Sports Management – Page 44 – The Sport Journal

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

Submitted by: David J. Laliberte, MSS, MA – Minnesota Hockey Coaches Association

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 Wood sticks, once the paragon of the sport, have largely been replaced by high-tech—and high-priced—graphite and composite models.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.

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

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

Submitted by: Stacey Hall, Lou Marciani, Dennis Phillips, and Trey Cunningham – University of Southern Mississippi

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

	n	%
Gender
Male	1,117	68.0
Female	525	32.0
Age
18-24	142	8.6
25-34	358	22.0
35-44	537	32.8
45-54	396	24.2
55-64	152	9.3
65 and over	51	3.1
Education
Some high school	119	7.8
High school	383	25.2
Community college	514	34
Some college	265	17.5
College	210	13.8
Graduate school	26	1.7
Income
<$25K	119	7.7
$25K–$49K	383	25
$50K–$74K	514	33.4
$75K–$99K	265	17.2
$100K–$149K	210	13.5
$150K–$199K	26	1.7
$200K–$249K	14	0.9
$250K+	9	0.6

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

Survey Item	M	Disagree (%)	Neutral (%)	Agree (%)
While planning for the event, security is a concern for you.	2.51	52	13	35
The number of security checkpoints upon entering the facility is adequate to ensure your safety.	4.22	6	10	84
Searches of personal items are handled in an appropriate manner.	4.05	6	20	74
You are fully aware of banned or prohibited items.	4.22	10	6	84
Security staff and ushers are highly visible.	4.54	2	4	94
Security measures taken at the event are adequate to protect you.	4.46	2	5	93
If emergency care is needed, you know where and how to get it.	2.91	43	10	47
Emergency evacuation procedures and signs are clear and easy to follow.	4.14	47	13	40
You watch out for unusual occurrences, packages, and people.	2.69	19	9	72
Crowd control is effectively managed.	3.8	7	11	82
Overall security measures in place take away from the enjoyment of this event.	1.42	87	4	9
You feel safe at the event.	4.68	1	2	97
You feel that professional sporting events are a likely target for future terrorist.	3.5	24	12	64

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.

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

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

Submitted by: Scott J. Callan and Janet M. Thomas – Bentley College

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

Class	Number of districts with football programs in the class	Number of schools with football programs	Average number of schools per district	Minimum enrollment	Mid-point enrollment	Maximum enrollment
1A	32	164	5.13	69.00	134.00	199.00
2A	31	205	6.61	201.00	314.75	428.50
3A	32	177	5.53	222.00	599.00	976.00
4A	32	241	7.53	533.00	1,308.50	2,084.00
5A	32	246	7.69	1,515.00	3,684.00	5,852.00

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

SALARY	82,179.00	10,457.00	50,117.00	106,044.00
GAMES	106.80	89.67	10.00	401.00
ROOKIE	0.07	0.26	0.00	1.00
WP	53.41	17.30	5.00	84.00
ADMIN	0.91	0.29	0	1.00
STADIUM	10,963.00	3,795.00	3,500	21,193
ENROLL	2,310	849.12	1,076	5,652
DALLAS	0.20	0.40	0.00	1.00

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)

Determinant	Parameter estimate
Intercept	11.11†

Human capital variables
GAMES	3.96 E-04†
ROOKIE	-0.09**

Job Performance variable
WP	8.88 E-04†

Institution-specific characteristics
ENROLL	2.94 E-05**
STADIUM	3.55 E-03†
DALLAS	-0.17†

Other factors
ADMIN	0.04

F-statistic	19.81 (p value < 0.001)
R-squared	61.45
Adjusted R-squared	58.34

* 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

Hamilton, B. H. (1997). Racial discrimination and professional basketball salaries in the 1990s. Applied Economics, 29, 287–296.

Humphreys, B. R. (2000). Equal pay on the hardwood: The earnings gap between male and female NCAA Division I basketball coaches. Journal of Sports Economics, 1(3), 299–307.

