Journal of Strength and Conditioning Research, 2001, 15(1), 116 122 2001 National Strength & Conditioning Association Prediction of Ice Skating Performance With Off- Ice Testing in Women s Ice Hockey Players MICHAEL R. BRACKO 1 AND JAMES D. GEORGE 2 1 Institute for Hockey Research, Calgary, Alberta T2H 0P9, Canada; 2 Department of Physical Education, Brigham Young University, Provo, Utah 84602. ABSTRACT Off-ice predictors of skating performance have not been investigated for women s hockey players. The purpose of this study was to identify the off-ice variables associated with high-performance skating acceleration, speed, agility, and on-ice anaerobic capacity and power in women s ice hockey players. Sixty-one women s ice hockey players between the ages of 8 and 16 years (x age 12.18 2.05 years, x playing experience 4.68 2.69 years) participated in the study. Subjects were 1 4 months postseason. Some players were continuing to play once per week during the off-season. Skating tests (ST) included (a) 6.10-m acceleration, (b) 47.85- m speed, (c) agility cornering S turn, and (d) modified repeat skate test (MRS). Two trials of each ST were measured with a photoelectric timing system (except MRS, which was measured with 1 trial). The off-ice variables that were evaluated included age, years of playing experience, height, body mass, predicted fat percentage, sit-and-reach flexibility, vertical jump height, 40-yd dash time, and 1-minute timed sit-ups and push-ups. The results of this study show that 40-yd dash time is the strongest predictor of skating speed in women s hockey players ages 8 16 years old. From the regression procedure the best prediction equation was speed 4.913 (0.0107 kilograms) (0.4356 40-yd dash time). Key Words: hockey performance, performance skating, women s ice hockey Reference Data: Bracko, M.R., and J.D. George. Prediction of ice skating performance with off-ice testing in women s ice hockey players. J. Strength Cond. Res. 15(1): 116 122. 2001. Introduction Women s hockey players have been competing against international competition since 1990 when the first world championships were held in Canada. The 1998 Olympic Winter Games in Nagano, Japan, included for the first time women s hockey as a medal sport. Yet knowledge of the physical performance characteristics of women s ice hockey players is limited. Understanding the physical performance characteristics of athletes can help establish baseline performance data, develop scientifically based training protocols, improve performance, and identify weaknesses in conditioning. Although no studies have investigated the off-ice variables that predict skating performance in women players, several studies have done so using men s hockey players (4, 5, 8, 11, 18). Forty-yard dash time and vertical jump height consistently predict performance on acceleration and speed skating tests in men s professional, college, youth, and deaf hockey players (4, 5, 8, 11, 18). Acceleration and speed could be considered the power components of skating or hockey, and they are consistently predicted by off-ice power tests such as vertical jump and the 40-yd dash. Although jumping, running, and skating are biomechanically different, it is the power component of each movement that seems to be similar. A men s hockey player who has a relatively good motor program for skating, and who is powerful, will skate and accelerate faster than an equally skilled hockey player who does not have the ability to generate as much power. It is reasonable to suppose that the off-ice power variables that predict skating acceleration in men would predict skating performance in women. Although women s hockey has rules against body checking, the game is played on the same-size ice surface and with all other rules being the same as men s hockey. This means that women s hockey, like men s hockey, is a game of power where the players are on the ice for short periods of time with high work output. The purpose of this study was to identify the off-ice fitness variables that predict on-ice skating performance in women s ice hockey players. Methods Subjects Sixty-one women s ice hockey players between the ages of 8 and 16 years (x age 12.18 2.05 years, x playing experience 4.68 2.69 years) participated in the 116
