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Distance Run Handicaps

This study delves into creating a handicap model for age and body weight in distance running, exploring how age and weight affect performance. It examines VO2max decline with age, body weight impact on running times, and proposes a model for fair competition across different age groups and body weights.

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Distance Run Handicaps

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  1. Distance Run Handicaps Paul Vanderburgh HSS 409: Kinesiology

  2. Agenda • Background • Distance Running and Body Weight • Scaling and Other Activities • Running and Age • Age and Weight Handicap Proposal • Summary and Conclusions

  3. Background Distance run times (DRT) well known to decrease with age and weight But…how much due to age and weight alone?

  4. Age Categories • Widely used in road races • Often very few competitors in the oldest categories • No easy way to compare runners of different age groups

  5. WAVA (World Association of Veterans Athletes) Age-Grading • Adjusts run time by an age-grading factor • Ex: 42 yr old male runs 24:00 5K • Factor = 0.9487 • Run time x Factor = 22:46 = Adjusted Run Time (ART) • ART can be compared to all other runners’ ART’s • Handicap based on world bests, not physiology (http://www.howardgrubb.co.uk/athletics/wavalookup.html)

  6. Team Clydesdale: BW and Age Categories: A1= Athenas 145-159lbs A2 = Athenas 160-179lbs A3 = Athenas 180lbs + C1 = Clydesdales 185-199lbs C2 = Clydesdales 200-224lbs C3 = Clydesdales 225-249lbs Y = Youth (Under 29 years) T = Thirty something (30-39 years) M = Master (40-49 years) GM = Grand Master (50 years +)

  7. Distance Running and Body Weight - Theory • VO2max  Body Weight1/3 (Astrand ’86) • 5K run time  VO2max/BW(Nevill ’92) • Therefore, 5K run time  BW1/3 (Vanderburgh 95) • Can probably be applied to other run distances

  8. DRT and Body Weight – Actual Data DRT  BW1/3 College-age men Lean, military academy cadets 2-mile run time (Crowder 95, Vanderburgh 95) Best-fit line

  9. Other Aerobic Activities - Cycling Cycling: lighter cyclists have advantage climbing but heavier are faster in flat time trials (quantified by Swain 94)

  10. Other Aerobic Activities - Rowing • Rowing Ergometer: 2500m time trial times  BW1/3 or H • Row Time x Ht yields an adjusted score that is fair (Vanderburgh 96)

  11. Strength and BW Handicaps • Strength is well known to be directly proportional to muscle cross sectional area (CSA) • Muscle Strength  CSA  BW2/3(Vanderburgh 99, Jaric 2002) • Wilks Powerlifting Formula provides an accurate handicap by BW (Vanderburgh 99)

  12. Running and Age - Theory • Max heart rate is well known to decline with age (220-age) • This would likely explain the decline in VO2max with age • Quantification of the independent effect of age on VO2max: • Males: 0.26 ml/kg.min O2 per yr • Females: 0.25 ml/kg.min O2 per yr (Jackson 95, 96)

  13. VO2max Decline Run Time • Metabolic equations available: VO2max and BW used to compute run speed • Example for 5K: 5K run speed = 84.3(VO2max1.01BW-1.03) (Nevill 92) • Run time changes could be calculated with VO2max changes due to age

  14. What Next? • Combine research findings to create a run-handicap model for age and body weight • Field test the model • Examine logistics (weigh-ins, database) • Validity

  15. Summary/Conclusions • Distance run time  BW1/3 • VO2max decreases, independent of other factors by: • Males: 0.26 ml/kg.min O2 per yr • Females: 0.25 ml/kg.min O2 per yr • This aerobic capacity decline can be linked, through metabolic equations, to actual run times • Research data can now be used to develop physiologically and biomechanically correct handicap models for age and BW

  16. References • Crowder T & Yunker C. Scaling of push-up, sit-up and two-mile run performances by body weight and fat-free weight in young, fit men. [Abstract]. Med Sci Sports Exerc. 28:S183, 1996. • Jackson A, E Beard, L Weir, R Ross, & S Blair. Changes in aerobic power of men, ages 25-70 yr. Med Sci Sports Exerc. 27:113-120, 1995. • Jackson A, L Weir, G Ayers, E Beard, J Stuteville, & S Blair. Changes in aerobic power of women, ages 20-64. Med Sci Sports Exerc. 28:884-891, 1996. • Jaric S, Ugarkovic D, & Kukolj M. Evaluation of methods of normalizing muscle strength in elite and young athletes. J Sports Med Physical Fitness. 42:141-151, 2002. • Nevill A, R Ramsbottom, & C Williams. Scaling physiological measurements for individuals of different body size. Eur J Appl Physiol. 65:110-117, 1992. • Swain D. The influence of body-mass in endurance bicycling. Med Sci Sports Exerc. 26:58-63, 1994. • Vanderburgh P. A simple index to adjust maximal strength measures. J Exerc Physiol. 2:2-7, 1999. • Vanderburgh P & A Batterham. Validation of the Wilks Powerlifting Formula. Med Sci Sports Exerc. 31:1869-1875, 1999. • Vanderburgh P, Katch F, Schoenleber J, Balabinis C & Elliott R. Multivariate allometric scaling of men’s world indoor rowing championship performance. Med Sci Sports Exerc. 28:626-630, 1996. • Vanderburgh P & M Mahar. Scaling of 2-mile run times by body weight and fat-free weight in college-age men. J Strength Cond Res. 9:67-70, 1995.

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