
Visualise your daily blood sugar as a Formula 1 race.
Author: Richard Hall
LinkedIn
EarthTunnelling.com
Glucose Grand Prix is a quirky project I put together after finding a neat way to extract my blood sugar data from Glooko. I wanted to create my own charts, but the data downloads only allowed 90 days at a time and came as multiple CSV files bundled in a ZIP. It was not exactly user-friendly.
With a bit of hacking around, I discovered how to use their session-authenticated browser APIs. That meant I could now grab all my data (or just a few hoursâ worth) in JSON format using Chromeâs DevTools. Perfect.
At first, I thought it would be a great trick to share with other Glooko users. Then I remembered not everyone is quite as obsessed with data as I am. That thought completely sidetracked me. I started wondering what someone else might actually do with this data.
Iâd recently seen stories about a diabetic Barbie and a diabetic Marvel superhero. Both were created for kids, which is a lovely idea. But not all kids relate to dolls or superheroes. There are loads of kids (and adults) who are really into F1.
Thatâs when it hit me. What if I could use glucose data to âfuelâ Formula 1 cars? Just like that, the idea of Glucose Grand Prix was born. A webpage that turns your blood sugar readings into something a bit different. A race car tearing around a virtual F1 track.
Each dayâs data becomes a lap. Each data point becomes a step forward. Your glucose control becomes the determining factor in how smoothly your car makes it around the track. The better your day, the faster and cleaner the lap.
This project is a proof of concept. Itâll be open to anyone who wants to try it or enhance it.
This is a browser-based web app (no install needed!) that:
What it doesnât do:
This guide shows how to extract your own Glooko data using the browserâs built-in developer tools.
No scripts. No extensions. Just you, Chrome, and a little patience. Once you have followed this step, you can use the data you have collected to run the Glucose Grand Prix.
â ď¸ Note: This method uses the same session your browser is already logged into.
It is secure and personal. The data is never shared unless you choose to download or use it elsewhere.
Open Glooko and log in as usual. You should land on the Summary page.

Click on the Graphs tab to load your glucose history.

Cmd + Option + I (Mac) / Ctrl + Shift + I (Windows).
In the DevTools panel, click the Network tab.

Reload the page (Cmd + R or F5) to capture the network traffic.
In the filter/search bar, type /data?patients=
This narrows the requests down to the one you want.

Youâll see one, two, possibly many results. Click on each one and inspect the Response tab.
The one that contains JSON data is the one you want.

Go to the Headers tab of that request and copy the Request URL.

Paste the URL into a text editor. Itâs long, so this will help you edit it cleanly.
Look for a section like this:
startDate=2025-07-07T00:00:00.000Z&endDate=2025-07-20T23:59:59.999Z

Modify the startDate and endDate to match the time range you want.
For example, changing the startDate year from 2025 to 2023 allows us to pull an extra two yearsâ worth of data:
startDate=2023-07-07T00:00:00.000Z&endDate=2025-07-20T23:59:59.999Z

Now, paste the edited URL into your browserâs address bar, in a tab where youâre still logged into Glooko.
Hit enter.

Wait a moment. If youâre requesting a lot of data (like 2 years), it may take some time.
When it loads, youâll see a screen filled with raw JSON text.
Cmd + A, then Cmd + C) and paste it into your text editor.

.json extension (e.g. glooko_data.json).

đ Done! Youâve now extracted your data. This file can now be used in your own visualisations, backups, or with projects like Glucose Grand Prix.
Download and/or open the HTML file
Download the webpage or run it from GitHub and double click on it to open it in a browser.

Prepare your data
Download your data from Glooko, paste the data into a file, give the file a name with the suffix â.jsonâ, then click âLoad JSONâ to load it. Instructions shown here.
Or you can try this out using some of my data I have uploaded here in a file called glucose.json.

Select your drivers
Select the drivers you wish to include in this race using the checkbox selection panel.

Select the track
Select the track you wish to race on. Click on the dropdown, make your selection and youâll see the track appear in the map.

Start the race
Click on the Start Race button.

Speed up or slow down the race pace
Use the Speed Slider to increase or decrease the time. These races have been set up to similate the fastest lap times as closely as possible for a small web app, so you may want to speed things up a bit.

The leaderboard
This shows the driver positions, the lap numbers, the âglucose dayâ that the lap corresponds to, the computed âpowerâ for that moment and the actual âglucoseâ reading that the power was calculated from.

The fastest laps table
This table shows the top 10 fastest laps for the race. It is constantly updated throughout the race.

Fastest lap details
You can drill into the detail of any âfastest lapâ by clicking on the âView JSONâ linkâŚ
âŚand seeing this detail in JSON format appear in a popup. This data can be downloaded.

getPerformance())This project is licensed under the MIT License. You can use, modify, and distribute it freely as long as attribution is preserved.
Glucose Grand Prix isnât a replacement for traditional analysis. Itâs a just a fun alternative way to look at your sugar data. This is just a proof of concept and could be enhanced to add many different features.
If you build on it, Iâd love to see what you create. Feel free to fork, remix, or race your own way.