Prediction of Women s Skating Performance 117 study. All subjects volunteered to participate in the study. Subjects were players in youth hockey leagues in and around Calgary, Canada, who were 1 4 months postseason. Some players were continuing to play once per week during the off-season. The procedures of the testing and the risks and benefits were explained to the subjects and their parents or guardians, and in addition, the subjects parents or guardians signed informed consents. The subjects were involved in ice hockey on a competitive-league level. At the time of the data collection, none of the subjects were involved in a formal off-ice training program for performance enhancement for hockey. Out of 61 subjects, 20 30 could be considered elite for their age group. Their fitness level coming into the study was based on a season of hockey and other recreational activities they were involved in during the spring and summer. Study Design The testing and data collection of all 61 players lasted 5 months. Subjects were tested once each for on-ice skating variables and off-ice variables. On-ice testing was conducted first, followed by off-ice testing approximately 1 week later. The on-ice testing (Figure 1) was done in the following order: (a) agility cornering S turn (14); (b) 6.10-m (20 ft) acceleration test (19, 20); (c) 44.80-m (147 ft) speed test; and (d) modified repeat skate test (MRS). Two trials of each skating test (except MRS, which was measured with 1 trial) were measured with a photoelectric timing system. The on-ice tests were used because they are most commonly referenced in the research literature by other investigators. Since women s hockey is played on the same-size ice surface with few differences from men s hockey, the same tests that have been used to evaluate men in predictive studies were used to evaluate women s hockey players. Additionally, the above-mentioned on-ice tests have previously been found to be reliable evaluations of skating performance. Off-ice testing consisted of the following evaluations: age, years of playing experience, height, body mass, predicted fat percentage, sit-and-reach flexibility, vertical jump height, 1-minute timed sit-ups and pushups, and the 40-yd dash. This battery of off-ice tests was used because most other investigations involving the prediction of skating performance in men s hockey players have used similar tests. On-Ice Testing Subjects were tested in alphabetical order for both trials of all tests. After a subject finished the first trial (of each test), she stayed at the opposite end of the ice and continued to skate to stay ready for the next trial or test. After all of the subjects finished the first trial, the entire group lined up for the second trial. While standing in line waiting for their next trial, the subjects Figure 1. Skating tests: (a) agility cornering S turn; (b) 6.10-m acceleration; (c) 44.80-m speed; (d) modified repeat sprints. stayed as active as possible. All subjects received at least 7 minutes of recovery time between each trial of each test. All subjects received at least 5 minutes of recovery time between skating tests while the timers were being repositioned. The first subject to perform the modified repeat sprint skating test received 10 minutes of recovery time between the second trial of the speed test and the skating sprints. While waiting to perform the repeat
118 Bracko and George sprint skating test, (which, in some cases, was 30 minutes), the subjects were lead through continuous, very low-intensity movements to promote a state of physical readiness. The height of the timers was adjusted for the height of the subject. The photoelectric beam was positioned at the subjects shoulder height while skating at full speed. The height of the timers ranged from 0.91 (3 ft) to 0.60 m (2 ft). Players were tested wearing full equipment and carried their stick while skating. Prior to testing, players were lead through a 15-minute on-ice warm-up consisting of low- and high-intensity skating, low-intensity muscle contractions while in a stationary position, and static stretching. Before each test, the investigator demonstrated the movement. The agility cornering S-turn test followed the protocol of Greer et al. (14). The length from goal line to finish line (Figure 1) was 18.90 m (62 ft) and the width was 22.55 m (74 ft). Subjects reversed direction for the second trial of the agility test. Greer et al. (14) reported a reliability rating for the agility cornering S-turn test of r 0.96 for 2 trials. The acceleration test and the speed test were measured in 1 continuous skating movement with the first 6.10 m (20 ft) being measured as a split time and the entire 44.80 m (147 ft) being measured as the speed performance. Subjects began stationary by positioning themselves facing forward behind a start line at the first timing device. When the clock was reset from the previous test, an investigator would tell the next subject to go. The final test was a modified version of the Reed repeat sprint skate test (21). Reed et al. (21) designed a skating fitness test that consisted of 6 91.44-m (300 ft) sprint skating repeats, each 30 seconds in length including work and rest, for a total of 3 minutes. Subjects skated 91.44 m as fast as possible (from