Websites as Help in the Recruiting Process: An Analysis of NCAA Women’s Cross Country Programs

Abstract

Universities are beginning to explore the Internet as one avenue for recruiting student-athletes, an avenue of potential use in nearly every phase of the process (Hornbuckle, 2001). Given the difficulty of recruiting for nonrevenue sports, as well as the concerns of NCAA divisions that have little or no recruiting budget, use of the World Wide Web for recruiting may hold great importance (Hornbuckle, 2001; Walsh, 1997). The purpose of this research was (a) to determine what content is featured on websites maintained by NCAA women’s cross country programs, (b) to observe any differences between NCAA divisions as to the frequency of exhibiting content, and (c) to determine areas that could be strengthened to enhance recruiting potential. A content analysis was used to analyze randomly sampled NCAA women’s cross country websites (N = 108). In general, it was found that the sites provided basic information that might be of interest to recruits, such as information about the coach and a means to submit personal information to the coach. Few sites included coaching philosophy, highlighted individual athletes, or contained photo albums, all relevant information that might be of interest to potential recruits.

Websites as Help in the Recruiting Process: An Analysis of NCAA Women’s Cross Country Programs

Recruiting potential student-athletes represents an important component of collegiate athletics. For students, the would-be recruits, “selecting a college is a time-consuming and difficult process” (Kirk & Kirk, 1993, p. 55). This process, at least for student-athletes, involves the consideration of several factors, including but not limited to a school’s geographic location, whether it is urban or rural, size of student population, academic and athletic reputations, and graduation rates, both for all student-athletes and for student-athletes in the sport of interest only (Kirk & Kirk, 1993). Students who wish to be recruited must sift through a great deal of information, often presented with clear bias. As Caryer (1996) notes,

If the student just listens to the stories, recruiting can be overwhelming; if he [she] actively seeks specific information needed to decide how to reach his [her] goals, the coaches tell him what he needs to know rather than a lot of impressive, but irrelevant stuff. (p. 13)

This highlights the importance of athletic departments presenting information for potential recruits in an efficient yet pleasing manner.

From the perspective of a coach, the recruiting process takes on greater importance with each passing year. According to Klenosky, Templin, and Troutman (2001), “Universities allocate a large portion of their athletic department funds each year for recruiting top student-athletes” (p. 95). Bill Conley, a former recruiting coordinator for football at Ohio State University, states (Caryer, 1996) that

Recruiting is the most important job a college coach has. The X’s and O’s are pretty much the same around the country, but if your X’s and O’s are bigger, faster and stronger, you have a better chance of being successful. (p. 31)

Of course, the same concept applies to other sports, such as basketball, soccer, and cross country. Coaches spend a great deal of time and money identifying recruits, maintaining contact with them, and convincing them to commit to a particular university. Efficiency of this work can perhaps be improved via technology, since, according to Hornbuckle (2001), “Much of this process can be done on the Internet by having an exceptional presence on the World Wide Web” (p. 11).

The Internet provides colleges and universities with an incredible method for reaching fans and potential recruits. According to Delpy and Bosetti (1998), “This media presents an unparalleled opportunity to reach sports fans worldwide at a fraction of traditional advertising costs” (p. 21). Further, “High school athletes today want instant access to collegiate program information in everything from program history to whether the school fields a men’s team or not” (Hornbuckle, 2001, p. 10). For providing instant access to information at a low cost, there is no better means than an effective website.

Further, Hornbuckle (2001) states, “Many athletic departments already use the Internet to assess potential recruits and determine factors that are most likely to influence their choice of school” (p. 29-30). The Internet can be used for nearly every phase of the recruiting process. Recruits can be identified via e-mail to scouts or high school coaches, and correspondence with a prospective athlete can also occur via e-mail. Potential athletes can often access a virtual tour of a campus, perhaps including training and competition facilities. Of course, the coach’s actual visit to the athlete cannot be replaced; however, for Division II, Division III, and junior college coaches, “this option may not be affordable–even more reason for these coaches to provide a first-class, usable website” (Hornbuckle, 2001, p. 12).

]Method[

The present researchers were guided by three research goals, as follows:

1. Determine the specific features (content) included on websites promoting women’s cross country programs at NCAA schools.

2. Determine any differences among NCAA divisions (I, II, III) in terms of website content provided and frequency with which such content is exhibited.

3. Make recommendations for improving websites’ function as aids in the recruiting process.

The research comprises a quantitative, descriptive analysis of 108 women’s cross country websites. Using a random number generator, 36 schools in each of the three NCAA divisions were randomly selected. In selecting 36 schools,  a sample was generated that represented at least 10% of all programs at each division level. Division III had the largest number of participating schools (357).

Analysis included obtaining frequency scores by each feature, overall, and by division. These scores are presented in Table 1 as the percentage of sites containing each website feature, both in each division and overall.

]Results[

As a whole, this examination revealed that colleges and universities create websites for women’s cross country that serve several primary functions. The sites contained, for the most part, headline stories (61.11%), schedules (92.59%), rosters (86.11%), results (71.30%), biographical information about the coach (70.37%), a photo of the coach (62.03%), and contact information for the coach (e-mail address, 75.92%; e-mail link, 73.15%; phone number, 62.96%). The presence of information forms for prospective athletes on over half of the sites (56.48%) supports the belief that many college and university administrators view their website as an important tool in the recruiting process. Further, the vast majority of sites that featured prospective-athlete information forms allowed them to be electronically transferred to the coach. Of 61 schools whose websites provided such prospective-athlete forms, 56 allowed them to be electronically transferred, while only 5 expected them to be mailed.

Beyond the components just described, however, the examination revealed many of the websites to be sorely lacking. The school websites were found not to promote the individuals on a team, as frequency scores were low for (a) content concerning individual athletes’ performance records (12.96%); (b) biographies of individual athletes (19.44%); and (c) photos of individual athletes (17.59%). Moreover, few schools went so far as to include even a simple team photo (23.15%).

Surprisingly, given the attention paid by websites maintained by institutions in all three divisions to promotion of  their coaches, the philosophy of the program (10.19%) and the philosophy of the coach (1.85%) were almost completely absent.

]Recommendations[

It is clear from these results that many colleges and universities already see the Internet as an important point of interaction between the institution and recruits. This is evidenced by the fact that the women’s cross country program websites include letters to potential student-athletes, NCAA compliance information, and access to NCAA recruiting rules. Many sites also provide personal information forms that prospective student-athletes are invited to submit to coaches in hopes of beginning a recruiting process. Recognizing that use of the Internet for recruiting purposes is likely to continue to grow, there are a number of recommendations that can be made based on these results.

Since more than half of the schools allowed prospective athletes to electronically submit personal information, the few who still rely on “snail mail” to receive this information might be at a serious disadvantage, as prospects may not be inclined to take the time to print out the form, complete it, and put it in the mail. Furthermore, schools that neglect to provide any means for prospects to deliver personal information may be seriously hindering their recruiting process.

The literature reveals that information about the coach–especially as to the coach’s philosophy, goals, values, and style–is important to recruits (Cooper, 1996; Doyle & Gaeth, as cited in Klenosky, Templin, & Troutman, 2001). It is of interest, then, that so few of the total 108 sites viewed provided information about philosophy and that those that did offer it often limited it to the mission statement of the athletic department as a whole.

There is some potential for testimonials about a program and coach to be influential from a recruitment standpoint, yet testimonials appear to be underutilized to date, according to this research. Two Division III sites included athletes’ testimonials about their teams, while one team site included other coaches’ written endorsements of the team’s coach.

Prospective student-athletes are likely to be interested in who might be their teammates. Furthermore, recruits could conceivably have more interest in a program that clearly values and promotes its athletes as individuals. Schools in all three NCAA divisions studied could improve in this area, as their websites did not contain a great deal of information about individual athletes.

Division II and Division III institutions could furthermore do a better job of updating the headline stories  on their websites. Regular updates give potential recruits a reason to revisit a site repeatedly, allowing them to assess the reputation of the team in an ongoing process.The connection represented in repeated visits to a website may help keep a school in the recruit’s mind over extended periods. Offering e-mailed updates of team progress through the season, as well as maintaining a “heritage” page and archived and current results and records, may be of further use in presenting a team’s reputation to site visitors.

Many of the university websites examined provided information about athletic facilities like the football stadium or basketball arena. Few, however, included information about the home cross country course. The information would not be difficult to include, and recruits would very likely be interested in the venues in which they would train and compete.

In an era of visual learners (Lester, 2000), pictures may go a long way toward impressing a recruit. Unfortunately, in all three NCAA divisions studied, most sites failed to provide a photo album or even a team picture. Digital cameras, typically available through athletic departments, could facilitate this process quite easily. Enlargeable thumbnail pictures would be helpful in decreasing downloading time.

To be sure, the Internet represents a powerful innovation that can play a major part in the recruiting process. This research is a first step in understanding, and thus in better utilizing, websites as aids in recruiting student-athletes. Future research could include analyses of websites for other sports, both revenue and nonrevenue. Further, it will be important to establish student-athletes as a source of data, inquiring of them which website features might most influence their college choices.

Table 1

Frequency of Website Features of NCAA Women’s Cross Country Programs, in Percentages


Division I
Division II
Division III
Overall
Headline Stories
91.67
38.89
52.78
61.11
Team/Program
Schedule
94.44
86.11
97.22
92.59
Roster
86.11
83.33
88.89
86.11
Results (current)
80.56
58.33
75.00
71.30
Team Photo
8.33
27.78
33.33
23.15
Program Philosophy
19.44
5.56
5.56
10.19
Heritage Page
16.67
2.78
16.67
12.04
Individual Information
Performance Records
25.00
2.78
11.11
12.96
Biographical Sketch
44.44
5.56
8.33
19.44
Photo
33.33
13.89
5.56
17.59
Coach Information
Photo
69.44
47.22
69.44
62.03
Biographical Sketch
75.00
61.11
75.00
70.37
Coaching Philosophy
0.00
0.00
5.56
1.85
E-mail Address
86.11
61.11
80.56
75.93
E-mail Link
86.11
58.33
75.00
73.15
Phone Number
69.44
55.56
63.89
62.96
Photo Album
19.44
19.44
8.33
15.74
Archive
Headline Stories
58.33
16.67
13.89
29.63
Record Book
36.11
8.33
30.56
25.00
Rosters 25.00 13.99 5.56 14.81
Results 61.11 33.33 30.56 41.67
Prospective Athletes
Letter to Prospective Athletes 41.67 8.33 13.89 29.63
Personal Information Form 63.89 33.33 72.22 56.48
Electronically Transferred
Personal Information Form
52.78 30.56 72.22 51.85
NCAA Clearinghouse
Recruiting Rules Information 30.56 8.33 0.00 12.96
Compliance Information 33.33 2.78 2.78 12.96
Additional
Course Description 16.67 0.00 11.11 9.26
Map to Course 5.56 0.00 2.78 2.78
Course Records List
5.56
2.78
0.00
2.78
Training Venues Information 8.33 0.00 5.56 4.63
Camps/Clinics Information 25.00 13.89 0.00 12.96
Offer E-mail Updates 36.11 2.78 8.33 15.74
Listing of Alumni Bios 2.78 0.00 0.00 0.93
Alumni Bio Questionnaire 2.78 0.00 0.00 0.93
Alumni E-mail List 5.56 0.00 0.00 1.85
Athletes’ Testimonials 0.00 0.00 5.56 1.85
Other Coaches’ Testimony
About the Coach
0.00 0.00 2.78 0.93
University Quick Facts 11.11 11.11 25.00 15.74
Video Webcast of Meet 0.00 2.78 0.00 0.93
Coach Interviewed on Video 0.00 2.78 0.00 0.93

]References[

Caryer, L. (1996). The recruiting struggle: A handbook. Columbus, OH: Partners Book Distributing.

