ahhchon wrote:
it would take some analysis, but i think for men, the sub 2:15 range would be a good point to start talking regarding genetically "gifted", meaning an outlier. just take all marathon finishers under 3-3:10 hours, find the outliers in that range, and by outliers, i'm taking 1.5 sd from the mean of that range. the reason i would chose 3:10 hours is because i believe that a majority of people can run 3:10 with dedication. it makes no sense to include 4-5 hour runners in our data as they are 1) generally haven't put in the time, or effort it requires to run 3:10, or are older, which adds another factor to the genetic component, because i would assume we're talking about prime aged men atm, vs 50-60 year olds.
this has been an interesting topic.. i might scrub some marathon results and run some analysis...
lets say i decide to do this.
what races should i chose? my guess would be that, if i'm looking to find the "genetic lottery limits", and outliers, i should be looking at big marathons, where the faster runners/more elites are going to show up, not to mention, larger samples, compared to a small local marathon where the winning time is 2:55. might also make sense to take data from the past 5 years of the same race, just to average out for random weather events, too. any other thoughts?
2:15 is fast enough that you getting populations that are good enough to try. For example if you look at all the DI runners who run 5k/10k but who don't break 14/29. Those DI runners aren't maxing out their ability by any extend but you are going to have a population that is trying and getting to the 95%+ type numbers rather than the average marathoner who just isn't trying. I wouldn't be shocked if 2:15 was well above a top 5% result. I know plenty of solid club runners (guys who ran DI in college and were 14:15-14:40 type guys. One was an XC all american) type runners who were still willing to to run 80+mpw and most of them struggle to get in the low 2:20s with only a couple making the OT. Granted most were in the old shoes so maybe that stud with his 2:16 would have been a 2:12 guys these days and all those 2:22 guys would have run 2:18. I am sure if they didn't have to work they could have squeaked out a few more mins but these guys were probably getting close. Maybe they had another 5 mins in them with mythetical perfect training but I sort of doubt it.
I don't think you are going to get much out of analyzing marathon results as you are missing the key input about how much the person running the race cares. I think you would get better info if you took Strava training data and then used it to look at results. You could plot up hours of training over the previous year and marathon results and you might find that people running 3:00 had a spread of 5-10 hours/week of training while those running 3:30 ran 3-6 hours.... You could then track people over time and see what happens to the subset of 3:30 runners who up their training time by 2 hours for their next marathon.
Just looking at marathon data, maybe trying to track improvement over time might be interesting (how many people run 4:00, 3:30 and then 2:50) and how many keep running the same time. But again you have to idea if the people who don't improve are trying to improve...