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Distance Run Handicaps. Paul Vanderburgh HSS 409: Kinesiology. Agenda. Background Distance Running and Body Weight Scaling and Other Activities Running and Age Age and Weight Handicap Proposal Summary and Conclusions. Background.

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distance run handicaps

Distance Run Handicaps

Paul Vanderburgh

HSS 409: Kinesiology

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

Distance run times (DRT) well known to decrease with age and weight

But…how much due to age and weight alone?

age categories
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
wava world association of veterans athletes age grading
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)

team clydesdale bw and age
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 +)

distance running and body weight theory
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
drt and body weight actual data
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

other aerobic activities cycling
Other Aerobic Activities - Cycling

Cycling: lighter cyclists have advantage climbing but heavier are faster in flat time trials (quantified by Swain 94)

other aerobic activities rowing
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)

strength and bw handicaps
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)
running and age theory
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)

vo 2max decline run time
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
what next
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
summary conclusions
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
references
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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