Cooper, K. (1996). What the basketball prospect wants to know about you! Coach and Athletic Director, 65(7), 24-26.

Delpy, L. A., & Bosetti, H. A. (1998). Sport management and marketing via the World Wide Web. Sport Marketing Quarterly, 7(1), 21-27.

Hornbuckle, V. (2001). An analysis of usability of women’s collegiate basketball Websites based on measurements of effectiveness, efficiency and appeal. Unpublished doctoral dissertation, University of Northern Colorado.

Kirk, W. D., & Kirk, S. V. (Eds.). (1993). Student athletes: Shattering the myths and sharing the realities. Alexandria, VA: American Counseling Association.

Klenosky, D. B., Templin, T. J., & Troutman, J. A. (2001). Recruiting student athletes: A means-end investigation of school-choice decision making. Journal of Sport Management, 15, 96-106.

Lester, P. M. (2000). Visual communication: Images with messages (2nd ed.). Belmont, CA: Wadsworth.

Walsh, J. (1997). Everything you need to know about college sports recruiting. Kansas City, MO: Andrews McMeel.

]Author Note[

Peter S. Finley; Laura L. Finley

2013-11-26T21:17:41-06:00February 18th, 2008|Contemporary Sports Issues, Sports Facilities, Sports Management, Women and Sports|Comments Off on Websites as Help in the Recruiting Process: An Analysis of NCAA Women’s Cross Country Programs

A Strength Training Program of “Ya-Tung” Women’s Basketball Team of Taiwan

Rebounding, jumping, shooting, and playing defense require a decent level of strength and power. A basketball player in great condition should demonstrate the endurance to run tirelessly on the court and should possess the strength to engage in the physical battles beneath the basket. There is no doubt that strength training plays an important part in building up the power to meet demands on the court (Fulton, 1992). College basketball has emphasized strength training to a great degree because it increases overall strength, flexibility, and lean body mass (Fulton, 1992). The implementation of strength training in order to increase vertical jumping ability, thereby enhancing overall sport performance, appears well founded (Renfro, 1996). This explains why college coaches prefer their players to stay involved in strength training even under the restrictive practice schedule of the NCAA.

In Taiwan, however, coaches of women’s basketball teams did not traditionally support the idea of strength training. They distrusted it (as some American coaches do, too), viewing it as a threat to players’ flexibility, athleticism, and shooting touch (Mannie & Vorkapich, 2000). Taiwanese coaches want their players to be quick and strong, but without strength training. Can such an objective be achieved?

Working since last March with the coaches of Taipei’s national women’s basketball team, the researchers observed an interesting fact. Female players with team Cathay, the perennial Taiwanese champion, were generally stronger and more “physical” than other players. The Cathay team was the only Taiwanese women’s team with a strength-training routine, so the researchers decided to study strength training in basketball more closely, designing for a rival Taiwan team called Yatung a lifting program reflecting sound basic strength-training principles.

Strength Training and Basketball

Groves and Gayle (1989) surveyed the top 100 men’s college basketball teams using data from a USA Today poll, and found that 98% of these schools had a pre-season weight-training program. In-season weight training was employed by 75% of the programs; 88% used off-season weight training for team members, and 64% used summer weight training. Analysis of variance (ANOVA) showed that a school with in-season weight training was likely to rank higher than a school without it. While the correlation does not indicate that strength training leads to wins, but does help explain, perhaps, why 87% of coaches and athletic directors endorse strength training for their teams.

Grove and Gayle also studied physiological change in 8 college players who engaged in a year-round training program (1993). Several findings resulted from repeated ANOVA testing. First, the players experienced a decrease in the proportion of body fat. Second, lean body mass was significantly increased, although body weight did not vary much over the course of the year. Finally, players on average experienced improvement of some 27.5 lb in the bench press but did not improve significantly in terms of the height of their vertical jumps. Fulton (1992) conducted research on the combined effects of strength training and plyometrics training. In contrast to Grove and Gayle’s findings (1993), a player in Fulton’s study on average improved vertical jumps by 4.5 in following 18 weeks of training; an average player furthermore added 45 lb to his bench press performance and experienced improvement of 4% on the I-test (a test of speed and agility).

There is no data to support concerns that strength training is detrimental to shooting in basketball. Shoenfelt (1991) tested the effect of an 8-week strength-training program on the accuracy of free throws, studying 14 female collegiate players divided into two groups. Every other day, one group engaged in weight training and the other in aerobic exercise. Results showed that the immediate effect of weight training was no more detrimental (or beneficial) to free throw accuracy than the immediate effect of aerobic exercise. Kerbs (2000) studied an entire women’s basketball team, measuring free throw and speed spot shooting accuracy 8 hours after a morning weight-lifting routine. According to the study results, accuracy did not differ significantly between days when the weight-lifting routine was followed and days when it was not followed. The results, then, indicated that these players could continue with a regular lifting program on game-day mornings without losing shooting accuracy.

The results of these studies indicate that basketball players experience more advantages than disadvantages from strength training, even on game days. The conclusion reached is that strength training for basketball players is beneficial to their overall development as athletes.

A typical strength-training program for women collegiate basketball players resembles one for men’s team players (Owens, 1998). General exercises (such as the squat and the split-squat) are often used to strengthen the muscles involved in jumping and running (Renfro, 1996). Certain upper-body exercises focusing on strength, flexibility, and coordination have been examined for their effects on rebounding (Stilger & Meador, 1999). In general, a strength-training program’s goal is to increase players’ power, not just size. Sessions should be designed to prevent muscle accommodation—and boredom; they should also take into account the individual player’s particular weaknesses (Owens, 1998). Hitchcock (1988) proposed that four criteria of importance in devising a strength-training program for women basketball players: specified goals, work assigned based on performance, an equal workload, and communication with the players.

Wilmore and Costill (1994) offered a prescription for basic strength training for basketball players based on four factors: mode, frequency, duration, and intensity; the concept is illustrated in Table 1. The present researchers devised a strength-training prescription for Taiwan’s Yatung women’s basketball team that similarly incorporated the mode, frequency, duration, and intensity factors (see Table 2).

Table 1

General strength-training prescription for basketball players

Factors Emphases References
Mode use of major muscle groups: leg, hip, back,

abdomen, chest, shoulder, upper arms*

____________________________________

major exercises: bench press, lat-pull, inclined/declined dumbbell press, squat, abdominal curl, leg curl/extension, good morning exercise, power cleans, hang cleans, upright and T-bar row*

____________________________________

*Olympic-style lifts preferred

 

Mannie & Vorkapich, 2000

 

________________________

Davies, 1993; Earles, 1989; Fulton, 1992; Johnson, 1989; Mannie & Vorkapich, 2000; Renfro, 1996; Zucker, 1989

 

_______________________

Owens, 1998

 

Fre-quency 3–4 times (sessions) per week, on alternate days*

 

 

____________________________________

*in season, 5 times weekly with shorter sessions

 

Earles, 1989; Fulton, 1992; Johnson, 1989; Mannie & Vorkapich, 2000; Zucker, 1989

________________________

Owens, 1998

Duration training period divided into “seasons,” each lasting about 8–10 weeks; pre-season may be as brief as 6 weeks*

 

____________________________________

each session is 1.25 hr – 1.5 hr ; 3 sessions per week*

____________________________________

30–45 min per session; 4 or more sessions per week*

____________________________________

*no more than 4 hours per week

Fulton, 1992; Groves & Gayle, 1993; Johnson, 1989; Owens, 1998; Shoenfelt, 1991; Zucker, 1989

________________________

Fulton, 1992; Mannie & Vorkapich, 2000

________________________

Owens, 1998

 

________________________

Hitchcock, 1988; Zucker, 1989

Intensity in general, 3 sets of each exercise including 3–12 repetitions per set*

 

____________________________________

off-season for hypertrophy and endurance—60–75% 1 RM; early season for strength—70-85% 1 RM; in season for maximum strength—3–5 RM, or >90% 1 RM*

____________________________________

*Variation within a week, e.g., Monday 8–12 RM, Wednesday 6–8 RM, & Friday 3–5 RM

Earles, 1989; Fulton, 1992; Owens, 1998; Mannie & Vorkapich, 2000

________________________

Davies, 1993; Earles, 1989; Fulton, 1992

 

 

________________________

Earles, 1989; Johnson, 1989; Owens, 1998; Zucker, 1989

 

 

 

 

Table 2

Experimental strength-training prescription for Yatung players

Period Exercise Intensity Sets/Reps Frequency

off-season,

April—July

bench press, shoulder press, knee extension, knee curl, squats, front/ side lunge, power cleans, bicep curl, good morning exercise, situps 70–75%> 1 RM 3 x 8–12;

3 x 25–30 for situps

Monday

Wednesday

Friday

Saturday

pre-season,

August—September

bench press, shoulder press, knee extension, knee curl, squats, front/ side lunge, power cleans, bicep curl, good morning exercise, situps 80–90%> 1 RM 3 x 5–8;

3 x 30–40 for situps

Monday

Wednesday

Friday

in season,

October—November

bench press, shoulder press, knee extension, knee curl, squats, front/ side lunge, power cleans, bicep curl, good morning exercise, situps 85–95%> 1 RM 3 x 2–3;

3 x 35–50 for situps

2–3 times/week; NOT on game days

 

Discussion

Since the late 1970s strength training has become popular among college basketball teams worldwide; however, strength training is just now emerging among Taiwan’s basketball players. The present researchers suggest to coaches and sport administrators that, in order to benefit the players, they

  1. work to educate Taiwanese coaches about the uses of strength training, putting to rest any misconceptions
  2. promote proper strength-training methods, for example introducing them in secondary schools and the high school basketball league
  3. support additional research examining physiological and psychological effects of strength training on elite Taiwanese players

References

 

Davies. (1993). Strength training for basketball at Maclay High School. Journal of Strength and Conditioning. 15(2), 37.

