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Strength of Religious Faith of Athletes and Nonathletes at Two NCAA Division III Institutions

U.S. Sports Academy2013-11-25T20:07:51-06:00January 7th, 2009|Contemporary Sports Issues, Sports Management, Sports Studies and Sports Psychology|

Abstract

Strength of religious faith of athletes and nonathletes attending (a) a religiously practicing institution (RPI) and (b) a non–religiously practicing (NRPI) institution in NCAA’s Division III was studied using the Santa Clara Strength of Religious Faith Questionnaire. A 2 × 2 × 2 ANOVA sought differences in strength of faith of RPI students (n = 201) versus NRPI students (n = 174). Results show RPI students displayed stronger faith than NRPI students, F(1, 367) = 25.44, p < .01. A significant interaction showed RPI nonathletes more faithful than RPI athletes, F(1, 367) = 6.73, p < .05; NRPI athletes did not differ significantly from NRPI nonathletes. Women’s faith was stronger than men’s, F(1, 367) = 12.99, p < .01.

Strength of Religious Faith of Athletes and Nonathletes at Two NCAA Division III Institutions

An increase in research examining the purpose of religion in the lives of intercollegiate athletes has occurred in recent years (Balague, 1999; Storch & Storch, 2002a; Storch & Storch, 2002b; Storch, Storch, & Adams, 2002; Storch, Storch, Kovacs, Okun, & Welsh, 2003). Religion can be an important aspect in athletes’ lives and may serve a protective function against psychological distress and maladaptive behaviors such as substance use or aggression (Storch, Roberti, Bravata, & Storch, 2004). Viewers of sporting events can frequently observe athletes pointing to the sky, engaging in team prayer on the court or field, and glorifying God following athletic competitions.

Numerous studies report athletes to be more religious than nonathletes (Fischer, 1997; Storch, Kolsky, Silvestri, & Storch, 2001; Storch et al., 2004). According to Storch, Kolsky, Silvestri, and Storch (2001), four reasons may explain why religion interacts with athletic performance. First, athletes may identify with religious beliefs for direction and humility. Second, athletes may turn to religion to gain a sense of optimism and security, benefiting from such beliefs following a disappointing athletic performance. Third, religion can be used for emotional and psychological support in stressful circumstances like the uncertainty of athletic competition, which can cause athletes an overwhelming amount of anxiety. Religious beliefs can offer the internal strength to persevere through the stress. Fourth, religion “provides a cognitive framework conducive to the relief of anxiety associated with competition” (Storch et al., 2001, p. 347). This framework allows relief from fear and anxiety on the basis of the athlete’s understanding (i.e., belief) that a supreme being is in complete control of the situation. For example, athletes may rely on religious faith to place a poor athletic performance in perspective.

Although research investigating the impact of religion within sports has recently increased, an abundance of such literature does not yet exist. Studies that are currently available of religion’s impact on the lives of students, in particular, have focused on athletes and nonathletes at National Collegiate Athletic Association (NCAA) Division I institutions (Fischer, 1997; Storch et al., 2001; Storch et al., 2004). There is a significant shortage of literature assessing religiosity in athletes in other collegiate settings, for example at institutions in the NCAA Division II, NCAA Division III, National Association of Intercollegiate Athletics (NAIA), or National Junior College Athletic Association (NJCAA). An athlete’s experience in any of these unique university environments may have a significant effect on his or her athletic, academic, and social development. In examining students at NCAA Division III institutions, the present study addressed this shortage. In addition, it is the first published investigation comparing the level of religious faith of athletes and nonathletes attending a religiously practicing institution (RPI). Given religion’s importance to the lives of many athletes (Balague, 1999), a need existed to investigate the impact of religion on students attending an NCAA Division III RPI and an NCAA Division III non–religiously practicing institution (NRPI).

The study’s purpose was to assess and compare the strength of religious faith characterizing athletes and nonathletes at an institution of each type. Acknowledging the impact of religious faith may help coaches understand athletes and may help clinicians and sports consultants develop appropriate interventions for athletes who are religious. For example, psychological interventions designed for sports, for example relaxation and visualization techniques, may make some religious athletes uncomfortable, if such psychological methods create a feeling of dissonance with the athletes’ religious creeds. Furthermore, knowledge of the role of religion in an athlete’s life can enhance the athlete-sports consultant relationship, as well as facilitate communication between the athlete and coach (Storch & Farber, 2002; Storch et al., 2001).

The following research questions guided this study:

• Were there significant differences in strength of religious faith between students attending an NCAA Division III RPI and students attending an NCAA Division III NRPI?
• Were there significant differences in strength of religious faith between athletes and nonathletes attending an NCAA Division III RPI?
• Were there significant differences in strength of religious faith between athletes and nonathletes attending an NCAA Division III NRPI?
• Were there significant gender differences in strength of religious faith of athletes and nonathletes attending the NCAA Division III RPI and the NCAA Division III NRPI?

Methods

Participants

The population for this study was undergraduate students enrolled at two institutions in the Midwest that have intercollegiate athletic programs competing at the NCAA Division III level. One institution was deemed an RPI, for purposes of the study, because of its membership in the Council for Christian Colleges and Universities (CCCU) and the mandatory chapel/worship services and religion courses students must attend. The other institution was deemed an NRPI, because it was not a member of CCCU and had not established religious requirements for its students. The RPI and NRPI codes used in the present investigation were developed by the primary researcher.

Of the study participants, 53.60% attended the RPI (n = 201), while 46.40% attended the NRPI (n = 174). Compiled demographics for the RPI and NRPI participants showed their average age to be 20.19 years (SD = 2.60). The youngest participant age was 18 years, the oldest 41 years; 53.60% of the participants were female (n = 201), and 46.40% were male (n = 174). Participants reported their ethnicity as follows: white/Caucasian (89.30%), African American (6.10%), Asian American (0.08%), Hispanic American (0.05%), Native American (0.03%), and other (2.90%). Freshman and sophomore students contributed 62.40% of the participant pool (see Table 1). The distribution of the participants in terms of their academic status or year at the institution was an accurate reflection of institution-wide distribution by academic status at each institution. Concerning current athletic participation, 53.30% of the participants did not currently participate in intercollegiate sports (n = 200), while 46.70% of the students did currently compete in intercollegiate sports (n = 175). The four sports in which the athletes in the sample most commonly participated were football, multiple sports, track and field, and basketball (see Table 2). Most participants indicated their religious affiliation was either Protestant (n = 111) or nondenominational (n = 110) (see Table 3).

Table 1

Frequencies and Percentages by Year at the Institution (i.e., Academic Status), Athletes and Nonathletes

Table 2

Frequencies and Percentages by Sport(s) Played, Athletes Only

Table 3

Frequencies and Percentages by Individual Religious Affiliation, Athletes and Nonathletes

Measures

The present study used the Santa Clara Strength of Religious Faith Questionnaire (SCSRFQ), developed by Plante and Boccaccini (1997). Additionally, a demographic assessment created by the primary researcher was used to collect information on age, gender, ethnicity, institution attended, year at institution (i.e., academic status), current participation in intercollegiate athletics, sport(s) played, and religious affiliation.

The SCSRFQ is a 10-item inventory assessing strength of religious faith regardless of religion or denomination, using statements such as “My religious faith is important to me” and “I look to my faith as a source of comfort.” Items are scored with a 4-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = agree, 4 = strongly agree), and higher scores indicate greater strength of religious faith. A cumulative score for the strength of religious faith is determined by summing the individual scores for each item. Cumulative scores may range from 10 (low strength of religious faith) to 40 (high strength of religious faith). Analyses have determined that the SCSRFQ has well-established psychometric properties. Its internal reliability is high (Cronbach’s alpha = .95) as is its split-half reliability (r = .92) (Plante & Boccaccini, 1997). In addition, an investigation by Plante, Yancey, Sherman, Guertin, and Pardini (1999) found the SCSRFQ to be significantly correlated with various measures of religiosity, including the Duke Religion Index (Koenig, Parkerson, & Meador, 1997), which assesses religious involvement; the Age Universal Religious Orientation Scale (Gorsuch & Venable, 1983), which examines both intrinsic and extrinsic religiousness; and the Intrinsic Religious Motivation Scale (Hoge, 1972), which measures religious motivation.

Procedures

Participants were recruited in selected psychology classes and from selected intercollegiate athletic teams at the two institutions. Both introductory psychology classes and more advanced psychology classes were included, creating a more balanced representation (by both age and academic major) of the participating institutions. The subsample of athletes was obtained by surveying selected male and female intercollegiate athletic teams at each institution; data from athletes whose teams had not been selected but who participated in the study through a selected psychology class were also included in the data analysis for athletes. All participants completed a packet comprising a demographic assessment and the SCSRFQ.

Results

Prior to addressing the research questions, descriptive statistics were calculated for the three independent variables of interest, which were gender, current athletic participation, and institution attended (see Table 4). Following these analyses, a 2 × 2 × 2 ANOVA (Gender × Current Athletic Participation × Institution Attended) was utilized to explore significant differences between various participants’ strength of religious faith (see Table 5). The 2 × 2 × 2 ANOVA addressed each research question, the first of which asked whether significant differences in strength of religious faith distinguished students attending an NCAA Division III RPI from those attending an NCAA Division III NRPI. The results showed a significant main effect for institution attended, F(1, 367) = 25.44, p < .01. Students attending the RPI and those attending the NRPI differed in terms of the strength of their religious faith. Specifically, participants attending the RPI (M = 32.99, SD = 6.65) reported stronger religious faith than participants attending the NRPI (M = 29.09, SD = 7.02).

The second research question inquired whether significant differences in strength of religious faith differentiated athletes attending the NCAA Division III RPI from nonathletes at the same institution. The results showed a significant interaction for Athlete × Institution Attended, F(1, 367) = 6.73, p < .05. Athletes at the RPI differed significantly from nonathletes there, in terms of the strength of their religious faith. Specifically, the RPI nonathletes (M = 34.43, SD = 5.25) reported stronger religious faith than the RPI athletes (M = 30.76, SD = 7.89).

The third research question asked whether the strength of religious faith of athletes attending the NCAA Division III NRPI differed significantly from the strength of religious faith of nonathletes attending that NRPI. As already noted, the data analysis showed a significant Athlete × Institution Attended interaction, F(1, 367) = 6.73, p < .05. However, the strength of religious faith reported in this study by athletes attending the NRPI did not differ significantly from that of the nonathletes at that NRPI. Specifically, the NRPI athletes (M = 29.09, SD = 6.63) reported the strength of their religious faith to be at a level similar to that of the NRPI nonathletes (M = 29.08, SD = 7.52).

The fourth research question concerned whether significant gender differences in strength of religious faith existed among students attending the NCAA Division III RPI and NRPI. The results indicated a significant main effect for gender, F(1, 367) = 12.99, p < .01. Female and male participants differed significantly in terms of the strength of their religious faith. Specifically, females (M = 32.77, SD = 6.41) reported stronger religious faith than males (M = 29.33, SD = 7.39). Despite this finding, however, no significant interactions were found for Gender × Athlete, F(1, 367) = 2.94, p > .05, or Gender × Institution Attended, F(1, 367) = 0.16, p > .05.

