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Power in Rowing Symposium: Stephen Seiler

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Power in Rowing Symposium: Stephen Seiler

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Power, Pulse rate and Perception as a telling trinity in training monitoring of endurance athletes.

The full video and audio presentation are on www.rowing.chat podcast network.

Stephen Seiler received his doctoral degree from the University of Texas at Austin. He is past Vice-Rector for Research and Innovation and past Dean of the Faculty of Health and Sport Sciences at the University of Agder in Kristiansand, Norway. Currently, he is working as a full professor at the same institution. His research interests include exercise physiology and training adaptations, particularly to endurance training for cyclists, rowers, XC skiers, orienteers and distance runners.

Power, Pulse rate and Perception as a telling trinity in training monitoring of endurance athletes.

The full video and audio presentation are on www.rowing.chat podcast network.

Stephen Seiler received his doctoral degree from the University of Texas at Austin. He is past Vice-Rector for Research and Innovation and past Dean of the Faculty of Health and Sport Sciences at the University of Agder in Kristiansand, Norway. Currently, he is working as a full professor at the same institution. His research interests include exercise physiology and training adaptations, particularly to endurance training for cyclists, rowers, XC skiers, orienteers and distance runners.

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Power in Rowing Symposium: Stephen Seiler

  1. 1. P3: Power, Physiology, Perception Integrating this “holy trinity” to monitor and prescribe training effectively
  2. 2. How many times have your athletes trained this year? 1.0001500≈ 1.05 10 training sessions per week x 50 weeks per year
  3. 3. ”…grant me the serenity to accept the things that cannot be calculated; courage to calculate the things that can be calculated; and wisdom to know the difference.” Rick Nason Coaching is managing complexity!
  4. 4. External Load (power x time) Internal Load Molecular signals for adaptation Cellular Damage & Systemic Stress
  5. 5. Adaptive Stimulus Stress (Adjusting training characteristics) • Bone-tendon-muscle damage • Inflammatory stress • Repetitive sympathetic stress • Immuno-suppression • Psychological fatigue
  6. 6. Seiler & Kjerland. Scand. J. Med. Sci. Sports. 16, 49-56, 2006.
  7. 7. 1970-1979 1980-1989 1990-2001 N 9 6 8 Height (cm) 191 192 193 Weight (kg) 89 87 90 VO2 max (L.min-1) 5.8 6.4 6.5
  8. 8. Training Intensity Distribution International Rowing Medalists 0 10 20 30 40 50 60 Traininghrs/month 70s 80s 90s Basic endurance High intensity Fiskerstrand & Seiler, SJMSS 14:303-310, 2004
  9. 9. Intensity Category Heart rate [b*min-1] Blood lactate [mM*l-1] % of Time (HR) Compensation < 140 < 2 8 (6) Extensive endurance 140-160 < 2 87 (6) Intensive endurance 156-168 2-4 2 (1) Highly intensive endurance > 180 4-8 1 (0.4) Race-specific velocity-endur. Max (0.5-2 min) 4-10 2 (0.6) Rowing Heart Rate distribution-37 weeks World Class Junior Rowers (n=36) Gullich A, Seiler S, & Emrich E. Training Methods and Intensity Distribution of Young World Class Rowers. Int. J. Sports Physiology and Performance. 4(4): 448-460. 2009
  10. 10. 0 20 40 60 80 100 120 I-sone 6 I-sone 5 I-sone 4 I-sone 3 I-sone 2 I-sone 1 Endurance training intensity distribution 2-time Gold medal winnerHours
  11. 11. Why so much Green Zone training? 3 interconnected mechanisms (?) Systemic Stress Load Management Energy Availability Management Optimization of adaptive signal stream Intensity x Duration Adaptive Signal Systemic Stress
  12. 12. The Physiology Feedback Trinity Physiological Responses Power/Pace Perceived Effort/ Exertion External Work Internal “Cost”
  13. 13. 13Exercise Intensity (%HRpeak) [La-] Z1 Z3 Z5 55 80 87 100 ~2mM VT1 ~4mM VT2 Z2 Z4 5 iZones? 9372 Z6+
  14. 14. 14Exercise Intensity (%HRpeak) [La-] 55 78 86 100 2mM VT1 4mM VT2 3 iZones Z1 Z2 Z3
  15. 15. Yes, I can speak comfortably Yes, I can speak, but not entirely comfortably No, I cannot speak comfortably Physiological responses associated with 3 answers to a standardized talk test. Data re-organized and color coded from original figures in Woltman et al. 2015
  16. 16. SESSION TYPE HR (%MAX) VO2 (%MAX) BLOOD LACTATE (mM) RPE (BORG 6-20) SESSION RPE (FOSTER 1-10) BELOW VT1 60MIN 68 ± 7 61 ± 0.7 1.0 ± 0.1 9.7 ± 0.4 2 ± 0 BELOW VT1 120 MIN 68 ± 7 Not measured, ran outdoors 1.0 ± 0.1 10 ± 0.4 2.4 ± 1.1 THRESHOLD 88 ± 2 84 ± 0.7 2.7 ± 0.4 13.9 ± 0.5 5 ± 0.6 ABOVE VT2 (6 X 3MIN) 95 ± 3 96 ± 0.7 7.1 ± 0.7 17.2 ± 0.8 8.1 ± 1 2007
  17. 17. 17Exercise Intensity (%HRpeak) [La-] 55 78 86 100 2 i-zones that «left-shift» with intensity x time? LIT HIT 1.4-2.5mM LOW systemic stress HIGH systemic stress 2.7- 6 mM
  18. 18. < LT1 > LT1 NO Cardiac Drift Cardiac drift = 11% of HRR
  19. 19. Even during Zone 1, “Green Zone” training, there is no such thing as a true physiological steady-state….. 3.5 hours @ 205 watts 53 year-old semi-fit professor
  20. 20. Heart Rate at a given power/pace threshold is stable even as threshold power/pace increase 155 156 158 200 220 240 260 280 300 320 340 360 380 400 Active Rest Preparation Competition WattsatLT 100 110 120 130 140 150 160 170 180 190 200 Power output Heart Rate Data from 13 professional cyclists, Lucia et al, 2000
  21. 21. Max HR- To thine own heart (and sport) be true DIFFERENCE, ACTUAL VS PREDICTED (BPM) N=102 220-AGE 208-0.7*AGE 211-0.64*AGE 0-3 25 26 40 4-7 35 29 27 8-12 23 24 22 13-19 15 18 10 20-30 4 5 3 AVERAGE DIFFERENCE ACTUAL VS CALCULATED 5 bpm underestimation 6 bpm underestimation Estimated and actual averages were identical Table 3. Laboratory determined versus estimated maximal heart rate See https://en.wikipedia.org/wiki/Heart_rate# for references and more information on the development of these age-adjusted maximal heart rate prediction equations.
  22. 22. Feed back
  23. 23. How do you feel? How are you responding to the training?
  24. 24. Photo courtesy of Dag Erik Tvedt
  25. 25. Embedded movement sensors (limbs, rackets, bats, boats, teams etc.) “Real-time” movement analysis Big (Training & Performance) Data analytics- hypothesis driven and “hypothesis free” approaches Home and field based physiological measurements
  26. 26. 1.07 1.64 1.03 1.24 2.32 4.18 7.00

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