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LottoNL-Jumbo Speed Skating Team
Skaters: Sven Kramer, Wouter Olde Heuvel, Kjeld Nuis, … Some 16 Olympic medals + numerous championships
Monitoring and Analysing Professional Speed Skaters Jac Orie Arno - - PowerPoint PPT Presentation
Monitoring and Analysing Professional Speed Skaters Jac Orie Arno - - PowerPoint PPT Presentation
Monitoring and Analysing Professional Speed Skaters Jac Orie Arno Knobbe LottoNL-Jumbo Speed Skating Team Skaters: Sven Kramer, Wouter Olde Heuvel, Kjeld Nuis, Some 16 Olympic medals + numerous championships Why? WE WANT TO WIN
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Why?
WE WANT TO WIN
Optimal periodization
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Periodization
‘Systematic planning of physical training’
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Challenges in Periodization
Simultaneous development of many abilities
decreases effectiveness of training
Adaptation of too many stimuli bad results Distance/event specific Athlete-specific
Male vs. female Individual physique
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Block Periodization Models
Issurin
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Taper
Issurin
Taper = superposition of residual training effects
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Taper/Peak
Accumulation Transmutation Realisation 12-30 days 12-25 days 8-14 days competition Meso-blocks residuals
Issurin
Superposition of residual training effects - timing
most complex phase
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Historical Training Data
- 15 years of data collected
- Some 40 athletes, currently nine: seven men, two women
- Daily training details
- Morning and afternoon training
- Six days per week
- Training type, intensity (subjective), duration, load
- Roughly bi-weekly physical test
- Aerobic
- Anaerobic
- Competition data
- Corrected for track-differences
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Speed Skating Data
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Speed Skating Data
0.98 0.99 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07
time_relative
0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 22.5 25.0 27.5 30.0
density
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The Effect of Training
test moment
tapering
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Aspects of Periodization
Within each window:
- count
How many exercises?
- sum
(duration, load) How many minutes, …?
- max
(duration, intensity, load) Did you recently …?
- stddev
(duration, intensity, load) How varying was …?
Determiners
- f specific activities
- just in the morning/afternoon
- certain intensity ranges (zones)
Sum of duration over 14-day period Max of intensity over 2-day period Sum of duration over 21-day period, morning sessions Sum of duration over 21-day period, intensities 6, …, 9 Maximum of load over 7-day period, cycling …
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Modelling Training/Response
Each variable will have a U-shape Neither too little, nor too much In theory non-linear, in practice only a sample
linear model threshold model
training load
- ptimum
relative time available data
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Modelling Training/Response
Each variable will have a U-shape Neither too little, nor too much In theory non-linear, in practice only a sample
linear model threshold model
training load
- ptimum
relative time
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Kjeld Nuis
178 races On average 2.89% above track record Specialises on 1000 m (2.1%) 2015-2016
Dutch champion 1000 m, 1500 m WC Distances: bronze 1000 m, silver 1500 m WC Sprint: ‘silver’ ISU World Cup: gold 1000 m, silver 1500 m
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250 500 750 1,000 1,250 1,500 1,750 2,000
sum_load_am_5
0.9975 1.0000 1.0025 1.0050 1.0075 1.0100 1.0125 1.0150 1.0175 1.0200 1.0225 1.0250 1.0275 1.0300 1.0325 1.0350 1.0375 1.0400 1.0425 1.0450 1.0475 1.0500 1.0525 1.0550
time_relative
undesired result due to over-training
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Fitness/Fatigue Parameters Kjeld
Parameter fitting on a physiological model of
fatigue and supercompensation
0" 5" 10" 15" 20" 25" 30" 35" 40" "fa*gue" "fitness" "kernel"
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