Earles, J. (1989). Implementing an in-season JV strength program for female athletes. Journal of Strength and Conditioning. 11(3), 32–34.

Fulton, K. T. (1992). Off-season strength training for basketball. Journal of Strength and Conditioning. 14(1), 31–44.

Groves, B. R., & Gayle, R. C. (1993). Physiological changes in male basketball players in year-round strength training. Journal of Strength and Conditioning Research. 7(1), 30–33.

Groves, B. R., & Gayle, R. C. (1989). Strength training and team success in NCAA men’s Division-I basketball. Journal of Strength and Conditioning. 11(6), 26–28.

Hitchcock, W. (1988). Individualized strength and conditioning program for women’s basketball. Journal of Strength and Conditioning. 10(5), 28–30.

Johnson, A. (1989). West Virginia University preseason basketball conditioning program. Journal of Strength and Conditioning. 11(1), 43–46.

Kerbs, B. (2000). Effects of same-day strength training on shooting skills of female collegiate basketball players. Microfilm Publication. Eugene, OR: University of Oregon.

Mannie, K., & Vorkapich, M. (2000). Off-season and preseason strength conditioning for basketball. Scholastic Coach and Athletic Director. 70(3), 6–11.

Owen, J. (1998). Strength training for basketball: Building post players. Journal of Strength and Conditioning. lang=FR>20 lang=FR>(1), 16–21.

Renfro, J. G. (1996). Basketball specific squats. Journal of Strength and Conditioning.18(6), 29–30.

Shoenfelt, E. L. (1991). Immediate effect of weight training as compared to aerobic exercise on free throw shooting in collegiate basketball players. Perceptual and Motor Skills. 73(2), 367–370.

Stilger, V., & Meador, R. (1999). Strength exercises: An upper body proprioceptive neuromuscular facilitation rebounding exercise. Journal of Strength and Conditioning. 21(6), 29–31.

Zucker, A. (1989). Men’s basketball off-season Phase I strength program. Journal of Strength and Conditioning. 10(6), 39–40.

Author Note

Dr. Richard C. Bell is the chair of sport management at the United States Sports Academy. Steven Chen is a doctoral candidate at the United States Sports Academy.

2015-10-22T23:42:41-05:00February 14th, 2008|Sports Exercise Science, Sports Studies and Sports Psychology, Women and Sports|Comments Off on A Strength Training Program of “Ya-Tung” Women’s Basketball Team of Taiwan

You Go Girl ! The Link Between Girls’ Positive Self-Esteem and Sports

Positive self-esteem is a favorable perception of one’s self, or, how happy you are with just being you. In general, feelings of self-esteem contribute to a person’s self-worth, confidence and competence. These feelings of worthiness, assurance and proficiency can influence a person’s life in regard to personal aspirations, motivation, achievement potential and relationships (Melpomene Institute, 1996). A person’s self-esteem is affected by and formed from a variety of circumstances in life, some of which are:

  • degree of parental expectations, encouragement and influence
  • degree of peer expectations, encouragement and influence
  • involvement in making of decisions
  • development of talents, hobbies or interests
  • influence and importance of role models
  • extent of emphasis on body image
  • experiences and interactions during education
  • participation in physical activity and/or sports (Kopecky, 1992)

 

Many studies have been done to investigate the self-esteem of young girls and have concluded that as girls move from grade school to high school, their self-esteem levels drop (Feldman & Elliott, 1990; Gilligan, Lyons & Hammer, 1990; How Schools Shortchange Girls, 1992). For example, one study found that 69% of grade school boys and 60% of grade school girls responded that they were “happy the way I am”. The same study found 46% of high school boys and only 29% of high schools girls reported being “happy the way I am”. Overall, girls self-esteem dropped at a rate three times that of boys. Feelings of low self-esteem in adolescence are one contributing factor that increases the likelihood of a young girl dropping out of school or becoming pregnant. The low self-esteem seen in girls does not disappear with maturity; girls with low self-esteem often grow to be women with low self-esteem. Low levels of self-esteem are linked to increased rates of depression, substance abuse, suicide and eating disorders in both adolescents and adults (How Schools Shortchange Girls, 1992; Melpomene Institute, 1996).

What can be done about the decrease in self-esteem? What can girls do to maintain their self-esteem as they mature? To answer these questions, it is important to look at what boys are doing differently from girls as both groups move from grade school to high school. One important difference to consider is the rate of sports participation among boys and girls. As girls move from grade school to high school, they drop-out of sports at a rate six times higher than boys (Women’s Sports Foundation, 1998). Could the lower rate of sports participation among girls be linked to a lower self-esteem? In order to answer the question, it is essential to consider two factors: what contributes to the development of self-esteem and the benefits of sport participation.

For girls living in the 1990s, self-esteem is linked to both physical attractiveness and physical competence. Prior to the 1990s, however, the main factor contributing to a girls’ self-esteem was physical attractiveness (Nelson, 1994). Coupling self-esteem to both competence and beauty is a step in the right direction, although it’s still unfortunate that girls place so much importance on physical attractiveness as it relates to their happiness. Recognizing that young girls often compare themselves to unrealistic standards of beauty can help parents better understand, guide and influence their children (Nelson, 1994; Women’s Sports Foundation, 1998). In attempting to de-emphasize the importance their daughters place on beauty and emphasize the importance of physical competence, parents may find it helpful to utilize the benefits of participation in sport.

Participating in sport is one way that girls can develop physical competence. Girls learn to appreciate their bodies for what they can do, instead of the perceived appearance by oneself or by others. In a sport environment girls learn to control their bodies and to rely on acquired physical skills. Partaking in sport also helps girls trust and rely on themselves and teammates while working toward common goals. In a sense, participation in sport allows each girl to become her own personal cheerleader – cheering on her physical self and what might be possible; not just standing on the sidelines, or in the bleachers, cheering others on (Nelson, 1994). Involvement in athletics provides lessons in teamwork and leadership, the development of citizenship, and community involvement. Membership in sport also offers girls a greater pool of adult role models from where they can draw guidance and support (Melpomene Institute, 1996; Murtaugh, 1988). Additionally, girls find new friends in the sport setting. For girls, this sense of friendship is essential, being liked by other girls is sometimes more important than having others see them as smart or independent (Feldman & Elliott, 1990).

 

A study published by the Women’s Sport Foundation on over 30,000 girls compared athletes to non-athletes.

The study stated that athletes were more likely than non-athletes to:

  • score well on achievement tests
  • feel “popular” among one’s peers
  • be involved in other extracurricular activities
  • graduate from high school (three times more likely)
  • attend college and obtain a bachelor’s degree
  • stay involved in sport as an adult
  • aspire to community involvement
  • not become involved with drugs (92% less likely)
  • not become pregnant (80% less likely)

(Women’s Sports Foundation, 1998).

 

It is important that parents realize the many contributions participation in sport can make to young girls’ development. The positive aspects of sport can help girls maintain their self-esteem as they make the difficult transition from grade school to high school.

References

Feldman, S. & Elliott, G. (Eds.). (1990). At the threshold: the developing adolescent. Cambridge, MA: Harvard University Press.

Gilligan, C., Lyons, L., & Hammer, T. (Eds.). (1990). Making connections: The relational worlds of adolescent girls at Emma Willard School. Cambridge, MA: Harvard University Press.

How Schools Shortchange Girls – The AAUW Report. (1992). New York, NY: Marlowe & Company.

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2017-08-07T15:37:24-05:00February 11th, 2008|Contemporary Sports Issues, Sports Coaching, Sports Exercise Science, Sports Management, Sports Studies and Sports Psychology, Women and Sports|Comments Off on You Go Girl ! The Link Between Girls’ Positive Self-Esteem and Sports

An Exploration of Female Athletes’ Experiences and Perceptions of Male and Female Coaches

Abstract

Gender may be a mediating factor for relationship effectiveness between
athletes and coaches (Lirgg, Dibrezzo, & Smith, 1994; Medwechuk &
Crossman, 1994). Ironically, with the increase in participation of female
athletes and sports that has occurred since Title IX, there has been a
decrease in the number of female coaches over the past 30 years (Felder
& Wishnietsky, 1990; Freeman, 2001; Pastore, 1992). The purpose of
this study was to explore twelve female athletes’ perceptions and
experiences of being coached by women and men. Semi-structured interviews
revealed four major themes: discipline and structure, personal relationships,
passivity and aggressiveness, and coach preference. Specifically, eight
of the participants stated a preference for male coaches, yet differences
were found when comparing various coaching qualities. Results are discussed
in regards to overall sport experiences.

Introduction

The coach-athlete relationship has been shown to have a profound effect
on an athlete’s satisfaction, performance, and quality of life (Greenleaf,
Gould, & Dieffenbach, 2001; Kenow & Williams, 1999; Vernacchia,
McGuire, Reardon, & Templin, 2000; Wrisberg, 1996) and several factors
may influence this relationship (Burke, Peterson, & Nix, 1995; Grisaffe,
Blom, & Burke, in press). Olympic athletes from the 1996 Summer Games
who did not perform as well as expected felt that conflict with the coach,
receiving inaccurate technical information, the coach’s inability to handle
selection controversy, and lack of focus on team climate played significant
roles in lower-level performances (Greenleaf, Gould, & Dieffenbach,
2001). Trust, friendship, and feedback from the coach had a positive impact
on the performances of athletes who met or exceeded expectations. Athletes
experiencing burnout have cited the coach as a negative influence due
to the coaches’ lack of belief in the athlete, extreme pressure,
and/or unrealistic expectations (Udry, Gould, Bridges, & Tuffey, 1997).
Stewart and Taylor (2000) found that athletes’ perceptions of coaching
competence and coaching behaviors were contributing factors to performance.

Numerous studies have examined the impact of gender on the coach-athlete
relationship. Athlete preferences for same-sex or opposite-sex coaches
have been examined, and factors taken into consideration have included
level of knowledge and ability to motivate, (Medwechuk & Crossman,
1994; Parkhouse & Williams, 1986), level of athlete’s comfort in disclosure
(Molstad & Whitaker, 1987; Sabock & Kleinfelter, 1987; Simmons,
1997), and capability of being a role model (Lirgg, Dibrezzo, & Smith,
1994). Molstad and Whitaker (1987) found that female basketball players
ranked female coaches as superior in the coaching qualities of relating
well to others and understanding athletes’ feelings (two of the three
most important rated qualities), while no difference was found among other
characteristics. Conversely, a strong sex bias favoring male coaches was
found in male and female high school basketball athletes who rated males
as more knowledgeable, more likely to achieve future success, more desirable
to play for, and having a greater ability to motivate (Parkhouse &
Williams, 1986). Overall, 89% of male athletes and 71% of female athletes
preferred a male coach. Previous research investigations have not shown
a clear consensus for coach gender for female athletes (Lirgg, Dibrezzo,
& Smith, 1994).