Table 4

Descriptive Statistics for Gender, Institution Attended, and Current Athletic Participation

Table 5

2 × 2 × 2 ANOVA for Gender, Institution Attended, and Current Athletic Participation

Note. InAt = institution attended.

*p < .05. **p < .01.

Discussion

In terms of the first research question, analyses showed that students attending the RPI reported stronger religious faith than students attending the NRPI. Religious institutions tend to appeal to students, whether athletes or nonathletes, who adhere to the religious beliefs and ideals the institutions promote. For example, a high school senior who values his or her Christian beliefs may apply to a college expected to provide a venue for strengthening those beliefs. In this study, then, the strength of the religious faith of students attending the RPI may be greater than that of students at the NRPI because Christian universities tend to attract and recruit highly religious individuals. In addition, according to the findings of Arnett and Jensen (as cited in Barry & Nelson, 2005), “emerging adulthood may be best characterized as a time during which young people: (a) question the beliefs in which they are raised, (b) place greater emphasis on individual spirituality and affiliation with a religious institution, and (c) pick and choose the aspects of religion that suit them best” (p. 246). At an NRPI, students may be exposed to secular viewpoints and perspectives during their academic experience. Professors at non–religiously practicing institutions often do not promote a certain religion, and they may deliberately keep their classrooms free of discussion on religion and spirituality. In contrast, students attending the RPI involved in this study were required by the institution to attend weekly religious services and to enroll in religion courses, which constitute part of the institution’s core curriculum. In addition, professors at Christian institutions tend to intertwine religion and academics by seeking the “integration of Christian faith with the living and learning experiences” (Schroeder & Scribner, 2006, p. 40). These reasons help explain the finding that students attending the RPI reported stronger religious faith than students attending the NRPI.

Concerning the second research question, analyses showed that the nonathletes attending the RPI reported stronger religious faith than the athletes at that RPI. Prior to the present research, most studies comparing the religiosity of athletes and nonathletes had been conducted at NCAA Division I public institutions and had suggested that athletes were more religious than nonathletes (Fischer, 1997; Storch et al., 2001; Storch et al., 2004). The results of the present study appear to contradict the published literature, although the contradiction may be substantially explained by society’s glorification of winning in athletics. That is, even at religiously practicing institutions, coaches feel pressure to win. Coaches at Christian institutions may tend to incorporate prayer in athletic practices and competitions, to make decisions based on Christian ideals, and to strive to be Christian role models (Schroeder & Scribner, 2006). In a context of athletics, they may work to teach such Christian values as self-discipline, hard work, perseverance, humility, and graciousness. But athletic success, even at Christian institutions, stems directly from the number of victories accumulated by a team. A victorious athletic program can be used as a “platform to market the college and encourage people in the community to have a connection with the institution, through sports” (Schroeder & Scribner, 2006, p. 49). Resulting pressure to win may lead even coaches at religious institutions to recruit athletes based on athletic ability rather than commitment to Christian beliefs. The adequacy of this explanation offers a topic for subsequent investigation focusing on recruiting practices of coaches at religiously practicing institutions versus those of coaches at non–religiously practicing institutions.

The present statistical analyses generated no significant results related to the third research question, in that athletes at the NRPI involved in this study reported the strength of their religious faith to be at a level similar to that reported by nonathletes at the NRPI. This result does not support previously published findings for athletes and nonathletes at NCAA Division I institutions (Fischer, 1997; Storch et al., 2001; Storch et al., 2004). It may, then, indicate a role for institutional environment. The NCAA Division III NRPI involved in the present study was located in the Midwest, a region in which residents typically adhere to conservative ideals and values. The cited investigations at NCAA Division I institutions were conducted in other regions of the United States, where moral standards may differ from those in the Midwest. Furthermore, it may be true that, in general, an NRPI in NCAA’s Division III may offer an institutional environment that more closely resembles the institutional environment of an NCAA Division I institution than that of an RPI in Division III.

As for the fourth research question, the present analyses showed that females reported stronger religious faith than males, a result supporting the majority of the previous research. Specifically, studies have found females to obtain higher intrinsic spirituality scores (Knox, Langehough, Walters, & Rowley, 1998), to pray more frequently, and to attend church more often than males (Francis, 1997b). In addition, a study of athletes and nonathletes by Storch et al. (2001) found that female athletes and female nonathletes (as well as male athletes) reported a higher degree of religiousness than male nonathletes did. Another study suggested that females may derive greater spiritual benefits than males from a Christian college experience (Ma, 2003). Perhaps such results can be explained by socialization factors. According to previous research, in general females have been taught to be relatively submissive, passive, obedient, nurturing, and gentle, as compared to males (Miller & Hoffmann, 1995; Thompson, 1991). Expressive personality characteristics like these are associated with higher levels of religiosity (Miller & Hoffmann, 1995) and have been categorized as a feminine gender orientation (Thompson, 1991). In other words, females (and males) who exhibit these personality characteristics tend to be more religious than females (and males) who do not exhibit them (Francis, 1997a). Perhaps, then, researchers should begin examining differences in religiosity not by gender but by specific gender role orientation (i.e., masculine gender orientation, feminine gender orientation) within each gender.

Conclusion

In this study, students attending the RPI reported stronger religious faith than students attending the NRPI. Institutional environment and relative overall appeal of RPIs and NRPIs may play a significant role in explaining this finding. In addition, nonathletes attending the RPI reported stronger religious faith than athletes attending the RPI. Societal pressure—even on the coaching staffs of religiously practicing institutions—to recruit athletes based on athletic ability rather than character may help explain this result.

Athletes attending the NRPI in this study did not differ significantly from nonathletes at the institution, in respect to strength of religious faith. This result does not support previous studies, which had revealed a significant difference in religiosity between athletes and nonathletes. This finding may be attributable to the institutional environment at the NRPI. Finally, in this study, females reported stronger religious faith than males, a result that may potentially be attributable to gender role orientation and socialization factors in our culture.

Findings from the present study provide direction for future research. First, levels of spirituality should be assessed, along with religious faith. Although many people equate religion and spirituality, the two are distinct concepts that can be addressed separately as well as collectively. Second, future studies should incorporate unstructured opportunities (i.e., interviews) allowing participants to express their religious beliefs. The SCSRFQ is a self-report scale not accommodating qualitative accounts of the role of religion as perceived by participants. Thus, both quantitative and qualitative methods should be utilized. Third, future investigators ought to study institutions at the NCAA Division II, National Association of Intercollegiate Athletics, and National Junior College Athletic Association levels. While the majority of existing research was conducted among NCAA Division I athletes, insight into the importance of religion at a variety of athletic levels is needed. Fourth, future studies should examine levels of religious faith by type of sports. They might ask, for instance, whether athletes in individual sports are more religious than athletes in team sports or whether athletes in contact sports display stronger religious faith than athletes in noncontact sports. Fifth, future investigations should evaluate levels of religious faith by individual religious affiliation, exploring, for example, whether Catholics report higher levels of religious faith than Protestants. Finally, further research must be conducted on the role of religions other than Christianity—Islam, Judaism, Hinduism, Buddhism—in sports and in the lives of athletes.

References

Balague, G. (1999). Understanding identity, value, and meaning when working with elite athletes. The Sport Psychologist, 13, 89–98.

Barry, C. M., & Nelson, L. J. (2005). The role of religion in the transition to adulthood for
young emerging adults. Journal of Youth and Adolescence, 34(3), 245–255.

Fischer, G. J. (1997). Abstention from sex and other pre-game rituals used by college
male varsity athletes. Journal of Sport Behavior, 20(2), 176–184.

Francis, L. J. (1997a). The psychology of gender differences in religion: A review of
empirical research. Religion, 27, 81–96.

Francis, L. J. (1997b). Personality, prayer, and church attendance among undergraduate
students. International Journal for the Psychology of Religion, 7(2), 127–132.

Gorsuch, R. I., & Venable, G. G. (1983). Development of an “age universal” I-E revised
scale. Journal for the Scientific Study of Religion, 22, 181–187.

Hoge, D. R. (1972). A validated intrinsic religious motivation scale. Journal for the
Scientific Study of Religion, 11, 369–376.

Knox, D., Langehough, S. O., Walters, C., & Rowley, M. (1998). Religiosity and
spirituality among college students. College Student Journal, 32(3), 430–432.

Koenig, H. G., Parkerson, G. R., & Meador, K. G. (1997). Religion index for psychiatric research. American Journal of Psychiatry, 154, 885–886.

Ma, S. Y. (2003). The Christian college experience and the development of spirituality
among students. Christian Higher Education, 2, 221–239.

Miller, A. S., & Hoffmann, J. P. (1995). Risk and religion: An explanation of gender
differences in religiosity. Journal for the Scientific Study of Religion, 34(1), 63–75.

Plante, T. G., & Boccaccini, M. T. (1997). The Santa Clara Strength of Religious Faith
Questionnaire. Pastoral Psychology, 45(5), 375–387.

Plante, T. G., Yancey, S., Sherman, A., Guertin, M., & Pardini, D. (1999). Further validation for the Santa Clara Strength of Religious Faith Questionnaire. Pastoral Psychology, 48(1), 11–21.

Schroeder, P. J., & Scribner, J. P. (2006). “To honor and glorify God”: The role of religion
in one intercollegiate athletics culture. Sport, Education, and Society, 11(1), 39–54.

Storch, E. A., & Farber, B. A. (2002). Psychotherapy with the religious athlete. Annals of
the American Psychotherapy Association, 3(6), 15–17.

Storch, E. A., Kolsky, A. R., Silvestri, S. M., & Storch, J. B. (2001). Religiosity of elite
college athletes. The Sport Psychologist, 13, 346–351.

Storch, E. A., Roberti, J. W., Bravata, E. A., & Storch, J. B. (2004). Strength of religious faith: A comparison of intercollegiate athletes and non-athletes. Pastoral Psychology, 52(6), 485 489.

Storch, E. A., & Storch, J. B. (2002a). Correlations for organizational, nonorganizational, and intrinsic religiosity with social support among intercollegiate athletes. Psychological Reports, 91, 333–334.

Storch, E. A., & Storch, J. B. (2002b). Intrinsic religiosity and aggression in a sample of intercollegiate athletes. Psychological Reports, 91, 1041–1042.

Storch, E. A., Storch, J. B., & Adams, B. G. (2002). Intrinsic religiosity and social anxiety of intercollegiate athletes. Psychological Reports, 91, 186.

Storch, E. A., Storch, J. B., Kovacs, A. H., Okun, A., & Welsh, E. (2003). Intrinsic religiosity and substance use in intercollegiate athletes. Journal of Sport and Exercise Psychology, 25, 248–252.

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religiousness. Journal for the Scientific Study of Religion, 30(4), 381–394.

Author Note

Nathan T. Bell, School of Physical Education, Sport, and Exercise
Science, Ball State University; Scott R. Johnson, School of Physical
Education, Sport, and Exercise Science, Ball State University; and
Jeffrey C. Petersen, School of Physical Education, Sport, and Exercise
Science, Ball State University.

Nathan T. Bell is now with the American Sport Education Program at
Human Kinetics publishing.

Correspondence concerning this article should be addressed to Nathan
T. Bell, Associate Acquisitions Editor, ASEP–Human Kinetics, 1607 N.
Market St.,Champaign, IL 61820.

