bowl games are a college tradition dating back to 1902, ending college football’s regular season long before the National Football League (NFL) existed. In fact, the NFL played its first 12 seasons before having a championship game.

However, in today’s sport culture, fans expect to recognize a champion. An official national champion is recognized in all other levels of college football and every other NCAA sport.

But what has transpired in major college football is a tradition the brings exposure to various communities around the country, allows 34 teams to finish the season with a victory and allows coaches to take 3-4 extra weeks of practice to develop their younger players.

The fact that there is a national champion, albeit unofficial, is touted by those who defend the status quo. “Every week is a playoff,” University of Georgia Head Football Coach Mark Richt once said. Defenders of the status quo say that college football’s regular season is the most exciting in all of sports.

The popular demand for a national championship game was used as justification for the creation of the Bowl Championship Series (BCS), which would allow the teams ranked No. 1 and No. 2 to play each other in a bowl game at the end of the season. The rankings system was based on a combination of the Associated Press (AP) media poll, the USA Today Coaches Poll and several computer-based ranking systems. Eventually, AP backed out of the process and the Harris Interactive poll was used in its place.

The ranking system and other aspects of the bowl culture have proven, over time, that conferences with larger, wealthier athletic programs and teams with a long tradition of successful football have an advantage in this system. Teams that have finished the season undefeated that are from smaller conferences do not have the option of changing conferences unless allowed by the conferences’ current members. Such a system has brought about questions from public officials as to whether this situation is a violation of the spirit, if not the letter, of the Sherman Anti-Trust Act. Often used in cases involving football, the Sherman Anti-Trust act prohibits illegal monopolies that are used to suppress competition.

Bowl committees in the BCS (Rose, Allstate Sugar, FedEx Orange and Tostitos Fiesta) continue to host the “major” bowl games and make a lion’s share of the bowl money, but they collectively award automatic bowl bids to teams that are in the BCS conferences, which could also be interpreted as an illegal trust.

Three teams finished the regular season undefeated in 2009 without getting to play in the BCS “National Championship” game. Two of those teams were not in the aforementioned “major” conferences. Two other teams from outside the “major” conferences finished the regular season undefeated without playing in the BCS Championship game. The participants in the first 12 BCS championship games were all from the “major” conferences: The Big 12, Big East, Big 10, Atlantic Coast, Pacific 10 and Southeastern.

Also, denying undefeated teams a chance to play in the BCS Championship game has led to some critics saying that to promote the event as a “National Championship Game” is actually false advertising.

Public officials as well as fans have been critical of college football in its current state. But the author believes that to preserve the bowl tradition, the significant regular season and the integrity of the national championship process would require some thinking “outside the box.” College football is a unique sport genre and requires a unique approach to change. The process that the author is suggesting is partially inspired by the Major League Baseball All-Star Game as well as the Davis Cup professional team tennis tournament.

Some have suggested that the bowl games be used as venues for playoff games, but that would significantly decrease attendance as fans would be expected to travel on a week’s notice. The NFL does not even have a neutral-site postseason game until the final game, the Super Bowl. Small college football playoffs are structured the same way. Postseason events in other college sports have more than two university teams participating at each site.

Having a playoff outside the bowls would further decrease the interest in bowl games for the neutral fans. But the author believes there is a way to keep the fan interest in bowl games without making all of them into playoff venues.

Hence, the title of the proposal is called “Every Bowl Counts,” also called the “EBC 1-2-3” program.

I. Playoffs

  1. Schedule
    Upon conclusion of the college football bowl season, there will be a four-team playoff tournament sponsored by the National Collegiate Athletic Association (NCAA) for the Division One Football Bowl Subdivision (FBS). The semifinals of the tournament will be held 7-11 days after the conclusion of the Bowl Championship Series (BCS) bowl games. The game now known as the BCS Championship Game will be discontinued.
  2. Participants
    The participants will be the winners of the four BCS bowl games, which will now be known as Playoff Bowl Games.
  3. Location
    The semifinal games will be played at the home stadiums of the higher-ranked teams in the field. The finals will take place at a neutral site.