Although female athletic participation has increased since the passage
of Title IX, there has been a decrease in the number of female coaches
over the past thirty years (Carpenter & Acosta, 1991; Freeman, 2001;
Pastore, 1992). According to Felder and Wishnietsky (1990), the percentage
of females coaching high school teams has dropped as much as 50% between
the mid-1970’s and early 1980’s. Similarly, females coached
90% of collegiate teams in 1972 while only 47.3% of teams were coached
by women in 1990 (Carpenter & Acosta, 1991).

Osborne (2002) suggested that although male and female athletes share
many attributes such as the desire to win, willingness to sacrifice time
and energy, and enjoyment of competition, athletes need to be coached
differently. Factors to consider include training methods, coaching philosophy,
motivation tactics, communication style, and ability to relate on a personal
level. The majority of research that has examined the impact of coach
gender on the female athlete has been conducted quantitatively and has
used hypothetical coaches (Frankl & Babbitt, 1998; Medwechuk &
Crossman, 1994; Molstad & Whitaker, 1987; Williams & Parkhouse,
1988). The present study utilized a qualitative approach to explore female
athletes’ experiences with actual male and female coaches. Further,
Carron and Bennett (1977) noted the importance of gaining the athlete’s
perspective of coach-athlete compatibility, while Osborne (2002) pointed
out that very little is known about the extent to which female athletes
prefer a same-sex or opposite-sex coach. Thus, the purpose of this study
was to obtain a first-person perspective of the female athlete’s
experiences of playing for a male and female coach.

Method

Participants

The participants in this investigation were twelve NCAA Division I female
athletes. All athletes were Caucasian and had participated in basketball,
golf, cross country, track and field softball, or soccer. The sample was
derived from two different southeastern NCAA Division I universities.
Four athletes had junior academic classification, four athletes had senior
academic classification, and four athletes had graduate academic classification.
These athletes were chosen for this study as a purposeful sample (Glesne,
1999) because they had the potential to provide a rich description of
the experience of being coached by both a male and female and had a recent
memory of this experience.

Procedure

The process of bracketing one’s own presuppositions was developed
from Husserl’s concept of reduction in the method of phenomenology
(Glesne, 1999). Before initiating the present study, a bracketing interview
was conducted to clarify the interviewer’s personal experiences
of having a male coach and to explore potential biases. Themes from this
interview included preference for organization, winning attitude, and
enjoyment of the game.

Semi-structured interviews were then employed to collect information
about the athletes’ experiences and perceptions of having both male
and female coaches. All participants were invited to participate in the
study by personal or telephone contact, and those expressing interest
were interviewed. Participants were informed that involvement was voluntary,
and were advised of the ability to terminate participation at any time.
To ensure confidentiality, the participants were informed that pseudonyms
would be used for actual names and any team affiliations. The interviews
were conducted in person and lasted approximately forty minutes in length.
After the interview, participants were given an opportunity to review
the transcript and suggest changes. No changes were suggested by the participants.

Interview Protocol

Questions posed to the participants were designed to achieve a comprehensive
understanding of the experiences of being coached by men and women. The
interviewer initially gathered information about coach history, as well
as the sport and level of competition. Participants were then asked questions
related to differences or similarities experienced with each coach in
training methods, encouragement and motivation, personal relationships,
level of sport knowledge, and the coach preferred. The interview guide
is provided in the Appendix.

Analysis

Interviews were transcribed verbatim and a research team of five individuals
derived themes using a combination of phenomenological approaches. The
procedures for analyzing were adapted more directly from those developed
by Barrell (1988), Goodrich (1988), Hawthorne (1989), Ross (1987), and
Henderson (1992). More specifically, the following steps of: Approaching
the interview (Transcribing the interview, Obtaining a grasp of the interview
through an interpretive group), Focusing the data (Clearing the text,
Grouping the text), Summarizing the interviews (Preparing a summary, Verifying
the summary), and Releasing meanings (Forming categories, Determining
themes, and Describing themes) were utilized to analyze the information.

Results

Table 1 gives a description of each participant and her history of having
both male and female coaches. All participants played at the college level
for at least two years and have played competitively for at least four
years. It is important to note that three of the participants’ experiences
of the female coach were from high school experiences. Four major themes
emerged from the interviews.

Discipline and Structure

The participants indicated that male coaches were more structured and
organized. Carmen stated, “[the male coach] was much more together,
he knew structure. He knew exactly where we needed to be, what time and
what time we needed to start.” Differences were notably significant
in the practice setting. The male coaches would develop practice plans
and execute every detail needed to make them work. Kelli M. confirmed
this by stating, “I know [the male coach] would sit down before
a game and write down every possible thing the other team could do to
beat us; and then write down next to it exactly what we could do to defend
them.” Drills that were done at practice had a purpose, whether
it was fundamentals, offense, defense, or conditioning. The male coaches
were seen as being harder on the athletes and “expected more”
from the players than the female coaches. The males tended to coach from
an authoritarian perspective and enforced the concept of “no excuses,
this is the rule and we’re going to stick with this rule,”
according to Kelli M. Many of the athletes felt there would be more consequences
to face in practices under the male coach if they did not pay attention
or were not serious. Some of the athletes in this study responded favorably
to the male coaches’ disciplinary tactics, as it aided in keeping
them focused; however the male coach was also considered to be “too
strict” by others in the study.

Four of the participants felt that the female coaches were unorganized and
non-authoritative. The female coaches tended to run late at times and
would not get the players prepared for the game. Practices were not structured,
nor on a time schedule. These athletes perceived that the female coaches
had a harder time trying to accomplish tasks in practice, and did not
have similar discipline compared to experiences with the male coaches.

With the female coach, she had different stuff everyday. It would take
her five minutes to explain what we’re supposed to do and then it
wouldn’t really work very well. So, we would just look at each other.
When we did the drill, we didn’t do it full out because we knew
she wasn’t keeping score or we weren’t on a time limit. We
knew we weren’t going to really be disciplined. (Kelli M.)

Female coaches were more likely to forget details in practice, such as
not keeping score of games, which led to lack of motivation during practice.
Participants indicated that female coaches would consider individual situations
instead of sticking to certain rules and consequences. For example, if
an athlete was late to practice, a male coach would have a set rule regarding
this behavior and if any player broke the rule, regardless of the reason,
she would have to face the consequences. However, a female coach would
listen to the athlete’s reason and then decide what type of consequence
the player should face.

Personal Relationships

All of the participants felt that female coaches had a greater ability
to relate to them. Jennifer C. stated, “[the female coaches] know
sometimes what [female athletes] going through, different life cycles
and stages of their life. They can relate to how girls change differently
than boys.” The participants indicated that the female coach understood
how to “deal with” the athletes and could sympathize with
them when it came to “girl stuff.” The female coaches had
a greater tendency toward being friends with the players and getting to
know them more than the male coaches did. Kelli C. stated, “[the
female coach] was more on our level. She wanted to “chit-chat”
with us. Like get to know us rather than having to be stern.” This
sometimes caused problems though, because the female coach would develop
emotional ties with the players and would construct feelings of whom she
liked and did not like. This made a difference in some of the participants’
experiences because the coach would “characterize a couple of players
as being similar to the way [the female coach] played and/or worked in
high school or college. So people with different work ethics were considered
different” (Sam). The players began to see differences in coaching
as favoritism. Mistakes made by some players would be overlooked, but
similar mistakes would be made into ‘an issue’ with other
players.

So, in practice a lot of the people knew that if they made a mistake
then the female coach tended to focus on that one mistake. But if another
person made a mistake, she would focus on something else, like just ignore
it. Like if somebody in a game continuously threw the ball out of bounds
or in the bleachers she wouldn’t really look at that. She would
look at it as a negative that somebody else who’s not getting the
rebounds or not playing good defense or something like that. She would
pick and choose which mistakes mattered and which ones didn’t, with
a lot of different kinds of players, depending on what she thought of
you already. (Kelli M.)

The athletes did experience a lot of positive feedback and encouragement
from the female coaches. Many of the participants believed this came naturally
from the female coaches. Emily stated, “in general, you are going
to have a female that’s better at [encouraging and motivating] just
because females are more encouraging in general.” Others, such as
Carmen, felt the bond shared with the female coach is what helped motivate
and encourage performance. “She was a girl and girls can relate
to girls. And when they encourage you and you’re friends with them
you feel better.” The female coaches were more inclined than the
male coaches to say positive statements to encourage players. Female coaches
tended to first point out the positive tasks the athletes did before saying
what could be improved.

The personal relationships between the female athletes and male coaches
were very different from the relationships with female coaches. Many of
the female athletes were intimidated by the male coaches. The female players
knew that they could discuss ‘most anything’ about the sport,
certain plays or tactics with the male coaches, but nothing outside of
practice or the game was “allowed to be discussed.” Whereas
the athletes felt a variety of issues could be discussed with the female
coaches. Carmen stated, “If I had a [personal] problem with my male
coach, I wouldn’t say anything about it.” There was no bond,
per se, like the one she had with the female coach. If something was bothering
a player, the male coach would simply punish the player for not paying
attention. In similar situations with a female coach, Carmen thought that,
“she would have asked ‘hey are you okay.’ She would
have known something was bothering me and said “hey let’s
play or practice.”

Four of the athletes indicated the biggest difference between the relationships
with the male and female coaches came from a lack of encouragement and
positive reinforcement. The males tended to correct and point out the
mistakes more often and hesitated to use compliments as motivation. Sam
stated, “My male coach always told us what we were doing wrong.
After a while in practice, he could tell it was getting to us so he would
throw in a compliment. But, everyone knew he had to think about it before
he said it.”

Passivity and Aggressiveness

The mentality of the male coach compared to the female coach was a major
theme throughout the interviews. The males seemed to be more aggressive
and demanding. The males’ mentality was “you gotta go out
and get it” and they wanted to “win, win, win,” which
made practices hard and strict. A typical mindset was that if the female
athletes would make a mistake or, as Kelli M. stated, “If we took
too long, or if we were loafing around and it took us more than ten to
fifteen seconds to get in a drill, we had to get on the line and run.
It was like clockwork. It made us a better team and I am thankful for
that.”

With female coaches, a more laid back approach was utilized. The tone
was much lighter and practice proceeded in a more calm and non-aggressive
fashion. Carmen stated, “The female coach I had, we always got things
done but it was in a lighter tone. Like we’d do what she said and
we’d follow what she wanted us to do but we could be playful at
the same time.” The pressure of doing something wrong or making
a mistake and having to face consequences was not as prevalent with a
female coach. Only one of the participants had a positive outlook towards
this mentality, as Emily explained, “we may not had to have done
[a drill] four hundred times like we did with the males, but the end result
was the same.”

