Ice Hockey Forward Skating Force-Velocity Profiling Using Single Unloaded vs. Multiple Loaded Methods

Abstract

Perez, J, Guilhem, G, and Brocherie, F. Ice hockey forward skating force-velocity profiling using single unloaded vs. multiple loaded methods. J Strength Cond Res 36(11): 3229–3233, 2022—This study aimed to compare skating force-velocity relationships determined throughout sprints performed against various loaded conditions or inferred from movement kinetics measured during a single unloaded sprint. Ten female ice hockey players performed one unloaded maximal skating sprint test measured with a radar gun followed by 4 resisted skating sprints against a robotic horizontal resistance with progressive loads in reference to equipped body mass (BM): 3 kg (robotic resistance), 25, 50, and 75% of equipped BM. Maximal theoretical force (F0), velocity (V0), power (Pmax), optimal velocity (Vopt) condition for producing maximal power, and slope of the linear force-velocity relationship (SFV) were determined from each method and compared using a paired sample t-test, absolute mean bias (±95% confidence intervals), Pearson correlations, and typical error of the estimate in standardized units (effect size [ES]). Statistical significance was set at p < 0.05. No statistical difference was found for all mechanical variables determined from the 2 methods (p ranging 0.09–0.59). Although exhibiting positive correlations ranging from moderate (r = 0.50 for SFV) to high (r ranging from 0.71 to 0.84 for F0, V0, Vopt, and Pmax) between methods, all variables exhibited large levels of error between approaches (ES ranging 0.66–1.71). Multiple loaded and single unloaded methods were comparable with determine force-velocity relationships during forward on-ice skating sprint. The low-cost fatigue-free unloaded method suggests it could be used in constrained contexts (i.e., congested schedule and low available time) or for a simple force-velocity profiling. Inversely, multiple loaded methods would be more appropriate to evaluate and individualize training for skilled ice hockey players accustomed to resistive skating sprint.

Exploring associations between sprinting mechanical capabilities, anaerobic capacity, and repeated-sprint ability of adolescent ice hockey players

“…The general aim of this study was to widen current knowledge around sprinting F-V and its links with anaerobic capacities measured threw common tests. Previous work analyzing the sprinting F-V of ice hockey players was fairly limited focusing more on the validity and reliability of the method with a limited number of subpopulations, that is, female French senior to junior national teams and male players from elite Finnish leagues (16)(17)(18)(19). The first objective of this study was to explore how the mechanical capabilities of sprinting F-V were related to variables from common anaerobic tests such as the Wingate and repeated-sprint test.…”

“…They demonstrated that maximal theoretical power (P max ) displayed the strongest associations with the three performance indicators (|r| ranging from 0.81 to 0.92; p < 0.001). Other work including ice hockey players was used to confirm the validity and reliability of the method on the ice, this time with French elite female players and Finnish elite male junior players (17)(18)(19). To our knowledge, F-V data for highly trained adolescent ice hockey players have yet to be published.…”

“…Glaude-Roy et al10.3389/fspor.2023.1258497 mechanics of teenage ice hockey players are different from elite adult sprinters. However, participants in this study have exhibited lower mechanical characteristics than higher-level athletes in previous studies(17)(18)(19). Given velocity follows the same mono-exponential function in youth (22) and aerodynamics included in the method adjusts to the stature and mass of each individual(14), there are a few reasons that the method should not be valid with this study population.…”

Elite Adolescent Ice Hockey Players: Analyzing Associations between Anthropometry, Fitness, and On-Ice Performance

“…With this long-term developmental approach in mind, talent identification processes have been developed [ 13 , 14 ], based on the assessment of anthropometric characteristics (e.g., body mass, height, body mass index); body composition (i.e., body fat percentage, lean mass rate) [ 15 , 16 ]; as well as performance, specifically, power–strength–velocity performances in jumping, sprinting and/or skating, and throwing/throwing [ 17 , 18 ]. Therefore, the stakeholders involved in team selection (and player evaluation) processes rely on all or on part of these precise, comprehensive, and complex evaluation methods [ 19 , 20 ], while considering the modern evolution of the sport and the associated standards [ 5 ]. Past research suggests that anthropometric characteristics and/or body composition are variables associated with success in sport, whether at the senior professional level [ 21 , 22 ], or among younger competitive athletes [ 23 , 24 ].…”