Does a cold affect athletic performance?

I’ve always wondered if having a cold messed up your performance. Well, the final of the NZ MTB Cup last weekend in Dunedin gave me a chance to see…

Now, I know a simple google search would yield decent answers such as this…

http://www.dcrainmaker.com/2008/10/effects-of-cold-on-athletic-performance.html

…But its always nice to see for yourself.

I noticed myself coming down with a headache and sore throat on Friday morning. by saturday race day it was pretty much all the usual cold symptoms headache, stuffy nose, sore throat etc. I raced anyway, and it was a good opportunity to collect data in particular heart rate and power, as I have a Stages power meter on my MTB.

Here’s what I found…

Power Curve

Here’s the curves for all of the Cup races this year.

Screen Shot 2016-03-01 at 4.34.22 pm

The most noticeable thing is the difference in the 20sec – 1min approx outputs. That’s typically representative of quite anaerobic respiration, and if you take a sample from the middle of that, where the difference (40 sec) is most pronounced theres a difference of 126 watts, or about 19% YIKES

Thats not necessarily the whole story of course, because course profile could be a factor. However, given the pattern of data from the other 3 races its good evidence for a +’ I’ve hypothesis.

The other thing you can look at is heart rate data. Check it out:

Here’s some data from the week before at Wanaka (healthy)

Screen Shot 2016-03-01 at 4.42.30 pm

…and from Dunedin (sick)

Screen Shot 2016-03-01 at 4.43.41 pm

…Thats a big variance, with much lower HR. Max HR in healthy mode, for the 3 ‘healthy’ races was 170-175 BPM or so. When sick, it only got to 166 max.

It’s as if there is a rev limiter in place when sick, that gives you a lower redline. Now, thats for me, and I know other people notice an increase in HR when sick, but I’ve always found I go the other way with HR.

 

Another thing I like to use to analyse performance data for my clients is a feature in Cycling Analytics, where you can refine efforts. You can select out efforts above X watts for Y time. So, you can review data in terms of repeatability as well as just best efforts, which is what a power curve represents.

For the Dunedin (sick) race, I only managed 4 efforts of 450+W for 40sec or greater.

Screen Shot 2016-03-01 at 4.58.44 pm

At Wanaka (healthy) I managed 6 efforts of 450+W for 40sec or greater.

Screen Shot 2016-03-01 at 5.01.26 pm

Like any performance analysis, you need to look at more than just one thing, and there is 3 converging sets of data here that I reckon are pretty compelling for a positive correlation.

So there you go – does a cold mess up your ride? Yep, it does.

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Dunedin Round 4. I even look sicker. Blleerrgghhhhhhhh…Photo by John Cosgrove

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Wanaka Round 3. Photos by BarkingCat Photography

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