one end to other and back to approximately the opposite blue line). Whatever was left of 30 seconds after crossing the finish line is used to rest before the next repeat begins on the 30-second mark. Reed et al (21) used midget, Jr. A, college, and professional men s hockey players to establish reliability and validity for the test. The results showed that the repeat times were between 12.5 and 21.7 seconds and fell in the anaerobic lactic range. Arnett (1) used the Reed repeat test to evaluate recovery in college hockey players and obtained investigator reliability of r 0.98 from test-retest results. The modified repeat skate test (Figure 1) was reduced from 6 repeats to 3. The same testing protocol was used in the modified test as it was in the original test. A modified test was used because of limited ice time, the young age of some subjects, and, most importantly, a 90-second on-ice anaerobic skating test more closely resembles reported time and motion analyses of game performance skating (10, 12, 13, 21). For the modified test the first 54.86 m (180 ft) was used to evaluate anaerobic power using the formula of Watson and Sargeant (23). The sum of the 3 repeats in seconds was calculated and used to establish anaerobic capacity using the formula of Watson and Sargeant (23). Off-Ice Testing The testing was completed in the following order: (a) skinfold measurements, (b) height and body mass, (c) vertical jump, (d) push-ups per minute, (e) sit-andreach flexibility, (f) sit-ups per minute, (g) 40-yd dash, and (h) playing experience questionnaire. A 15-minute warm-up, consisting of low-intensity muscle contractions, running, and static and dynamic stretching exercises, was performed after the skinfold, height, and body mass were measured. Three skinfold sites were measured triceps, supra ilium, and thigh and the estimate of fat percentage of Baumgartner and Jackson (3) was used to determine the predicted body fat percentage. Each skinfold was measured 3 times with the measurement occurring more than once, or the average of 3 different measurements being used as the skinfold measurement. Height was measured by having the subjects stand against a tape measure taped to a wall and the height measured with a ruler. Body mass was measured with a standard weight scale, calibrated after each subject was weighed. Vertical jump was measured using the protocol of Baumgartner and Jackson (3) with the best 2 of 3 jumps being registered. Push-ups were counted by an investigator while a subject started flat on an exercise mat and pushed herself up on her toes until her elbows were straight and went down until her elbows were at 90. Each time a subject went up and down, a push-up was counted. When a subject s technique deviated from the protocol, she was instructed to take a rest but was encouraged to do more when she was able. Sit-and-reach flexibility was measured with a meter stick placed between the subject s feet whereupon the subject reached as far down the stick as possible while keeping her heels on a line on the ground, her knees straight, and one hand over the other with fingers parallel. Sit-ups were performed with an investigator holding the feet of the subject, her knees at a 90 angle, arms crossed over her body, and with hands touching the opposite shoulder. A subject started in the down position and proceeded to sit up until her arms touched her thighs and lower back down until her lower back touched the exercise mat. When a subject s hips started to come off the ground, her arms were not touching her body, or her hands were not touching her shoulders, she was instructed to rest but was encouraged to attempt more sit-ups when she was able. Forty-yard dash was measured with photoelectric timing cells. Subjects were instructed to go on the command of the investigator. The average of 2 trials was calculated and used in the anal-
Prediction of Women s Skating Performance 119 Table 1. Means and SD for off-ice and on-ice variables. Variable Mean SD Off-ice variables Age Playing experience Height Mass Vertical jump 40-yd dash Push-ups Sit-ups Sit-and-reach Predicted fat percentage On-ice variables Acceleration Speed Agility AnPow AnCap 12.18 y 4.68 y 153.05 cm 44.41 kg 31.29 cm 7.19 s 29.16 33.17 38.83 cm 18.37 % 1.63 s 7.56 s 11.27 s 6.72 W kg 1 4.83 W kg 1 2.05 2.60 14.38 12.30 8.15 0.70 11.10 8.75 9.04 5.50 0.12 0.50 0.93 1.24 0.43 ysis. Subjects ran in the opposite direction on the second trial. The number of years a subject has been playing hockey was recorded based on verbal questioning, which, in most cases, was in the presence of the subject s mother or father. Number of years a subject participated in a game called ringette, which is very similar to ice hockey, was also recorded and added to the years of playing