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Subreddit dedicated to 'Formula Data Analysis' (@FDataAnalysis), content creator producing data analysis on F1. Here you will find discussions on Vehicle Dynamics, telemetry, setup and all the physics-based, data-driven side of F1. Contribute to the discussion, and find me at the social links below for additional contents!

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Bahrain GP - Race | Race Pace Analysis: PIA was unbeatable: 0.39s/lap quicker than his teammate ON AVERAGE! Pace per team: 1)McL quickest; 2)Mercedes +0.48/lap; 3)Ferrari +0.50; 4)RBR +0.90!; 5)Alpine +0.93!! McL’s advantage over the 2nd best car (0.48s) is the same that RBR had last year (0.47s).

Japanese GP - Quali | Corner Analysis: VER gained 0.112s in the last chicane, getting pole by 0.012s! NOR lifted and braked early; LEC less so; VER did for last. VER had to brake the most (largest longitudinal accel.) Yet, he made the corner (largest lateral accel.). His exit was no worse than LEC's

Chinese GP - Sprint Qualifying | Aero Performance, Track Domination & Gap to Ideal Lap

Chinese GP - Practice 1 | Long Runs: Ferrari didn't do any➡️an issue for the Sprint? Everyone on Mediums: McL & Merc were quickest (Excluding ALO/OCO who did just 3 valid laps). Merc's degradation was high. VER was slowest: RBR used very low PU modes and a lot of fuel (slow in the fast corners).

Chinese GP - Race | Top Speed per Lap

Bahrain GP - Practice 1 | Top Speeds vs 2024 Qualifying

Bahrain GP - Tyres [Image by: Pirelli Motorsport]

Chinese GP - Race | Norris's Brake Issue [Made via JMP Software]

Japanese GP - Practice 1 | Aero Characteristics, Best Sector Gap & Gap to Ideal Lap

Japanese GP - Quali | Aero Perofrmance: The race could be wet, at least in part. In that case, teams running a more loaded aero setup (McL, Haas) should gain over those that focused more on reducing drag (Ferrari, Mercedes, Red Bull): the drag penalty will be lower, and downforce more important.