Tuesday, May 19, 2015

Twin Cities 1 Mile in retrospect: How slow was it? A statistical analysis



2015 TC 1 Mile Champions Garrett Heath and Heather Kampf

The Medtronic Twin Cities 1 Mile is one of the premier road miles in the United States.  It has hosted Olympic medalists and has borne witness to several sub-four-minute miles.  In addition to a top-flight pro race, the TC 1 Mile features several "open" waves, which usually total over two thousand finishers.  The traditional course was flat and very fast.  This year, the installation of a new light-rail transit line forced the course through downtown Minneapolis to be changed, likely permanently. 

This course change was announced a few months ago, and after researching the elevation profile of the new course, which gains about 30 feet of elevation in the first half mile before flattening out, I published an article in which I predicted the new course would be five to eight seconds slower. 

The race itself, which happened last Thursday, was held on a cool, rainy evening with slight winds.  Weather data pegs the exact conditions at 54 degrees F, light rain, and 9 mph winds at race time—certainly not conducive to the very fastest times, but not terrible.  The winner, Garrett Heath (a Minnesota native), took the win in 4:08, which was a sharp contrast to Nick Willis' blistering 3:56 course record the last time the race was held.  Heath himself was runner-up in that race with a 3:57. 

By looking just at the pro results, the new course looks substantially slower than the old one, but you could chalk this up to cautious tactics early in the race, or just a fluke from a small sample size.  To get a real answer on how much slower the new course was, and how accurate my prediction was, we'll have to do some statistical analysis.

The rest of this article will go in detail on the methods I used to compute how slow the course actually was, but if you're just looking for a quick conversion, here it is: For competitive runners, the 2015 TC 1 Mile was 13 ± 3 seconds slower than the 2013 course. A more accurate conversion is to multiply your 2015 race time by 0.9581 to get the equivalent 2013 time and multiply your time by 0.009 for the uncertainty.