Jacob, M. (2006, January 9). High school football coaches cashing in. Dallas Morning News. Retrieved September 24, 2008, from http://www.dallasnews.com/sharedcontent/ dws/spt/highschools/topstories/stories/010806dnspocoachsalaries.2a4475f.html

Jones, J. C. H., & Walsh, W. D. (1988). Salary determination in the National Hockey League: The effects of skills, franchise characteristics, and discrimination. Industrial and Labor Relations Review 41(4), 592–604.

Kahn, L. M. (1993). Managerial quality, team success, and individual player performance in Major League Baseball. Industrial and Labor Relations Review 46(3), 531–547.

Scully, G. W. (1974). Pay and performance in Major League Baseball. American Economic Review, 64, 915–930.

Texas twist: Football coaches earn more than teachers. (2006, August 27). ESPN.com. Retrieved September 24, 2008, from http://sports.espn.go.com/sports/news/story?id=2562629

UIL [University Interscholastic League] alignments (updated for 2008–2010). (n.d.). Retrieved June 14, 2008, from http://www.uil.utexas.edu/athletics/football/

U.S. Department of Labor, Bureau of Labor Statistics. (n.d.). Consumer Price Index, Retrieved July 15, 2008, from http://www.bls.gov/CPI/home.htm

West, Davis, and Company. (2008, January 25). University Interscholastic League: Annual financial report (statutory basis) for the year ended August 31, 2006. Retrieved June 14, 2008, from http://www.uil.utexas.edu/policy/pdf/05_06financial_report.pdf

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

Big League Deals: A Descriptive Study of Sponsorship Levels in Grassroots U.S. Baseball and Softball Programs

Submitted by: Scott Obsniuk and Scott J. Smith – Central Michigan University

Abstract

Sport sponsorship lets businesses break through cluttered marketplaces, deliver messages effectively, and segment by demographics. Sponsorship also helps grassroots sports organizations enhance services as they strengthen bottom lines. Despite a decade’s marked growth in grassroots sport sponsorship, little data exists detailing it. Statistics describing sponsorship in grassroots baseball and softball offer a benchmark for organizations seeking new ventures or developing established sponsorships. Furthermore, understanding why some organizations rely on sponsorships and others do not can help managers choose wisely for their own programs. A convenience sample was surveyed; results showed sponsorships were used by 86.36% of respondents from organizations operating for 20 years and by 76.70% of all respondents. Another finding was that players’ costs were not lowered by sponsorships.

(more…)

U.S. Sports Academy2016-10-20T11:27:17-05:00October 7th, 2008|Contemporary Sports Issues, Sports Facilities, Sports Management|Comments Off

Energy Drinks’ Effects on Student-Athletes and Implications for Athletic Departments

Submitted by: Russ Paddock – United States Sports Academy

Abstract

Worldwide, the market for so-called energy drinks has grown exponentially in the last decade. The primary targets of the industry’s marketing campaigns are young adults, and college athletes are frequent consumers of the products. Campaigns promote consumption of energy drinks to enhance performance and suggest their addition to cocktails. Studies have shown college athletes to engage regularly in binge drinking; they are also, clearly, individuals eager to maximize performance. In this article, the ingredients of energy drinks are discussed and the dangers of combining those ingredients with alcohol are explored. In addition, recent research about energy drinks and athletic performance is reviewed. Specific implications for college athletic departments are discussed.

Energy Drinks’ Effects on Student-Athletes and Implications for Athletic Departments

The worldwide market for so-called energy drink has grown exponentially in the last decade. The primary targets of the industry’s marketing campaigns are young adults. As a result, university and college athletes are frequent consumers of the products. The effects of these beverages can be quite significant. Therefore, their use by student-athletes requires analysis, results of which administrators and coaches need to be aware of so that they can share this knowledge with student-athletes in need of direction. They should also track the current trends among student-athletes concerning energy drinks.

Caffeine is the main “energy” ingredient in energy drinks. Its ability to enhance performance, under certain conditions, has been well documented. Yet consuming too much caffeine often has negative effects on overall wellness. Elite athletes continually strive for enhanced performance, trying a variety of strategies to reach that goal. Incorporating energy drinks within a training regime may be one such strategy. Many of the marketing campaigns explicitly state that an energy drink improves functioning, implying that it can boost athletic performance.

