Formula Data Analysis
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πŸ”΅VER will start the #F1 Sprint in P1, yet he wasn't the quickest in any sector! (But quick everywhere)
βšͺ️The upgraded Haas was mighty!

1) BEST SECTORS:
- S1: HAM fastest, by far (+0.13s vs VER)
- S2: RUS fastest, then NOR
- S3: LEC and HUL fastest
VER struggled in S2, NOR in S3

2) GRIP:
RUS reached the highest top speed (330km/h) yet he was also stronger than VER and LEC under braking! (Reached 6g of deceleration)

VER had excellent cornering grip, but braking was lacking.

πŸ”΄LEC produced the lowest maximum lateral acceleration (in fact he struggled in S1).
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RACE PACE - F1 SPRINT

Verstappen was quickest on average, but Sainz was almost as quick despite the numerous fights!
He can win the race. πŸ€

πŸ₯‡πŸ”΅VER
πŸ₯ˆπŸ”΄SAI +0.05s/lap (traffic)
πŸ₯‰πŸ”΄LEC+0.24s/lap (traffic)

πŸ“ˆImpressed: Ferrari.
πŸ“‰Disappointed: Mercedes (Big drop in pace), McL.

The race will probably be down to how the relative performance will differ on a full tank and different tyre compounds.
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RACE PACE Austin GP

Ferrari's 1-2 was their most 'dominant' race of the year: 0.26s/lap advantage on McL! (LEC vs NOR) πŸ†

Next best: Australia (+0.11s/lap)
Best pace since early '22! πŸ’‘

NOR: 0.1s/lap quicker than VER πŸ‘Œ
RUS and PER: underwhelming pace even considering traffic. 🚨

Ferrari's aero updates (introduced in Singapore) seem to have worked, as Austin is a very representative track (diverse sectors; downforce and drag are both important).
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TOP SPEEDS - Austin GP

RUS reached 344km/h! Plenty of slipstream+DRS during his comeback.

VER was slowest - by far. Just 313km/h, as he never used DRS on the main straight. That's low even considering that.

PIA's drag was high: lowest top speed with (326) and without DRS (312).
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Mexico City GP offers a unique challenge:
The ~20% lower air density (due to altitude) reduces downforce and drag massively.
⬇️
- High drag not as critical (will help McL)
- High downforce even more crucial!

Often highest top speeds of the season despite the high-downforce wings. πŸ’‘

Cars will be sliding significantly due to the decreased downforce and the slippery tarmac.

πŸ“Έ @pirellisport
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In the race, Charles Leclerc was on average over THREE SECONDS PER LAP quicker than last year... using the same strategy (Medium➑️Hard)! 🀯

Track conditions alone cannot explain this impressive improvement... and now Ferrari is given over 1 in 4 chances of getting the WCC. πŸ€

The team also introduced a more flexible front wing, providing at least two benefits:
-Reduced drag at high speed;
-Speed-dependent aero balance (Low speed: more front downforce ➑️ better agility and overall grip; High speed: less front downforce ➑️ better stability, aiding driver confidence).

Race pace Improvement by other drivers:
NOR: 2.44s/lap (one less stop than in β€˜23)
VER: 2.04 s/lap (one less stop than in β€˜23)
SAI: 2.55s/lap (one less stop than in β€˜23)

Even SAI, despite being quicker than LEC in β€˜23 (due to the additional stop) and slower in β€˜24, gained over half a second vs VER.
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Mexico's lower air density is forcing Ferrari to add cooling louvres to its car - even compared to another high-altitude track like Austria. πŸ”₯

Engine cooling is improved at the expense of more drag and less rear downforce. πŸ“‰

Ferrari struggled with temperatures in '23 when they opted for an asymmetrical cooling arrangement. 🚨

F1 teams with lower cooling requirements and turbocompressors better suited to the less dense air will lose less performance in Mexico!
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Austin GP damaged Lando Norris's championship hopes while reviving Ferrari’s chances. πŸ”₯

WDC probability (Before vs After Austin)
πŸ₯‡πŸ”΅VER: 58.89% ➑️ 80.13% (+21.24%πŸ“ˆ)
πŸ₯ˆπŸŸ NOR: 38.37% ➑️ 17.60% (-20.77%πŸ“‰)

WCC
πŸ₯‡πŸŸ McL: 86.86% ➑️ 88.50% (+1.64%πŸ“ˆ)
πŸ₯ˆπŸ”΄Ferrari: 6.47% ➑️ 14.29% (+7.82%πŸ“‰)
πŸ₯‰πŸ”΅RBR: 9.20% ➑️ 5.88% (-3.32%πŸ“‰)

The probability swing after Mexico will be wild (as fewer and fewer points are available).
Data by : @oddschecker

You might have noticed that the sum of the β€˜post Austin’ WCC percentages is over 100%. That’s because I forgot to remove the bookmaker’s edge, my bad!

The pecking order is not affected by that, obviously.
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FP2 - F1 DATA HIGHLIGHTS

πŸ”΄SAI was 0.178s quicker than 🟠PIA, but McL's engine mode was clearly lower! 😏

1) TOP SPEEDS:
Ferrari: 352km/h... and it's still FP2!
+5km/h vs RedBull, +9km/h vs McL

2) BEST SECTORS:
In fact, SAI/LEC were quickest in S1 (two long straights)
McL dominated the slow S3

3) Sainz vs Piastri:
SAI's higher engine power is clear as day: he gained significantly through all the straights.
Once McL turns up the power, they should be on par or quicker than Ferrari. πŸ”₯
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Sainz beat Verstappen by 0.225s by gaining significantly from Turn 3 to 6 - and not losing his advantage afterwards πŸ”₯

SAI: +1km/h top speed on the main straight; +4km/h on the next one πŸš€

VER used III gear in T4, while SAI downshifted to II

VER took T9 full-throttle!
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Who's excited for the race? πŸ”₯πŸ˜‰
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πŸ“Š RACE PACE #MexicoGP 

SAI just 0.05s/lap quicker than NOR! (Who suffered the initial gap)

VER was no quicker than HAM: what a difference vs season-start!

MAG as quick as (traffic-hit) PIA

Change vs '23 (s/lap)
McL: -2.33πŸ“ˆ
Ferrari: -2.20πŸ“ˆ
Merc: -1.45πŸ‘Œ
RBR: -1.03🚨

It's your turn: who will win the two championships?πŸ€”
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πŸ‘‡Use this linkπŸ‘‡
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In the 2nd stint, Magnussen was 0.1s/lap QUICKER than Verstappen, on average 🀯
VER's tyres were just 4 laps older

In the 1st stint (Mediums, slow laps removed), VER's pace was better.
In the last 15 laps of the race, MAG was much quicker than him
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Yep… that was close! 😳
Impressive commitment by the cameraman 😲

πŸ“Έ: @FlorentGooden
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Piastri reached 361km/h in the #MexicoGP  ! He had frequent slipstreams and DRS opportunities during his recovery drive

Mercedes’ top speed was very high, too: 359km/h for HAM and RUS

Ferrari had the lowest one: SAI used the DRS on the main straight just once, overtaking VER!
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