experience. Statistical Analysis of Data Sample means and SD were calculated for each off-ice and on-ice testing variable (Table 1). Stepwise regression analysis identified the significant predictor variables and correlations were computed (22). The level of significance was set at p 0.05. The predicted residual sum of squares (PRESS) cross-validation statistic estimated the degree of shrinkage that could be expected when a given prediction equation is used across a similar, but independent, sample (22). Results The degree of consistency of the on-ice tests as measured with intraclass correlation coefficients (22) were computed based on 2 test administrations on the same day to find reliability of the agility, acceleration, and speed skating tests. The reliability coefficients for the on-ice tests ranged from r 0.60 to r 0.98. The strongest off-ice fitness variable to predict skating performance (skating speed over 44.80 m) was 40- yd dash time with a reliability coefficient of r 0.72 (Table 2). From the regression procedure the best equation was speed 4.913 (0.0107 kilogram) (0.4356 40-yd dash time), r 2 0.58; r 0.76, SEE 0.327 seconds and SEE PRESS 0.344 seconds. Vertical jump and 40-yd dash time had reliability ratings of r 0.62 and r 0.66 when predicting on-ice anaerobic capacity as calculated with the Watson and Sargeant formula (23). The Pearson correlation coefficients between various on-ice and off-ice skating variables are presented in Table 2. Discussion The sport of women s ice hockey is not new. In fact, the earliest documented women s hockey competition was in the late 1800s. There have been 4 world championships of women s ice hockey, with Canada winning the gold medal and the U.S.A. winning the silver medal at every tournament. Women s hockey debuted as a medal sport in the 1998 Olympic Winter Games in Nagano, Japan, with the U.S.A. winning the gold medal. Because of the Olympics, there has been increased interest in women s hockey by players, the public, and media. From a sports science perspective, there is little available objective information about the physical performance characteristics of women s hockey players. The sports scientists of the hockey playing countries conduct on-ice and off-ice testing of their hockey players. They are reluctant, however, to make public the results of their testing for fear that opposing counties Table 2. Pearson correlation coefficients. Acceleration Speed Agility AnPow AnCap Age Play experience Height Mass Fat percentage Vertical jump 40-yd dash Push-ups Sit-ups Sit-and-reach 0.31 0.15 0.33 0.29 0.03 0.31 0.44 0.05 0.13 0.25 0.62 0.39 0.60 0.59 0.06 0.055 0.72 0.09 0.20 0.35 0.65 0.53 0.62 0.64 0.06 0.38 0.52 0.22 0.37 0.22 0.71 0.57 0.16 0.12 0.06 0.29 0.14 0.56 0.48 0.13 0.71 0.57 0.66 0.69 0.006 0.62 0.66 0.15 0.26 0.42
120 Bracko and George will use the performance data to improve their own hockey programs. One of the 2 scientific investigations found on women s ice hockey players was an abstract of a study by Baker and Fagan (2) who performed physiological testing on 24 provincial caliber hockey players with a mean age of 19.4 years. The players had a mean office V O2 max of 45.51 ml kg min 1, peak off-ice anaerobic power of 8.60 W kg 1, and an on-ice fatigue index from an 18.3-m test of 23.29%. Other relevant off-ice evaluations included the bench press (53.80 kg), trunk flexion flexibility (43.93 cm), and muscle mass (38.49 kg). The other study on women s ice hockey players was conducted by Bracko (7) who compared elite (Canadian and Finnish national team members) to nonelite women players and found that the major differences between the 2 groups were that the elite players were older, faster skaters and had higher levels of on-ice fitness. Bracko (7) hypothesizes that the reason the elite players were playing at a high level was that because of their age they may have been more physically mature, and they had been involved in specialized training longer than the nonelite players. The national team members had previously been involved in on-ice and off-ice training. Another possible reason for the elite players superior performance was familiarity with the testing protocols used by Bracko (7) as most of the players had performed the tests previously. The training protocols used by the elite players were not investigated. With specific reference to on-ice skating performance, Bracko (7) found that the elite players were significantly faster skaters over 15.17 m (49.80 ft) after a moving start. Whereas there were no differences between the elite and nonelite players on acceleration (6.10 m [20 ft]) and speed (44.80 m [147 ft]) from a stationary start. The most consistent differences in performance between the elite and nonelite hockey players were in onice fitness. Bracko (7) found that the elite players had significantly better scores on all aspects of the Reed repeat sprint skate (21): (a) sum of 6 repeats in seconds, (b) drop-off index (slowest repeat fastest repeat slowest repeat), and (c) drop-off time (slowest repeat fastest repeat). There was also a significant difference in on-ice anaerobic capacity as measured by the formula of Watson and Sargeant (23). The present study investigated the off-ice variables that predict skating performance and on-ice fitness. Forty-yard dash time was the strongest predictor of skating speed in women s ice hockey players. Fortyyard dash time also predicted anaerobic capacity as calculated with the formula of Watson and Sargeant (23). According to time motion analysis of game performance skating, surprisingly little time is spent skating full speed or at a high intensity. Bracko et al. (10) found that in professional hockey only 4.6% of time on the ice is spent skating forward at a high intensity and that the fast skating was rarely sustained. However, high intensity (full-speed skating) is an important skating characteristic for a hockey player because of the explosive nature of the game (15, 16). Although no other studies were found that investigated what off-ice fitness measures predicted skating performance in women s hockey players, the findings of the present study concur with similar investigations on men players. Blatherwick (4) reported that 40-yd dash time predicted skating speed with a reliability of r 0.81 for 14-year-old boy hockey players. Diakoumis and Bracko (11) also found 40-yd dash time to predict (r 0.84) skating speed in young deaf hockey players. These results suggest that a hockey player who can run fast will also be able to skate fast and be able to maintain a high work output during her time on the ice. This assumption must be viewed with some caution, however, because a player who has a poorly developed motor program for skating will be unable to skate fast even though she is a fast runner. A caveat must be placed on any conclusions regarding off-ice fitness predicting skating performance because of the complex nature of hockey skating, which can limit players from performing at high levels. Other studies that investigated the off-ice fitness variables predicting skating performance in men s hockey players found the 40-yd dash to predict acceleration. Blatherwick and Knolbach (5) and Blatherwick, Knolbach, and Greer (6) used 12-year-olds, high school, college, Olympic teams, and professional men s hockey players as subjects and found that 40-yd dash time was one of the most consistent predictors of skating acceleration (r 0.69 to r 0.91). In the present study, there was a reasonably strong correlation between vertical jump and on-ice anaerobic capacity. Vertical jump has been found to be a very consistent predictor of both acceleration and speed in men s hockey players. Blatherwick, Knolbach, and Greer (6) reported correlations of r 0.55 to 0.72 for vertical jump predicting acceleration. Blatherwick and Knolbach (5) found that vertical jump predicted both acceleration and speed with reliability ratings of r 0.71 and 0.72. Mascaro, Seaver, and Swanson (18) studied professional hockey players and found that the best predictor (r 0.85) for skating 54.9 m was vertical jump anaerobic power as calculated with the Lewis formula. Diakoumis and Bracko (11) found vertical jump to predict acceleration (r 0.62) and speed (r 0.65). Here again, the assumption is that a hockey player who can jump high (ability to generate powerful muscle contractions) will be able to accelerate quickly. Age, playing experience, body mass, and height were found to be reasonable predictors of speed, agility, and anaerobic capacity with the women in the pre-
Prediction of Women s Skating Performance 121 sent study. These 4 variables seem to be linked together in that as a player ages she will gain more playing experience, gain weight (with a corresponding increase in muscle mass), and grow taller. As important as speed and acceleration are to highperformance hockey, it may be the agility cornering S- turn test that is most representative for evaluating game performance skating. Bracko et al. (10) found that professional hockey forwards incorporated static and dynamic acceleration; high, medium, and low speed turns; and skating straight at varying speeds, which closely matches the skating characteristics needed to complete the agility skating test. Considering the importance of agility in game performance skating, there has been no investigation, including the present study, that has found an off-ice fitness variable that predicts skating agility. In this study, on-ice agility was predicted only by age and playing experience, although these were not strong