Protective Headgear for Soccer Players: An Overview

U.S. Sports Academy2013-11-25T20:10:16-06:00January 7th, 2009|Contemporary Sports Issues, Sports Facilities, Sports Management|

Abstract

Protective headgear has been worn by thousands of American soccer players in youth leagues, high schools, colleges, and even professional leagues. While some current studies indicate that concussions occur among soccer players at a rate similar to that among football players, other studies contradict such results and the issue remains disputed. Moreover, studies disagree on whether heading the ball can cause concussions or long-term brain impairment. This article examines the causes and occurrence of head injuries in soccer and the possible role of protective headgear in preventing those injuries.

Protective Headgear for Soccer Players: An Overview

Since the International Federation of Association Football, or FIFA, soccer’s Zurich-based world governing body, began to allow the practice, thousands of American soccer players have worn protective headgear in youth league play, high school and college competition, and professional play. Such headgear gained international visibility during the 2003 Women’s World Cup and the 2004 Athens Olympics (Longman, 2004). In the United States itself, the United States Soccer Federation, National Collegiate Athletic Association, and National Federation of State High School Associations all now permit the use of protective headgear in soccer (Delaney, 2008). But these developments did not occur without controversy.

The U.S. Soccer Federation, which permits protective headgear but does not endorse it, fears that wide use of the gear would undermine the assertion that soccer is a safe alternative to football. When soccer officials voice doubts like this, similarities to the failed arguments once made against bicycle helmets, automobile seat belts, and even soccer shin guards may give them a familiar sound (Longman, 2004). According to Jeff Skeen, founder of one soccer headgear company, “Soccer officials are trying to thwart the evolution of headgear in soccer because they think it will scare soccer moms away from the sign-up table” (Longman, 2004, p. 1). “And they also think [headgear use] could be viewed as an admission that heading the ball itself is dangerous,” Skeen added (Longman, 2004, p. 1).

Anson Dorrance, who has coached the women’s team at the University of North Carolina to 19 national championships, has noted that compulsory use of shin guards did not change the nature of soccer, as many feared it would. It is Dorrance’s prediction that headgear will not change soccer’s nature either (Longman, 2004). Steve Ryan, commissioner of the Major Indoor Soccer League (which has approved the use of headgear), agreed. “I remember when baseball players didn’t wear batting helmets,” he said. “You see some resistance in soccer, which is natural. But I expect, over time, you will see [protective headgear use] broadly accepted” (Longman, 2004, p. 1)

Adding to the controversy is the fact that some headgear manufacturers pay professional players the equivalent of $50–$100 per game to endorse their products and furthermore have paid some state soccer associations $4,000–$10,000 for endorsements (Longman, 2004). This arrangement makes company claims of injury reduction suspect, according to the U.S. Soccer Federation (U.S. Soccer Federation, 2005). But several independent studies have shown that head injuries, particularly concussions, have become a significant issue in soccer. The Centers for Disease Control and Prevention has reported that doctors treat more than 200,000 children annually for soccer-related injuries including concussions (Francois, 2006). A recent independent study by Scott Delaney of Canada’s McGill University, published in the Clinical Journal of Sports Medicine, found that the rate of head injuries among soccer players was similar to the rate among football players (Francois, 2006).

While concussions are significant potential sports injuries that the U.S. Soccer Federation takes seriously (U.S. Soccer Federation Statement on Head Injuries, 2005), there is disagreement about whether heading the ball can cause concussions or long-term brain impairment. Studies have presented contradictory results, and the matter remains disputed as the soccer federation undertakes a long-term examination of head injuries (Longman, 2004). For example, a survey of college-age players (athletes 18 to 22 years old) conducted by Boden et al (cited in Kirkendall & Garrett, 2001). demonstrated that a team can anticipate having one player each season sustain a concussion. However, concussions reported for Boden and colleagues’ survey were largely due to game situations not involving purposeful heading of the ball. Kirkendall and Garrett have stated (2001) that 4%–20% of all injuries in soccer are “head injuries,” under which term they include concussions, nasal fractures, injuries of the eye, lacerations, and contusions.

Powell and Barber-Foss (cited in Kirkendall & Garrett, 2001) reported that mild traumatic brain injuries account for 3.9% of all injuries in boys’ scholastic soccer and 4.3% of all injuries in girls’ scholastic soccer. Powell and Barber-Foss’s ongoing survey of high-level youth soccer players (12 to 18 years old) in North Carolina to date shows that about 15% of all injuries were to the head (though these were not solely concussions) and involved player-to-player or player-to-ground contact (Kirkendall & Garrett, 2001). The researchers noted that, “The most frequent mechanism of injury was head-to-head contact, followed by head-to-ground and then head-to-other body part (e.g., foot, knee, and elbow). Importantly, purposeful heading was never a mechanism of injury, but injuries did occur when the player was accidentally struck by the ball (the head and neck were not stabilized).”

According to a study of concussions in soccer players by Dick, Putukian, Agel, Evans, and Marshall (2007), 67.7% of reported concussions were due to player contact, while 18.3% were associated with contacting the ball and 13.4% with contacting the playing surface. Less than 1% were associated with contacting the goal. The study found that concussions represented 6.0% of severe game injuries—those resulting in 10 or more days lost from practice and play (Dick, Putukian, Agel, Evans, & Marshall, 2007).

Delaney’s study of 328 Canadian university football players and 201 university soccer players reporting for training in fall 1999 found that 70.4 % of the football players and 62.7% of the soccer players had experienced symptoms of a concussion in the previous year. Delaney said that concussions are a proven problem, one that, in the lab, protective headgear alleviates. He questioned why players are not being offered the protection (Longman, 2004). “Girls, in general, are more prone to concussions in soccer, and they may be more aware of the possible benefits of wearing headgear,” Delaney, who practices at McGill University’s sports medicine clinic, has noted (Delaney, 2008).

Other studies have yielded contradictory results. For example, 100 male and female athletes were asked to complete neuropsychological tests before and after two training sessions, one session involving heading the ball and one avoiding heading. The tests included the alphabet backwards test, Trail Making Test (Parts A and B), Stroop Color and Word Test, and VIGIL/W. No test yielded significant differences between the control (no-heading) condition and experimental (heading) condition (Kirkendall & Garrett, 2001). Fuller et al. (cited in Dick et al., 2007) investigated 248 cases of head and neck injuries and found only a single incidence of cervical strain that could be attributed to purposeful heading of the ball, while Anderson et al. (cited in Dick et al., 2007) did not identify heading the ball as a mechanism for head injury. These results and others do not show purposeful heading to be a primary cause of concussions. Nor has contact with the ball been consistently identified as a mechanism of head injuries in general, although player-to-player contact has been (Dick et al., 2007).

It appears that definitive evidence for one side or the other in the soccer headgear controversy is not available. But there does seem to be solid evidence that more concussions occur as the level of play and competition advances (Kirkendall & Garrett, 2001). The use of protective headgear has grown most significantly, however, among youth players (age 12 and younger), even though players at this level are least likely to engage in play that would lead to concussions (U.S. Soccer Federation Statement on Head Injuries, 2005). The U.S. Soccer Federation has said marketing of protective headgear is primarily to children, even though the incidence of concussion in players under 12 is low.

A next step in research would be to determine clearly whether protective headgear prevents head injuries in soccer players. An innovative Canadian study examined the issue with 268 adolescents playing club soccer and generated the first results from the field instead of the lab. Just after the 2006 soccer season, the 12- to 17-year-old participants from Oakville Soccer Club, Canada’s biggest, were studied. Although only 52 of them had worn headgear during the season, the study showed a significant decrease in risk of concussion for those players. The unprotected majority of the players in the study was 2.65 times more likely to have been injured: 52.8% of participants who did not use headgear reported being injured, compared to 26.9% of participants who did. According to Delaney, “This study may help convince parents and players that soft protective soccer headgear can be an effective part of a comprehensive plan to reduce the number of head injuries and concussions in soccer” (To Avoid Soccer Head Injuries, 2007).

Manufacturers of soccer headgear have designed the gear to decrease the forces associated with heading and assume that doing so reduces the risk of head trauma. To date, however, only one study has been conducted to evaluate the gear’s efficacy. The most substantial finding of that study was that application of the headgear was linked to a decrease in the peak force of impact from a soccer ball traveling at 56.4 kph (35 mph). This force was approximately 112.5% lower (nearly 400 N), as compared to the unprotected force platform (Broglio, Ju, Broglio, & Sell, 2003). No differences were seen among the different brands of headgear; the decrease measured in the peak force suggests that a soccer player using any of the tested brands of headgear would be subjected to lower forces. Naunheim et al. (cited in Broglio et al., 2003) reported a similar decrease, when soccer headgear was used, in peak acceleration from a high-pressure soccer ball traveling at 34 mph (54.72 kph).

The founder of a company based in San Diego, California, said he had sold 100,000 pieces of headgear. The gear resembles an enlarged headband and covers the forehead, temples, and occipital bone in back of the head. Made of shock-absorbing foam between an outer layer of Lycra and an inner layer of sweat-absorbing polypropylene, the device weighs less than 2 oz. The company does not claim the gear prevents concussions, but rather that it can reduce by up to 50% the peak impact forces occurring in typical collisions when a player’s head strikes the ground or goal post or another’s head or elbow (Longman, 2004).

Delaney has argued that such headgear could also protect those players who are designated as headers, particularly at the elite level (at that level, such a player may head the ball up to 10 times per game). Delaney has been involved in drafting the Canadian Academy of Sports Medicine’s position paper on the prevention of head injuries in soccer (Robillard, 2004). But Ottawa-based orthopedic surgeon Rudy Gittens, who chairs the Canadian Soccer Association’s sports medicine committee and is furthermore a member of FIFA’s sports-medical committee, said to date no scientific evidence “conclusively” shows that purposefully heading the ball leads to concussions. Gittens, head of the medical commission of one of the six FIFA continental governing bodies, the Confederation of North, Central American and Caribbean Association Football or CONCACAF, said he is unaware of any scientific studies supporting use of soccer protective headgear to prevent concussions (Robillard, 2004).

A clinical professor of sports medicine at UCLA, Gary Green, has pointed out that, while there is “no evidence” headgear helps, there are theoretical grounds for questioning whether headgear use might actually hurt some players. For example, the headgear could produce a false sense of security in players, leading them to rely on a device instead of proper medical evaluation after suffering a possible concussion. Or headgear use could contribute to feelings of being invincible that promote recklessly aggressive play, a phenomenon known as the Superman effect. Green, who serves on the U.S. Soccer Federation’s medical advisory committee, said headgear use should be better studied before players “take a chance” by using it (Longman, 2004).

There is much to learn about headgear. A recent study sponsored by FIFA’s sports medicine committee concluded that headgear has a negligible effect in head-to-ball impacts but does provide “measurable benefit” in subconcussive head-to-head impacts. One still-unanswered question—and the most important—is the extent to which soccer protective headgear diminishes risk of concussion, if indeed it does. The U.S. Soccer Federation’s own sports medicine committee continues to monitor the available literature and encourage further research into, for example, whether decreasing impact force translates into decreasing concussions or whether using headgear gives players a false sense of security or causes them to play unusually aggressively (U.S. Soccer Federation Statement on Use of Padded Headgear, 2005). In the mean time, for those who do use protective headgear, it is important to remind players, coaches, and parents that headgear is not a substitute for proper medical evaluation and treatment of possible concussions. Consultation with a doctor is always a best first step when any sort of head injury occurs (U.S. Soccer Federation Statement on Use of Padded Headgear, 2005).

