> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/TracingInsights-Archive/Stats/llms.txt
> Use this file to discover all available pages before exploring further.

# Data Structure Overview

> Understanding the organization of the F1 Stats Archive

The F1 Stats Archive is organized in a hierarchical structure that mirrors the Formula 1 calendar, making it intuitive to navigate and query historical F1 data.

## Organization Philosophy

The archive follows a logical hierarchy from broadest to most specific:

```
Year → Race → Data Files
```

This structure allows you to:

* Navigate chronologically through F1 history (1950-present)
* Access all data for a specific season
* Drill down to individual race weekends
* Find specific data types (results, qualifying, lap times, etc.)

## Directory Hierarchy

Each year directory contains:

* **Season-level files**: Championship standings and race calendar
* **Race directories**: Individual folders for each Grand Prix

### Season-Level Files

At the year level (e.g., `2024/`):

* `events.json` - Calendar of all races in the season
* `driverPoints.json` - Final driver championship standings
* `teamPoints.json` - Final constructor championship standings

### Race-Level Files

Each race directory (e.g., `2024/australian-grand-prix/`) contains:

* `event_info.json` - Race weekend schedule and circuit information
* `results.json` - Race results with positions, times, and points
* `quali_results.json` - Qualifying results for all sessions (Q1, Q2, Q3)
* `laptimes.json` - Lap-by-lap timing data for all drivers
* `pitstops.json` - Pit stop data including duration and lap number
* `driverPoints.json` - Driver standings after this race
* `teamPoints.json` - Constructor standings after this race
* `sprint_results.json` - Sprint race results (only for sprint weekends)

## Data Consistency

All data files follow consistent schemas based on the Ergast API format:

* Data is stored in JSON format
* Each file contains metadata headers (`MRData` wrapper)
* Driver and constructor information uses consistent IDs across all files
* Times are stored in ISO 8601 format
* Coordinates use decimal degrees for circuit locations

## Navigating the Archive

### By Time Period

Start at a year directory to explore a complete season:

```
2024/                    # Season overview
├── events.json          # All races
├── driverPoints.json    # Final standings
└── teamPoints.json      # Final team standings
```

### By Race Weekend

Drill into a race directory for complete weekend data:

```
2024/australian-grand-prix/
├── event_info.json      # Circuit and schedule
├── quali_results.json   # Qualifying
├── results.json         # Race results
└── laptimes.json        # Detailed lap data
```

### By Data Type

Access the same data type across multiple races:

* Compare qualifying performance: `*/*/quali_results.json`
* Track championship progression: `*/driverPoints.json`
* Analyze pit strategies: `*/*/pitstops.json`

## Historical Coverage

The archive spans from **1950** (the first F1 World Championship) to the present day:

* Early years (1950s-1990s) have fewer data types due to limited historical records
* Modern seasons (2000s+) include comprehensive data
* Lap times and pit stops become available from 1996 onwards
* Sprint races appear from 2021 onwards

## Use Cases

This structure supports various analytical workflows:

<AccordionGroup>
  <Accordion title="Season Analysis">
    Access `events.json` and championship standings files to analyze season-long trends, championship battles, and calendar changes over time.
  </Accordion>

  <Accordion title="Race Comparison">
    Compare the same Grand Prix across different years by navigating to the same race name in different year directories.
  </Accordion>

  <Accordion title="Driver Performance">
    Track a driver's qualifying and race results by searching for their `driverId` across multiple `results.json` and `quali_results.json` files.
  </Accordion>

  <Accordion title="Strategy Analysis">
    Use `pitstops.json` and `laptimes.json` to analyze tire strategies, pit stop efficiency, and stint performance.
  </Accordion>
</AccordionGroup>

## Next Steps

<CardGroup cols={2}>
  <Card title="Directory Layout" icon="folder-tree" href="/data-structure/directory-layout">
    Explore the detailed file and folder structure
  </Card>

  <Card title="JSON Schemas" icon="code" href="/data-structure/json-schemas">
    Learn about the structure of each data file
  </Card>
</CardGroup>