Visualizing Strava Data in Looker as preparation for the London to Brighton Bike Ride 2023 : Fundraising for Dementia UK

Most readers of this blog who know me personally are probably aware that I started cycling a few years ago, when I had some sabbatical time-off while waiting for the sale of my previous analytics consultancy to complete. Eight years later I thought it was about time to finally do the famous London to Brighton Bike Ride on June 18th 2023, raising money for Dementia UK.

My original driver for getting into cycling was to collect some real-world “big data” from the various bike computers, health trackers and other gadgets, put it into a Hadoop cluster and use it for a “quantified self” exercise, then combine and wrangle with other datasets to see if I could find any insights to improve my cycling performance.

Since then I’ve continued to record all my bike rides in Strava, bought a few new bikes and got a few years older and so I thought I’d be interesting to download my activities, segments and efforts data to-date from Strava again, put it all into BigQuery and use Looker to see how things have progressed since 2016.

Looking at distance cycled, 2020 was definitely my peak year primarily because, in the UK at least, lockdown meant we could go out and get exercise during the day for an hour but everything else was shut, which meant that more or less every day I got out on my bike at lunchtime, cycled for that hour and probably got the fittest I’ve been in years.

This year was, until I decided to do the London to Brighton, following the trend of the last two years where I’d began to cycle less, but the prospect of 90km and Ditchling Beacon at the end has meant that I’ve been getting out and training more recently.

The second chart above, if you know your bike brands, shows that I primarily ride road bikes and gravel bikes and, I’m afraid to say, get out far more in the spring and summer than when it’s cold, wet and famously in the UK, raining, as shown in the scatter chart with the new quadrants feature in Looker shown below.

The map chart above uses the new Google Maps integration in Looker and plots out the route of a typical three-day cycling trip I went on last year around Suffolk, where each circle represents a Strava segment effort (route cycled) coloured by the average power amount during the ride expressed in Watts, giving me a way to visualize how much energy I was placing into the pedals when the route got hillier or went off-road.

Another way to look at performance is to take a particular set of Strava segments, crowd-sourced, named popular cycling routes that you can then compare your time against your own previous rides, or others riding the same segment. Looking at my time to complete three segments local to me over the past few years my only excuse is that I’m eight years older now, but again with the prospect of the London to Brighton I’ve bucked the trend a bit this last couple of months and the numbers are starting to improve again.

So i’m doing the ride and raising money in memory of my mum who had Alzheimer’s disease before she passed away a few years ago; if you’d like to sponsor me, I’m using JustGiving to collect donations and also the gift aid part if you’re based in the UK.

All donations are gratefully received and Rittman Analytics will be matching, 100%, any donations that are raised. I’m looking forward to finally arriving at Brighton Pier around 10pm on Sunday 18th June, complaining about the final hill up to Ditching Beacon and wondering if there’ll be anyone still left at the finish line and whether the pubs are still open.

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