Formula Data Analysis – Telegram
Formula Data Analysis
3.41K subscribers
1.42K photos
10 videos
3 files
918 links
All the analyses of the world’s most famous page on Formula 1 telemetry: join NOW to understand F1 better!🏎📈
Download Telegram
Ferrari in Monza👀

'18: 346km/h, 1.19.119 (Pole)
⬇️Dragster
'19: 354km/h, 1.19.307 (Pole)
⬇️Nerfed Engine
'20: 341km/h, 1.20.273 (P13)
⬇️Loaded Wing
'21: 335km/h, 1.20.462 (P7)
⬇️Ground Effect
'22: 343km/h, 1.20.161 (Pole)
⬇️Lower Drag
'23: 350km/h, 1.20.294 (Pole)
5👍4😁1
QUALIFYING GAPS👀

The field got much closer than in 2022!
Only🔴Ferrari got farther from pole (Still, not far off🔵RB)

🟢Aston was the most improved team. Still, 🟠McL matched it despite a terrible start

Mercedes: 3rd fastest

What's your 2024 prediction?🤔
3👍3
Formula Data Analysis
QUALIFYING GAPS👀 The field got much closer than in 2022! Only🔴Ferrari got farther from pole (Still, not far off🔵RB) 🟢Aston was the most improved team. Still, 🟠McL matched it despite a terrible start Mercedes: 3rd fastest What's your 2024 prediction?🤔
2022 for comparison

The slowest team (Williams) was the same as in 2023, but it got significantly closer to the top: from a ~2.1s gap to a ~1.3s one!

I expect the team to be even closer next year! (as unsuccessful design choices are dropped and performance gain rate decreases).

The single fastest lap of the team was considered for each session.
2👍1
Weekly reminder that you can JOIN the CHAT channel to discuss my analyses OUTSIDE of the 'comments'!
👇Use this link👇
https://news.1rj.ru/str/FDataAnCHAT
📊 QUALIFYING PERFORMANCE
- Races 1-11: Aston was as quick as Merc, and Alpine quicker than McL.
- Races 12-22: Ferrari was quickest! Alpine was fighting with Aston.

DEVELOPMENT
📈 Improved: AT -0.52%, McL -0.49%, Williams -0.39.
📉 Got worse: Aston +0.52%, RB +0.23%, Alpine +0.11%.

Values are relative to each team’s quicker driver for each session.
👍31🔥1
QUALIFYING PERFORMANCE PER GP

🟠McLaren's improvement is clear: from 1-2% off the best to pole in Brazil!

🟢Aston, instead, got progressively less competitive

First 9 dry sessions: 7 RB, 1 Ferrari, 1 Merc
Last 9: 5 Ferrari, 3 RB, 1 McL.

Mercedes had stable performance.
👍43
DISTRIBUTION OF QUALI PERFORMANCE

On average:
🔵RB >🔴Ferrari >🟢Merc >🟢Aston =🟠McL

Ferrari was very consistent: they were never farther than 0.8% off pole!👌

Excluding Singapore, RB was the most consistent.

🟡Yellow Dots = Abu Dhabi.

McL, Haas, AT and Williams were quick!

Values are relative to each team’s quickest lap in the session.

Ferrari’s consistency in qualifying mirrors their inconsistency in the races!
👍51🔥1
This media is not supported in your browser
VIEW IN TELEGRAM
2023 has been amazing:

> I've been to the Monaco GP and to Rahal Letterman Lanigan Racing (@RLLracing), thanks to two wonderful fans!
> Many new types of analyses
> Expanded to Threads and Telegram
> Collab with JMP Software (@JMP_software)


2024 will start with a BIG announcement! 🤫👀

Opening my page (almost two years ago) was one of the best decisions of my life!

Thanks for everything: I will also accompany you during the next season, hoping to make your F1 experience more exciting and interesting!

Thanks to you for making this possible! ❤️
20👍1🔥1
Under stable rules, sub-optimal design choices are replaced by 'winning' philosophies.🏆

This year, especially in the last few races, we've had a much tighter pack than in 2022.

