guinea pig: the results

guinea pig results – image © https://unsplash.com/@rvrmakes

Back in November last year I posted about how I had entered a research study as a guinea pig, to investigate the effects of strength training on running economy for endurance athletes. I’ve posted a few updates since then about how the programme went and how it finished up and ultimately influenced my choice of training regime for the current year. However, I haven’t yet posted about the resulting data that both confirmed how I was feeling and convinced me so much about the benefits of strength training.

Given my recent hospital stay and injury-enforced time off my feet, it seems like a good point to revisit this in some detail. Mark has kindly given me the thumbs up to publish the data. I’ve been waiting to write something about this for a long time now but couldn’t gather my thoughts fully. Opportunity knocks in the form of illness! I have broken the data down into three areas: mechanical, physiological, and umbrella. For each of the graphs shown, some data points in the series are missing. This is because the corresponding test did not reach this point or due to specific reasons that will be explained in each case. Each graph depicts pre and post series taken at the start and end of the trial respectively. Let’s see what the data says about this guinea pig.

mechanical

Data collected while performing treadmill-based tests reflected two mechanical measures. Ground Contact Time (GCT) is the first of these measures. This figure is the duration for which my feet were in contact with the treadmill belt every time they take a stride. The longer the GCT the less efficient you are. Prolonged impact with the ground results in lost energy. There are suggestions of what an ‘ideal’ GCT is; typically elite distance runners are less than 200ms.

guinea pig GCT showing improvement with intervention
guinea pig GCT showing improvement with intervention

As you can see from the chart above, I am a long way off the profile of an elite runner, about 100ms. However, the good news is that following intervention there is an observable improvement in my GCT. Roughly 1.3% more efficient at 14km/h. No data exists up to 13km/h as my feet don’t lift high enough at that speed to break the sensor’s beam. Also, the pre test concluded before I reached 15km/h and thus has no data at this point.

The second of the mechanical measurements is Stride Frequency. This is measured in steps per minute (spm) or essentially, how fast do my feet turnover while running. Again there are some heuristics that suggest an ‘ideal’ frequency, most sources focussing in on 180spm but ultimately it does depend on the runner.

searching for the magic 180spm but happy with the improvement
searching for the magic 180spm but happy with the improvement

There are those who suggest, no matter what speed you run at, your cadence should be the same. I don’t agree with those people because I’ve tried to achieve that and failed repeatedly. Again we see some improvements here following intervention. There is a significant gain in frequency at 14km/h and continued performance up to 15km/h when the test concluded. It’s not the magic 180 but I’m pretty happy with that score. Again the data points up to 13km/h and at 15km/h are missing for the reasons explained above.

physiological

Two more data sets to present. This time we look at the physiological measurements of heart rate and blood lactate. In some ways these should be controls and not benefit from intervention. Neither are measures of efficiency but in the context of my sustained training for the trial period, they stand to present some interesting observations.

no changes observed in cardio patterns as was expected
no changes observed in cardio patterns as was expected

First up is Heart Rate, measured in Beats per Minute (bpm). No surprises here at all. One small variance of 4bpm at 12km/h but everything else was almost identical throughout the speed range.

blood lactate: the lower the score, the longer you can run that pace
blood lactate: the lower the score, the longer you can run that pace

Next up is Blood Lactate, measured in Millimoles per Litre (mmol/l). This is test that I was most looking forward to seeing the results of, both at pre and post trial moments. I have never had my lactate threshold measured precisely before with blood tests (only inferred from VO2max testing) so now I truly was like a guinea pig in the lab. This should not really have changed much as a result of the trial but it did. Over the 12 weeks I gained roughly 1km/h in my pace at lactate threshold (accepted as being ~4mmol/l). That’s significant.

This score means that my theoretical limit is now just over 14km/h before my body can’t cope with the lactate levels. Immediately my mind runs away on me: “14.x km/h multiplied by 3 = >42km I can run a sub-3 marathon!” Sadly, we all know that it doesn’t exactly scale that way. However, it does mean that the dream 3:20 I seek is very much within my reach. The problem now is why haven’t I already done it?

umbrella

I decided to call this collection of data the ‘umbrella’. It’s a collection of summary measurements that indicate general aspects of my profile rather than specific details. First up is my interpreted Running Economy.

guinea pig economy: the lower the value, the more economical you run and that's good
the lower the value, the more economical you run and that’s good

My results for Running Economy are interesting. Not just because the intervention has shown significant improvement over the 12 weeks but because of the pattern I create. I confess, I don’t know if this is a normal trendline. However, in both tests I exhibited the same behaviour of being more economical at 13km/h than I was at 12km/h. In both cases the increment to 14km/h causes a big drop in my economy. Curiously, in the post test I reached 15km/h and my economy improved, despite being under much more strain. I appear to suffer well, if not for very long.

Next up is the test that so many runners obsess over, the VO2max test. I’ve taken a few of these already outside of this trial at different stages of training with scores ranging from 60.9 to 62.5 at the upper end. It was a dent to my ego to see my scores being returned this time around at 55.6 (pre) and 56.1 (post). Runners are naturally competitive no matter how fast we are. Seeing a score drop by a few numbers, despite it not really meaning anything in terms of performance (only theoretical capacity to perform), is like giving us a kick in the pants. It’s gathering greater acceptance though that this result is little more than an indicator in isolation. If you score well in VO2max, unless you’re Eliud Kipchoge, you’ll have no trouble finding another runner who’s faster than you with a lower score.

 prepost
VO2max55.656.1
vVO2max16.517.0

a kick in the pants compared to my previous test scores or is it?

Also observed during this process was my vVO2max value. While VO2max is the amount of oxygen you can process per minute, per kilogram of body mass the vVO2max score is the speed at which your body is at maximal oxygen uptake before the anaerobic contribution starts to aid your velocity. Like the Heart Rate and Blood Lactate tests these scores should be relatively controlled and not show great deviation as a result of intervention. Shown above, this appears to be as expected with only marginal positive increases for both following the trial period.

conclusions

One should always be a guinea pig when the opportunity presents. So long as the opportunity is a safe one that allows you to discover something new about yourself. This entire trial was a complete eye-opener to me. For so many years I’ve been that typical runner, faced with the choice of gym or run and always choosing to run. It is the wrong choice – I have no doubt whatsoever in my mind any longer. Fears of gaining mass, sacrificing miles in favour of weight sessions, etc, etc are all unfounded in my experience. Obviously there are exceptions, thresholds, other things to consider here but for a runner like me, fear alone is a very ill-informed decision maker.

At the end of the trial I was in great shape (not a picturesque gym Adonis but healthy, running well, recovering quickly). I weighed in at roughly a kilo more at the end than I did at the start and Christmas holidays were in the middle of the trial too. I’m taking that as a weight loss scenario! The data doesn’t lie though and that is the most compelling argument here. We’re talking about fractions of a second improvement in efficiency for each stride but that all adds up. The strength gained from the weight sessions means that I run more connected and less prone to injury. I also run more powerfully, getting more from each stride. Over the course of a marathon distance that all helps to shave time off the distance between me and my goal. A transformative experience.

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