Anthony Donskov

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1/N: A 3 G Approach to Training Hockey Players

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When it comes to programming for ice hockey we must ask ourselves…what qualities matter most in sport competition?  In other words, what qualities can we train off the ice, that make the most tangible differences on the ice?  What abilities make great players great?   In order to answer these questions, a good place to start is to look at some of the existing literature and attempt to see what correlates best with on-ice performance. 

  1. (Runner, Lehnhard, Butterfield, Tu, & O'neill, 2016)

Population:  Male Collegiate Hockey Players

Key Findings:  Only Vertical Jump (not standing broad jump, 1RM Squat or 40-yard dash) was associated with skating speed (fwd. and bwd. 90’ acceleration test).

  1. (Burr et al., 2008)

Population:  853 Elite Draft Eligible Players (Combine testing as a predictor of hockey playing potential

Key Findings:  When eliminating goaltenders using multivariate modeling,peak anaerobic power (Wingate), body fat index and standing long jump appear to be most correlative to playing potential (as opposed to bench press, sit ups, and VJ). 

  1. (Janot, Beltz, & Dalleck, 2015)

      Population:  Division III Ice Hockey Players

Key Findings:  Vertical Jump, 40-yard dash, peak power % drop and 1.5 mile run time were the     best predictors ofperformance.  In particular the VJ and 40-yard dash were the best predictors of repeat skate performance using the Modified Repeat Skate Sprint Test.

  1. (Farlinger, Kruisselbrink, & Fowles, 2007)

Population:  AA and AAA hockey players

Key Findings:  Both the 30-meter sprint and 3 hop jump (as opposed to VJ or BJ) correlated most with on-ice performance (35-meter sprint and cornering S Test)

  1. (Henriksson, Vescovi, Fjellman-Wiklund, & Gilenstam, 2016)

Population:  Female Ice Hockey Players (Ages 15-25)

Key Findings:  Single Leg Broad Jump (as opposed to 1RM bench press, 1Rm squat, 20-meter shuttle run) was correlated most with on-ice transition agility, cornering S-Test, and modified repeat skate sprint test).

  1. (Mascaro, Seaver, & Swanson, 1992)

Population:  Professional Hockey Players

Key Findings:  Vertical Jump (as opposed to broad jump, 40-yard dash, and isokinetic strength of the quads and hamstrings) was most correlated with on-ice t cornering speed (54.9 meters).

  1. (Gilenstam, Thorsen, & Henriksson-Larsén, 2011)

Population:  Men and Women Players

Key Findings:  In men, VO2peak (as opposed to lean body mass and peak torque of the thigh muscles) was most closely associated with on-ice acceleration of 6.1 meters).  In women, body weight was most correlated to on-ice speed (47.85 meters). 

When looking at the sport of ice hockey the research is debatable as to which off-ice motor abilities correlate with on-ice success.  Certainly, sample size, group demographic (youth hockey vs college hockey vs pro), sex (male vs female), testing methods, and time of year all play a role in the results.  No doubt testing and monitoring play a major role as well.  With questions unanswered, coaches are left wondering what qualities to focus on.  In this situation a 1/n approach may be the best way to prepare the players for the demands of the game.  1/n simply means diversifying the portfolio.  In economics this done to offset potential loss while maximizing gains. The same basic principle applies in sport preparation.  In the coaching world, the 1/n heuristic means diversifying programming to include horizontal force development, vertical force development, strength and power training within the weekly microcylce.  This covers most abilities that have moderate to strong correlations to on-ice performance on a weekly basis as it pertains to current research. Thus, minimizing losses while maximizing gains. 

At Donskov Strength and Conditioning, our diversification approach is daily undulating periodization. Each day has a theme, training goal, and physiological target.  In the track and field world, this is often referred to as a three day-rollover plan. Here is a 30,000-foot view of our summer programming at DSC.

Goal:  Tax all motor abilities within the microcyle

Frequency:  3xweek (These are professional players.  To get better they need ice touches.  This comes at a physiological cost.  Hence, three touch points/week

Day 1:  Gain: Max Effort day complimented with high impulse jump training and acceleration work

Day 2:  Go: Dynamic Effort day complimented with true plyometrics, and speed work

Day 3:  Grow:  Repeat Effort day complimented with frontal plane jump training and change of direction work OR lactic work (schedule depending)  


The 1/n approach seeks to diversify the portfolio of physiological stress.  Using the 3 G approach (nothing new here, just an easy way we can communicate the message to our athletes) we can measure our program results based on our unique KPI’s, allow our micro plan to dictate programming decisions, and complement our energy system work with our weight room focus.  In addition, we can hit both ends of the force/velocity curve within the same week while strategically planning higher load days at the backend of the week, thus, not competing with ice touches/skill work.  These are just a few reasons why we believe the 1/n heuristic is paramount in program design. 


Burr, J. F., Jamnik, R. K., Baker, J., Macpherson, A., Gledhill, N., & McGuire, E. (2008). Relationship of physical fitness test results and hockey playing potential in elite-level ice hockey players. The Journal of Strength & Conditioning Research, 22(5), 1535-1543.

Farlinger, C. M., Kruisselbrink, L. D., & Fowles, J. R. (2007). Relationships to skating performance in competitive hockey players. Journal of Strength and Conditioning Research, 21(3), 915-922.

Gilenstam, K. M., Thorsen, K., & Henriksson-Larsén, K. B. (2011). Physiological correlates of skating performance in women's and men's ice hockey. The Journal of Strength & Conditioning Research, 25(8), 2133-2142.

Henriksson, T., Vescovi, J. D., Fjellman-Wiklund, A., & Gilenstam, K. (2016). Laboratory-and field-based testing as predictors of skating performance in competitive-level female ice hockey. Open access journal of sports medicine, 7, 81.

Janot, J. M., Beltz, N. M., & Dalleck, L. D. (2015). Multiple off-ice performance variables predict on-ice skating performance in male and female division III ice hockey players. Journal of sports science & medicine, 14(3), 522.

Mascaro, T., Seaver, B. L., & Swanson, L. (1992). Prediction of skating speed with off-ice testing in professional hockey players. journal of orthopaedic & sports physical therapy, 15(2), 92-98.

Runner, A. R., Lehnhard, R. A., Butterfield, S. A., Tu, S., & O'neill, T. (2016). Predictors of speed using off-ice measures of college hockey players. Journal of Strength and Conditioning Research, 30(6), 1626-1632.


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