predictors. The inability to find correlations between fitness and agility skating may simply be a function of specificity of movement because no off-ice agility tests were performed. This seems to be an indication that agility skating is not so much a function of fitness in women s hockey players, but probably related to age and playing experience (the number of years a player has had to develop a high-performance motor program). This appears to be an indication of the high degree of specialization of movement patterns required to be a successful hockey skater. Marino (17) alludes to this when he indicates that skating is such a complex motor skill that it takes many years to develop a motor program enabling players to perform at high levels. When they investigated the effect of off-ice training on skating performance in college hockey players, Blatherwick and Knolbach (5) found that a training protocol of sprint interval running, hill running, and weighted plyometrics significantly improved acceleration and on-ice endurance. Acceleration was measured dynamically with a flying start and on-ice endurance was measured with a 6 rink-length skating test. Understanding what training protocol was the most influential in the improved on-ice performance is difficult. Therefore, it could be suggested that a training program consisting of a variety of sprinting intervals, hill running, and plyometrics may have the most impact on skating performance. On the other hand, 2 out of 3 fitness components used in the study consistently predict skating speed and acceleration. Therefore, the results of this study may indicate that incorporating sprinting and jump training into an off-ice fitness program is important for college hockey players. Bracko and Fellingham (9) compared the effect of upper-body strength/endurance training and jump training on young hockey players (mean age 12.5 years). Both the upper-body training group and the jump training group significantly improved their 6.01- m acceleration time. However, the times for both groups on speed, agility, and full speed increased (got worse) despite the fact that their off-ice test scores on vertical jump, vertical jump mechanical power, and push-ups per minute significantly improved. This could be an indication that at a young age, improvements in skating speed and agility are specific to onice training and that off-ice training, although it may improve fitness, may not be a significant factor in the improvement of skating performance until the players have a well developed motor program. Understanding the off-ice fitness variables that predict skating performance can enhance a coach s ability to evaluate physical capabilities. Many amateur, volunteer coaches of youth hockey teams are realizing the importance of off-ice training for their players during the season and off-season. It is common for coaches to meet with their teams in a gymnasium once or twice a week during the season to participate in fitness activities. Many coaches will encourage their players to participate in an off-season training program to better prepare for the upcoming season. Considering this move toward improving off-ice fitness, it is important to have a better understanding of the off-ice fitness variables that are important for success in women s hockey. Understanding the components of off-ice fitness that predict on-ice skating performance and onice fitness can help a coach structure an off-ice fitness program. The use of off-ice training for hockey teams during the season has taken on much added importance in the last 5 10 years. The number of women playing hockey has drastically increased, which has increased the demand for practice ice. Practice ice is so limited (at least in Calgary, Canada) that many teams must share practice ice with another team. This means that they are practicing on only one-half of the ice surface, which severely limits the amount of gamelike skating that can be accomplished. Therefore, coaches are inclined to use their practice time to develop team strategies rather than spend time practicing skating or improving on-ice fitness. Future research could investigate what effect half-ice practice has on fitness. On-ice testing of players may not be warranted since ice time is so limited. However, off-ice testing can reveal important information that can help a coach evaluate players using objective measures. When a coach has a good understanding of the off-ice fitness variables that predict skating performance, he or she can conduct off-ice testing to evaluate and monitor the hockey-fitness of the players. Practical Applications Once predictor variables are established, objective training studies can be designed to evaluate the effect
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