Strava Guide: Features to Take Your Training to The Next Level

Multidesporto

, by Katherine Turner

Photography by: Strava

Strava not only lets you track your activities, connect with the community, and explore new places, it also features a wealth of tools that allow you to analyze your training - and help you to progress. In the latest installment of the Strava Guide series, we take a look at four features that can help take your training to the next level.

Do you ever feel like you couldn’t possibly go for a run without a GPS watch? Or couldn’t bear to ride without having a power file to analyze over a post-ride coffee? In today’s world, it can feel like we’re increasingly having our training dictated by technology – from heart rate to lactate, power to pace, there’s more data available than ever before. So, for the third installment in the Strava Coach series, we’re diving into how Strava can help you utilize this technology to benefit your training, without it becoming an obsession.

Did you know that the first watch with integrated GPS technology wasn’t released until 1999? And it wasn’t until 2003 that the first GPS watch targeted specifically to runners hit the market. The same year that Paula Radcliffe ran her legendary 2:15:25 world-record performance at the London Marathon. 

RELATED: Strava Guide: Four Features to Help Level Up Your Training

The first cycling power meter dates back further – in 1987 Ulrich Schoberer patented the SRM PowerMeter. Three-times Tour de France winner Greg LeMonde was an early adopter and slowly over the next decade or so, the technology filtered down to amateur cyclists. 

It’s clear that two things are true: One, it’s possible to be very very good without technology. We only have to look at legends like Eddie Mercx and Ingrid Kristiansen for evidence of that. Two, once these technologies became available, they quickly started to dominate which suggests, they’re probably pretty helpful. 

Photography by: Strava

So, what does that mean for us, today’s athletes? It’s complicated. But in this article, I’m going to try and make it simple. We’re going to take a look at four Strava features, that rely on data from devices, to show how you can utilize them to train smarter, and when to let the data go. 

Workout Analysis 

We’re going to start with one of my personal favorite Strava features: Workout Analysis. If you’re a runner, you’re probably used to running most of your runs at a consistent effort. But sometimes, if you want to become a faster runner, you need to stress your body in new ways, to run quicker than you're used to. Do this, and you will find that those faster paces gradually feel easier. 

RELATED: Strava Guide: How to Get Started on Strava

A great starting point for an interval workout is to practice 1 minute of harder running followed by 1 minute of jogging a few times, with an easy jog at the start and finish. 

Once you’ve uploaded the workout to Strava, make sure to change the “Type of Run” to a “Workout” so Strava knows you’re interested in the splits and generates the Workout Analysis data view. Workout Analysis breaks down your workout so you can see each split individually, and then it color codes the intervals so you’re easily able to see trends in your pace at a glance. Darker colors represent the times you were moving at your fastest, and the lighter colors represent the slowest parts of your workout, most likely your recovery jog between intervals. 

A sample Workout Analysis graph

Did you start too fast? Or not fast enough? Were you inconsistent or did you run the same pace like clockwork? Workout analysis can help you understand the effort you just put in and, over time, you should see your paces speed up. 

All this information can be incredibly helpful, but it’s important to also remember that the splits only tell half of the story. If you’re hitting your goal pace but the effort feels unsustainable, you might be better backing off than continuing to push beyond the assigned effort level. Think of splits as just another data point, alongside effort and, one we’ll come to later, heart rate. 

Power Zones

In last week’s article, we took a look at Pace Zones in running. Today, we’re looking at how this feature can be used by cyclists. Power Zones can help you better understand the intensity of your training which ultimately can help you avoid burnout or a plateau in your progression.

In order to set accurate and personalized Power Zones, you’ll need to know your Functional Threshold Power, or FTP. Check out this article by cycling coach Nikalas Cook for all the details on how to establish your FTP. 

RELATED: Power Meter Guide: The Watts, Whys and Hows of Functional Threshold Power (FTP)

Sample Power Zones from a Tour de France rider.

Once you know what yours is, you’ll need to add it to your profile so Strava can use that information to set your power zones. On the app, go to the “You” tab and click on your profile photo. Tap the “Edit” button and scroll down to “Functional Threshold Power”. 

Now, that’s done, you’ll be able to start using Power Zones to train smarter. Power Zone charts take each second of power from your ride and distribute it by training zone based on your FTP. Simply put, you’ll be able to see what percentage of your ride you’re spending at different effort levels.  

RELATED: Power Meter Guide: Know your Training Zones & How They Should Feel

But how can you practically apply that to your training to get faster? Give this article a read to learn more about what the different zones mean and how you might want to use them in your training. 

Heart Rate Zones

Heart Rate Zones are similar to Power Zones in that they help you understand your effort levels. While Power Zones are simply measuring your output, Heart Rate Zones measure how hard your body is working. That’ll be influenced by fatigue, emotional stress, wind, illness, temperature and so much more. And this is where it’s important to learn to strike a balance between all the competing data points that you might be tracking. 

Sometimes your goal might be to hit a specific power or pace. On those days, heart rate will help you understand your fitness – the effort it required to go that pace. Other days, your goal might be to recover. On those days, pace and power are secondary to heart rate – it’s your heart rate that will tell you whether you’re going at the right pace to recover. And, some days you might simply want to have fun and enjoy the feeling of running or riding – on those days, neither power, pace or heart rate will tell you if you had a good run or ride. Only your heart and head will know. 

RELATED: Understanding Heart Rate Zones and How They Impact Your Training

We recently released a three-part series on heart rate to truly help you understand how you can get the most out of tracking it. Check it out here.

Fitness and Freshness

The last feature you should check out if you want to make the most of all the data technology provides is Fitness and Freshness. Simply put, this plots your fitness – how much training you’ve accumulated – against your fatigue – how tired all that training is making you. 

Fitness - fatigue = form. How ready are you to perform at your best? 

If you want to know more about the data that is behind each metric, you can learn more here

IN DEPTH: How to Use Strava’s Fitness & Freshness Tool

You can think of Fitness and Freshness as the best training spreadsheet you’ve ever made – rather than having to make guesses at when you might need to back off training to get the benefits of a big block, or how long a taper you’ll need before you’re ready to race, you can confidently adjust your training and track the impact of those changes. 

Rather than encouraging you to train more, the data from your technology should be a tool to train smarter. Pushing excessively in training to increase fitness will quickly see your fatigue skyrocketing and your form plummeting, reminding you to plan some rest days. When you taper for an event you might see your fitness declining, but that form line will be climbing as fatigue decreases, so you can trust that the taper is doing its job. 

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