Saturday, September 23, 2017

Dubai Desert Road Run 10K Race 1 : The Metrics

Today's Dubai Desert Road Run 10K packed a quality field of 392 with some of the fastest male and female runners in Dubai showing up. As many observed, this became a fast race for a season opener and there was plenty of visible excitement in the air to complement the energy.

Overall Standings

The top 100 in standings show who's done their homework over the summer. I'm somewhere in there. It seems to me that older individuals are getting faster while (we) the whatsapp generation continue to tumble down in fitness. Need to reduce thumbing up and down stupid messages and run more! 

Fig 1 : Official results, top 100 at Desert Road Run 10K Race 1

I didn't exactly throw a kitchen sink at the race. Starting a bit on the conservative side and tossing a negative split cost me a bit of ground to cover in the later part. However, for the same course and same race for more or less similar ambient temperature profile, I broke a 3 min PR from 2013 which is interesting. As you can tell, I do not do a lot of these 10K's.

The following data table are my numbers from the race. Cost of running and running economy are surrogate values calculated purely from external mechanical power and running speed. I also choose to leave critical power and/or FTP from the data table. The -ve splitting today meant dabbling with something like a -3% to +20% CP distribution beginning to end, capping with a final kick at + 60% CP.

Fig 2 : Run data for Desert Road Run 10K Race 1

A Look at Riegel Fatigue Factor

Readers will note that I extensively explored Riegel fatigue factors for both world class male and female racing in this post and this post. Many readers on Facebook expressed the concern for applicability of the exponents to everyday age-groupers.

Very conveniently, I ran a constant pace 3K (00:12:12) and a 5K TT (00:23:40) within 1 month's gap of each well before today's race. The first and second TT were in Abu Dhabi, by the Corniche, an obviously humid place to run due to the effect of water. Today's race in Dubai was in-land, a tad bit on the cooler side and much less humid.

The slope of Ln Speed to Ln Distance, when corrected to the Riegel fatigue factor becomes 1.0995 with a 51.7% regression fit. This exponent predicts a 10K time of 00:51:00 from previous 5K time. Actual finish time however was 00:46:18.

Fig 3: Riegel exponent for race and pre-10K time trials executed in the months of August and September 2017

Which means nearly 5 minutes is unexplained by Riegel and that's inexcusable for my finishing time and placing. The poor linear fit of the slope is most likely due to insufficient data or variabilities in course, temperature and pacing strategy.

I will build this up as I accumulate more seasonal data for other distances and hopefully I can get a more composite picture of what the final fatigue factor is.

Well done to all runners today. See you soon.   -Ron

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