Binge drinking, too, has a negative effect on wellness, and research findings indicate that student-athletes—to a greater extent than other students—display a propensity to engage in it. On college campuses today, students commonly use energy drinks as an ingredient in alcoholic cocktails. When they consume alcohol and large amounts of caffeine in combination, many students find themselves drinking more and becoming more intoxicated, which can lead to serious health and other consequences.

History of the Energy Drink

Energy drinks entered the North American beverage market with exotic names, catchy slogans, and expensive marketing campaigns and now occupy a significant portion of the industry. They have become available everywhere, offered alongside soft drinks in vending machines, convenience stores, and grocery stores. Their manufacturers say that, in addition to providing a boost in energy, the drinks promote wellness through medicinal properties (they usually contain vitamins and/or ingredients like ginseng, guarana, and taurine). In 2005 such claims prompted Health Canada (the department of Canada’s federal government responsible for helping Canadians maintain and improve their health) to state, “Energy drinks are meant to supply mental and physical stimulation for a short period of time” (Safe Use of Energy Drinks, n.d., Background section, ¶ 2). Whatever their intended use and purported benefits, consumers today consume energy drinks for a variety of reasons: to boost energy, quench thirst, mix cocktails. Moreover, consumers are constantly pioneering new uses, such as flavoring smoothies with popular energy drinks.

The term energy drink suggests activity, and the uninformed consumer may assume that such a drink would support physical exercise. Locating energy drinks on store shelves adjacent to traditional sports drinks like Gatorade and Powerade reinforces such an assumption of a positive relationship between their use and exercise. Caffeine, the main stimulant ingredient in most energy drinks, has been shown by research to offer questionable potential (at best) as a performance enhancer, in light of the broad variation in individuals’ tolerance of it and also in light of an accompanying range of possible adverse effects (Caffeine—Performance, n.d.).

Drinks providing high doses of caffeine are not a new concept. Jolt cola, a precursor to today’s energy drink phenomenon, was first distributed in the 1980s (Retelny, 2007). Jolt was not marketed as a medicinal health product as, to an extent, energy drinks are. But like energy drinks, it was and is laden with caffeine. The Red Bull energy drink, introduced in the United States in 1997, was the forerunner of the modern energy drink and remains the most recognizable brand in the industry (Retelny, 2007). However, it has considerable competition in today’s marketplace: 500 new varieties of energy drink were introduced to the worldwide market in 2006 (Fornicola, 2007). According to Cohen (2008), the marketing research firm A. C. Nielsen indicated that worldwide sales of the drinks rose from $3.5 billion in 2006 to $4.7 billion in 2007. This speaks volumes for the drinks’ profitability and potential new markets, chiefly within the young teen to young adult demographic. Many companies continue to introduce new drinks, hoping to capture a share of a growing consumer base. Responding to the influx of new products with which they must compete, manufacturers push the boundaries, producing drinks with increasingly complex combinations of medicinal ingredients, with ever higher levels of caffeine, served in larger sizes (Fornicola, 2007).

Ingredients of the Energy Drink

Content labeling has always been inconsistent across North America, and the steady stream of new products developed for the energy drink market further complicates the picture. Energy drinks’ proliferation and popularity clearly caught regulatory agencies such as Health Canada off guard; by all accounts, agencies were ill equipped to respond to initial claims made by the drinks’ various manufacturers. In Canada, most energy drinks have been approved since 2004 as “natural health products.” Approval was a controversial decision, resulting in the establishment of Health Canada’s Natural Health Products Directorate (Raging Bull, 2005). Dr. Eric Marsden of the Ontario Association of Naturopathic Doctors considers Red Bull to be like “sin in a tin” (Raging Bull, 2005, p. 2, All In a Label section, ¶ 8), making a mockery of proper natural health products. On the other hand, energy drinks’ designation as natural health products means that, in Canada, they must be labeled with detailed information about amounts of medicinal and nonmedicinal ingredients and about recommended uses and doses, including cautionary statements.