Around the world, players of all ages and skill levels play soccer. Available data on the efficacy of soccer protective headgear may suggest, in light of the relatively ordinary ball speed employed in the research, that use of headgear decreases the force of an impacting soccer ball and thus offers typical players protection. But before any recommendation or mandate is issued for all players to use soccer protective headgear on the field, further investigation of these products should directly address their clinical utility (Broglio et al., 2003).

References

Broglio, S. P., Ju, Y., Broglio, M. D., & Sell, T. C. (2003). The efficacy of soccer headgear. Journal of Athletic Training, 38(3), 220–224.

Delaney, J. S. (2008). Canadian study examined more than 260 adolescents playing club soccer. British Journal of Sports Medicine, 42, 110–115.

Dick, R., Putukian, M., Agel, J., Evans, T. A., & Marshall, S. W. (2007). Descriptive epidemiology of collegiate women’s soccer injuries: National Collegiate Athletic Association Injury Surveillance System, 1988–1989 through 2002–2003. Journal of Athletic Training, 42(2), 278–285.

Francois, M. (2006). DJ Orthopedics to offer soccer headgear in response to new ASTM [American Society for Testing and Materials] Sports Safety Equipment Standard. Retrieved February 23, 2008, from http://investors.djortho.com/releasedetail.cfm?ReleaseID=221887

Kirkendall, D. T., & Garrett, E., Jr. (2001). Heading in soccer: Integral skill or grounds for cognitive dysfunction? Journal of Athletic Training, 36(3), 328–333.

Longman, J. (2004, November 27). Soccer headgear: Does it do any good? The New York Times. Retrieved December 30, 2008, from http://www.nytimes.com/2004/11/27/sports/soccer/27soccer.html?pagewanted=1&_r=1

Robillard, S. (2004). Safety in soccer: Protective headgear gets kicked around by advocates and critics. Living Safety, 48(2). Retrieved February 25, 2008, from http://www.safety-council.org/info/sport/soccer-ls.html

To avoid soccer head injuries, soft protective headgear is only effective solution, study shows. (2007, July 14). Science Daily. Retrieved February 24, 2008, from http://www.sciencedaily.com/releases/2007/07/070712134638.htm

U.S. Soccer Federation statement on head injuries in soccer and padded headgear. (2005). Retrieved March 11, 2008, from the U.S. Soccer Federation website: http://www.ussoccer.com/articles/viewArticle.jsp_145974.html

Author Note

Michael Gray, Department of Kinesiology, Health, and Educational Foundations, Northern Kentucky University; Jennifer Bain, Department of Kinesiology, Health, and Educational Foundations, Northern Kentucky University; Lindsay Willis, Department of Kinesiology, Health, and Educational Foundations, Northern Kentucky University.

Michael Gray is now at the University of Trinidad & Tobago.

Correspondence concerning this article should be addressed to Michael Gray, Programme Professor, University of Trinidad & Tobago, Academy of Sports and Leisure. E-mail: Michael.gray@utt.edu.tt.

Biomechanics of Ice Hockey Slap Shots: Which Stick Is Best?

U.S. Sports Academy2015-10-24T01:32:44-05:00January 7th, 2009|Contemporary Sports Issues, Sports Exercise Science, Sports Management|

Abstract

Cutting-edge technologies and space-age synthetics are dramatically recreating ice hockey sticks today. But how does current scholarship view these high-priced innovations, particularly during performance of the slap shot, hockey’s most explosive maneuver? This literature review on both slap shot biomechanics and technological developments in ice hockey sticks suggests that player technique and strength exert much greater influence on slap shot puck velocity than does stick composition. Moreover, this study illuminates how stick flexibility, rather than composition, should be the key mechanical consideration in stick selection, since highly flexible sticks can enhance both stick deflection and strain energy storage, two important variables in the velocity of slap shots.

Biomechanics of Ice Hockey Slap Shots: Which Stick Is Best?

At its historical core, hockey is a game rooted in the natural environment. First played on the frozen lakes and rivers of upper North America, ice hockey—begun as the Native American game of shinny—featured carved wooden poles as sticks and hand-sewn fabrics as balls (Oxendine, 1988). As Europeans took up the game, they applied their technologies to this traditional equipment, gradually yet substantially changing the hockey stick by constructing it out of multiple pieces of wood, curving the stick blade, and wrapping the stick in fiberglass and laminate plastics to increase its durability and performance (Pearsall, Montgomery, Rothsching, & Turcotte, 1999).

Now, however, burgeoning technologies are virtually recreating hockey sticks with each passing day. Wood sticks, once the paragon of the sport, have largely been replaced by high-tech—and high-priced—graphite and composite models. Because of the seeming popularity of these “one-piece” composite sticks amongst professional players, hordes of youth and high-school-age hockey participants are now outfitting themselves with these technological marvels, much to the delight of proliferating hockey equipment companies. Certainly, the need for scholarly research on hockey technology has never been greater: Thousands of participants in the sport stand to benefit from a deeper understanding of the new developments in hockey stick technology.

This paper, then, provides a scholarly education on hockey sticks, both by analyzing the biomechanics of ice hockey shooting and by investigating the extant literature on hockey stick research. In particular, this essay explores the implications of stick technologies and biomechanics for the hockey slap shot, presenting the stick selections and key bodily mechanics that stand to enhance performance of this complex and critical hockey skill.

Slap Shot Mechanics

The Slap Shot’s Six Phases

A variety of scholars have explored the biomechanical aspects of ice hockey, with studies centering primarily around skating (Bracko, 2004; De Koning & Van Ingen Schenau, 2000) and shooting (Doré & Roy, 1978; Hache, 2002; Pearsall, Turcotte, & Murphy, 2000; Roy & Doré, 1976). Of these, several studies have analyzed the mechanics involved in various types of hockey shots, including the wrist, snap, slap, and backhand shots, performed both while stationary and when skating (Carr, 2004, p. 42; Doré & Roy, 1976, 1978; Hache, 2002, p. 84; Alexander, 1964, cited in Pearsall et al., 2000, p. 689; Cotton, 1966, cited in Pearsall et al., 2000, p. 689; Furlong, 1968, cited in Pearsall et al., 2000, p. 689). The slap shot in particular has garnered much scholarly attention, with researchers dividing the shot into six distinct phases: backswing, downswing, preloading, loading, release, and follow-through (Pearsall et al., 1999; Villasenor, Turcotte, & Pearsall, 2006). Three of the six—the preloading, loading, and release phases—concern the mechanical behaviors exhibited by the stick after its contact with the ice surface. This blade-ice contact time has been the intense focus of the majority of researchers investigating the hockey slap shot.

Blade Orientation

Past studies have uncovered several key differences between elite and novice performers of this critical blade-ice contact portion of the slap shot. For example, researchers have cited the orientation of the stick blade during its contact with the ice as an element differentiating elite from recreational performers. For instance, in their study of 15 college-age hockey players, Lomond, Turcotte, and Pearsall (2007) reported that experts tended to demonstrate a unique blade orientation whereby on contact with the ice, the stick blade was tilted forward (or cupped) more than recreational players’ sticks. In addition, Lomond et al. described a distinctive “rocker” component between the loading and release phases of the shot, during which the cupped stick blade almost instantaneously tilted perpendicular to the ice, infusing the puck with additional kinetic energy generated from the slight recoil of the stick blade itself. The authors noted this “rocker” component in the slap shot execution of all subjects in their study, both elite and recreational; blade “rocker” would seem, then, to be a component of slap shots in general. The Lomond et al. report does, however, emphasize the importance of the more tilted blade orientation demonstrated by expert players, a finding corroborated by greater puck velocities during their slap shots (Lomond et al., 2007).

Hand Position

In addition, researchers have cited player hand position as a distinguishing factor in expert slap shot performance. Wu and colleagues, studying male and female collegiate hockey players, noted that a lowered bottom hand, even past the midpoint of the shaft, generated additional stick bend and thus more strain energy, resulting in greater puck velocities (Wu et al., 2003); work of Canadian physicist and hockey enthusiast Alain Hache has seconded these mechanical benefits (Hache, 2002, p. 88). Thus, while it remains unquantified for now, some contribution to force generation in the hockey slap shot seems to result from a low bottom-hand grip on the stick, even past the shaft midpoint.

Impulse Duration

Beyond blade orientation and hand position, two additional factors likely play considerable roles in determining slap shot velocity. The first of these significant contributors is impulse duration, or the force applied to an object over time, the elongation of which increases the transfer of force to an object (Carr, 2004, p. 38). Carr cites the “whiplike” effect of a kinetic chain—a progressive increase in velocity from the most massive to the least massive body parts—as one key technique that allows for a lengthened application of impulse which imparts greater force to the struck object (2004, p. 39). Hockey players employ this “whiplike” technique in a slap shot by rotating the torso, the shoulders, the biceps, and the forearms in sequence, elongating the duration of stick blade contact with the puck. This extended impulse duration has been noted as a primary factor in heightened velocities of hockey slap, wrist, and backhand shots (Roy & Doré, 1976).

Further, Villasenor, Turcotte, and Pearsall (2006) found that among 20- to 30-year-old male slap shot performers, both expert and recreational, the longer the blade contacted the puck, the greater the final puck velocity. Moreover, all elite players in the study demonstrated longer blade-puck contact time than their nonelite counterparts (an average 38 ms for elite players vs. an average 27 ms for nonelite players), corresponding to substantially greater slap shot velocities for experts than for novices (averaging 120 km/h for elite players vs. 80.3 km/h for nonelite players) (Villasenor et al., 2006). Clearly, extending the blade’s contact time with the puck provides an advantage for players seeking greater slap shot velocity.

Stick Bending

A final (and perhaps most important) area contributing to the speed of slap shots is the bending of the stick’s shaft, which begins when the stick blade contacts the ice and lasts through the recoil of the stick just before a player’s follow-through. Hockey scientists David Pearsall, Rene Turcotte, and Stephen Murphy have gone so far as to attribute 40% to 50% of final slap shot velocity to the amount of deflection, or bending, in the stick shaft (Pearsall et al., 2000, p. 690), and photographs in Alain Hache’s Physics of Hockey attest to the considerable stick bend generated by contemporary National Hockey League players (Hache, 2002).

In exploring the stick-bending phenomenon, Villasenor et al. (2006) determined that several crucial relationships exist between stick bending and increased slap shot velocities. First, they noted that elite hockey performers initiated stick bending at the instant of, or shortly before, first contact with the puck, whereas recreational players commenced stick bending after contacting the puck and fully halfway through their stick blade’s contact time with the ice. Expert players also spent a greater percentage (28.8%) of the ice-stick blade contact window bending the stick, in comparison to their nonexpert counterparts (18.2%). Finally, elite performers employed a lower “kick point”—or area of maximum deflection—along the stick shaft than less skilled players did, which has spurred current hockey stick companies to engineer composite sticks designed to lower this spot of maximum bend (Hache, 2002, p. 95). Overall, Villasenor et al. describe a “strong relationship” between final puck velocity and maximum angle of stick deflection, underlining the importance to hockey athletes of initiating considerable stick bend during their slap shots (Villasenor et al., 2006). Alongside blade orientation, hand position, and impulse duration, stick bending contributes to the multiplicity of mechanical factors generated by the player during the performance of this most forceful of hockey skills.