Coach Preference

When asked which coach they preferred the most, eight participants responded
favorably toward the male coach for various reasons. The athletes believed
that to be a good coach, the coach must have respect from the players.
According to Kelli C., “demonstrating their (coaches) soccer knowledge,
ability to control the team, and to enforce discipline,” were all
key elements in gaining the respect of players. Jennifer C. thought, “some
coaches you just respect because they know how to make you respect them.”
Along with respect, the female athletes viewed a good coach as one who
was able to perform the skill and have more than adequate knowledge about
the sport. Carmen stated that “[the male coach] was the one that
knew the most about soccer. He knew the most and challenged me the most.
I grew as a player when I was with him.” Further, Kelli M. stated,
“the males assumed to know more about the basics and the fundamentals.
Everything that’s required for a successful team.” The female
athletes considered an ideal coach to be a good leader, teacher, friend,
and motivator. Specifically, Sam thought a coach should “challenge
players to become better physically, mentally, tactically, and technically,”
while Emily felt that coaches should “teach [athletes], prepare
them for any kind of obstacles that they’re going to have to come
into contact with. Teaching them basics like discipline, punctuality,
getting to practice on time, dealing with other people, teamwork, and
good sportsmanship.” Four of the female participants believed that
a coach should be a good example and help in the teaching of life lessons.
Sam felt that a coach should be “a little bit of everything.”

Discussion

The purpose of the present investigation was to explore a group of female
athletes’ experiences of having female and male coaches. This comparison
demonstrated that four of the six female athletes preferred a male coach,
including various differences of opinions of each coach.

Discipline and Structure

While men were reported to be more detailed in instruction and structured,
the women were more lenient disciplinarians. This finding coincides with
Masin’s (1998) results, which found that 75% of female athletes
preferred male coaches because of more perceived organization. The desire
for this quality might exist because many female athletes want to be pushed
physically, challenged in skill development, and feel the need for competition,
and they believe this can be achieved through a structured environment
(Osborne, 2002). Five of the female athletes in this study expressed a
positive perception of the discipline enforced by the male coaches.

Personal Relationships

A female athlete may benefit from a personal connection with the coach.
When coaching females, there is the need for warmth, empathy, and a sense
of humor (Burke, Peterson, & Nix, 1995; Grisaffe, Blom, & Burke,
in press) with the players (Osborne, 2002). Female high school and college
basketball players ranked the coaching qualities of “relating well
to athletes” and understanding athletes’ feelings” as
two of the top three desirable characteristics, and female coaches rated
significantly higher than male coaches in demonstrating these qualities
(Molstad & Whitaker, 1987). Sabock and Kleinfelter (1987) and Simmons
(1997) found that female athletes were more inclined to disclose personal
information to a female coach. Many of the athletes in the present study
experienced these traits from female coaches. Female coaches in this study
were better at relating and more likely to establish a friendship. Although
the athletes expressed a desire to bond with the coach, they indicated
did not want favoritism to be shown toward any players. Further, many
female athletes thrive on self-satisfaction and the belief they are capable
of doing a certain task or drill, and can best achieve this through encouragement
from the coach (Osborne, 2002). The present findings indicated that female
coaches were viewed as more encouraging and motivating through a greater
use of positive feedback.

Passivity and Aggressiveness

Female athletes tended to be more acceptable of the male coaches’
mentality than that of the female coaches’ mentality. Nine participants
in this study approved the authoritarian style of coaching utilized by
the male coaches. Women may prefer this style of coaching due to cultural
expectations of men in authority positions, male dominance in women’s
sports, or the lack of female coaches as role models (Osborne, 2002).
As with male athletes, female athletes want to be trained hard and challenged.
However, if coaches use an extreme “in your face” mentality,
such as constant yelling, the female athlete may be less receptive to
this style (Osborne, 2002).

Coach Preference

Nine of the female athletes in the present study expressed a preference
for male coaches, citing factors such as a greater level of knowledge,
knowing what it takes to be successful, and having more respect for him.
Previous research (Parkhouse & Williams, 1986) has not shown a clear
consensus as to whether female athletes prefer a male or a female coach
(Lirgg, Dibrezzo, & Smith, 1994; Osborne, 2002). Some of the literature
has claimed that athletes may be more comfortable with male authority
figures who could explain their perceptions (Frankl & Babbitt, 1998;
Osbourne, 2002; Whitaker & Molstad, 1985). Similarly, since men have
held coaching positions for a longer period of time, athletes may have
more confidence in their knowledge levels and coaching abilities (Sabock
& Kleinfelter, 1987). In the late 1980’s and early 1990’s,
much of the literature stated that female athletes preferred a male coach
because there was simply a lack of women in the profession (Osborne, 2002).
Further, coach preference may depend on the gender of the athletes’
present coaches (Medwechuk & Crossman, 1994; Sabock & Kleinfelter,
1987). Since the majority of coaches have been male, this could help to
explain the female athletes’ preference toward male coaches.

Caution must be taken in assuming that coach preference is due only
to gender.
Additional factors exist that may influence athletes’ perceptions
of coaches such as the success of the team (Williams & Parkhouse,
1988) or influence of current coach (Parkhouse & Williams, 1986).
Female athletes who exhibited higher trait anxiety, higher state cognitive
and somatic anxiety, and lower state self-confidence have been shown to
have more negative perceptions of coaches (Kenow & Williams, 1992;
1999). Lirgg, Dibrezzo, & Smith (1994) found that female athletes
coached by females reported a greater desire to become head coaches than
those coached by male coaches. Other personal attributes such as athlete
age (Burke, Peterson, & Nix, 1995; Whitaker & Molstad, 1988),
socioeconomic status, ethnicity, and the athletes’ level of skills
and abilities (Williams & Parkhouse,1988) may also impact athletes’
experiences with coaches. Longitudinal studies should be employed to more
thoroughly examine the influences that male and female coaches have on
athletes.

References

  1. Burke, K. L., Peterson, D., & Nix, C. L. (1995). The effects of the coaches’ use of humor on female volleyball players’ evaluation of their coaches. Journal of Sport Behavior, 18, 83-90.
  2. Carpenter, L. J. & Acosta, V. (1991). Back to the future: Reform with a woman’s voice. Academe, 23-27.
  3. Carron, A. V. & Bennett, B. B. (1977). Compatibility in the coach-athlete dyad. Research Quarterly, 48, 671-679.
  4. Felder, D. & Wishnietsky, D. (1990). Role conflict, coaching burnout, and the reduction in the number of female interscholastic coaches. The Physical Educator, 47, 7-13.
  5. Frankl, D. & Babbitt, D. G. (1998). Gender bias: A study of high school track & field athletes’ perceptions of hypothetical male and female head coaches. Journal of Sport Behavior, 21, 396-407.
  6. Freeman, W. H. (2001). Physical Education and Sport. Boston: Allyn and Bacon.
  7. Glesne, C. (1999). Becoming Qualitative Researchers. New York: Addison Wesley Longman.
  8. Greenleaf, C., Gould, D., & Dieffenbach, K. (2001). Factors influencing Olympic performance: Interviews with Atlanta and Nagano U.S. Olympians. Journal of Applied Sport Psychology, 13, 154-184.
  9. Grisaffee, C., Blom, L. C., & Burke, K. L. (in press). The Effects of Head and Assistant Coaches’ Uses of Humor on Collegiate Soccer Players’ Evaluation of Their Coaches. Journal of Sport Behavior.
  10. Kenow, L. J. & Williams, J. M. (1992). Relationship between anxiety, self-confidence, and evaluation of coaching behaviors. The Sport Psychologist, 6, 344-357.
  11. Kenow, L. & Williams, J. M. (1999). Coach-athlete compatibility and athlete’s perception of coaching behaviors. Journal of Sport Behavior, 22, 251 – 259.
  12. Lirgg, C. D., Dibrezzo, R., & Smith, A. N. (1994). Influence of gender of coach on perceptions of basketball and coaching self-efficacy and aspirations of high school female basketball players. Women, Sport, and Physical Activity Journal, 3, 1-14.
  13. Masin, H. L. (1998). Men coaching women…..Coach and Athletic Director, 68, 16.
  14. Medwechuk, N. & Crossman, J. (1994). Effects of gender bias on the evaluation of male and female swim coaches’. Perceptual and Motor Skills, 78, 163-169.
  15. Molstad, S. & Whitaker, G. (1987). Perceptions of female basketball players regarding coaching qualities of males and females. Journal of Applied Research in Coaching and Athletics, 2, 57-71.
  16. Osborne, B. (2002). Coaching the female athlete. In John M. Silva III & Diane E. Stevens (Eds)., Psychological foundations of sport (pp. 428 – 437). Boston: Allyn and Bacon.
  17. Parkhouse, B. L. & Williams, J. M. (1986). Differential effects of sex and status on evaluation of coaching ability. Research Quarterly for Exercise and Sport, 57, 53-59.
  18. Pastore, D. L. (1992). Two-year college coaches of women’s teams: Gender differences in coaching career selections. Journal of Sport Management, 6, 179-190.
  19. Sabock, R. J. & Kleinfelter, E. R. (1987). Should coaches be gendered? Coaching Review, 10, 28-29.
  20. Simmons, C. D. (1997). The effects of gender of coach on the psychosocial development of college female student-athletes. Unpublished master’s thesis, University of Louisville.
  21. Stewart, C. & Taylor, J. (2000). Why female athletes quit: Implications for coach education. Physical Educator, 57, 170.
  22. Udry, E., Gould, D., Bridges, D., & Tuffey, S. (1997). People helping people? Examining the social ties of athletes coping with burnout and injury stress. Journal of Sport and Exercise Psychology, 19, 368-395.
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Table 1
Mean Demographic Data of Female Athletes

Participant
(Pseudonym)
Sport(s) Years of Experience Years coached by a male Years coached by a female
Kelli C. Basketball Soccer and
Softball
10 7 3
Kelli M. Basketball 11 7 4
Carmen Soccer 13 10 3
Emily Soccer 12 9 3
Jennifer C. Golf and Basketball 13 6 ½ 6 ½
Sam Soccer and Basketball 12 8 4
Lekeisha Basketball 10 7 3
Tyler Cross Country 11 8 3
Misha Soccer 9 4 5
Kylie Softball 10 5 5
Alexis Basketball 8 3 5
Natalie Track and Field 9 7 2
Carmen Soccer 13 10 3

Appendix

Interview Guide
The initial question posed to participants: “What do you think the role of a coach should be?”

