Relationships to Skating Performance in Competitive Hockey Players

Farlinger, Chris Mj; Kruisselbrink, L. Darren; Fowles, Jonathon R.

doi:10.1519/r-19155.1

Cited by 58 publications

(76 citation statements)

References 5 publications

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“…This indicates that both field-based and laboratory-based assessments can be considered valid tools for coaches when they want to gain knowledge about a female player’s skating abilities. These findings are in agreement with previous studies on male hockey players,14,15,27 which have shown correlations between skating performance and field-based assessments. Farlinger et al14 reported that on-ice cornering and sprint ability were strongly correlated to three hop jump ( r =−0.53, r =−0.78) and broad jump ( r =−0.59, r =−0.74).…”

Section: Discussionsupporting

confidence: 93%

“…Some researchers have indicated that field-based testing is a valid predictor for successful performance in male ice hockey,10,13 while others considered field-based testing as proxies for specific components of hockey performance 14,15. This is a relatively unexplored area in female ice hockey; however, one recent study16 has indicated that field-based assessments can be used to predict speed and recovery ability in lower level (division III) female ice hockey.…”

Section: Introductionmentioning

confidence: 99%

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Laboratory- and field-based testing as predictors of skating performance in competitive-level female ice hockey

Henriksson¹,

Vescovi²,

Fjellman‐Wiklund³

et al. 2016

OAJSM

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ObjectivesThe purpose of this study was to examine whether field-based and/or laboratory-based assessments are valid tools for predicting key performance characteristics of skating in competitive-level female hockey players.DesignCross-sectional study.MethodsTwenty-three female ice hockey players aged 15–25 years (body mass: 66.1±6.3 kg; height: 169.5±5.5 cm), with 10.6±3.2 years playing experience volunteered to participate in the study. The field-based assessments included 20 m sprint, squat jump, countermovement jump, 30-second repeated jump test, standing long jump, single-leg standing long jump, 20 m shuttle run test, isometric leg pull, one-repetition maximum bench press, and one-repetition maximum squats. The laboratory-based assessments included body composition (dual energy X-ray absorptiometry), maximal aerobic power, and isokinetic strength (Biodex). The on-ice tests included agility cornering s-turn, cone agility skate, transition agility skate, and modified repeat skate sprint. Data were analyzed using stepwise multivariate linear regression analysis. Linear regression analysis was used to establish the relationship between key performance characteristics of skating and the predictor variables.ResultsRegression models (adj R2) for the on-ice variables ranged from 0.244 to 0.663 for the field-based assessments and from 0.136 to 0.420 for the laboratory-based assessments. Single-leg tests were the strongest predictors for key performance characteristics of skating. Single leg standing long jump alone explained 57.1%, 38.1%, and 29.1% of the variance in skating time during transition agility skate, agility cornering s-turn, and modified repeat skate sprint, respectively. Isokinetic peak torque in the quadriceps at 90° explained 42.0% and 32.2% of the variance in skating time during agility cornering s-turn and modified repeat skate sprint, respectively.ConclusionField-based assessments, particularly single-leg tests, are an adequate substitute to more expensive and time-consuming laboratory assessments if the purpose is to gain knowledge about key performance characteristics of skating.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Laboratory- and field-based testing as predictors of skating performance in competitive-level female ice hockey

Henriksson¹,

Vescovi²,

Fjellman‐Wiklund³

et al. 2016

OAJSM

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“…Power output is calculated as a mean each 5 s. The best 5 s is called peak power, which is related to maximum and explosive strength abilities of individual [21]. The values can either be expressed in absolute values of peak power (P max ) expressed in Watt (W), relative peak power per body weight (P max .kg −1 ) expressed in Watt per body weight (W.kg −1 ) or relative peak power per FFM expressed in Watt per FFM (W.kg −1 FFM ).…”

Section: Methodsmentioning

confidence: 99%

“…P max is regarded to mirror the alactate anaerobic processes, strength-speed abilities [22] and muscle rheological properties [23] of the tested subject. The WT30 test is a standard laboratory test for ice-hockey players and it is related to their skating performance [21], [24]. The WT30 test was conducted on a calibrated friction loaded cycle ergometer (Monark 894E Peak bike, MONARK, Sweden) interfaced with a microcomputer.…”