Stick Composition

Beyond each hockey player’s individual slap shot technique, an additional facet of the shot remains variable: the stick. With the onslaught of new hockey technologies over the past decade, no shortage of stick options exists. Whereas hockey sticks were once constructed almost exclusively out of Rock elm, then in the 1990s from aluminum for the shaft and wood for the blade, 21st-century trends now incorporate space-age composite materials like graphite, Kevlar, and carbon in hockey stick design (Sports Materials, 2005; Hache, 2002; Marino, 1998; Pearsall et al., 1999; Wu et al., 2003). Technological advancement, however, has not come without cost, both in monetary terms (most composite sticks retail for at least $100, compared to $40 for a wood stick) and in reduced sensitivity for puckhandling (“feel”) attributed to composite sticks (Barpanda, 1998; Hache, 2002, p. 94; Hove, 2004; Marino, 1998). Nevertheless, today’s hockey players largely face three distinct stick options: an all-wood stick, a stick with a composite shaft and wood blade, or a fully composite stick. The remainder of this paper explores mechanical differences that can be discerned among these construction types during the performance of hockey slap shots.

Stick Construction Materials’ Role in Shot Velocity

Key to enhancing slap shot velocity is maximizing strain energy stored in and released from the hockey stick. Indeed, the current revolutions in hockey stick materials are efforts to capitalize on this mechanical principle. Several scholars have recently studied the effect of hockey stick composition on slap shot velocities, yielding intriguing and somewhat unexpected results. In a study of wood, graphite, and aluminum stick constructions and their role in slap shot velocity, for instance, Wu et al. found that puck velocity was influenced not by stick type but by player skill level and overall body strength. Although the authors reported stick bend to be a key factor in force generation during a slap shot, they attributed any significant differences in stick bend (and therefore puck speed) to the athlete’s bottom hand placement rather than to differences in stick composition (Wu et al., 2003).

Analyzing synthetic-shaft sticks in slap shots performed by varsity high school players, Rothsching found that, although relatively flexible sticks achieved the greatest puck velocities overall, “substantial variation between subjects occurred, emphasizing the greater importance of player technique and strength” (1997, cited in Pearsall et al., 2000, p. 691). Similarly, in an experiment with identical models of wood sticks with laminate shafts, Villasenor et al. (2006) found that stick deflection angles and subsequent puck velocities were significantly higher for elite versus recreational players, indicating that slap shot speeds generated by identically constructed sticks vary greatly from athlete to athlete. To date, then, and contrary to much conventional belief, scholars have not linked any particular stick material to increased slap shot velocity. Rather, what has surfaced from research reports is the clear primacy of the athlete’s variables—technique and strength—over any differences in stick composition.

Stick Stiffness and Flexibility

Beyond the individual athlete’s overriding influence on slap shot speeds, what has also emerged from recent scholarly investigations is the notion that stick flexibility, not stick composition, is of primary concern. In fact, several slap shot studies involving both wood and composite sticks demonstrate the influence of stick flexibility on shooting velocity. For instance, in a study of composite sticks exhibiting eight different stiffness levels (from “low” to “pro-stiff”), Worobets, Fairbairn, and Stefanyshyn (2006) found that in wrist shots, highly flexible sticks stored the most strain energy during the loading phase. Complicating matters, however, are the authors’ conclusions that the benefits of utilizing a flexible stick did not extend to slap shots, where “it is the athlete and not the equipment influencing shot speed” (p. 191). With this conclusion, Worobets et al. issue hockey players a strong reminder of the primacy of their own performance over any technological innovations in hockey sticks.

In a related investigation, Pearsall et al. (1999) explored slap shot velocities generated by four different “flexes” of carbon-fiber composite shafts with wood blades. The authors reported that, for each of the 6 college- and professional-level hockey player subjects, puck velocities were highest with the least stiff stick (“medium flex”); conversely, puck velocities were lowest when the subjects used the “extra stiff flex” stick. A “significant advantage” for puck velocity during slap shots was attributed to those hockey sticks with less shaft stiffness (p. 9). Qualifying such positive language, however, the authors also noted that variability in shooting velocity across subjects was greater than variability across shaft stiffness, concluding that “the subjects themselves are perhaps more important in determining slap shot velocity than the stick characteristics” (p. 10).

Finally, exploring slap shot velocities produced by 11-year-olds utilizing wood sticks of two different stiffness levels, Roy and Doré (1976) found that using the more flexible stick produced slightly higher slap shot speeds (56.8 km/h) than did using the stiffer model (54.4 km/h). The results prompted the authors to advise flexible sticks for use by younger players, since with flexible sticks, “lower forces are required to achieve the same puck velocity” recorded with stiffer shafts (Roy and Doré, 1976, cited in Pearsall et al., 2000, p. 690). Overall, then, the findings of Worobets et al., Pearsall et al. (1999), and Roy and Doré strongly suggest that the use of flexible hockey sticks contributes substantially to final puck velocity during the slap shot, especially when used by younger players. If any characteristic of a stick deserves to be considered for its effect on the slap shot, then, it appears to be stick flexibility, not stick composition.

Improved Slap Shot Performance

This review suggests that both player techniques and stick characteristics are important to slap shot success. Technical aspects of hockey shooting that may, if performed correctly, heighten ensuing puck velocities include intentionally tilting the stick blade forward to cup the puck and gripping the stick shaft low, even beyond the stick’s mid-point, to generate increased strain energy throughout the stick. In addition, expert shooters contacted the ice roughly 1 foot behind the puck to initiate stick bending at or before first contact with the puck—a crucial factor in maximizing shot velocity. Finally, accelerating the downswing phase first with the torso, then with the shoulders and arms, allows a hockey player to create a “whiplike” kinetic chain, lengthening the duration of impulse application to the stick, thereby increasing final puck velocity. Clearly, hockey coaches and players stand to adjust a variety of technical details to hone their technique and positively influence their level of success in the slap shot.

Recommendations for Hockey Stick Selection

Equally clear as the need for these technical adjustments is the extant literature’s recurring theme that player technique and strength are the most important variables influencing slap shot velocity. Across studies of players from youths to professionals and of sticks from wood to composite, stiff to flexible, the preeminence of player influence on achieved slap shot speeds rings consistently true and thus deserves to be the primary focus of performance-driven hockey coaches and players alike.

That said, this review has uncovered several findings relating to hockey sticks themselves. First, current research does not clearly demonstrate any advantage for one particular stick composition (wood, aluminum, or composite) over others. Instead, scholarly findings point to stick flexibility as the key mechanical consideration in stick selection. Several investigations attest to the mechanical benefits—most notably in stick deflection and strain energy storage—achieved with highly flexible sticks. It would seem sensible for coaches to advise hockey players to use the most flexible sticks possible (without incurring constant breakage) to maximize shooting velocity. This recommendation seems particularly apt for younger, less powerful players who may generate more stick bending with less applied force. Research suggests, then, that attention to hockey stick flexibility over any particular stick material may best aid players in heightening slap shot speeds.

While shooting remains only one of a multitude of hockey stick tasks—including the precision skills of stickhandling, passing, and receiving—players nevertheless stand to positively affect slap shot performance by supplementing the principal concerns of player technique and bodily strength with the use of flexible hockey sticks. In this regard, improvement in various aspects of ice hockey slap shots contributes toward every player and coach’s ultimate goal: enhancing athletic performance.

References

Barpanda, D. (1998). Dynamic performance characterization of hockey sticks and golf clubs using a combined vibrational energy level and modal analysis approach. Unpublished doctoral dissertation, University of Mississippi.

Bracko, M. R. (2004, September). Biomechanics powers ice hockey performance. BioMechanics 11(9), 1–7. Retrieved March 29, 2008, from http://www.biomech.com/full_article/?ArticleID=827&month=09&year=2004

Carr, G. (2004). Sport mechanics for coaches (2nd ed.). Champaign, IL: Human Kinetics.

De Koning, J. J., & Van Ingen Schenau, G. J. (2000). Performance-determining factors in speed skating. In V. M.
Zatsiorsky (Ed.), Biomechanics in sport: Volume IX of the Encyclopaedia of Sports Medicine (pp. 232–246). London: International Olympic Committee.

Doré, R., & Roy, B. (1976). Dynamometric analysis of different hockey shots. In P. V. Kumo (Ed.), Proceedings of the Fourth International Congress on Biomechanics, V-B (pp. 277–285). Baltimore: University Park Press.

Doré, R., & Roy, B. (1978). The biomechanics of hockey shots. In Proceedings: 1978 national coaches certification program level 5 seminar (pp. 59–71). Ottawa, Ontario, Canada: Canadian Amateur Hockey Association.

Hache, A. (2002). The physics of hockey. Baltimore: Johns Hopkins University Press.

Hove, P. (2004). Haptic perception of affordances of a sport implement: Choosing hockey sticks for power versus precision actions on the basis of “feel.” Unpublished doctoral dissertation, University of Cincinnati.

Lomond, K. V., Turcotte, R. A., & Pearsall, D. J. (2007). Three-dimensional analysis of blade contact in an ice hockey slap shot, in relation to player skill. Sports Engineering, 10(2), 87–100.

Madill, H. W. (1980). An EMG analysis of the validity of using weighted hockey sticks for specific overload training. Unpublished master’s thesis, McGill University, Montreal, Quebec, Canada.

Marino, G. W. (1998). Biomechanical investigations of performance characteristics of various types of ice hockey sticks. In H. J. Riehle & M. M. Vieten (Eds.), ISBS conference proceedings, 16th international symposium (pp. 184-187). Konstanz, Germany: International Society of Biomechanics in Sports. Retrieved March 30, 2008, from http://w4.ub.uni-konstanz.de/cpa/article/viewFile/1633/1535

Oxendine, J. B. (1988). American Indian sports heritage. Champaign, IL: Human Kinetics.

Pearsall, D. J., Montgomery, D., Rothsching, N., & Turcotte, R. (1999). The influence of stick stiffness on the performance of ice hockey slap shots. Sports Engineering, 2(1), 3–11.

Pearsall, D. J., Turcotte, R. A., & Murphy, S. D. (2000). Biomechanics of ice hockey. In W. E. Garrett, Jr., & D. T. Kirkendall (Eds.), Exercise and sport science (pp. 675–692). Philadelphia: Lippincott, Williams, and Wilkins.

Roy, B., & Doré, R. (1976). Kinematics of the slap shot in ice hockey as executed by players of different age classifications. In P. V. Komi (Ed.), International society on biomechanics (pp. 286–290). Baltimore: University Park Press.

Sports materials: materials for sports equipment have advanced dramatically over the past several years. Here is a sampling of some of the materials that enable players to move faster, hit the ball farther, pedal longer, and be better protected. (2005, October). Advanced Materials and Processes 163(10), 22-25. Retrieved March 29, 2008, from http://findarticles.com/p/articles/mi_hb5260/is_/ai_n20378099?tag=artBody;col1

Villasenor, A., Turcotte, R. A., & Pearsall, D. J. (2006). Recoil effect of the ice hockey stick during a slap shot. Journal of Applied Biomechanics, 22(5), 202–211.

