Purpose:The primary purpose of this study was to determine whether tests performed at the National Hockey League (NHL) Combine could distinguish draft status (ie, the round selected). A secondary aim was to provide performance ranges and percentiles for each of the dependent variables.Methods:A retrospective, cross-sectional study design was used with performance data and draft order from 2001, 2002, and 2003 Combine participants. Draft round was divided into 5 classifications (rounds 1, 2, 3, 4, and 5 through 9), and performances on 12 physical tests served as dependent variables. Three multiple analyses of covariance (MANCOVAs) were used to determine the significance of performance scores at the NHL Combine on draft selection. Age (years), body mass (kg), height (cm), and percentage body fat were treated as covariates.Results:Overall, MANCOVA results indicated no significant effect of performance on draft selection for 2001, 2002, or 2003. Subsequent univariate tests revealed that no single dependent variable was able to distinguish between draft rounds for any of the 3 years sampled.Conclusions:Using draft status as an indicator of ice hockey performance, it appears that off-ice tests cannot accurately predict ice hockey playing ability in an elite group of athletes. This might stem from homogeneity of the Combine participants, a lack of validity of the tests, or other factors (eg, on-ice hockey skills, psychological variables, etc) that play a role in draft selection.
Ransdell, LB, Murray, T, Gao, Y, Jones, P, and Bycura, D. A 4-year profile of game demands in elite women's Division I college basketball. J Strength Cond Res 34(3): 632-638, 2020-Workload for a Division I women's collegiate basketball team (0.817 win percentage) was examined by: (a) season, (b) player position, and (c) game outcome (wins vs. losses). Female athletes (n 5 6, mean 19.7 6 1.5 years, at beginning of study) wore Catapult S5 units during 91.8% of games over a 4-year period. Average PlayerLoad, PlayerLoad per minute (PL•min 21), high inertial movement analysis (high-IMA), and jumps were quantified using Catapult Openfield software (version 1.14.1+). Data were checked for normality and log-or square-root-transformed when they were non-normal. A series of linear mixed model analyses were conducted to detect differences in PlayerLoad, PL•min 21 , high-IMA, and jumps by season, position, and game outcome. PL•min 21 and jumps data were not normal, so they were transformed, analyses were run; because there were no differences in findings, data are reported in original units to allow for comparisons with other studies. Cohen's d and confidence intervals were provided as additional information about the strength of reported differences. The 3 most consistent findings were that across a 4-year period, jumps increased, PL•min 21 was higher in guards compared with posts, and high-IMA was higher in losses compared with wins. Other workload patterns were inconsistent, and inappropriate for making conclusive statements. Therefore, comparing jumps across multiple seasons, PL•min 21 by player position and high-IMA in losses are important; in addition, all data can be used to profile National Collegiate Athletic Association Division I women's basketball players and set game workload expectations.
Purpose:The primary purpose of this study was to determine whether positional profiling is possible for elite ice hockey players by examining anthropometric characteristics and physiological performance. In addition, performance ranges and percentiles were determined for each position (forwards, defensemen, and goalkeepers) on all dependent variables.Methods:A retrospective, cross-sectional study design was used with performance data from ice hockey players (mean age = 18.0 ± 0.6 years) attending the 2001 (n = 74), 2002 (n = 84), and 2003 (n = 92) Combines. Four anthropometric characteristics and 12 performance tests were the dependent variables. A 3 × 3 (position × year) 2-way ANOVA was used to determine whether any significant interactions were present. No significant interactions were observed, so the data were collapsed over the 3-year period and positional characteristics were analyzed using a 1-way ANOVA.Results:Defenders were heavier and/or taller compared with the other 2 positions (P ≤ .01), whereas goalkeepers showed greater body-fat percentage compared with that of forwards (P = .001). It was found that goalkeepers had significantly lower strength measures for the upper body (P ≤ .043) and lower anaerobic capacity (P ≤ .039) values compared with at least one other position, but they had greater flexibility (P ≤ .013). No positional differences were observed for the broad jump, vertical jump, aerobic power, or curl-ups.Conclusion:The current findings provide evidence supporting the use of anthropometric measurements, upper body strength, and anaerobic capacity to effectively distinguish among positions for elite-level ice hockey players.
This study 1) quantitates the effect of a 42.2-km footrace (marathon) on leg extensor strength (maximal peak torque, MPT) and work capacity (WC, measured during a leg extensor fatigue test), and 2) describes the effect of either a rest or exercise regimen for 1 wk after the marathon on the recovery of MPT and WC. Ten trained male runners performed personal records in a marathon and were then randomly assigned to either a rest or exercise-recovery group. The rest group did not train, whereas the exercise group ran 20-45 min/day at their selected intensity of exercise [50-60% maximal O2 consumption (Vo2max)] during the recovery week. MPT was measured at 1.1, 3.2, and 5.3 rad X s-1. The total work generated during a 50-contraction active extension-passive flexion fatigue test conducted at 3.2 rad X s-1 was defined as WC. Reports of perceived soreness of the quadriceps were obtained before each strength-testing session. These measurements were obtained before the marathon and 15-20 min and 1, 3, 5, and 7 days postmarathon. A significant reduction in MPT and WC resulted and continued 1 day postmarathon. MPT of both groups improved through day 5 postmarathon at 1.1 and 3.2 rad X s-1. MPT of the rest group improved through day 7 postmarathon but remained less than premarathon MPT. Recovery of MPT was impaired in the exercise group through days 5-7 postmarathon after 40-45 min exercise at 60% Vo2max. WC was recovered 3 days postmarathon in the rest group but was still impaired 7 days postmarathon in the exercise group.(ABSTRACT TRUNCATED AT 250 WORDS)
Despite impressive numbers of hockey participants, there is little research examining elite female ice hockey players. Therefore, the purpose of this study was to describe the physical characteristics of elite female ice hockey players who were trying out for the 2010 US Women's Ice Hockey team. Twenty-three women participated in the study and were evaluated for body mass (kilograms), height (centimeters), age (years) vertical jump (centimeters), standing long jump (centimeters), 1RM front squat (kilograms), front squat relative to body mass (percent), 1RM bench press (kilograms), bench press relative to body mass (percent), pull-ups, and body composition (percent body fat). The athletes in this sample were 24.7 years of age (SD = 3.1) and 169.7 cm tall (SD = 6.9); on average, they weighed 70.4 kg (SD = 7.1) and reported 15.8% body fat (SD = 1.9). Mean vertical jump height was 50.3 cm (SD = 5.7) and standing long jump was 214.8 cm (SD = 10.9). Mean 1RM for the upper body strength (bench press) was 65.3 kg (SD = 12.2) (95.1 ± 15.5% of body mass), and 1RM for lower body (front squat) was 88.6 kg (SD = 11.2) (127.7 ± 16.3% of body mass). This study is the first to report the physical characteristics of elite female ice hockey players from the USA. Data should assist strength and conditioning coaches in identifying talent, testing for strengths and weaknesses, comparing future teams to these indicators, and designing programs that will enhance the performance capabilities of female ice hockey athletes.
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