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Grand Prix Driver Behaviour Data
Data Science and Analytics
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About
This collection of race data enables users to predict position changes and optimal pit strategies by leveraging driver behaviour metrics and prevailing race conditions. Each record focuses on a specific driver's stint within a particular race, integrating information scraped and processed from several leading Formula 1 data sources, including the FastF1 API for lap/tire information, Open-Meteo for historical weather details, and telemetry tools for race positions and schedules.
Columns
The dataset features 10 core columns:
- Season: Indicates the year the race took place.
- Round: Specifies the race number within that specific season.
- Circuit: Identifies the venue where the race was held.
- Driver: The individual who drove in the race.
- Constructor: Represents the team participating in the race (e.g., Ferrari, McLaren).
- Laps: The total number of laps completed in that race.
- Position: The final finishing position of the driver.
- TotalPitStops: The overall number of stops made by the driver.
- AvgPitStopTime: The average duration of time taken for the pit stops (note: 79% of records are missing this value).
- PitStops: Detailed information about the stops, including the lap number and time taken.
Distribution
The data is delivered in a CSV format, specifically named Formula1_Pitstop_Data_1950-2024_all_rounds.csv, with a size of 2.16 MB. The structure includes 10 columns and contains approximately 26.8 thousand valid records.
Usage
The data is highly suited for several applications, including:
- Developing machine learning models aimed at predicting race outcomes based on driver aggression and environmental factors.
- Conducting historical sports analytics focused on the evolution of pit strategy efficiency across decades.
- Studying the correlation between weather metrics (track temperature, humidity, wind speed) and pit stop frequency.
- Providing intermediate-level material for data cleaning and categorical analysis exercises.
Coverage
This dataset spans a substantial time range, covering races from 1950 up to 2024. It includes information on 77 unique racing circuits globally. The data is meant to capture all rounds across the included seasons. Updates to this collection are expected to occur annually.
License
Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Who Can Use It
- Data Analysts: To perform exploratory analysis on historical F1 trends.
- Machine Learning Engineers: To train models predicting driver success or optimal strategy adjustments mid-race.
- Academic Researchers: To study motorsport logistics and the impact of behavioural metrics.
- F1 Enthusiasts: To gain deeper insight into the strategic elements of Grand Prix racing.
Dataset Name Suggestions
- F1 Historical Pit Stop Metrics
- Grand Prix Driver Behaviour Data
- Formula 1 Pit Strategy Analyzer
Attributes
Original Data Source: Grand Prix Driver Behaviour Data
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