Worobets, J. T., Fairbairn, J. C., & Stefanyshyn, D. J. (2006). The influence of shaft stiffness on potential energy and puck speed during wrist and slap shots in ice hockey. Sports Engineering, 9(4), 191–200.

Wu, T.-C., Pearsall, D., Hodges, A., Turcotte, R., Lefebvre, R., Montgomery, D., et al. (2003). The performance of the ice hockey slap and wrist shots: The effects of stick construction and player skill. Sports Engineering, 6(1), 31–40.

Author Note

David J. Laliberte, MSS, MA, Minnesota Hockey Coaches Association.

The author thanks Dr. Douglas Goar of the United States Sports Academy for his encouragement and insight regarding this essay.

Correspondence concerning this article should be addressed to David J. Laliberte, Minnesota Hockey Coaches Association, 1108 N. Seventh Ave., St. Cloud, MN 56303. E-mail: dlaliberte@usa.net.

Spectator Perceptions of Security Management at a NASCAR (National Association for Stock Car Auto Racing) Event

U.S. Sports Academy2016-04-01T09:53:37-05:00January 7th, 2009|Contemporary Sports Issues, Sports Management, Sports Studies and Sports Psychology|

Abstract

Major U.S. sporting events constitute potential terrorist targets (Lipton, 2005). Since 9/11, more money has been spent on security at events (Hall, 2006). This study investigated spectators’ perceptions of security at a NASCAR event, via a survey administered by the Center for Spectator Sports Security Management collaborating with Turnkey Sports and Entertainment. Of 1,642 spectators participating in the study, 52% said they had not been concerned with security while planning to attend the event. Further, only 47% knew where and how to seek emergency care while attending the event, and 47% deemed emergency evacuation procedures and signs to be clear and easy to follow. Overall, 64% indicated an opinion that professional sporting events are a likely target of terrorist attacks.

Spectator Perceptions of Security Management
at a NASCAR (National Association for Stock Car Auto Racing) Event

High-profile sporting events in the United States have been identified by the federal Department of Homeland Security as potential terrorist targets (Office of Homeland Security, 2002, p. 86). According to Goss, Jubenville, and MacBeth (n.d.), an act of sports-related terrorism is inevitable, a matter of when and where, not if—and of how the act will change the sporting world forever. Philpott (2007) explained that effective security management is imperative at large sporting events with many spectators, because there is potential for mass casualties as well as for catastrophic social and economic impacts.

Noted sports-related terrorism in the past includes incidents at the 1972 Summer Olympics in Munich, West Germany, and at the 1996 Atlanta Olympic Games, as well as several other recent events in the United States. In October 2005, an Oklahoma University student prematurely detonated a bomb strapped to his body outside an 85,000-seat stadium filled to capacity (Hagmann, 2005). In October 2006, the National Football League received a radiological bomb threat against several of its stadiums (Homeland Security: NFL Stadiums Threat Not Credible, 2006). The terrorist group Al-Qaeda prepared a “manual of Afghan jihad” in which football stadiums are proposed as sites of possible attacks, and in July 2002 the FBI warned that terrorist groups were downloading stadium images” (Estell, 2002, p. 8).

The present study intended to investigate the security-related perceptions of spectators at a high-profile NASCAR (National Association for Stock Car Auto Racing) event conducted in the southeastern region of the United States. Knowledge was sought of whether fans are concerned about security at sporting events they attend, whether and how strongly they believe their safety is adequately assured by security measures and personnel, and whether they believe sporting events are a likely target for future attacks.

Background

The University of Southern Mississippi Center for Spectator Sports Security Management was established in 2005 through a Department of Homeland Security grant. The center is the first of its kind in the United States. Through research, education, and outreach efforts, it works to build the capabilities of those responsible for managing security practices at sporting events. The center promotes, supports, and enhances academic research, technology development, and education and training in the domain of sports event security management. Its mission is to provide an interdisciplinary environment for building security awareness, improving sports-related security policies and procedures, and enhancing emergency response, evacuation, and recovery operations that follow acts of terrorism or natural disasters (Center for Spectator Sports Security Management, n.d.).

The Center for Spectator Sports Security Management was approached by the NASCAR organization to conduct research on NASCAR’s security management systems at one racing venue. Faculty, staff, and graduate students affiliated with the center collaborated with Turnkey Sports and Entertainment, LLC, to complete the proposed project. Turnkey Sports and Entertainment is a sports marketing firm that helps its clients develop insights into their audiences and marketplaces, gathering demographic information, collecting sales leads, and measuring sponsorships with custom market tools (Turnkey Sports and Entertainment, n.d.). Clients of Turnkey Sports and Entertainment include more than 80 leagues, properties, agencies, and brands (Turnkey Clients and Partners, n.d.).

Methods

Participants

The population for this study was limited to spectators at a NASCAR event in the southeastern region of the United States (N = 1,642). Potential participants were approached inside and outside the racing venue by members of a team of 11 graduate students and 5 faculty members from the Center for Spectator Sports Security Management. Team members collected data utilizing personal digital assistants (PDAs). No incentive was offered for participation, and participants were assured of their anonymity. Institutional review board approval was obtained prior to the study.

Instrument

The survey instrument was developed by the Center for Spectator Sports Security Management in partnership with Turnkey Sports and Entertainment. A panel of experts also assisted in developing the instrument and included the head of security for the national organization that controls the sport; event security managers; marketing staff; and administrative personnel. The survey instrument consisted of two parts. The first part of the questionnaire obtained demographic data measuring gender, age, education, and income. The second part comprised items about the management of security during the NASCAR event. This section of the instrument employed a 5-point Likert scale for participants’ responses (1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = strongly agree).

Data Analysis

Survey data from the research team’s PDAs were uploaded to the FanTrak Surveyor system established by Turnkey Sports and Entertainment and were analyzed using SPSS (version 11.0). Descriptive statistics and frequencies were used to investigate spectator security concerns. Means for each survey item question were reported. Likert scale responses measured how strongly participants agreed or disagreed with survey items; as part of the data analysis, the researchers categorized the respondents’ Likert scale responses as either disagree (1–2), neutral (3), or agree (4–5).

Results

A total of 1,642 spectators participated in this study. According to the results, a spectator attends, on average, 2.07 NASCAR events during the NASCAR season. Demographic data describing participants in the study (see Table 1) were consistent with the general demographic profile of spectators at similar events, as compiled by NASCAR’s central office. For example, men outnumbered women in the study sample (1,117 or 68% vs. 525 or 32%), and the majority of study participants had completed at least some community college. The income bracket into which most of the study participants fell was the $54,999–$74,000 bracket.

Table 1

Demographic Profile of Study Participants (N = 1,642), From Instrument Part 1

The second part of the survey instrument questioned participants about whether security was a concern for them as spectators at a large sporting event; whether they felt safe attending the event; whether they perceived emergency care available at the event to be managed effectively; and whether they perceived crowd control at the event to be managed effectively. Participants also indicated whether security measures implemented for the event were an impediment to their enjoyment of the event and whether they believed professional sporting events are a likely target of future terrorist attacks. Mean Likert scores for each item from the second part of the survey instrument were calculated, ranging from 1 (strongly disagree) to 5 (strongly agree), and participants’ responses were also categorized as disagree, neutral, or agree (see Table 2).

Table 2

Participants’ Perceptions Concerning NASCAR Event Security, From Instrument Part 2

The results suggest that security was not a concern for the surveyed spectators at this NASCAR venue. Overall, they agreed that security checkpoints were adequate (M = 4.22), as were item searches (M = 4.05) and security staff presence (M = 4.54). In addition, 84% of the study participants agreed they were fully aware of items banned or prohibited within the venue (M = 4.22). This indicates that the organization effectively communicates its entry policies. However, participants tended to indicate that they were unaware of where and how to seek emergency care at the venue and that they found its emergency evacuation procedures neither clear nor easy to follow (M = 2.91).

Most study participants—87%—disagreed fairly strongly with the item stating “Overall security measures in place take away from the enjoyment of this event”; the mean Likert scale score for this item was 1.42. The respondents also indicated a perception that crowd control was effectively managed (M = 3.8). In addition, the majority of the surveyed spectators (64%) felt that professional sporting events are a likely target for future terrorist activity.

Summary and Implications

Findings from the present study suggest that venue and event operators must ensure that emergency services and security staff are visible and accessible to patrons. Adequate training and placement of key personnel are critical to ensure effective responses to incidents. Over half of the participants (52%) indicated that security was not a concern for them as they made plans to attend the event; an even larger percentage, however, (72%) said they were vigilant concerning unusual packages and people at the event, a notion reinforced by the finding that 64% of participants consider professional sporting events to be likely future terrorist targets.

One important implication of these findings is that sports spectators seem to have an awareness concerning potential incidents. Another is that sports organizations need to implement effective strategies for communicating with event attendees about critical security information: entry and exit policies, items not allowed at the venue, parking regulations, and so on. Many sports organizations do provide such information for spectators, sometimes in fan guides and sometimes through websites designed for spectators’ review prior to attending events.

For many sports organizations, attaining balance between effective security management and a pleasant experience for the sports consumer is an important issue. Overwhelming spectators with security measures may deter their attendance, posing economic consequences for the sports organization; yet an effective security operation may prevent or alleviate incidents that would also bring financial losses.

In conclusion, various sporting organizations should consider conducting self-evaluations similar to the present study, in order to assess their security systems and identify any problems in the operations of those systems or with the consumers’ experience of events. Such knowledge can enhance the effectiveness of security systems and, ultimately, the safety of sports spectators.

References

Center for Spectator Sports Security Management. (n.d.). Retrieved April 8, 2008, from University of Southern Mississippi, Center for Spectator Sports Security Management website: http://www.sporteventsecurity.com/

Estell, L. (2002). A banner year for stadiums? Security concerns could put an end to stadium fly-overs. Incentive, 176(12), 8. Retrieved September 29, 2005, from the EBSCOhost database.

Goss, B. D., Jubenville, C. B., & MacBeth, J. L. (n.d.). Primary principles of post-9/11 stadium security in the United States: Transatlantic implications from British practices. Retrieved October 3, 2005, from http://www.iaam.org/CVMS/Post%20911%20Stadium%20Security.doc

Hagmann, D. J. (2005). Black hole in America’s heartland. In Articles: The Bombing at the University of Oklahoma (¶ 9). Retrieved July 20, 2006, from http://www.homelandsecurityus.com/site/modules/news/article.php?storyid=16

Hall, S. (2006). Effective security management of university sport venues. The Sport Journal, 9(4). Retrieved August 10, 2008, from http://thesportjournal.org/article/effective-security-management-university-sport-venues

Homeland security: NFL stadiums threat not credible. (2006). Retrieved July 28, 2007, from http://sports.espn.go.com/nfl/news/story?id=2631048

Lipton, E. (2005, March 16). U.S. report lists possibilities for terrorist attacks and likely toll. New York Times, p. A1.

