Written By Katie Hickling
Katie is an amateur ultra runner (emphasis on the word amateur -- her words, not ours!) who, when not running, tries to fit in a career in financial services technology. Other interests are also known to include dogs, cricket, and writing Ultra X articles.
The acceleration of technological innovation over the past few years has enabled data to become readily accessible at a low-cost. Unsurprisingly, this has also filtered through to amateur and grass roots levels of the sport with the explosion of commercial companies selling products to capture and track training data. Garmin Connect, Training Peaks, Suunto Movescount, and perhaps the most famous of them all, Strava.
To start with, the caveat: that generally such inventions can be considered a good thing. The ability to record and track sessions and receive output data such as pace, heart rate, cadence etc helps us to train more effectively, improve performance and become more informed as a runner of the impact that training sessions are having on our bodies – data previously only accessible to elite athletes or those willing to fork out a lot of money for it. I remember back to 2014-2015 during my university triathlon days, testing and sports science technology was only available to those on elite scholarship programmes. The rest of us had to make do with conducting sessions using RPE and timing off Casio F91W’s (Google it if you want to see what sports watches looked like back in the day).
Apps with a social media angle such as Strava also offer a valuable connection to others in the running community, providing inspiration and encouragement and, recently, enabling virtual challenges to take place in the absence of real-life events, which have provided an outlet and source of motivation to many during testing times. Such is the popularity of these products that it is very rare indeed to find a runner who doesn’t use at least one of them, but do these tools add value, or are they just a smoke screen that distracts us from what actually matters when it comes to following the basic training principles that enable success?
Have we lost sight of what the purpose of training is?
Endurance sports such as ultra running follow relatively straightforward training principles. However, with gadgets that now allow us to analyse every minute detail of an easy run this can make it easier to get distracted from the purpose of specific sessions and lose sense of the bigger picture of what training is for… helping us achieve a personal goal or race performance at the end. Psychologically, it can be harder to execute sessions as intended when there is concern about the fact this week’s easy run was 15 secs per mile slower or what everyone on Strava is going to think about it.
From personal experience I know of several athletes who have purposefully stopped uploading recovery runs onto Strava due to worry about others judging the slow pace. I have also in the past deleted track sessions after I was unable to hit similar speeds as in previous sessions. More runners have done this than they probably care to admit in some form or another. For example, titling runs as “strong headwind” or “hot” to explain why the output metrics might be slightly off than usual. Ultimately the question to be asked is do we train for ourselves and/or the purpose of performance in a race goal that is important to us or to produce outcome “vanity stats” to impress others?
Judging performance based on training data rather than race results
An interesting point is the difference between the process of training and “race day” and the ability of training data to predict race results. “Race day” is arguably a different beast to training, as there is a lot less scope to control factors such as weather, time of day the event occurs etc. Also, in the pressure of a race day environment it can be very easy to do stupid things that wouldn’t otherwise happen in a controlled training scenario. However, the deluge of training data available has created a mindset where individuals can judge and predict race outcomes by comparing training data shared on apps such as Strava.
Picture this 10 years ago: a group of runners turn up at a local race, on the start line they would have limited knowledge of what training their competitors had put in the weeks beforehand and, afterwards, if they wished, they go away with an idea of how they compare to each other based on the race results. Nowadays, the whole training process up to what you had to eat the night before can be shared for all to see on social media.
There are two fundamental flaws with taking training data on Strava as the gospel for race day performance. Firstly, as was mentioned previously, “race day” is an entirely different environment to training and there is no guarantee that training metrics can be reproduced in race conditions. Secondly, metrics on apps such as Strava can be easily manipulated to paint a picture that isn’t necessarily the true version of reality.
In extreme examples, there are a group of people for whom it can be argued Strava has almost replaced racing. By manipulating training data they create this persona of themselves and their performance levels that they feel they need to live up to. Therefore, why go through the pressure of a race environment when you can just train and produce stats in exchange for kudos. Although, ultimately such a scenario isn’t good for a long-term, healthy relationship with the sport.
‘If it’s not on Strava then it didn’t happen’
Just because we have the capability to measure and record every run we do, does that mean we should? Using a GPS watch can be helpful when trying to work out pacing for a tempo or interval session but there is something to be said about every so often leaving the tech behind and running for enjoyment using perceived effort.
On a final note, adding data does not necessarily guarantee quality. For example, take two athletes training for a mountain ultra marathon. Athlete A does a long run session of several hours over hilly terrain with extended periods of time spent walking and stopping to refuel. He doesn’t record output variables such as pace per km, preferring instead to match his effort levels to the terrain. Athlete B choses instead to do a two hour long run on road with structured sections spent at three different intensities. His stats look very impressive when posted to Strava and he gets a lot of likes. However, compared to Athlete A’s so called unstructured session, it is a lot less likely to prepare him adequately for the demands of the event.
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