II. Qualification

  1. For Playoff Bowl Games
    1. Ranking system — A ranking system will be developed to determine the “At-large” invitees to the Playoff Bowl Games and for seeding of the teams participating in such games. This system will be derived from a formula developed using regression analysis to determine the weight of factors that correlate with success in the previous 10 years of NCAA Division One Football Championship Subdivision (FCS) playoffs and Division Two playoffs. Ten years after the beginning of the EBC 1-2-3 program, the formula will be refigured to where it reflects factors contributing to success in the first 10 years of the Division One FBS playoffs.
    2. Automatic qualification — Certain conferences will be selected as “Automatic Qualifiers” each year. In order to obtain such status, teams from a conference must win three non-BCS bowl games, further known as Non-Playoff Bowls, during the previous season. Champions of these conferences will automatically receive an invitation to participate in Playoff Bowl Games.
    3. The Boise State Rule — Any team that is undefeated and has defeated 11 Division One FBS teams during the regular season (including conference championship games) will receive first priority in filling Playoff Bowl positions after the automatic qualifiers have been determined.
    4. Limitation — No conference will be represented by more than two teams in the Playoff Bowl Games.
    5. The ranking system alluded to in section IIA1 will be used to determine which teams fill the remaining positions in the Playoff Bowl Games after the provisions of sections IIA2 and IIA3 have been met.
  2. For Non-Playoff Bowl Games
    1. First-Tier Bowl Eligible Teams will receive first priority when being invited to Non-Playoff Bowl Games. To be classified as a First-Tier Bowl Eligible Team, a team must defeat six Division One FBS teams in its first 12 games of the regular season and finish either
      1. Among the top five in the standings of a non-divided conference (one that does not have a championship game) or
      2. Among the top three in a division of a divided conference (one that does have a championship game).
    2. Second-Tier Bowl eligible teams are ones that defeat six Division One FBS teams but do not meet the other criteria of First-Tier Bowl Eligible Teams. These teams can be invited to Non-Playoff Bowl Games once the First-Tier Bowl Eligible Teams have accepted their bowl invitations.

III. Matchups

  1. For Playoff Bowl Games
    1. Seeds — The system alluded to in Section IIA1 will be used to seed the playoff teams, first through eighth.
    2. Placement — The top four seeds will be assigned to bowl games according to their geographic location. The teams seeded 5-8 will be assigned according to their ranking (No. 1 vs. No. 8, No. 2 vs. No. 7, No. 3 vs. No. 6 and No. 4 vs. No. 5).
  2. For Semifinals
    The winners of the Playoff Bowl Games will be re-seeded, with the No. 1 team playing host to the No. 4 team and the No. 2 team playing host to the No. 3 team.

IV. First-year exception

During the first year of the EBC 1-2-3 program, the seeding process will be used to determine all eight playoff participants. This will keep from the major bowl games from losing their significant in the final season before the EBC 1-2-3 program would begin.

Commentary

The Boise State rule is designed to assure that undefeated teams have an opportunity to play for a national championship. The fact that only two teams will have to play more than one neutral-site game softens travel concerns that would be an issue in a playoff system that every round in a bowl site.

The EBC aspect, where three non-playoff bowl victories in one season gives a conference an automatic playoff bid the following season, would make the games that are now called non-BCS bowls more meaningful than they are now.

The EBC also keeps the major conferences from being “grandfathered in” to the playoff bowl games like they are now in the Bowl Championship Series games. The Tire I playoff rule keeps the larger conferences from “packing” the non-playoff bowls to improve their playoff chances for the following year. Every deserving team will get a postseason bid.

This system actually enhances the significance of 33 of the existing 34 bowl games. And it still preserves the excitement of the regular season. In the NFL you have 32 teams playing 16 games each to see which 12 go to the playoffs. In the National Basketball Association, you have 30 teams playing 82 games each to see which 16 got to the playoffs. In Major League Baseball, you have 30 teams playing 162 games to see which eight go to the playoffs. But, under this system, you have 120 teams playing 12-13 games each to determine which eight go to the playoffs.

Note: Dr. Kelly E. Flanagan is Director of Development at The United States Sports Academy and a member of the faculty since 2005. A student of the college football postseason process, Dr. Flanagan completed his master’s mentorship with the Jeep Aloha Bowl/O’ahu Bowl Doubleheader in 1999 and the Chick-fil-A Peach Bowl in 2002. He also served on the Atlanta Local Organizing Committee for the 2003 NCAA Women’s Basketball Final Four and wrote a dissertation titled “Factors Affecting Institutional Ticket Sales at College Football’s Non-Bowl Championship Series Postseason Events” when completing his Doctor of Sports Management degree at the Academy.

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2017-11-02T13:56:40-05:00January 8th, 2010|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off on Making College Football’s Postseason Fair, Legal and Ethical While Preserving its Unique Traditions
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The Sport Jounral

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ISSN: 1543-9518
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