F1 Data Animations

Tl;DR

The season has just started: How much slower cars are?

How about looking at some data?

Intro

After talking about geo recently

creating HUDs overlays for my action cam videos…

Today, its about F1.

But not the ML f1 score, just…formula 1.

Particularly, F1 data.

F1 Animated Stories

According to people risking their money in Polymarket: the championship is leaning towards Ferrari and Mercedes.

But how about digging to car telemetry and lap times?

#sudo apt install gh
gh auth login
#gh repo create eda-f1 --private --source=. --remote=origin --push
    
git init && git add . && git commit -m "Initial commit: simple eda-f1" && gh repo create eda-f1 --private --source=. --remote=origin --push

Lets build some data stories that can potentially be more interesting than races itself.

The Data

• https://github.com/IAmTomShaw/f1-race-replay
  • https://github.com/JAlcocerT/f1-race-replay

Uses fastf1 package to source the data via API

The cool telemetry data is from 2018+, but there is lap timing from 1950 :

uv init

uv add -r requirements.txt
uv run check_sessions.py

uv run extract_laps.py
uv run plot_laps.py

uv run extract_telemetry.py
uv run plot_telemetry.py

The Look and Feel

1. With the BRD -> Development plan approach

2. This enhanced prompt to get amazing UIs

3. Plus, these CRO tricks

See https://github.com/petervdpas/goop2 Goop² is an ephemeral, peer-to-peer system for personal web spaces.

Conclusions

Was there any doubt that new regulations make the ones learning faster be way ahead of the rest?

Ops

I mean, Im came to this post after the geospatial eda and some oa5 x hud…

This is what reality shows it happens after an aggresive change of rules:

uv run f1_q3_plots.py

Was there any surprise that keeping a rule long enough is what makes teams be closer to each other?

Diminishing returns….anyone?

uv run f1_q3_short.py

AUS 2025 Q3 P1 to P10 gap ~1s (+0.835s)

And this is not a debate whether making drivers race with less dispair cars is good or not.

Neither if F1 should be similar to e-f1…or just going close to the limit each lap.

About Unfolding Data

It was about time to make some use of this fantastic api.

Because, in case you havent realize yet: shipping is becoming more and more about asking questions

Do you have questions?

Consulting Services

Consulting - Tier of Service

DIY via ebooks

Distilled knowledge via web/ooks to enable you to create

I had some, and created these:

Also, thinking about unifying these would be next.

Because IoTrack and Unfolding data need some love and attention.

And yep: making those animated stories of points per seasons is possible thanks to:

uv run extract_results.py #race classification
#uv run extract_qualifying.py #saturday qualifying results