Following questions:

  1. What sport do you play?
  2. When were you coached by a male and a female?
  3. How many years were you coached by a male and a female?
  4. In what setting did you have the male and female coach?
  5. Which coach did you prefer the most?
  6. Who do you think knew more about the sport? Why?
  7. If you had daughters, whom would you want them to be coached by?
    Why? Were there any differences/ similarities between the male and female
    coaches in regards to:
  8. Training practices and evaluation performance?
  9. Encouragement and motivation?
  10. Punishments and commands?
  11. Helping with personal problems and enjoyment?
  12. Encouraging after mistakes and correcting behavior?
  13. Coaching methods?
  14. In an ideal world, what would you like to see in the world of female
    sports in regards to coaching?
  15. In general, what are your thoughts about males and females coaching
    female athletes?
2015-03-27T13:38:02-05:00September 3rd, 2006|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology, Women and Sports|Comments Off on An Exploration of Female Athletes’ Experiences and Perceptions of Male and Female Coaches

Gender, Skill, and Performance in Amateur Golf: An Examination of NCAA Division I Golfers

Abstract

In a previous study, it was found that male amateur golfers must possess a variety of shot-making skills to be successful and that relative to driving ability, putting skills and reaching greens in regulation contribute more to explaining tournament success. This present research extends these findings by expanding the investigation to analyze the performance determinants of both female and male amateur golfers. In so doing, we are able to test for the presence of gender-based differences in skill levels and in the relationship between skills and tournament performance. Using a sample of NCAA Division I male and female golfers who participated in tournament play during 2004-2005, our research offers two interesting observations. First, on average, male and female amateur golfers possess different levels of shot-making skills. Second, these disparate skills influence tournament performance differently across genders. Although the causality of these gender-based disparities cannot be identified with certainty, several plausible explanations are considered.

Introduction

In an earlier research study of amateur golfers, we empirically examine the relationship between a male golfer’s tournament performance and a set of shot-making skills (Callan and Thomas, 2004). This initial investigation was the first of its kind to focus on a sample of NCAA Division I male golfers. Statistically, those findings validate analogous research on the performance of professional golfers. What we discovered is that male amateur golfers, like their professional counterparts, must possess a wide variety of shot-making skills to be successful. Moreover, we found that, relative to driving ability, putting skills and reaching greens in regulation contribute more to explaining the variability in a player’s success. This present study extends that research to study both men and women amateur golfers and, in so doing, allows us to test for the presence of gender-based differences in skill levels or in any skill-to-performance relationship.

That gender-specific skill differences exist in the game of golf is explicitly recognized by the United States Golf Association (USGA), which is the governing body for the rules of golf. For example, in its rating system of golf courses, the USGA specifically defines a bogey golfer and a scratch golfer according to the golfer’s gender, as noted below (United States Golf Association, 2005).

Bogey Golfer:

“A male bogey golfer is a player who has a Course Handicap© of approximately 20 on a course of standard difficulty. He can hit tee shots an average of 200 yards and can reach a 370-yard hole in two shots at sea level.

A female bogey golfer is a player who has a Course Handicap© of approximately 24 on a course of standard difficulty. She can hit tee shots an average of 150 yards and can reach a 280-yard hole in two shots at sea level.”

Scratch Golfer:
“A male scratch golfer is a player who can play to a Course Handicap© of zero on any and all rated golf courses. A male scratch golfer, for rating purposes, can hit tee shots an average of 250 yards and can reach a 470-yard hole in two shots at sea level.

A female scratch golfer is a player who can play to a Course Handicap© of zero on any and all rated golf courses. A female scratch golfer, for rating purposes, can hit tee shots an average of 210 yards and can reach a 400-yard hole in two shots at sea level.”

Following these and other gender-specific distinctions made by the USGA, it is reasonable to expect that on average, male golfers are able to drive the ball longer distances off the tee, and female golfers have shorter approach shots to each green. Similar assertions, some with supporting data, are found in the literature, for example, Shmanske (2000) and Wiseman, Chatterjee, Wiseman, and Chatterjee (1994). Such observations motivate the need to learn how such gender-based skill differences translate into scoring performances under actual tournament conditions.

While no existing research papers examine this skill-to-performance relationship across male and female amateur golfers, there are studies that investigate the existence and degree of gender differences among professional golfers. Generally in such investigations, two questions are examined:

  1. Do the data support the hypothesis that there are statistically different shot-making skills across male and female golfers?
  2. How do shot-making skills influence a golfer’s tournament performance, and is this set of relationships gender specific?

To illustrate, we offer a few salient examples of this research and an overview of the approach used in each case.

Using performance measures for the 1992 season, Wiseman, Chatterjee, Wiseman, and Chatterjee (1994) investigate the influence of gender differences across golfers in the Professional Golfers’ Association (PGA), Senior PGA (SPGA), and Ladies PGA (LPGA). Overall performance is measured in their study by the average score per round of golf, and the shot-making skills considered are driving distance, driving accuracy, hitting greens in regulation, and putting. What these researchers find is that, on average, male PGA golfers drive the ball farther and hit a larger percentage of greens in regulation than female professionals. Driving accuracy was approximately the same across genders. Because the PGA and LPGA do not collect putting data in the same manner, no gender comparisons could be made about putting ability. However, using multiple regression analysis, Wiseman, et al. (1994) discover that the two most influential skills for female golfers are putting and hitting greens in regulations. These two skills explained 88 percent of the variability in an LPGA member’s average score per round. However, male PGA golfers need a more well-rounded game, as indicated by the importance of all shot-making skills in determining their tournament performance.

In a more recent study, Moy and Liaw (1998) examine golfers’ shot-making skills and tournament performance during the 1993 tournament season for the same professional tours used by Wiseman, et al. (1994). For the most part, Moy and Liaw’s findings agree with those of Wiseman, et al. (1994) regarding PGA golfers’ skills at driving the ball and reaching greens in regulation relative to LPGA golfers. However, they add a variable that captures sand saves, measured as the percentage of time a player gets out of a greenside bunker and scores par or better on the hole. They find that, on average, PGA golfers achieve a higher proportion of sand saves relative to their female counterparts in the LPGA. Given that no comparable putting statistic was available across the two tours, Moy and Liaw were unable to test for gender differences with respect to putting skills.

Shmanske (2000) statistically compares the skill-to-performance relationship for a sample of PGA golfers and LPGA golfers for the 1998 tournament season. In addition to the conventional shot-making skills, Shmanske constructed a comparable putting skill measure for each set of tour professionals. Overall, his results on gender differences are consistent with those of previous researchers. Specifically, he finds that male professional golfers drive the ball farther off the tee, have a higher sand save percentage, and demonstrate a higher putting proficiency. For the other key shot-making skills, namely driving accuracy and hitting greens in regulation, Shmanske observes no meaningful difference across genders.

While these studies have contributed to our understanding of gender differences in professional golf, no analogous investigations have been done for amateur golf. Recognizing the importance of this issue, we extend our previous study of amateur golfers (Callan and Thomas, 2004) to an analysis of skills and performance across male and female amateurs. Using the fundamental framework suggested by Wiseman, et al. (1994) and others, we use a two-pronged approach to our investigation. First, we statistically test for gender-specific skill differences at the amateur level. Second, we use regression analysis to assess the influence of a player’s shot-making skills on tournament performance and statistically determine if these skill-to-performance relationships are affected by gender.

Method

Sample

To conduct our investigation, we use a subset of NCAA Division I male and female golfers who participated in at least one tournament during the 2004–2005 season. Data on members of all Division I teams are not available. The colleges and universities represented in this study are identified in Table 1 along with the number of players on each team, the number of tournaments played during the season, and the average length in yards of the typical course on which the teams played. Most of these data are obtained from Golfstat, Inc. (2005), which is accessible on the Internet at www.golfstat.com.

Notice that the data presented in Table 1 suggest some important distinctions across genders. At a fundamental level, we observe that male golf teams, on average, comprise between 8 and 9 players, while female teams are smaller, averaging between 7 and 8 players. We also note that males play in slightly more tournaments than females, averaging 10.8 for males and 9.7 for females. Consistent with the USGA’s rating system, we also observe that the average male golfer plays courses that are almost 1,000 yards longer than those played by females, specifically 7,042 yards for men versus 6,104 for women. As a consequence, one might infer that male golfers place a higher premium on driving distance, while female golfers might focus more on developing their short game skills.

Measures

For each of the universities included in this research, Golfstat, Inc. collects and reports statistics for player skills and tournament performance. In this study, we use data for the 2004–2005 NCAA Division I tournament season for men and women teams from the same group of institutions. Just as we argue in our 2004 study, AVERAGE SCORE per round is a viable measure of tournament performance, since earnings are not relevant at the amateur level. Moreover, Wiseman et al. (1994) assert that correlation results are actually stronger when scoring average, as opposed to earnings, is used. As for the shot-making skills, we use a set of variables that collectively capture each player’s golf game from tee to green. Among these are measures of driving ability, fairways hit, greens in regulation, sand saves, and putting, which follows the approach used in Callan and Thomas (2004). We briefly discuss each measure in turn, starting with those capturing a player’s long game.

To capture each amateur’s ability to drive the golf ball, we use the variable EAGLES, defined as the cumulative number of recorded eagles (i.e., two strokes under par on any hole) a player makes each season. This variable serves as a proxy for driving distance, which is a statistic not reported by Golfstat. In support of this proxy measure, Dorsel and Rotunda (2001) report a positive correlation between a player’s driving distance and the number of eagles made. Related to driving distance is accuracy in driving the ball into the fairway. To measure this skill, we use the variable FAIRWAYS HIT, measured as the percentage of time a player drives the golf ball off the tee and into the fairway. We also define a variable called GREENS IN REGULATION (GIR) as the percentage of time a player reaches a green in the requisite number of strokes, specifically one for a par three, two for a par four, and three for a par five. This follows the work of Belkin, Gansneder, Pickens, Rotella, and Striegel (1994), who assert that GIR captures a player’s iron skill and success in reaching a green within the regulation number of strokes.

As for a player’s short game, we employ two skill variables that are commonly used in the literature. The first is SAND SAVES, which measures the percentage of time a player gets out of a greenside bunker and achieves a score of par or better. The second is a player’s ability to putt the ball into the hole once on the green. To capture this shot-making skill, we use the variable PUTTS PER ROUND, which measures the average number of putts a golfer makes per round of golf. This follows Belkin, et al. (1994).

Beyond the effect of shot-making skills, we hypothesize that a golfer’s overall performance is influenced by two other key factors – a player’s experience level and any associated team effects. Recognizing experience as a determinant of a golfer’s performance follows Shmanske (1992) and others. In the professional literature, experience is typically captured by the number of years a player has been a professional player. For this analysis of amateur golfers, we construct two experience variables. One is the variable ROUNDS, which is simply the number of tournament rounds completed by each player during the 2004–2005 season. This variable effectively measures a player’s short-term experience, because it captures the way each additional round played in a season adds to the knowledge a player can call upon in subsequent rounds. The second experience measure controls for longer-term cumulative experience and is modeled through a set of dummy variables that reflect the player’s academic age, specifically FRESHMAN, SOPHOMORE, JUNIOR, or SENIOR. The underlying expectation is that the more advanced is a player’s academic age, the more collegiate golfing experience has been gained and, therefore, the lower the expected average score.