Office of Homeland Security. (2002). National strategy for homeland security. Retrieved September 22, 2005, from http://www.whitehouse.gov/homeland/book/nat_strat_hls.pdf

Philpott, D. (2007). How your facility can avert a terrorist attack. Journal of Homeland Defense: Special Report. Retrieved , from http://www.homelanddefensejournal.com/hdl/TerroristAttack.htm

Turnkey Clients and Partners. (n.d.). Retrieved February 27, 2008, from http://www.turnkeyse.com/clients.html

Turnkey Sports and Entertainment. (n.d.). Retrieved February 27, 2008, from http://www.turnkeyse.com

Author Note

Stacey Hall, Center for Spectator Sports Security Management,
University of Southern Mississippi; Lou Marciani, Center for Spectator Sports Security Management, University of Southern Mississippi; Dennis Phillips, Center for Spectator Sports Security Management, University of Southern Mississippi; Trey Cunningham Center for Spectator Sports Security Management, University of Southern Mississippi.

Trey Cunningham is now at Northwestern State University of Louisiana.

This research effort was supported by Turnkey Sports and Entertainment, LLC.

Correspondence concerning this article should be addressed to Stacey Hall, Center for Spectator Sports Security Management, University of Southern Mississippi, 118 College Dr. #10013, Hattiesburg, MS 39406-0001. E-mail: Stacey.A.Hall@usm.edu.

Pay and Performance: An Examination of Texas High School Football Coaches

U.S. Sports Academy2016-10-12T14:56:39-05:00October 7th, 2008|Contemporary Sports Issues, Sports Coaching, Sports Facilities, Sports Management|

Abstract

Salaries paid to high school coaches and team managers have recently generated media and public debate over their justifiability. This research represents an earnings function estimation designed to identify salary determinants for high school football coaches. The theoretical model supporting the analysis builds on models presented in the sports economics literature. To conduct the empirical estimation, we used salary, human capital, performance, and institutional data for coaches of Class 4A and Class 5A 11-man high school football programs in Texas (N = 95). Our results indicate that the determination of overall coaching compensation is significantly affected by human capital investment, measured through experience; by job performance, captured in winning percentage; and by school characteristics, such as location and stadium size.

Pay and Performance: An Examination of Texas High School Football Coaches

Over the past decade, economic investigations of professional sports teams—particularly pay-for-performance studies—have become increasingly prevalent. This emerging research trend has evolved in part because of the broad applicability of economic principles to sporting contexts and also because of the increasing availability of performance and salary data for professional sports participants. Although it has not always been the case, reliable data for selected amateur sports, such as NCAA golf, are also starting to become available, allowing researchers to apply economic reasoning to these varied and important sports environments. (Examples are Callan and Thomas, 2004, 2006, which are investigations of the determinants of success in amateur golf that employed two different samples of NCAA golfers.)

From a theoretical perspective, economic research on sports salaries and performance builds on human capital theory, as first suggested by Becker (1964). Critical to this theory is the belief that education and experience play a significant role in the determination of a worker’s performance and earnings. Simply stated, investments in human capital, such as education, training, and work-related experience, are expected to positively influence compensation.

As for the empirical testing of these theoretical models, most salary investigations within the professional sports literature have focused on individual players as opposed to coaches or managers. It is also the case that most used an earnings function model similar to the one developed by Scully (1974), who studied salary determinants for Major League Baseball players. Consistent with Becker’s (1964) fundamental hypothesis, Scully’s model assumes that a professional baseball player’s development of human capital and skill are critical determinants of his earnings. Since Scully’s original work, numerous studies have adapted his model to other sports settings. For example, Jones and Walsh (1988) examined salary determination for players in the National Hockey League, and Hamilton (1997) did the same for players in the National Basketball Association.

Despite the accumulating research on players’ salaries in various sports, we know of only two papers that adapted Scully’s (1974) original model to an examination of the earnings of team managers or coaches. One is a study by Kahn (1993), and the other is an investigation conducted by Humphreys (2000). A brief overview of each follows.

Kahn (1993) used 1987 data for professional baseball teams to estimate an earnings function for team managers, which in turn was used to analyze managerial quality. Following human capital theory, Kahn’s model specifies earnings as the natural log of manager salary and includes the following as explanatory variables: years of managerial experience; lifetime winning percentage; and a binary variable to control for league (i.e., American or National). Kahn asserts that there are at least two reasons why experience is expected to have a positive effect on earnings. Specifically, more years of experience should reflect (a) greater skills, developed through on-the-job training, and (b) longevity, based on relatively high-quality management ability exhibited over time. Winning percentage captures team performance or success, which also should positively affect earnings, and the binary league variable controls for any league-specific differences in the demand for managerial quality. As expected, Kahn’s results showed that a manager’s experience level and career winning percentage have significant and positive effects on salary, although the league variable was not found to be statistically significant.

Humphreys (2000) used Division I NCAA basketball program data for the 1990–1991 academic year to test for possible gender-based differences in compensation among head basketball coaches. Similar to Kahn’s model, Humphreys’s earnings function defines the dependent variable as the log of annual base salary. Two groups of hypothesized salary determinants are specified: a set of coach characteristics and several control variables to represent the institution where each coach is employed. For the coach characteristics, Humphreys included a dummy variable for gender; experience, in years, to represent investment in human capital; and career winning percentage to measure job performance. In accordance with conventional human capital theory, both experience and winning percentage were assumed to have a positive effect on salary. The institution-specific control variables were intended to capture potential demand-side influences on a coach’s earnings. Included among these were total student enrollment, ticket revenues, and school location. The underlying hypothesis was that greater demand for basketball entertainment, which can be proxied by higher enrollment and larger revenues, should positively influence a coach’s salary.

Humphreys’s empirical estimation across several variations of his model found neither gender nor experience to be significant. However, the results did suggest that performance (measured through career winning percentage) positively affects earnings. Humphreys believed that a high correlation between performance and experience in his sample likely explained the lack of significance found for the experience parameter. Among the institutional control variables, Humphreys found that total enrollment, participation in Division IA games, and ticket revenues exhibited consistently positive effects on collegiate basketball coaches’ salaries.

Clearly, the studies by Kahn (1993) and Humphreys (2000) have helped to identify some of the factors responsible for manager or coach salaries at the professional and collegiate level, respectively. However, to our knowledge, no analogous earnings function estimations exist for noncollegiate amateur coaches, leaving many questions unanswered.

At least until recently, the primary reason for this lack of research on noncollegiate school sports was, apparently, limited or nonexistent data. However, reliable data on high school football in some regions of the United States have now become available. That such a turn of events is timely is evidenced in part by recent media attention to high school coaches’ salaries, particularly in comparison to teachers’ and other school administrators’ salaries. Some journalists report on the relatively high salaries earned by high school football coaches, particularly in the southern and western United States, where high school football is markedly more important to local communities than in other regions (Jacob, 2006; Associated Press, 2006). Others, such as Abramson (2006), counter with a different perspective about coaches’ earnings, referring to long hours worked, particularly in so-called football states like Texas, Florida, and Georgia.

A related issue raised by the media is the extraordinary level of monetary investments made in some high school football programs, an observation that some find particularly striking in the face of funding cuts for educational resources and programs. In a recent issue of a national newspaper, Wieberg (2004) reported on multimillion-dollar projects in Texas, Georgia, and Indiana to build state-of-the art high school football stadiums. This trend, he argued, arises from a competitive race involving high-end facilities and highly paid coaches that has trickled down from the college level. In some states, such competition arises from open enrollment policies, under which schools literally compete for students to preserve their state funding (which is linked to enrollment). Schools also compete for a strong fan base to generate revenues to help support the costs of football programs—including elevated salaries for coaches, some reportedly reaching six figures. Such activity, which is consistent with the demand-side effects on salary suggested by Humphreys (2000), identifies another motivation for exploring the issue empirically.

The present research addressed the critical issues by empirically examining salary determinants for a sample of high school football coaches in Texas. There were a number of reasons for using Texas as the context of the analysis. First, high school football is enormously popular in Texas, and schools there invest heavily in football programs. These observations translate to a favorable opportunity to study demand-side salary determinants for coaches along with the usual human capital factors. Second, and perhaps not unrelated to the first reason, the necessary sample data to conduct an empirical estimation of earnings have become available for the state. Third, because Texas high school football is nationally recognized, we anticipated that our findings concerning Texas coaches would both call attention to underlying issues and stimulate new research on salary determination for those who coach in other parts of the country and in other high school sports.

Method

Sample

Reflecting both data availability and our motivation to capture possible demand-side factors in our model, the sample for this study was 95 head coaches at Class 4A and Class 5A Texas high schools during the 2005–2006 football season. Oversight of high school football in Texas is provided by the University Interscholastic League (UIL). The UIL is a nonprofit organization with a purpose to “organize and properly supervise contests that assist in preparing students for citizenship” (About the UIL, n.d., ¶3); extracurricular activities outside athletics also fall within UIL’s purview. The UIL organizes Texas high school football contests based on schools’ geographic locations and enrollments. It divides football programs into 6-man and 11-man classifications. Most small schools (i.e., those with fewer than 100 enrolled students) participate in 6-man football, but the majority of Texas high school football programs are 11-man programs. The sample for this study was drawn from 11-man programs only.

Giving greater context for our analysis, table 1 presents the breakdown by classification of the 1,033 11-man high school football programs in Texas. The UIL identifies 32 geographic districts within Texas. The average number of football teams within each district ranges from 5.13 in Class 1A, to 7.53 and 7.69, respectively, in the larger 4A and 5A classes. The data indicate that significant enrollment differences exist across these various conferences. Classes 4A and 5A comprise the largest schools, those with enrollments as high as 2,084 and 5,852, respectively.

Table 1

2008–2009 Season Data for Texas High School 11-Man Football Teams, by Class

Note. Conference 2A spans 32 districts, but no school in District 24 has an 11-man football program. From “Alignments (updated for 2008–2010),” n.d., retrieved June 14, 2008, from http://www.uil.utexas.edu/athletics/football/

Measures

For each coach in our sample, we collected earnings data for the 2005–2006 academic year from a Dallas Morning News article, creating our empirical model’s dependent variable, SALARY (Jacob, 2006). According to a recent article in the popular press, a Class 4A or Class 5A head coach typically works 70–100 hr per week and is under contract for a 226-day work year (Texas Twist, 2006). Some coaches also teach, and some hold administrative positions such as athletic coordinator or athletic director. Our empirical model defined the variable ADMIN as a binary variable equal to 1 for a coach having administrative responsibilities or to 0 otherwise. We expected that coaches with administrative positions in addition to coaching responsibilities would earn higher salaries than those with coaching responsibilities only. Hence, we anticipated that the estimated parameter associated with ADMIN would be positive.

To capture each coach’s investment in human capital, we defined two distinct measures, GAMES and ROOKIE. Because the number of contests each team plays annually is fairly consistent, the GAMES variable was allowed to serve as a proxy for each coach’s cumulative head coaching experience in years (the data we would have preferred as our measure of human capital investment, had they been available). The GAMES variable actually measured the cumulative number of games for which an individual had acted as a head coach. Increases in this human capital variable were expected to have a positive influence on coaches’ salaries. The binary variable ROOKIE equaled 1 for a coach who was a rookie head coach (i.e., had no more than one year’s experience) and 0 for more experienced coaches. We anticipated that the parameter on this variable would be negative, reflecting the market’s ability to pay a rookie coach a lower salary than a veteran coach.