Still, I loved the early-2022 variability in design: look at this Aston!😍

[📸 @Motorsport]
👍32🔥1👏1
Weekly reminder that you can find ALL my socials and extra content through THIS link
👇
https://linktr.ee/fdataanalysis
👍2🔥1
Thank you guys and gals: thanks to your activity, this channel is now large enough to be eligible to addtional customisation options!🤩 (For example, the possibility to change its background)

For that, we need 10 people to Boost the channel (Telegram Premium is needed): Boost it through this link👇https://news.1rj.ru/str/FDataAn?boost
👏4👍31🔥1🍾1
Highest Percentage Wins in a Season (Drivers)

🥇Verstappen 2023 - 86.36% (19/22)
🥈Ascari 1952 - 75.00% (6/8)
🥉Schumacher 2004 - 72.22% (13/18)

This year Max Verstappen beat a 71-year old record!🤯

Ascari's record is impressive considering old #F1 cars' bad reliability.
👏3🤯3👍1
Weekly reminder that you can JOIN the CHAT channel to discuss my analyses OUTSIDE of the 'comments'!
👇Use this link👇
https://news.1rj.ru/str/FDataAnCHAT
👍2🔥1
Ferrari SF-23 (Top) vs SF21 (Bottom)🔎

Notice how different the shape (and size) of the bodywork is!👀

The 18'' rims made the 2023 tyres' diameter larger (despite the thinner sidewall): 660mm➡️720mm

The next comparison will be based on your comments: choose two #F1 cars!🤩
👍42
RedBull decidedly improved over their already great 2022 season:
4 more wins
6 more poles
3 more fastest laps
101 more points

RB19>RB18 in every way: In Adu Dhabi, both the top speed (+2km/h) and high-speed cornering (+8km/h) improved!
More downforce AND less drag
🔥9👍5😢21🥰1👏1
What is your favourite F1 car, or the one you consider most iconic?👀

Comment with a photo of that!🤩

I will start: Ferrari F2002🐎

[📸 ZNR Automotive Renders]
5👍3
The most powerful F1 engine ever?

The tiny 1500cc 4-cylinder 1986 BMW M12: over 1400hp in qualifying!🔥

Power is estimated: no dyno could accurately measure over 1000hp!💡

The Benetton reached 352km/h in Monza, with much worse drag (and grip) than current cars!

Mind-blowing! 😳
9🤯6👍3🔥21
Formula Data Analysis
The most powerful F1 engine ever? The tiny 1500cc 4-cylinder 1986 BMW M12: over 1400hp in qualifying!🔥 Power is estimated: no dyno could accurately measure over 1000hp!💡 The Benetton reached 352km/h in Monza, with much worse drag (and grip) than current…
The inline-4 layout of the BMW engine gave it a clear advantage over the V6 engines used by Ferrari and Renault:
1 fewer turbos, 2 fewer cylinders, 8 fewer valves➡️lower frictional losses➡️More power and better reliability.
👍6🔥2
Weekly reminder that you can find ALL my socials and extra content through THIS link
👇
https://linktr.ee/fdataanalysis
🔥1
F1 vs MotoGP Aero

In F1, wings make you corner quicker
In MotoGP, cornering might get worse!😳

F1:🔵downforce increases the🔴tyre load➡️more grip (higher lat. accel. ay).

MotoGP:🔵"down"-force has a horizontal (centrifugal) component, pushing the bike out of the corner!

🔵Downforce acts on the bike midplane
⬇️
-The tyres🔴vertical load increases (good).
-More🟣lateral tyre force is required for a given lateral acceleration (bad!).

At best, the two effects cancel out.
At worst, cornering gets worse as the friction coefficient μ decreases! 📉

So, why do MotoGP engineers add wings on the bikes if they cause additional drag while potentially making cornering worse? 🤔

Mostly to limit wheelie: that's the limiting factor out of most corners, and not the rear tyre grip! 🏍

Braking improves too.👌
[📸Getty Images]
🔥6👍2