Formula Data Analysis
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HUNGARIAN GP - PRACTICE 2
AERO CHART (Best lap on softs)

🟒 Sauber/πŸ”΅ RBR/🟒 Aston/πŸ”΄ Ferrari/🟠 McL all reached 318km/h in their best lap - downforce and the mechanical setup determined the order, not drag.

🟒 Mercedes had the lowest drag by far (+4km/h vs next best).

🟣 Alpine's only reached 314km/h, yet their downforce didn't impress.

Different engine modes could mask drag a bit: for example, NOR seems to have been running slightly more power than PIA (+2km/h, no sign of less downforce).
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Formula Data Analysis
HUNGARIAN GP - PRACTICE 2 AERO CHART (Best lap on softs) 🟒 Sauber/πŸ”΅ RBR/🟒 Aston/πŸ”΄ Ferrari/🟠 McL all reached 318km/h in their best lap - downforce and the mechanical setup determined the order, not drag. 🟒 Mercedes had the lowest drag by far (+4km/h vs next…
BEST SECTORS

πŸ”΄ HAM was quickest in S1 (the fastest one, which includes the 2 DRS straights). Alpine's high drag made them slowest there.

🟠 NOR was out of reach in S2 (endless series of medium-speed corners) where McL's high downforce shined.

🟠 McL 1-2 in S3, too, where PIA was quickest.

πŸ”΅ VER struggled massively in sectors 1 and 3: he was 2nd slowest in both!
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HUNGARIAN GP
πŸ“Š FP2 LONG RUNS

McL vs Ferrari: similar pace on 🟑 Mediums:
🟧 NOR quickest;
🟧 PIA +0.065s/lap;
πŸŸ₯ LEC +0.082s/lap.

ALB impressed: very consistent, pace similar to the top cars!

Only HAM ran πŸ”΄ Softs and had high deg.

ANT: 2 tenths off.

VER doesn't impress even after removing his slow laps.

What's YOUR F1 quali and race prediction? πŸ‘€
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HUNGARIAN GP - QUALIFYING ANALYSIS

πŸ”΄ 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...
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HUNGARIAN GP - RACE

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

1️⃣ Lap 9: Bozzi calls for 'FS1' PU mode➑️top speed drops to ~280km/h❌ (ERS cut abruptly).
πŸ”΄ 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 set➑️destroyed 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
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HUNGARIAN GP - RACE PACE πŸ“Š

🟧 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!

πŸŸ₯ 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?
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Do you remember the JMP Summer Challenge, the motorsport-related data analysis challenge? πŸŽπŸ“Š

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! πŸ› 

Don't miss it!
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Forwarded from Formula Data Analysis
Media is too big
VIEW IN TELEGRAM
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 commentπŸ‘‡
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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. 😬
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Performance gains in the ground-effect era have been wild:
~3% less drag, ~12% more high-speed acceleration 😳

πŸ“ Ferrari in Hungary quali:
2022 ➑️2025
βœ…-2.195s laptime‼️
βœ…+3km/h top speed
βœ…+4km/h minimum speed
βœ…+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
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What's the best looking F1 car ever? πŸ€”
Comment below!

I will start: McLaren MP4-20 🫠
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The most powerful naturally-aspirated #F1 engine ever was... Japanese, likely πŸ‡―πŸ‡΅

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!
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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 β€˜14, and Caterham’s car was terrible all-around!

I explain this strange result in this threadπŸ‘‡
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Formula Data Analysis
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 β€˜14, and Caterham’s car was terrible all-around! I explain this strange result in this…
F1 cars became terribly slow in 2014.

This was due to:
- New PU➑️Significantly 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.
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Formula Data Analysis
F1 cars became terribly slow in 2014. This was due to: - New PU➑️Significantly 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…
Caterham, in particular, suffered from the low power of the Renault PU and the very low aerodynamic efficiency (look at how wide, β€˜boxy’ and simple their sidepods are. Moreover, the air intakes were HUGE).

They were 4s off the pole!
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