FFigawi
DIS Veteran
- Joined
- Dec 28, 2009
Something I've done in the past is compare percentile finishes from year to year. For example, let's say there were 1700 runners this year and you finished in 800th place.
800/1700 = 47%
Now look at how many people finished in 2017, let's say it was 1950.
1950*0.47 = 917th place (just round if decimal).
Now look through the 2017 results for the runner who finished in 917th place. What time did they finish in?
Let's say your time was 2:20 in 2018 at a 47% finish and the 917th place runner in 2017 was a 2:16 finish. This would lead me to believe that this year's course was about 4 min (or 2.9% (4 min/140 min) more difficult than last year. Do the last 3-4 years and you get a general idea at the baseline time for the percentile finish and the ebbs and flows to more challenging weather condition years from others.
Using this method has a few assumptions:
1) The race course is the same.
2) We assume that the population of runners from 2017 to 2018 is roughly equal. No real good way to prove this one way or another, but as long as there was nothing special differentiating the 2017 pool of runners from the 2018 pool of runners, then in most cases this is a safe assumption.
3) No extenuating circumstances influenced the pools time other than weather. Example, no train crossed the course forcing people to stop or it wasn't black flagged and many entries weren't recorded, etc.
Doing this helps isolate the actual race day conditions as a variable for how difficult the course was from one year to the next.
Geeez. Whatever happened to #NoMathMonday? @Keels will not be pleased.