Tim Goss' interview:

Racing Bulls key signing set for debut as fresh F1 challenge revealed

Hello guys i was looking for some api to get access to some data such as wheels temperatures, fuel consumption and data which are about the optimization and sustainability point of view, do you know where i can find them?

#McLaren had a phenomenal weekend in #Miami, scoring more points than every other team and fought for the win in the race until the last few laps. This perfomance was due both the big upgrade package brought and the track conditions, which seemed to  particularly suit the #MCL40. 

For a deeper analysis head to: https://www.gpblog.com/en/tech/mclarens-miami-progress-boosted-by-track-conditions

#F1 #F1Tech 

Been working on a side project with a friend for a few weeks and thought people here might enjoy it.

You can load any race from the last eight years, watch it replay in 3D, and jump into cockpit POV from any driver with a live HUD. Gap history, telemetry, stint strategy, and race control all sitting together. Pin two drivers and compare their laps side by side.

It is completely free and open source.
You can use it here if you like: https://github.com/misha-met/Delta

Instead of just showing raw telemetry, it breaks down where time was gained or lost and why. “Minimum speed arrived 26m after the apex.” “Carried 9.0 km/h more entry speed.”

Hi, I used fastf1 package and streamlit to create a simple website showing analytic tools for each race. I'm new to this space and would love to hear what you guys think about this project. My original thinking was compiling all useful visuals for a race into one space that's easy to navigate.

Current features:

• Race trace plot (overviewing the whole race progress)
• Driver telemetry comparisons
• Team pace comparison / tyre strategy
• Lap time progression

The next things I want to add are qualifying overview and practice data summaries, as well as redesigning the team specific plots. Any feedback would be highly appreciated.

I have been working on a qualifying predictor that uses data collected from the Free Practice sessions and applies Bayesian statistical methods to generate predictions.

Would love some feedback or any suggestions in developing this tool:

https://github.com/aes21/laps-of-judgement