The sports economics literature suggests that in addition to experience level, how able a coach is, reflected in job performance, is an important determinant of compensation. Both Kahn (1993) and Humphreys (2000) used a coach’s career winning percentage to capture job performance. Following their approach, we defined a variable, WP, to measure the overall career winning percentage for each coach in our sample. If a coach’s winning percentage increased, we hypothesized, his salary will be higher, holding all other factors constant.

We further theorized that a coach’s salary would be influenced by demand-side characteristics (Humphreys, 2000), which would be linked to attributes of the high school employing the coach. One such characteristic was student enrollment, which we measured in the ENROLL variable, obtaining data from PigskinPrep.com, a website devoted to Texas high school football. (PigskinPrep.com’s Class 4A data was found at www.texasfootballratings.com/4ADistEnrollmentRealign.html and its Class 5A data at www.texasfootballratings.com/5ADistEnrollmentRealign.html). Schools with larger enrollments are expected to pay their coaches higher salaries, so we expected to find a positive relationship between ENROLL and SALARY.

Moreover, because Texas football has a following that extends beyond the student body, it was important to include some measure of community demand for the sport. Indeed, H. G. Bissinger (1990) suggests, in his best-selling book Friday Night Lights, that football in Texas is a community event. Therefore, we included the variable STADIUM in our empirical model to measure seating capacity at the facility where each coach’s school played its home games; the Texas High School Stadium Database (www.texasbob.com/stadium) provided the measures for each stadium. STADIUM was intended to capture a community’s market demand for high school football. Adapting Humphreys’s (2000) logic to our model, we expected that high school teams playing in larger stadiums would generate more revenue than those playing in smaller facilities, yielding more funds with which to compensate their head coaches, and hence we expected STADIUM to be positively related to SALARY. While we viewed stadium capacity as a reasonable proxy, we would have preferred including ticket revenues directly in our model, as Humphreys did, had such data been available for the individual Texas high schools. UIL does track football gate receipts for Texas high schools as a group. They totaled $1,102,798 for the 2005–2006 season, more than any other high school sport in Texas generated (West, Davis, and Company, 2008).

Lastly, following Humphreys (2000) we included a location-specific variable, DALLAS, in our model. The measure is a binary variable equal to 1 for a school located in the Dallas school district or to 0 otherwise. The variable controls any salary differences associated with location in the Dallas urban district. Earnings levels in urban districts may differ from those in other districts, due to differences in cost of living and/or population. However, since the relative magnitude of any such effect was not known a priori, the qualitative relationship between SALARY and DALLAS could not be predicted.

Procedures

To estimate the earnings function for each head coach in the sample, we used multiple regression analysis to examine the relationship between earnings and the defined human capital investment measures, job performance, and demand-side characteristics. As the literature suggests is typical, we transformed the dependent variable, SALARY, by natural logs. This transformation meant that the effect of each explanatory variable on earnings could be interpreted as a percentage change.

Results and Discussion

Fundamental statistical analysis was used to describe the variables in our data set. Table 2 presents the basic descriptive statistics for the sample of 95 Class 4A and Class 5A head football coaches. Note that, on average, a coach in this sample earned slightly more than $82,000 per year, and that 9 out of 10 coaches performed some administrative duties. The average coach had participated in approximately 107 games and achieved an overall career winning percentage of 53.41. Because a typical season consists of approximately 10 games, the mean value of 106.8 for GAMES suggests that the average coach in our sample had over 10 years of head coaching experience. Only 7% of the coaches were rookies.

Regarding institution-specific characteristics, the mean value for school enrollment was 2,310 students, and the average high school stadium seated 10,963 fans. The difference between the two measures indicates that demand for Conference 4A and 5A football extends well beyond the student body to the larger community. We also observed that 20% of coaches in the sample were employed at schools in the Dallas school district.

Table 2

Basic Descriptive Statistics for Class 4A and Class 5A Head Coaches (N = 95)

VariableMeanStandard DeviationMinimumMaximum

Table 3 presents the multiple regression estimates for our hypothesized earnings function model. (Several model specifications were estimated; overall results for the alternative model specifications did not differ significantly from the results presented in table 3.) On the basis of the adjusted R-squared statistic, our regression model explains over 58% of the variability in the natural log of earnings. The overall fit of our model compares favorably with those presented by other researchers. Each regression model presented by Kahn (1993) and Humphreys (2000) explained less than 50% of the variability in, respectively, professional coaches’ salaries and collegiate coaches’ salaries.

Table 3

Regression Model Parameter Estimates (Dependent Variable = Natural Log of Salary)

* p < 0.05, assuming a one-tailed test of hypothesis for ENROLL and two-tailed tests elsewhere. ** p < 0.01, assuming a one-tailed test of hypothesis for GAMES and two-tailed tests elsewhere. † p < 0.10, assuming a one-tailed test of hypothesis for WP and STADIUM.

Turning attention next to the model’s individual parameter estimates, we made a series of important observations, starting with the two measures of human capital investment. First, as anticipated, the algebraic sign on the ROOKIE parameter was negative, meaning that a coach with no more than 1 year of experience received less compensation than veteran coaches. On average, the difference was approximately 9%. Second, the estimated directional effect for a coach’s level of experience, measured through the GAMES variable, was consistent with expectations. Specifically, we found that GAMES had a statistically significant positive effect on a coach’s salary. Holding all other factors constant, each additional year of coaching experience increased salary by, on average, approximately 0.4 percentage points. (We assumed that 10 games represented about 1 year of play; the GAMES parameter estimate hence indicates that each additional game coached translated to a salary increase of about 0.04%, a year’s worth of games thus representing 10 times that salary increase, or 0.4%.) In contrast Kahn’s (1993) investigation of Major League Baseball managers showed that each additional year of experience in professional ball increased a manager’s salary by 2.35%. Humphreys’s (2000) investigation of NCAA basketball coaches did not find the analogous effect on salary to be statistically significant. He argued that a high correlation (0.60) between career winning percentage and years of experience most likely produced the insignificant result for the latter variable. The correlation coefficient between GAMES and WP in our model was markedly lower (0.46).

Holding constant a coach’s investment in human capital, we obtained further results indicating that a coach’s job performance, measured by WP, has a statistically significant positive effect on compensation (a one-tailed test was used). Qualitatively, this result is consistent with those presented by Kahn (1993) and Humphreys (2000). The specific estimated value suggested that an increase of 10 percentage points for WP increased a coach’s salary by approximately 0.9%. Clearly, this finding suggests that winning is important in high school football. However, the common sports adage “Winning is everything” seems an overstatement, at least in the context of how high school football coaches’ salaries are determined.

Quite predictably, our results also indicate that demand-side factors are relevant to the determination of coaches’ overall compensation. For two of the demand-side, institution-specific variables, STADIUM and ENROLL, each of the obtained parameters had the predicted positive sign. Using a one-tailed test, the parameter on STADIUM was statistically significant at the 10% level. This suggests that coaches at schools with larger stadiums, and hence greater demand for high school football, receive higher compensation than those at schools with smaller stadiums. The parameter on ENROLL was positive and statistically significant on the basis of a two-tailed test. As expected, then, larger schools tend to compensate coaches at higher rates than do schools with relatively fewer students. The specific estimated value implies that for every additional 100 students enrolled in a school, its football coach’s salary is about 0.29% higher. The underlying premise is that demand for football games is greater when the student body is larger.

The algebraic sign of the parameter on the urban location variable, DALLAS, was negative and statistically significant at the 1% level. This finding differs from Humphreys (2000), who in his study of NCAA basketball coaches did not find the urban location variable to be significant. It might be the case that the result in our model is specific to the Dallas, Texas, area and cannot be generalized to other urban areas. In any case, we can say that the subsample of Texas high school coaches employed by the Dallas school district earned about 17% less than their counterparts in other districts. This negative effect might reflect a larger population of available coaches in the area, which would mean greater competition for available positions and hence lower salaries. It might also be a function of the relatively low cost of living in Dallas, suggested by consumer price index levels for Dallas versus other areas (U.S. Department of Labor, 2008).

Finally, while the parameter on ADMIN had the expected sign, the finding was not statistically significant. This result may be due to the fact that over 90% of the head coaches in our sample held some type of administrative position in addition to their regular coaching duties. The resulting lack of variability in this measure may be responsible for its insignificance in our earnings function.

Conclusion

It is well documented in the sports economics literature that, holding ability constant, a player’s investment in human capital and his overall performance contribute significantly to the determination of overall compensation. Building on these findings, recent research in sports economics has applied earnings function analysis to an examination of salaries paid to professional and collegiate team managers and coaches. Although this segment of the sports literature is still in its infancy, thus far the empirical findings are generally consistent with those for players. That is, investments in human capital and job performance seem to be significant determinants of managers’ and coaches’ salaries, just as they are of players’ salaries.

In this research study, we extended the analysis of sports managers’ and coaches’ salaries to the noncollegiate amateur level, using a sample of Texas high school football head coaches employed during the 2005–2006 season. Following the approach used in investigations of professional sports, we modeled and estimated an earnings function, using conventional regression analysis. Our model specified a series of potential salary determinants, including human capital measures, a performance variable, and institution-specific demand-side factors.

Our statistical findings indicate that coaches’ salary determinants at the high school level are qualitatively consistent with those identified in the literature for professional and collegiate coaches. Specifically, a high school coach’s development of human capital was shown to be a statistically significant determinant of his salary. Moreover, a coach’s performance or ability to win games, as measured by career winning percentage, also affected his earnings. Lastly, consistent with findings presented by Humphreys (2000), we found that demand-side, institution-specific influences such as the size of the fan base can affect a coach’s compensation.

Taken together, the results of this research, we believe, make an important contribution to the literature examining compensation paid to sports participants, because they broaden its scope to include coaches at the high school level. The findings are timely, as well, given recent media attention to coaching salaries and the associated debate about rising investments in high school sports programs concurrent with funding cuts for education. We are hopeful that, as new data become available, other researchers will seek to validate our findings in other locations and for other high school sports throughout the country. This in turn could help stimulate important dialogue about the level of compensation for coaches relative to other educational professionals and whether that compensation appropriately rewards experience and performance.

References

About the UIL [University Interscholastic League]. (n.d.). Retrieved June 14, 2008, from http://www.uil.utexas.edu/about.html

Abramson, A. (2006, October 31). High school football coaches want pay to stay. Palm Beach Post. Retrieved September 24, 2008, from http://www.palmbeachpost.com/highschools/content/sports/epaper/2006/10/31/a1c_highschoolcoaches_1031.html

Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. New York: National Bureau of Economic Research.

Bissinger, H. G. (1990). Friday night lights: A town, a team, and a dream. Cambridge, MA: DaCapo Press.

Callan, S. J., & Thomas, J. M. (2004). Determinants of success among amateur golfers: An examination of NCAA Division I male golfers. The Sport Journal, 7(3). Retrieved September 24, 2008, from http://www.thesportjournal.org/article/determinants-success-among-amateur-golfers-examination-ncaa-division-i-male-golfers

Callan, S. J., & Thomas, J. M. (2006). Gender, skill, and performance in amateur golf: An examination of NCAA Division I golfers.” The Sport Journal, 9(3). Retrieved September 24, 2008, from http://www.thesportjournal.org/article/gender-skill-and-performance-amateur-golf-examination-ncaa-division-i-golfers

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