In the United States, in contrast, the Food and Drug Administration (FDA), while it regulates caffeine content in soft drinks, does not regulate caffeine contained in energy drinks (Cohen, 2008, Anxiety Attacks section, ¶ 9). The FDA is authorized to move to regulate caffeine in energy drinks but tends not to do so unless a given product provides more caffeine than is found in the average cup of coffee (Cohen, 2008, Anxiety Attacks section, ¶ 10). In the United States, it is not required that manufacturers list the ingredients of energy drinks; therefore, it is difficult for consumers to appreciate how much caffeine they ingest with an energy drink. While the information often is available on the manufacturer’s website, it is unlikely typical consumers are concerned about product ingredients to the point of visiting a website. Most take it for granted that a product is safe simply because it is found on the shelves of food stores. And yet, studies have suggested that people with high blood pressure or heart disease should avoid energy drinks. The American Heart Association issued an alert in November 2007 concerning dangers energy drinks pose to those with known cardiovascular issues (Lofshult, 2008).

The variety of energy drinks available makes a complete review of their contents a daunting task. Sugar (whether in the form of glucose, sucrose, fructose, or other compound) is found in most, and sugar’s effects are well known. Sugar-free varieties of energy drinks are now being consumed in significant numbers, as well. In their study, Malinauskas, Aeby, Overton, Carpenter-Aeby, and Barber-Heidal (2007) found that 26% of college students who use energy drinks chose sugar-free versions; significantly more females than males opted for the low-calorie version. Sugar and sweeteners are household ingredients, but the various brands of energy drinks also contain many exotic components, as well. Four in particular seem central in the majority of the marketed products: caffeine, taurine, glucuronolactone, and vitamins.

Caffeine

The primary exotic ingredient of energy drinks is the stimulant drug caffeine. According to the website of the Sports Medicine Council of Manitoba (Caffeine—Performance, n.d.), there is scientific evidence that caffeine raises both heart rate and blood pressure, which can increase alertness and enhance performance of some tasks if small doses only are consumed. Caffeine’s effects are such that it is included in the World Anti-Doping Agency’s monitoring program, although the agency removed caffeine from its list of restricted substances in 2004 (Desbrow & Leveritt, 2007). The decision by the World Anti-Doping Agency implies that the performance-enhancing capacity of caffeine is limited; most research confirms that. Although caffeine in limited quantities improves mood and cognitive performance (Scholey & Kennedy, 2004), consuming more than limited quantities can generate many negative effects. As a result, any beneficial effect on athletic performance proposed for caffeine is not universally accepted.

The Sports Medicine Council of Manitoba (Caffeine—Performance, n.d., p. 2) indicated that a 250-ml can of Red Bull contains 80 mg of caffeine, while in caffeinated soft drinks the concentration ranges from 29 mg to 55 mg per 355-ml serving. Coffee’s caffeine content varies, but it typically contains 100 mg per 250-ml serving (Fornicola, 2007). Popular energy drinks including Monster, Full Throttle, and Rockstar contain about the same amount of caffeine as Red Bull. Some manufacturers, however, in attempting to create a unique product, have added significantly more caffeine to certain niche energy drinks. An article in the McLatchy–Tribune Business News (Energy Drinks’ Buzz, 2008) identified three drinks with extremely high caffeine levels: Boo-Koo Energy, with 360 mg of caffeine in 24 oz; Wired X344, with 344 mg in 16 oz; and Fixx, with 500 mg in 20 oz (Energy Drinks section).

When used in moderation, caffeine rarely produces visible effects, despite the fact that many negative effects have been identified in research. The acceptance and use of caffeine in contemporary society is commonplace, most caffeine being consumed without ill effect in morning coffee, to improve alertness and mood. Since coffee is generally served hot, it is generally drunk slowly. But energy drinks’ good taste and chilled state mean they can be consumed quickly (Fornicola, 2007), allowing a high dose of caffeine to enter the body fairly quickly. Even moderate amounts of caffeine can lead to severe negative effects in people who are caffeine sensitive, as well as in children, with their relatively low body weight. High doses of caffeine can negatively affect concentration, attention, and behavior and can produce irregular heartbeat, nausea, restlessness, headache, and dehydration (Griffith, 2008). Even when dehydration is not a problem, choosing an energy drink over drinks like juice, milk, and water can deprive children of nutrients (and can deplete a parent’s budget). Their students’ increasing access to energy drinks is for good reason causing concern among school officials.

