On-Ice and Off-Ice Linear Sprint Performance Across Competitive Levels in Ice Hockey Players: Insights from Continuous Velocity Profiling
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Jablonka, Dominik
Uthoff, Aaron
Eustace, Steven
Morris, Rhys
Smoliga, Julian Enrik
Augustovicova, Dusana
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MDPI AG
Abstract
Linear speed is a key performance determinant in ice hockey, yet no studies have compared continuous on-ice and off-ice velocity profiles across multiple competitive levels. This study examined continuous velocity curves and discrete sprint variables during 20 m on-ice (skating) and off-ice (running) sprints across three competitive levels. Sixty male ice hockey players (A-Team n = 20, U20A n = 20, U20B n = 20) completed maximal 20 m sprints in both conditions using a motorized resistance device. Bayesian analyses were used to evaluate continuous velocity profiles and discrete variables. Posterior estimates consistently favored greater off-ice velocity profiles than on-ice velocity profiles across all groups, particularly during the early portion of the sprint (P(diff) ~85%), although the practical meaningfulness of these differences remained uncertain. Discrete sprint variables showed stronger and more consistent practically meaningful differences (P(diff > SWC) = 66–99%). Between-group comparisons suggested a competitive hierarchy, with posterior estimates favoring greater velocity values in adults than lower competitive-level late adolescents (P(diff) ~87%). Practitioners should consider potential differences between on-ice and off-ice sprint performance and hierarchical trends across competitive levels when structuring training and assessment. Continuous velocity profiling may provide additional insight into velocity-development patterns, whereas discrete metrics may be more appropriate for routine team-level monitoring.
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42 Health Sciences, 4207 Sports Science and Exercise, 4.2 Evaluation of markers and technologies, 1106 Human Movement and Sports Sciences, 4207 Sports science and exercise, ice hockey, linear speed assessment, continuous velocity profiling, Bayesian analysis
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Sports, ISSN: 2075-4663 (Print); 2075-4663 (Online), MDPI AG, 14(7), 290-290. doi: 10.3390/sports14070290
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CC-BY Creative Commons Attribution
© 2026 by the authors. Licensee MDPI, Basel, Switzerland.
© 2026 by the authors. Licensee MDPI, Basel, Switzerland.
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Except where otherwise noted, this item's license is described as CC-BY Creative Commons Attribution