Playing with StatsHunters

Playing with StatsHunters

Byrichard

Today I saw a link to Stats Hunters on the Google App so I clicked through on a laptop, once I was sitting at a computer. This is an app that looks at Strava data and gives you a summary of how many activities you’ve done as well as how far you have travelled. 


According to the data this Strava add on can access I have 2753 logged activities with a total distance of 25,l404 kilometres. November 2018 was my best month with 898 kilometres travelled. I think this was kilometres ridden on Zwift if I remember correctly. 


My longest ride was La Visit Horlogère where I cycled from around Nyon to Le Post, around the Lac de Joux and back down via St Cergue. 


The biggest vertical gain in a day of hiking was the EuropaWeg part 1 where I gained 1803.2m of altitude. 


It’s fun to see the distance per year graph because my best year was 2775km of distance travelled. For context I had 2775 in 2019, 2487 in 2020, 2267 in 2021 and 2499km in 2022. The pandemic has really affected how far I travel by bike and by foot, despite hardly driving to do any of these activities.  We should not ignore how much we can do, without touching a car. 


You can see a breakdown per week for the last year if you want to., 


The general stats are interesting. My average distance per activity is 9.23 kilometres. My average speed is 9.29 km/h. My maximum speed is wrong, because that’s when I played with a GPS watch in a plane. 


The website gives a lot more information than I am exploring in this blog post. It’s interesting to see the hour stats. This tells you at what times of the day you are most active. 


In the type statistics you can select from moving time, distance and other factors. My walking habit accounts for 36.8 percent of sports, with hiking accountiing for 28 percent. That is 64.8 percent of my sporting time. Bike rides account for 20 percent and running for 4 percent. 


According to some stats I have done 2639 activities of 0-35km, 107 between 35-70km and 7 between 70-105km. The main reason for this is the mountainous nature of the landscape. If it was possible to do longer distances without too much climbing then I would. 


And finally


Although I have done no group activities for years now, my sporting habit endures, and has thrived. I have done so much more now that I don’t wait for the weekend to do things with others. Solitude is not a reason to do nothing. It is a reason to do more. I like the data trends that this app shows. 

Day Nineteen of ORCA in Switzerland – TGIF
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Day Nineteen of ORCA in Switzerland – TGIF

Byrichard

Do you have that TGIF feeling like no one else does? In theory today is the day when people are happy, knowing that the weekend is about to start and they can do the things they love for the next two days. In this context though, that is unlikely. We’re meant to stay home.


This weekend is going to be extra special because the temperature is meant to reach 20°c, i.e. summer temperatures and so people will go out like ants on an applecore by the side of the road. If ever a weekend was likely to see a boom of cases next Friday it’s this one. According to the Swiss government people are good at following the rules but I still see examples of inconsiderate behaviour, both by young and not so young people.


Google has come up with the Google COVID-19 Mobility report. You may already be familiar with the discussion centered around how governments are asking telecom operators to provide them with mobile phone information about where and whether people are gathering.


Telecom operators, and application makers already have some information of where we are, where we’re gathering, how often we’re commuting and more. Google is making that data available in reports by countries. As I was curious to see this data I looked up Switzerland and then Geneva and Vaud.



The beauty of this data is that it shows the lag between the time people were told to stay home and when they did. It’s also to see where the peaks for parks, pharmacies and transit were. Last week we read about how the CFF are reducing the number of trains running. Today I was listening to the Don’t Touch Your Face episode discussing “The Airline Industry crashes“.



It’s interesting to think about transportation. Geneva is a city, and for a walker like me everything is within walking distance, if I have enough time. Vaud is larger so people are more used to using the car. This may explain why Vaud has a 68 percent drop in public transport use whereas Geneva has an 84 percent drop. Retail and recreation dropped by almost the same amount.



It’s interesting to compare Greater London with Geneva and Vaud because we see that the curves for transit and retail are more gradual, more rounded. The graphs suggest that Londoners started self-isolating of their own accord, and so when the order was given by the government to do so there was no great change. Of course the timescale is different so this might explain the softer change.


To some degree this pandemic is interesting because of all the data we can collect. Between blogs, instagram feeds, tweets, Facebook updates, mobile phone movements and more we really get a granular look at how the pandemic has affected people’s movements and habits.


During the post-pandemic discussions, studies and reports there will be millions of data points for people to study. Data analysts are going to have fun. So are big-data historians. This is a unique opportunity to see what worked, how long it took to be effective and more.


It’s a shame that Facebook and Twitter are so filled with marketers and PR professionals, rather than conversationalists. We’re going to have to see what remains of individual interactions later.


Do you have any interesting graphs or metrics to share?

StravistiX for Strava

StravistiX for Strava

Byrichard

StravistiX for Strava

Stravistix for strava is a Chrome plugin. It allows you to analyse the data from your ride in more detail and with more graphs. In the detailed view you can see heart rate information, speed, power, grade, elevation and  ascent speed. It allows you to see each metric in more depth.

It allows you to look at your statistics in detail. You can see what percentage of the ride was flat, uphill or downhill. You can see how fast you were climbing and how your speed varies.

This breadth of data is fun to play with. It allows you to see whether you do spend as much time as you thought climbing. It also allows you to see how much of your time was spent static or moving.

There is a weather module for wind, temperature, clouds and humidity. This is a nice way of checking whether the wind is favourable to the ride you are thinking of doing that day.

What I would like to see next is a log of the weather and especially wind during the ride. It would like to see ground speed in contrast to wind speed. This data should be relatively easy to acquire.

Plugins are great because they allow you to do more with the data that you or other people generate. They allow weekend and professional riders to analyse how they are progressing. It also allows riders to compare themselves with others.