The other theorized non-skill determinant of amateur performance is characterized as team effects. These are expected to arise from various factors, including the expertise and experience of the coach and the relative challenge of the courses played by the team. Coaches can directly affect the success of each player in myriad ways, such as through mentoring, leadership, instruction, and guidance. As a leader, the coach is responsible for setting team strategy and for determining the extent of each player’s tournament participation. As an instructor, the coach guides and motivates the development of each player’s athleticism and skills. Hence, collegiate golfers can achieve varying levels of success in the sport based in part on the expertise and experience of their coach, holding skill levels constant.

Likewise, a player’s amateur performance might be affected by the courses played by their team, because course venues, and hence their relative difficulty, vary across collegiate teams. Therefore, a member of a team that plays on relatively easy courses in a tournament season might enjoy a lower average score for that season, and, of course, the converse is true. To account for such team effects, we construct university-specific dummy variables for each player, whereby each identifies the team to which a player belongs.

Procedures

For this study, two conventional statistical procedures were used to analyze the skill and non-skill determinants of amateur golf performance, controlling for gender. One is the two-sample t-test, which was used to statistically examine the difference between mean values of male and female shot-making skills. The second procedure is the use of a multiple regression model that estimates the influence of skill, experience, and team effects on a player’s tournament score, holding constant all other score determinants. Ordinary least squares (OLS) is used to derive the regression estimates.

Results and Discussion

In Table 2, we present descriptive statistics for the sample of 179 amateur golfers, comprising 94 males and 85 females. At the collegiate level, tournaments generally consist of 3 rounds of golf, and each round comprises 18 holes of play. In our sample, the average NCAA Division I male golfer had an average score per round of approximately 75 strokes during the 2004–2005 season. In comparison, the average female golfer had a higher average score per round of about 79 for the season.

Based on the two experience variables, the average male amateur has more experience than the average female. For short-term experience, we observe that males play slightly more than 24 rounds of golf in the season, while females play fewer rounds, at about 22. As for longer-term experience based on academic age, approximately 61 percent of male team members are juniors and seniors, while the comparable value for females is lower at 47 percent.

Turning our attention to shot-making skills, we observe the following distinctions across genders. The average male golfer hits approximately 64 percent of fairways and reaches greens in the regulation number of strokes 60 percent of the time. Female golfers, on the other hand, hit 70 percent of fairways and reach greens in regulation 50 percent of the time. Over the course of a round, a male golfer makes slightly less than 31 putts, while the female golfer makes slightly more than 32 putts. For sand saves, the data show that the amateur male golfer makes par or better when hitting from a bunker 39 percent of the time, which is notably higher than the amateur female golfer, who has a comparable success rate of 29 percent. Lastly, over the course of the 2004–2005 season, the average male player makes 1.8 eagles, while the average female had 0.34 eagles, suggesting superior driving distance for males.

For each variable in the table, we also find the coefficient of variation for each gender group. As a measure of dispersion, this statistic contributes useful information about performance and skills across genders. Notice that for AVERAGE SCORE, the coefficient of variation is smaller for males than females. The same is true for all shot-making skill variables with the single exception of PUTTS PER ROUND. What these results imply is that there is a greater degree of competition among amateur male golfers than among females, an interpretation that follows Moy and Liaw (1998).

By simple observation, these data suggest that there may be statistically significant differences in skill levels across genders. To formally examine this theory, we use two-sample t-tests across the gender-specific skill variables and present our findings in Table 3. Not surprisingly, there are indeed statistically significant differences across genders (i.e., p < 0.0001) for all shot-making skills. Specifically, NCAA Division I male golfers, on average, possess superior shot-making skills relative to their female counterparts for EAGLES, GIR, PUTTS PER ROUND, and SAND SAVES. These findings generally agree with those found in research studies of professional golfers (Wiseman, et al., 1994; Moy and Liaw, 1998; Shmanske, 2000). The opposite relationship holds for FAIRWAYS HIT, the measure of driving accuracy, for which female collegiate golfers are statistically superior to males, on average.

While certainly of interest, the observation of gender-specific skill differences does not ensure that they translate into comparable changes in tournament performances. Investigation of this important issue requires the use of a multiple regression model. To that end, we specify a model to estimate the relationship between an amateur golfer’s average score and each of the determinants identified previously, specifically the set of five shot-making skills, the two experience measures, and the team dummy variables. To identify whether these determinants affect average score differently across males and females, we explicitly control for gender through the use of an interactive binary variable, FEMALE. This variable equals 1 if the golfer is female and 0 if male. It enters the model by itself as well as multiplicatively with each of the other explanatory variables. That way, each score determinant enters the model directly to represent males and multiplicatively with FEMALE to represent any incremental differences for females. In so doing, the estimation results quantify not only how shot-making skills, experience, and team effects influence average score but also whether those effects vary across genders.

The results of this multiple regression analysis are given in Table 4. Based on the adjusted R2 statistic, the regression model explains approximately 95 percent of the variability in a golfer’s tournament performance. Of particular interest are the gender-specific estimates that communicate the relative importance of each shot-making skill on overall performance, holding constant all other skills, team effects, and player experience. We also can assess the influence of all non-skill factors on a player’s average score independent of skill levels, and again, we can do so by gender. The estimated values for male golfers are listed in the first two columns of the table, and the estimates of any incremental differences for females are given in the second pair of columns.

To determine if the gender-based distinctions are collectively relevant, we conducted several F-tests, the results of which are shown at the bottom of Table 4. Other than the test for academic age variables for which gender differences are only marginally significant, all other F-tests indicate that gender differences exist and are statistically significant. These include tests for the overall model, for shot-making skills, and for team effects. These are important findings, which, to the best of our knowledge, have not yet been identified in the literature. They communicate far more than differences in skill levels across males and females. Rather, these results suggest that improvements in skill levels do not translate equivalently to better performance outcomes for both gender groups.

Next consider the individual results for each of the explanatory variables, starting with the set of shot-making skills. With the exception of FAIRWAYS HIT, each shot-making skill has a statistically significant influence on a player’s tournament performance, and each bears the expected algebraic sign. We also find that for several of these shot-making skills, gender differences exist and are statistically significant. Specifically, male golfers gain more tournament success than females from improving SAND SAVES. Conversely, increasing the GIR proportion statistically improves a female golfer’s tournament performance more than it does for a male. An analogous argument is relevant to reducing PUTTS PER ROUND. There are no apparent gender-based differences for EAGLES. Perhaps this outcome is due to the USGA establishing different tee boxes for males and females, which may correctly adjust for any inherent gender-based differences in driving ability.

As for the experience measures, the results suggest that short-term experience measured through ROUNDS does improve tournament performance and does so with no difference between the genders. For cumulative experience, captured through the academic age variables, FRESHMAN, SOPHOMORE, JUNIOR, and SENIOR, only the results for females are reasonable. Specifically, we find that female sophomores achieve higher average scores relative to seniors (the suppressed academic age variable). This makes sense, suggesting that greater collegiate experience improves performance. For males, the parameter on SOPHOMORE is significant, but its algebraic sign is negative. This outcome may be an artifact of the data sample, such as an unusually talented group of male sophomores in the 2004–2005 tournament season. It might also be related to the fact that in this sample, there are about 50 percent more male seniors than male sophomores, while for females there are 12.5 percent fewer seniors than sophomores.

We further find that team effects exist for certain universities. Golfers from East Tennessee State, on average, have higher average scores for the season than those from Vanderbilt University (the suppressed variable), regardless of gender. The same is true for players at the University of Texas. This implies that Vanderbilt University may have a better coaching staff and/or the Vanderbilt teams may play on less challenging courses. Interestingly, the team effect results also suggest a gender difference for teams at Indiana University and Kent State. In both cases, female teams perform at a lower level (i.e., have higher average scores), than their male counterparts, holding constant all other score determinants, including shot-making skills.

To quantify the effect of these differences, we follow Shmanske (2000) and compare the fitted value of average score for an arbitrarily defined male (e.g., a sophomore at Kent State University), with a predicted value that uses female parameter estimates with mean values of male score determinants. What we find is that the fitted value for average score is 73.88, but the predicted value is 75.38. This helps to underscore how the skill-to-performance relationship for females causes their scores to be higher than males, holding all else constant. Using the same approach for an analogously defined female (i.e., a sophomore at Kent State University) yields a fitted value for average score of 79.51, but a predicted value of 77.35, using mean values of female score determinants with male parameter estimates. Again, the difference indicates that the skill-to-performance relationship for males contributes to their scores being lower than that of females, holding skills, experience, and team effects constant.

That these collective results provide some evidence of gender-specific differences in how various factors affect performance is an interesting set of findings. That is, we now have a better sense of why amateur golf performance varies across gender groups. The commonly discussed observation of different average scores for males versus females seems not to be solely a function of differences in skill levels or years of experience but also a function of how changes in score determinants affect golfer performance.

How might we explain these differences? Although definitive answers are beyond the scope of this research, we offer three possible explanations based on selected analyses and theories that have been explored in the literature. These are based on: (1) differences in the degree of competition; (2) varying opportunities within and across university athletic programs; and (3) dissimilar physiological and psychological factors. We present a brief overview of each, which may encourage further investigation of these and other possible explanations.

First, based on the calculations of the coefficient of variation discussed previously and presented in Table 2, there seems to be a greater degree of competition among male amateurs. This is not unlike what Moy and Liaw (1998) find in their analysis comparing professional male and female golfers. More competition among males might encourage longer practice sessions and greater concentration, which in turn should yield higher skill levels and correspondingly greater improvements in performance as those skills develop. Somewhat related to this issue is that male amateurs might also be more highly motivated to practice and may compete more aggressively because of greater earnings potential at the professional level than females. This reality is based in part on higher purses offered on the PGA tour than on the LPGA tour. In fact, some studies of professional golf suggest that golfer success depends on effort, which in turn is influenced by the skewed distribution of tournament purses, meaning that performance improves when the stakes are higher (Ehrenberg and Bognanno, 1990; Shmanske, 2000).

Second, there may be disparate expertise in the coaching staffs and/or significant differences in course difficulty for male teams relative to female teams. This might be the case across institutions or it may arise within a university’s athletic department. The source of such differences is important, since the provision of unequal opportunities based on gender is a violation of Title IX of the Educational Amendment Act of 1972, in which Section 106.41 pertains specifically to athletic programs. Part C of that section identifies several factors that are to be considered when assessing the provision of equal opportunities to both sexes. These include the provision of equipment and supplies, the scheduling of games and practice time, the opportunity to receive coaching and academic tutoring, and the provision of practice and competitive facilities (U.S. Department of Education, 1972).