Taurine

The most widely used medicinal ingredient in energy drinks after caffeine is also, perhaps, the least understood: the amino acid taurine. The human body on its own replenishes its supply of taurine (Lidz, 2003, With Taurine section, ¶ 3), which is involved in several metabolic processes and may also have antioxidant properties (Raging Bull, 2005, p. 4, Medicinal Ingredients chart, ¶ 1). A typical person’s intake of taurine is about 60 mg per day (Laquale, 2007), but a single serving of Red Bull (and of most other energy drinks) contains 1,000 mg of taurine. That amount is doubled in the 473-ml serving of Monster and nearly doubled (1,894 mg) in the same size container of Rock Star. Manufacturers imply that a special synergy exists among energy drink ingredients, and certainly taurine would be key to it. Laquale (2007) challenges the synergy notion, suggesting that taurine’s benefits were declared on the basis of testing on house cats in the 1970s.

The taurine in Red Bull has been promoted as the drink’s secret and controversial ingredient. Research on the effects of taurine is limited and inconclusive. But taurine is the reason Red Bull’s acceptance has been delayed in many countries; until recently it was actually illegal to sell Red Bull in Canada (Raging Bull, 2005). According to Lidz, Red Bull’s manufacturer “admits that taurine’s main function [in its product] is simply that of flavor enhancer” (2003, With Taurine section, ¶ 3). The German Institute for the Protection of Consumer Health suggests that claims of taurine’s value are “misleading” (Lidz, 2003, With Taurine section, ¶ 3). Alford et al.’s study (as cited in Laquale, 2007) indicated that Red Bull improved aerobic endurance and anaerobic performance, but whether that resulted from caffeine or taurine (or the combination of the two) was not determined. Griffiths’ research (also cited in Laquale, 2007) furthermore showed that consumers were being misled and that energy drinks’ effects depended on how much caffeine they contained. At this point, not enough research has been done to substantiate any positive effect of taurine, much less to investigate long-term effects of consuming taurine in the amounts present in energy drinks.

Glucuronolactone

Glucuronolactone is a carbohydrate that occurs naturally in the body and, like taurine, is suspected of helping “detoxify the body” (Raging Bull, 2005, p. 4, Medicinal Ingredients chart, ¶ 2). Red Bull includes glucuronolactone to increase energy and feelings of well-being (Laquale, 2007). Not surprisingly, the hundreds of energy drink brands joining the market following Red Bull’s introduction also contain glucuronolactone. Laquale notes that glucuronolactone has been made known by undocumented reports that it was given to American soldiers during the Vietnam War to increase energy but was eventually linked to deadly brain tumors and banned. Glucuronolactone research to date has focused on animals, making its effects in humans difficult to assess (Raging Bull, 2005, p. 4, Medicinal Ingredients chart, ¶ 2).

Vitamins

An assortment of B vitamins (B2, riboflavin; B3, niacin; B6; and B12) are the final ingredient common to the majority of energy drinks. While these vitamins’ importance to healthy living is undeniable, it may be more appropriate to ingest them in the form of a balanced diet than in the form of an energy drink supplement.

Although U.S. products may not be labeled as to their ingredients, they may include some type of warning label with recommendations for use of the product.

Effects

The long-term effects of energy drink consumption are unknown. Many studies have analyzed extended use of caffeine, generating mixed findings—although moderate use of caffeine is commonly accepted to pose little health risk. Fornicola (2007) found that on average, adults consumed 200 mg of caffeine per day, the amount in about two cups of coffee. While caffeine is undoubtedly the greatest contributor to the effect produced by energy drinks, the fact remains there is no research into possible problems associated with long-term ingestion of high concentrations of taurine and glucuronolactone.

Red Bull states that short-term positive effects of the drink—of its particular combination of ingredients—are proven by publicly available academic studies (FAQ, n.d., What proof is there that Red Bull energy drink does what it says it does? section). But the Red Bull website does not provide links or directions for accessing those studies. The majority of the extant research clearly disputes the claims, essentially attributing to caffeine the quantifiable short-term effect of increased energy (Malinauskas et al., 2007). Caffeine is also a diuretic, however, and the manufacturer of Red Bull recommends that users of its product drink ample amounts of water when they exercise (FAQ, n.d., Is Red Bull Energy Drink Suitable As Fluid Replacement? section).

