above photo courtesy of Dan Slovitt
Header photo courtesy of John MacMillan
The “beginning” for the duncanSCORE was the very late autumn of 2015. Without going into details, I was on committees that were selecting “Athlete of the Year” in a couple of jurisdictions. My input involved athletes’ successes in terms of medals won at various championships, and records set.
Needless to say athletes in different age groups and across the track and field event spectrum were involved. Picking winner(s) was difficult. Often the discussion came back to “well Abc had an Age Grading of xx.xx% while Xyz‘s Age Grade was only xx.xx-1%”.
After much back and forth, I gave up, infuriated. Comparisons were being made across age groups and events and disciplines, and the Age Grade differences in my mind were insignificant. Knowing that the sample “sizes” for each age year and event were only ONE, and the model created included some manual “tweaking”, I knew this was a very inappropriate use of Age Grading. Believing that an Age Grade to the 1/100 was significant over a similar result from a different age group and event was ludicrous.
There had to be (and needed to be) a better way!
A few days later it started dawning on me. For the last year or so, since he had taken over the masters world rankings from Martin Gasselsberger, John Seto was beginning to amass a treasure trove of Masters’ performances. (For some history on rankings for masters, read this on Ken Stone’s masterstrack blog https://masterstrack.blog/rankings/).
Could these not be used? Perhaps they could be!
I started pulling the data for a few track events and a couple of field events from a single year for a collection of age groups. I wanted to see if it was possible, and moreover, if the results made any sense. They seemed to. I consulted with my coaches Paul Osland and Mike Sherar, and they too thought there was something there.
I pressed on. Adding more age groups and looking at 3 years of data for M50 800m. I added a few more events.
All this took me into the late spring of 2016.
I played around with different scoring systems and ideas. At the same time I started gathering more data. As many years as possible. To this point I have organized 4 years of best performance (2013, 2014, 2015, and 2016). See here the mechanics how it works
I won’t further bore you with all the problems and blind alleys I pursued. Just know I explored a lot of them before deciding on the concept you see today. I’m a slow learner and worker, but here at last, is a “beta” look at the concept.
For a more in-depth understanding see An Introduction