Formula 1 Qualifying and Race Results: Ground Effect Era (2022–2025)

This dataset provides a structured record of qualifying and race classification results from the Formula 1 Ground Effect Era (2022–2025).

Beginning in 2022, Formula 1 introduced a new aerodynamic framework centred on ground-effect floor designs aimed at reducing wake turbulence and enabling closer on-track racing. The regulations simplified upper-body aerodynamic surfaces, eliminated bargeboards, redesigned front and rear wings, and placed greater emphasis on underfloor venturi tunnels for downforce generation, while maintaining the 1.6-litre turbo-hybrid power unit architecture used in the preceding era.

During this period, sprint weekend formats were introduced and subsequently revised, altering the structure of selected race weekends and the determination of starting grids.

The competitive landscape during this era was more distributed than in the preceding period. Red Bull Racing won the Constructors’ Championships in 2022 and 2023, while McLaren secured the Constructors’ titles in 2024 and 2025. Max Verstappen won the Drivers’ Championship in 2022, 2023, and 2024, with Lando Norris winning the 2025 Drivers’ Championship.

Each entry represents a driver–event classification and includes:

Championship season and round number,

Official Grand Prix name,

Consistent driver identifier and driver name,

Constructor (team) at the event,

Final classified qualifying position,

Official race grid position,

Final classified race finishing position,

Net position change during the race (finish position minus grid position),

Qualifying session times (Q1, Q2, Q3 where applicable), and

Classification status (e.g. Finished, DNF, DSQ).

The dataset has been harmonised to ensure consistent driver identifiers, constructor naming, and alignment across varying weekend formats, including sprint-affected race grids.

Typical applications include comparative analysis across regulatory eras, modelling of positional movement and race outcomes, and use in teaching contexts involving data science and sports analytics.

The datasets and accompanying documentation are provided as CSV and Markdown files.