There remains considerable concern regarding the negative effects of energy drinks. Emergency room visits arising from energy drink consumption are becoming commonplace. For example, Child Health Alert reported a 23-year-old was hospitalized with a dangerously high heart rate after consuming the energy drink GNC Speed Shot followed by a Mountain Dew soft drink, also containing caffeine (Caffeine: Watch Out, 2008). The report noted that the GNC Speed Shot website does warn against using the product together with others that contain caffeine. There are countries, France, Denmark, and Norway among them, that continue to ban the sale of Red Bull. Several highly publicized deaths linked to energy drinks have fueled ongoing suspicion. In one such tragedy, a healthy 18-year-old Irish basketball player experienced cardiac arrest after consuming four cans of Red Bull prior to a game (Laquale, 2007).

Consumption Patterns

Malinauskas et al. (2007) stated that energy drinks are intended for young adults but that little formal research is available accurately describing the multibillion-dollar energy drink industry’s actual clientele. Studying energy drink consumption by college students, Malinauskas et al. found that 51% used energy drinks, defined as consuming more than one energy drink monthly during the academic semester in which they were surveyed. In Canada, energy drinks labeled as natural health products must provide cautions complying with requirements of Health Canada’s Natural Health Products Directorate. For example, the beverages are not recommended for nursing or pregnant women, caffeine-sensitive persons, or children. Product labeling also establishes a maximum daily dose and advises against mixing the beverages with alcohol. An analysis of the labels on three popular energy drinks found that all delivered the same messages except when offering a maximum daily dose. Red Bull and Rock Star advise consumers not to exceed 500 ml of the product per day, while Monster recommends no more than 1,000 ml per day.

It is not clear how many adults consume energy drinks, but it is certain that, despite manufacturers’ warnings, many children are regular consumers. The Florida Poison Control Center started to track cases of caffeine overexposure after 39 people ages 2 to 20 years developed symptoms between January 2007 and March 2008 (Cohen, 2008, Anxiety Attacks section, ¶ 3). A school nurse in California sent three students to hospital by ambulance in the past year because they had irregular heart rates brought on by consumption of energy drinks (Dorsey, 2008). Energy drinks are not recommended for children or adolescents nor are they marketed directly to them. But surprisingly, there is currently no restriction on children’s purchase of energy drinks, even though caffeine’s effects are more pronounced in children than adults, due to body size and tolerance. It is furthermore clear that children and adolescents contribute significantly to the total market. Some schools have banned energy drinks from school property, and many jurisdictions are considering attempting to restrict energy drink sales to children.

Marketing

Energy drinks are marketed with colorful descriptions and provocative names that make them sound fun and exciting. Rockstar, Monster, Full Throttle, Throw Down, and Sobe No Fear are just a sampling of the inviting products that fill store shelves. Marketing slogans are developed to stimulate interest in a product and distinguish it from its competition: “Get spiked,” “Party like a rockstar,” and “Feel the freak” are slogans representing the marketing strategies of energy drink companies. The language and images of such advertising are not directed at mature adults. If anything, the marketing of energy drinks removes all ambiguity about whom these products are meant to appeal to: teens and young adults.

With 40% of the market share, Red Bull remains the leader in energy drink sales (Agriculture and Agri-Food Canada, 2008, Background section, ¶ 2). Not surprisingly, the “Red Bull gives you wiiings” slogan is widely recognized. Red Bull has developed its image over the past decade by sponsoring extreme sports and targeting college students (Lidz, 2003, Red Bull’s Effects Have Been Recognized by World-Class Athletes section, ¶ 3-4). More than other brand’s marketing, Red Bull’s marketing has created a connection between the product and sports and fitness, with the implication that greater performance in athletics is achieved by those who consume Red Bull. Currently, Red Bull containers feature the phrase “Vitalizes body and mind.” Lidz (2003) identified other slogans from Red Bull that have made a connection to sports: “increases concentration,” “improves reaction speed,” “stimulates metabolism,” and “Red Bull’s effects have been recognized by world-class athletes.” Miller (2008) suggested that other manufacturers have copied Red Bull’s strategy, since “energy drink advertising consistently emphasizes a physically active lifestyle featuring a range of extreme sports” (p. 481). Miller further suggested that, in their appeal to the young, energy drink marketing strategies are similar to those of the tobacco and alcohol industry (p. 488). Such an affinity between a “healthy natural product” and smoking and drinking is incongruous.

