On the first Sunday in April I joined Bill Murdock and John Cahill for our annual rite of Spring: run in the Carlsbad 5000 road race. We love this festival of 5K races which features 6 separate races: masters men, masters women, men and women 30-39, male and female 0-29, elite women, and elite men. Since ours is the first race of the day, we get to marvel at the leaders of each of the other races. The highlight of the trip is watching the world elite runners and marveling at their prowess on the road. Most people naturally assume that the elite winners had the best races of everyone else because they had the fastest time. However, I had my doubts because I know that Carlsbad draws probably the best age groupers of any 5k in the country. I decided to see if I could come up with a method to compare the times of the age group winners with that of the elite winners. Here’s what I found.
2016 CARLSBAD 5000 RELATIVE AGE ADJUSTED ESTIMATED RESULTS
WOMEN’S WR 14:16 MEN’S WR 12:37
ELITE 15:00 (3) ELITE 13:24
40-44 17:30 x .90 = 15:45 15:15 x .92 = 14:01
45-49 17:59 x .88 = 15:49 15:11 x .86 = 13:03 (1)
50-54 18:38 x .84 = 15:39 16:08 x .84 = 13:33
55-59 19:07 x .77 = 14:43 (2) 17:04 x .78 = 13:18 (2)
60-64 21:44 x .75 = 16:18 17:59 x .74 = 13:18 (2)
65-69 23:00 x .70 = 16:06 19:46 x .72 = 14:14
70-74 26:30 x .64 = 16:57 21:39 x .70 = 15:09
75-79 32:15 x .61 = 19:40 22:26 x .65 = 14.35
80-84 29:40 x .49 = 14:32 (1) 28:32 x .57 = 16:16
85-89 32:00 x .48 = 15:21
90+ 49:31 x .37 = 18:19
AGE ADJUSTED PODIUM FINISHERS
WOMEN MEN
- 80-84 = 14:32 (29:40) 45-49 = 13:03 (15:11)
- 55-59 = 14:43 (19:07) 55-59 = 13:18 (17:04)
- ELITE = 15:00 60-64 = 13:18 (17:59)
Note: Age adjustment factor calculated by dividing the women’s and men’s 5K world record by the respective American masters 5km age group road records (USATF website).
This data suggests that while the elites may have had the fastest times, their performances might have actually been the 3rd and 4th best race results for their respective genders. Do these adjusted times make sense? What struck me immediately was how narrow the range of adjusted times were, which is the quality of performances you would expect if the best age groupers were competing in the same race. Of what practical use is this exercise?
If you are a masters runner, you can find your age group adjustment factor from the data and multiple it times your current 5K times to see how it compares to the younger runners in their prime. I shared the information with John, who at 92 still runs in a 5K race almost every weekend. His comment was priceless, “Well, I used to be a fast old fart. Now I’m only half-fast.” Gotta run, Tom.
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