Third, it is often argued in both the common press and professional journals that gender differences in golf skills and performance might be attributable to physiological or psychological distinctions between males and females. The nature and validity of such arguments are being studied and intensely debated in the literature, and hence no definitive conclusion can be offered here. However, we can identify some of the more salient elements of these arguments, and suggest that they may help to explain the gender differences observed in our sample of amateur golfers.

Some researchers focus on psychological factors that may have differing effects on the play of male and female golfers. To illustrate, consider that Hassmen, Raglin, and Lundqvist (2004) identify a significant correlation between the variability of amateur male golfers’ somatic (or physiological) anxiety levels and the variability of their golf scores. However, Krane and Williams (1992) find no such relationship for their sample of amateur female golfers.

Others ascribe gender-based performance differences to physiological attributes. A common assertion in the professional golf literature is that men’s larger physical size and greater strength explains their ability to drive the ball further than females, and this may in turn explain the lower mean golf scores achieved by males. See, for example, Moy and Liaw (1998). However, others argue that such an assertion is incorrect, because driving a golf ball requires more skill than brute strength alone would provide (Shmanske, 2000). Indeed, in a sophisticated study of the biomechanics of golf, Hume, Keogh and Reid (2005), analyze the two main movements in golf – the swing and the putt, and show that golfers must possess strength, flexibility, and timing to achieve the distance and accuracy necessary for success. Hence, observed gender differences in shot-making skills might be linked to dissimilarities in any or all of these attributes. Some evidence of this hypothesis is offered by Myers, Gebhardt, Crump, and Fleishman (1993), who find within their tests of male and female physical abilities that males scored higher than females on tests of strength and stamina, while females scored higher on tests of flexibility. These findings might explain why male golfers generally drive the ball farther than women and why females typically achieve greater driving accuracy, results found in our analysis and others.

Conclusions

In our previous study of NCAA Division I male golfers, we identified the relationship between an amateur golfer’s tournament performance and various shot-making skills (Callan and Thomas, 2004). This present investigation advances this work by extending the analysis to both females and males. In so doing, we are able to examine whether the skill levels of amateur female golfers differ from those identified for males. Taking this one step further, we also are able to estimate the relationship between each shot-making skill and overall performance for males and females and specifically test for any statistically significant gender differences. To our knowledge, this is the first such study to examine gender differences in amateur golf.

Using a sample of NCAA Division I male and female golfers who participated in tournament play during 2004-2005, our empirical estimation and subsequent analysis supports two important conclusions. First, male and female amateur golfers, on average, possess dissimilar levels of various shot-making skills, and these differences indeed are statistically significant. Such dissimilarities are consistent with the literature examining gender distinctions among professional golfers. In this case, we find that on average, NCAA Division I male golfers possess superior shot-making skills relative to females for all shot-making skills except FAIRWAYS HIT, for which the opposite is true. Second, the manner in which shot-making skills influence tournament performance is not independent of gender. For example, male golfers achieve greater performance improvements by improving SAND SAVES, while females gain more from increasing the GIR proportion and from reducing PUTTS PER ROUND.

Both sets of results are of interest because they improve our understanding of the complexities of amateur golf tournament play. Moreover, through statistical testing, they validate anecdotal evidence of differing skill levels and performance outcomes across male and female collegiate teams. In so doing, the findings suggest the need for further research to learn more about these distinctions and, if necessary, to suggest changes in tournament play that recognize, and perhaps correct for, these disparities.

Although the root causes of gender-based differences in NCAA Division I golf cannot be identified, we do offer several plausible explanations based on research findings from the economics, sports medicine, and physiology literatures. First, we offer the possibility that the higher degree of competition among male golfers may incite more practice and more intensity of play, which in turn may translate into superior skills and/or tournament scores. Second, we suggest that skill and performance distinctions may be related to differences in facilities, coaching, and/or varying course venues. Further study is needed to identify these differences and to determine if there are associated implications for Title IX. Lastly, we consider the role of physiological and psychological factors in explaining gender-specific skill levels and performance in sports, an area that has been, and likely will continue to be, studied in earnest.

We believe that our study and its associated findings are of interest in their own right and contribute to the literature examining both professional and amateur golf. However, it is our hope that this work will have broader implications by encouraging new research in amateur golf and other sports aimed at learning more about the skill-to-performance relationship and the influence of gender and other factors on this important connection in amateur and professional sports.

REFERENCES

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TABLE 1
UNIVERSITIES INCLUDED IN THE STUDY
MEN’S GOLF TEAM WOMEN’S GOLF TEAM
UNIVERSITY NUMBER
OF
GOLFERS
NUMBER OF TOURNAMENTS AVERAGE YARDS PER TOURNAMENT (STANDARD DEVIATION NUMBER OF GOLFERS NUMBER OF TOURNAMENTS AVERAGE YARDS PER TOURNAMENT (STANDARD DEVIATION)
Coastal Carolina University 10 11 6971
(119)
5 10 5994
(75)
Ea. Tenn. State University 9 10 7029
(125)
7 9 5978
(106)
Fresno State University 8 14 6924
(238)
8 11 6080
(121)
Indiana
University
9 11 7035
(129)
8 10 6120
(111)
Kent State University 8 10 7017
(156)
7 11 6111
(123)
University of Kentucky 7 10 7091
(227)
11 11 6162
(377)
University of New Mexico 8 11 7128
(330)
6 8 6090
(177)
University of So. California 9 11 6934
(186)
10 9 6115
(169)
Texas A & M University 10 11 7066
(213)
9 10 6187
(125)
University of
Texas
8 10 7218
(224)
8 9 6169
(186)
Vanderbilt University 8 10 7045
(215)
6 9 6139
(171)
Average
(std. deviation)
8.5
(0.93)
10.8
(1.17)
7042
(85.34)
7.7
(1.8)
9.7
(1.01)
6104
(66.99)

Source: Golfstat, Inc. (2005) and individual team Web pages.

TABLE 2
BASIC DESCRIPTIVE STATISTICS
MEAN STANDARD DEVIATION MINIMUM MAXIMUM COEFFICIENT OF VARIATION
VARIABLE MALE
(N=94)
FEMALE
(N=85)
MALE FEMALE MALE FEMALE MALE FEMALE MALE FEMALE
Score 74.97 79.23 2.22 3.53 69.95 73.50 81.33 94.45 0.030 0.045
Eagles 1.80 0.34 2.23 0.61 0.00 0.00 9.00 2.00 1.239 1.794
Fairways Hit 0.64 0.70 0.08 0.09 0.36 0.47 0.86 0.88 0.125 0.129
Greens in Regulation 0.60 0.50 0.08 0.10 0.33 0.16 0.81 0.65 0.133 0.200
Putts per Round 30.83 32.31 1.42 1.29 23.00 29.84 35.33 35.71 0.046 0.040
Sand Saves 0.39 0.29 0.15 0.13 0.00 0.06 1.00 1.00 0.385 0.448
Rounds 24.11 22.31 12.83 8.89 3.00 3.00 43.00 36.00 0.532 0.398
Freshman 0.17 0.29 0.38 0.46 0.00 0.00 1.00 1.00 2.235 1.586
Sophomore 0.22 0.24 0.42 0.43 0.00 0.00 1.00 1.00 1.909 1.792
Junior 0.28 0.26 0.45 0.44 0.00 0.00 1.00 1.00 1.607 1.692
Senior 0.33 0.21 0.47 0.41 0.00 0.00 1.00 1.00 1.424 1.952

NOTE: Basic statistics for each university dummy variable are available from the authors upon request.

TABLE 3
MEAN DIFFERENCES IN SHOT–MAKING SKILLS ACROSS GENDERS
Variable Mean Difference
(Male – Female)
Standard Error* t-statistic p-value
Eagles 1.4567 0.2501 5.82 <.0001
Fairways Hit –0.0540 0.0128 –4.24 <.0001
Greens in Regulation 0.0982 0.0132 7.46 <.0001
Putts per Round –1.4810 0.2036 –7.27 <.0001
Sand Saves 0.0984 0.0216 4.56 <.0001

*Standard error calculation assumes male and female populations have equal variances.

 

 

TABLE 4
REGRESSION MODEL PARAMETER ESTIMATES
DETERMINANTS PARAMETER ESTIMATE INTERACTION TERMS (FOR FEMALES) PARAMETER ESTIMATE
Intercept 69.40 *** Female Intercept –15.24 ***
Shot-Making Skill Variables Shot-Making Skill Variables
Eagles –0.10 ** (Female)(Eagles) 0.22
Fairways Hit 0.05 (Female)(Fairways Hit) –0.40
Greens in Regulation (GIR) –21.86 *** (Female)(GIR) –4.08 *
Putts per round 0.64 *** (Female)(Putts per Round) 0.53 ***
Sand Saves –1.32 ** (Female)(Sand Saves) 1.68 **
Experience Variables Academic Age Variables
Rounds –0.03 *** (Female)(Rounds) 0.01
Junior 0.05 (female)(Junior) –0.23
Sophomore –0.41 * (Female)(Sophomore) 0.68 *
Freshman 0.08 (Female)(Freshman) 0.02
Team Variables Team Variables
Coastal Carolina 0.44 (Female)(Coastal Carolina) 0.95
East Tennessee State 1.11 *** (Female)(East Tennessee) 0.49
Fresno State 0.58 (Female)(Fresno State) –0.14
Indiana University –0.21 (Female)(Indiana University) 1.77 **
Kent State –0.34 (Female)(Kent State) 1.13 *
Univ. of Kentucky 0.56 (Female)(Univ. of Kentucky) 0.35
Univ. of New Mexico 0.32 (Female)(Univ. of New Mexico) 0.07
Univ. of Southern California 0.44 (Female)(Univ. of Southern California) –0.55
Texas A&M University 0.06 (Female)(Texas A&M University) 1.01
University of Texas 0.99 ** (Female)(University of Texas) –0.56
F-Statistic 82.75
(p-value< 0.001)
R-Squared 95.87
Adjusted R-Squared 94.71
F-Statistic (no gender differences overall) 2.83
(p-value < 0.001)
F-Statistic (no gender differences with respect to shot-making skills) 2.84
(p-value = 0.012)
F-Statistic (no gender differences with respect to academic age) 2.10
(p-value = 0.103)
F-Statistic (no gender differences with respect to team variables) 2.39
(p-value = 0.012)

* significant at the 0.10 level, assuming a one-tailed test of hypothesis for skills and two-tailed test elsewhere
** significant at the 0.05 level, assuming a one-tailed test of hypothesis for skills and two-tailed test elsewhere
*** significant at the 0.01 level, assuming a one-tailed test of hypothesis for skills and two-tailed test elsewhere

2015-03-27T11:50:33-05:00June 3rd, 2006|Contemporary Sports Issues, Sports Exercise Science, Sports Studies and Sports Psychology, Women and Sports|Comments Off on Gender, Skill, and Performance in Amateur Golf: An Examination of NCAA Division I Golfers
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