Consumption Among Student-Athletes

Malinauskas et al. (2007) found that 51% of college students consume energy drinks, so logic would dictate that student-athletes in colleges and universities consume the product at a similar or perhaps higher rate, given the marketing-constructed connection between energy drinks and sports. Promotional statements for Red Bull suggest consuming the product prior to a demanding athletic contest like a race or game (FAQ, n.d., When Should Red Bull Energy Drink Be Consumed? section). Also suggesting student-athletes’ susceptibility to energy drink marketing is Miller’s confirmation (2008) of the phenomenon called toxic jock identity. Miller defined toxic jock identity as the state of having “a sport-related identity predicated on risk taking and hyper masculinity” (p. 481). Toxic jock identity may increase risky behaviors, and consuming energy drinks may be a predictor of the phenomenon (Miller, 2008). The drive to improve athletic performance and exhibit one’s athletic identity could influence student-athletes to consume energy drinks at a relatively high level compared to that of the general student body.

Consumption to Boost Athletic Performance

Does ingestion of an energy drink really boost athletic performance? Caffeine is the only ingredient in energy drinks that has been studied in depth and that shows proven effects; short- and long-term effects of high doses of taurine and glucuronolactone require additional study. Athletes have long used caffeine prior to training sessions and competitions, but most nevertheless do not well understand how the drug works, for example that, as a diuretic, caffeine is capable of aggravating the dehydration athletes may experience during competition. The scientific literature itself provides mixed messages about caffeine’s performance-enhancing capability and its value prior to exercise. Fornicola (2007) stated that no real need exists to use energy drinks for performance advantage and that that quick caffeine fix is not a very intelligent strategy. In contrast, the website of the Sports Medicine Council of Manitoba reports that endurance athletes might gain some advantage by exploiting caffeine to derive energy from fat early in a competition, thereby leaving more muscle glycogen available to provide energy later on (Caffeine—Performance, n.d., p. 1). However, the website also advises athletes that “4% dehydration equals 20% of performance lost” (p. 1). Caffeine promotes dehydration, so the amount of it to be ingested for athletic advantage would have to be determined very precisely. Desbrow and Leveritt (2007) demonstrated that the majority of elite triathletes use caffeine to improve physical performance and concentration. However, these athletes’ knowledge of which products contain caffeine (and how much they contain) was limited (Desbrow & Leveritt, 2007). Umaña-Alvarado and Moncada-Jiménez (2005) studied the effects of energy drinks on male athletes’ aerobic activity, finding no performance improvement from energy drink consumption prior to testing. However, their results did demonstrate that those participants who consumed energy drinks reported lower levels of perceived exertion.

Consumption With Alcohol

Studies show student-athletes are more prone to binge drinking than other students. Grossman, Wechsler, Davenport, and Dowdall (1997) found college athletes engaged in binge drinking and used chewing tobacco at higher rates than nonathletes, although they were less likely to smoke cigarettes or marijuana. Other research indicates that team sports participants are especially likely to consume alcohol in a high-risk manner (Brenner & Swanik, 2007). Such findings, particularly when considered in light of something like toxic jock identity, suggest that the newly popular practice of mixing energy drinks into alcoholic cocktails may place student-athletes at an elevated risk. Consuming energy drinks along with alcohol lessens the subjective sense of intoxication (O’Brien, McCoy, Rhodes, Wagoner, & Wolfson, 2008). This means one can consume more alcohol than usual because one doesn’t feel intoxicated. In addition, the alcohol-induced fatigue that normally tends to limit further alcohol consumption may be masked by the caffeine in the energy drink (Dunlap, 2008).

Although energy drink companies may caution consumers against mixing the products with alcohol, young people, especially, do so. According to Miller (2008), the website Drinknation.com contained 201 Red Bull–based alcoholic beverage recipes. And despite the Red Bull label’s warning about mixing the product with alcohol, the manufacturer’s website tells visitors that Red Bull can be used for more than nonstop partying (Benefits, n.d., Red Bull—More Than Just a Myth section, ¶ 3).

