The Numbers Game
How to interpret your running data so that it helps, not hinders
Getting the most from your running data
WE LOVE TO MEASURE AND QUANTIFY – it makes us feel in control. Powerful wearable devices have given runners access to a huge range of data. We can capture information on our performance, recovery and general health, and even use AI to tailor our planning. This gives today’s runner a phenomenal digital toolkit with which to optimise all areas of performance. However, as a runner, you should also be aware of the limitations of data and when it’s more important to read between the numbers on your wrist. Here are my pros and cons of data, so you know when to take note of your GPS or app, and when it’s better to listen to your body.
Data-driven: THE PROS
• Clear feedback Data provides some of the evidence you need to find out if you are heading in the right direction. You can track if your paces are improving for similar heart rates, if you are getting faster on similar routes or races, and if you are recovering better from run to run.
• Know yourself Data such as heart-rate variability (HRV) and sleep tracking can give you a glimpse into how your body is recovering. This data can help you to adapt your training if the numbers suggest you are struggling to recover.
• Build focus Knowing the pace, power or heart rate required for a session can help you focus. You can even download workouts and routes onto your watch to talk you through every step of a workout. Data on cadence or ground contact time can help you focus on the process of running rather than purely on the outcome of each run.
• Quantify ‘feel’ Runners often struggle with ‘perceived effort’. Some think they are running ‘easy’ while barely able to speak; others believe they are at full pelt while being able to chat.
Heart rate can provide an objective measure to help guide your effort.
• Improve discipline Data such as heart rate and pace can help give each run a purpose. Many runners tend to start off too hard in races or push their easy, steady or threshold runs too fast and, as a result, often struggle in their fastest sessions.
• Context If a session doesn’t go to plan and you can refer back to your HRV, your sleep data or training load, you might be better able to get it into perspective. If a session goes to plan, this wider data might give you ideas on things you can repeat in future to achieve a similar result.
HEART RATE CAN PROVIDE AN OBJECTIVE MEASURE TO HELP GUIDE YOUR EFFORT
Paralysis by analysis? THE CONS
• Progression isn’t linear Relying too much on data can demoralise runners who expect their training to immediately show ‘in the numbers’. Over-analysis can be psychologically damaging. It takes time before training is reflected in the stats.
• Losing the essence For many of us, running is a meditative process and an opportunity to have a break from a world that’s flooded with measurement and technology. Ask yourself why you run and why you exercise. If it’s primarily for headspace or stress relief, think about whether you need data in the long run.
• External distraction: Research shows pacing by Rate of Perceived Exertion (RPE) can be a great way to structure your training and racing. Relying too much on data can make it harder for you to listen to the sensory feedback your body gives you.
• ‘Painting by numbers’ X input + X input = success. We love to think in this mechanistic way and structuring all your sessions by hard data can encourage this notion. In many ways, running is a simple sport, but our lives are far from simple. Some days, an eight-minute mile feels comfortable; on other days, it’s a real challenge – data can’t always predict this.
• Biophysical bias We tend to overvalue what we can measure, but just because we can’t measure something doesn’t mean it’s not critical to performance. The harder-to-measure psychosocial components of performance (eg mood and stress levels) can often be ignored in favour of pace, power and heart-rate zones.
• The judge on your wrist For many, the constant judgment coming from their wrist is an unhelpful pressure. Training sessions are there to get you fit, not judge your fitness.
• Validity and reliability Any set of data is only as good as the system used to collect it. And even when the technology is reliable, user error can undermine data accuracy – the most common example is positioning your heart-rate monitor incorrectly.
• Chasing the numbers Constantly staring at your watch in training can lead to poor decision-making. If you are hyper-aware of your GPS or your local Strava segment, do you have the self-discipline on your recovery run to not push harder than you should?
• Machine thinking You’re a human being. Your emotions, instincts and psychology are key to your sport – don’t beat this out of yourself by overprescribing every run. Sometimes it’s good to simply explore. No app, watch, lab test or algorithm is more important than the conversation you have with yourself.