HUNGARIAN GP - QUALIFYING ANALYSIS

🔴 LEC got pole by having the most well-rounded performance!

🟠 McL (PIA): best cornering (both low and high speed), but hurt by high drag.

⚫️ Mercedes (RUS): best top speed, but also worst low-speed cornering.

🟢 Aston (ALO): Similar to Ferrari, but slower in the fast corners.

The closest Q3 session in F1's history (0.543s separating the top 10)!

McL will struggle overtaking with that top speed...

HUNGARIAN GP - RACE

LEC had a plank wear issue - here’s how it ruined his race ⚠️ (Data-backed theory) 👇

1️⃣ Lap 9: Bozzi calls for 'FS1' PU mode➡️top speed drops to ~280km/h❌ (ERS cut abruptly).
🔴 LEC was faster than 🟠 PIA before, slower after; pace still decent.

2️⃣ Still bottoming at Turn 11 (FS1 had no effect there). He’s told to back off there, further losing pace. ❌

3️⃣ Despite these measures, wear remained excessive. Final blow? Sky-high pressures on his final set➡️destroyed pace ❌
(~2s/lap slower than PIA, undriveable, even slower than his 1st with ~70kg more fuel)!

He finished. But at what cost?

Made via @JMP_software

HUNGARIAN GP - RACE PACE 📊

🟧 NOR's bad start was a blessing in disguise: was forced to rely on an alternate strategy (one-stopper) to make places, and it worked!

Not only was 🟦 VER 1s/lap slower than 🟧 PIA on the same strategy, he was barely quicker than ALO/BOR/STR/LAW despite using one more tire set!

🟥 LEC’s pace was dominant until L9, then his issues began. Still decent until his last pit (L40), then it collapsed: only 4 drivers were slower by the end, including both Alpines.

Can VER fight back?

Will we ever know the truth about LEC's issue?

Do you remember the JMP Summer Challenge, the motorsport-related data analysis challenge? 🏎📊

I made a video walking you through the dataset, explaining the meaning of its many variables and also giving you some ideas for an analysis! 🛠

Don't miss it!

So... I did something😬

I'm teaming up with JMP to organise an F1-themed data analysis summer challenge!🤩

You'll analyse the data from an F1 race: laptimes, compounds, pit stops, speed traps, you name it!🏎

Same data for everyone: may the best among you win!
Info in comment👇

The time to join the challenge is running out!

Here’s how to join:
1️⃣ Sign up
2️⃣ Download the free JMP trial + dataset
3️⃣ Submit your visualisation in JMP
4️⃣ Join the live webinar

Click here to join:

https://www.jmp.com/en/offers/summer-challenge/motorsport?utm_source=fdanalysis&utm_medium=social&utm_campaign=701Ki000000EZJgIAO

HUNGARIAN GP - START ANALYSIS

Albon was quickest, right in front of his teammate. The Softs aided Williams' traction (SAI was quickest to 100km/h).

The two Haas cars were quickest among those who started on Mediums.

HAM was quickest on Hards.

RUS had to back off not to rear-end NOR. 😬

Same data, showing the compound used through colour.

As expected, 🟥Softs had the highest potential, then 🟨Mediums, then ⬜️Hards.

Performance gains in the ground-effect era have been wild:
~3% less drag, ~12% more high-speed acceleration 😳

📍 Ferrari in Hungary quali:
2022 ➡️2025
✅-2.195s laptime‼️
✅+3km/h top speed
✅+4km/h minimum speed
✅+13km/h in Turn 11‼️

Each year, laptime improved and top speed was higher or equal, but downforce improved the most.

Ferrari cut drag while massively boosting downforce:
- Increasing the top speed from 312 to 315km/h means a ~3% reduction in drag {(312/315)^3 - 1}.
- Increasing the minimum speed in T11 from 228 to 241km/h is a ~12% increase in lateral acceleration {(241/228)^2}, or ~0.5g more!

Made via @JMP_software

What's the best looking F1 car ever? 🤔
Comment below!

I will start: McLaren MP4-20 🫠

Also:

https://x.com/FDataAnalysis/status/1956330445844459743

400+ beauties here! Check them out!

The most powerful naturally-aspirated #F1 engine ever was... Japanese, likely 🇯🇵

Peak power reached in 2005 (end of 3000cc, 'V10' era)!

Renault ~900hp
Cosworth 915hp
Mercedes ~930hp
Ferrari 920-940hp
Honda >965hp (Last power step in Suzuka)
Toyota >1000hp, detuned to ~960hp for reliability

The straight-line acceleration of these cars was insane, much higher than the current ones' (and did so 20 years ago)!

Compared to current cars:
- Similar peak power;
- Higher end-of-straight power (No ERS, always full power);
- 200kg lighter (600kg, including driver!);
- 20cm narrower track, reducing drag.

Crazy!

The pictures are inverted: Toyota produced ~1000hp but had to be detuned.

In 2014 in Barcelona, Caterham’s F1 car was SLOWER than their GP2 car! 🤯

- 1.30.3 for the F1 car.
- 1.29.8 for the GP2 car(0.5s faster)!

#F1 cars became terribly slow in ‘14, and Caterham’s car was terrible all-around!

I explain this strange result in this thread👇

F1 cars became terribly slow in 2014.

This was due to:
- New PU➡️Significantly increased mass (+49kg over 2013);
- Lower peak and mean power than the already weak V8s (Considering Caterham’s Renault PU: around 750hp+80hp of KERS for V8, around 600+160hp for V6s);
- Narrower front wing.

Caterham, in particular, suffered from the low power of the Renault PU and the very low aerodynamic efficiency (look at how wide, ‘boxy’ and simple their sidepods are. Moreover, the air intakes were HUGE).

They were 4s off the pole!

The GP2s, on the contrary, kept the same performance as the previous years' thanks to stable rules:
- They were, for the first time, lighter than F1 (-3kg, 688kg vs 691kg);
- The engine produced 612hp, around the same as the Combustion Engine of F1 cars (~600hp);
- Same track width.

The main advantages of F1 cars were:
- Better acceleration (thanks to better peak power due to the ERS system, which, however, was still inefficient in 2014 for most teams);
- DRS (that is worth several tenths in a fast, high-load track like Barcelona);
- Higher aero complexity.

Consequently, the GP2 pole was good enough to beat FOUR F1 cars!

And what is even more impressive is one team, such as Caterham, having a faster GP2 car than their F1 car. 🤯

Surely the GP2 team was grinning! 🤣

And don’t let all this tech talk distract you from the ‘14 Caterham F1 having an ‘interesting’ shape of the nose.

🤣