Combining a depressant (alcohol) with a stimulant (energy drink containing caffeine) clearly could exacerbate the typical risks of alcohol consumption. The practice, combined with the tendency of student-athletes to binge on alcohol, should raise concern. O’Brien et al. (2008) indicated that “students who reported consuming alcohol mixed with energy drinks had significantly higher prevalence of alcohol–related consequences, including being taken advantage of sexually, taking advantage of another sexually, riding with an intoxicated driver, being physically hurt or injured, and requiring medical treatment” (p. 453). Further, the U.S. Surgeon General has reported that in the United States, close to 5,000 people under age 21 die each year of alcohol-related injuries (Dunlap, 2008).

Consumption in Conjunction With Studying

Long before the introduction of energy drinks, students used caffeine to stay up late at night studying. Today student-athletes who do not like the taste of coffee can choose an energy drink instead. In moderation, use of energy drinks to sustain a study session would appear to be harmless. Nevertheless, coaches and athletic department staff should make sure student-athletes are familiar with caffeine’s potential negative effects (when it is consumed to excess), in order to help them make informed and responsible choices, whatever the circumstance.

Consumption Representing Casual Use

Casual consumption of energy drinks accounts most significantly for the rapid rise in their popularity. Now available everywhere, energy drinks strike many consumers as a choice akin to a soft drink or coffee. The market seems poised for continued expansion, supported by aggressive marketing. The consumption of energy drinks is likely to become even more common and socially acceptable. Student-athletes are likely to be part of the trend, increasing their consumption, especially if they lack complete information about energy drinks, their ingredients, and their actual effects on athletic performance and health.

Summary and Conclusions

Given the proliferation of energy drinks and their growing popularity despite possible negative effects, coaches and athletic department administrators should take the initiative in educating student-athletes about the products. Energy drinks are aggressively marketed to college students with messages touting the performance and other benefits of consuming the beverages. Students are urged be energy drink consumers, and for the uninformed student-athlete, the trend’s influence may produce negative consequences.

While the purported benefits of the taurine and glucuronolactone in energy drinks are unproven, potential positive and negative effects of another common ingredient, caffeine, are well documented. The choice to use caffeine prior to training or competition should belong to the individual, based on adequate knowledge of pros and cons and on past experiences with caffeine. Student-athletes who choose to use caffeine should be encouraged to do so in moderation. They should also be provided information about levels of caffeine contained in various foods and beverages, in order to monitor their intake. Most energy drinks in fact have not contained more caffeine than a cup of coffee, but there is a noticeable trend toward selling the beverages in larger containers—meaning larger servings and more caffeine. If consuming an energy drink before a competition improves mood and concentration, it would be difficult to suggest that it poses significant danger. Assuming a consumer is not caffeine-sensitive, caffeine’s negative effects are unlikely to become evident unless intake becomes excessive. Although deaths associated with energy drink consumption and sport have been reported, they seem to be isolated cases involving multiple servings with high levels of caffeine.

While it is important to provide student-athletes with accurate information on energy drinks and caffeine as these affect athletic performance, of greater concern to athletic departments should be the growing trend of combining energy drinks and alcohol. Take the not uncommon pattern of student-athletes, dehydrated by the effort of playing a game, gathering after that game to consume alcohol. If the alcohol is mixed with caffeinated energy drinks, the student-athletes are subjected to a double diuretic effect, since alcohol, like caffeine, has diuretic properties. Thus they further compromise hydration.

Moreover, energy drinks’ capacity to mask intoxicated feelings allows increased alcohol consumption, which in turn increases the likelihood that a young drinker will make the kind of choices that have negative, if not disastrous, results. Evidence suggests that energy drink consumption with and without alcohol remains on the increase, so educating student-athletes on all aspects of energy drink consumption needs to become an athletic department priority, to ensure both wellness and safety.

References

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U.S. Sports Academy2015-02-12T11:36:51-06:00October 7th, 2008|Contemporary Sports Issues, Sports Exercise Science, Sports Management, Sports Studies and Sports Psychology|Comments Off