Section: Methodsmentioning

confidence: 99%

PPARA Intron Polymorphism Associated with Power Performance in 30-s Anaerobic Wingate Test

et al. 2014

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To date, polymorphisms in several genes have been associated with a strength/power performance including alpha 3 actinin, ciliary neurotrophic factor, vitamin D receptor, or angiotensin I converting enzyme, underlining the importance of genetic component of the multifactorial strength/power-related phenotypes. The single nucleotide variation in peroxisome proliferator-activated receptor alpha gene (PPARA) intron 7 G/C (rs4253778; g.46630634G>C) has been repeatedly found to play a significant role in response to different types of physical activity. We investigated the effect of PPARA intron 7 G/C polymorphism specifically on anaerobic power output in a group of 77 elite male Czech ice hockey players (18–36 y). We determined the relative peak power per body weight (Pmax.kg−1) and relative peak power per fat free mass (W.kg−1 FFM) during the 30-second Wingate Test (WT30) on bicycle ergometer (Monark 894E Peak bike, MONARK, Sweden). All WT30s were performed during the hockey season. Overall genotype frequencies were 50.6% GG homozygotes, 40.3% CG heterozygotes, and 9.1% CC homozygotes. We found statistically significant differences in Pmax.kg−1 and marginally significant differences in Pmax.kg−1 FFM values in WT30 between carriers and non-carriers for C allele (14.6±0.2 vs. 13.9±0.3 W.kg−1 and 15.8±0.2 vs. 15.2±0.3 W.kg−1 FFM, P = 0.036 and 0.12, respectively). Furthermore, Pmax.kg−1 FFM strongly positively correlated with the body weight only in individuals with GG genotypes (R = 0.55; p<0.001). Our results indicate that PPARA 7C carriers exhibited higher speed strength measures in WT30. We hypothesize that C allele carriers within the cohort of trained individuals may possess a metabolic advantage towards anaerobic metabolism.

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“…Several studies (2,4,6,8,9,18) have found vertical jump and off-ice 40-yd dash to be significant predictors of on-ice maximum skating speed and acceleration time. However, these studies did not assess performance during actual games or over the course of the season.…”

Section: Discussionmentioning

confidence: 99%

Physiological Characteristics of National Collegiate Athletic Association Division I Ice Hockey Players and Their Relation to Game Performance

Peyer

Pivarnik

Eisenmann

et al. 2011

Journal of Strength and Conditioning Research

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Previous ice hockey research has focused on physiological profiles and determinants of skating speed, but few studies have examined the association of preseason player evaluations with a measure of season-long performance. Understanding which tests are most predictive of player performance could help coaches organize practice and training more effectively. The purpose of this study was to describe physical characteristics and skill levels of 24 members of an NCAA Division I men's ice hockey team and relate them to game performance over the course of a season as measured by plus/minus (+/-) score. Subjects performed a battery of preseason tests including treadmill maximal aerobic capacity, body fat, leg press, push-ups, bench press, chin-ups, and sprinting ability both on and off ice. Pearson and Spearman correlations were used to examine correlations between preseason measures and +/- score. One coach also subjectively grouped the top and bottom 6 players, and analysis of variance was used to examine any differences in preseason measures and +/- score between these 2 groups. Leg press, chin-ups, bench press, and repeat sprint performance were significantly correlated with +/- score (r = 0.554, 0.462, 0.499, and -0.568, respectively). Teams with limited time and resources may choose to perform these tests to evaluate player potential efficiently. Only +/- score differed between top and bottom players suggesting that +/- accurately reflected the coach's perception of player success in this sample.

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Relationships to Skating Performance in Competitive Hockey Players

Cited by 58 publications

References 5 publications

Laboratory- and field-based testing as predictors of skating performance in competitive-level female ice hockey

Laboratory- and field-based testing as predictors of skating performance in competitive-level female ice hockey

PPARA Intron Polymorphism Associated with Power Performance in 30-s Anaerobic Wingate Test

Physiological Characteristics of National Collegiate Athletic Association Division I Ice Hockey Players and Their Relation to Game Performance

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