Overview
External data sources allow FUSE graphics to display information from spreadsheets and APIs that isn't part of the standard LIGR data model. This is useful for displaying tournament brackets, custom statistics, sponsor information, or any data maintained outside of LIGR Live.
You'll use external data when:
* Building tournament bracket graphics that pull bracket data from spreadsheets
* Displaying custom statistics or metrics not tracked in LIGR
* Showing sponsor information maintained in external databases
* Combining LIGR match data with supplementary information from other sources
Key Concepts
External Data Source: A spreadsheet or API endpoint that provides data to FUSE graphics. The data is separate from the standard LIGR data hierarchy (leagues, competitions, matches, teams, players).
Header Row: The first row of your external data spreadsheet. FUSE reads these headers and creates named fields for each column. These field names are used in FUSE expressions to reference the data.
Field Names: The column headers from your spreadsheet become field names in FUSE. For example, a column header "Round1_Team1" becomes a field you can reference in expressions.
Data Mapping: The process of linking external data fields to graphic elements in FUSE. You create expressions that reference the external data field names to populate text, images, or other elements.
Mixed Data Expressions: FUSE expressions can combine LIGR data and external data in the same graphic. For example, you can display team names from LIGR alongside tournament bracket positions from an external spreadsheet.
How External Data Works
External data sources are connected to FUSE and their column headers become available as field names in expressions. The data updates dynamically - when you change values in the external spreadsheet, the graphic reflects the new data without needing to re-publish.
External data can come from:
* Google Sheets
* CSV files
* API endpoints
Preparing Your External Data Spreadsheet
Before connecting an external data source to FUSE, structure your spreadsheet correctly:
1. Create the first row as your header row with descriptive column names
2. Use clear, consistent naming conventions for headers (e.g., Round1_Team1, Round1_Team2, Round1_Score1)
3. Include all data you want to display in the graphic
4. Ensure data types are consistent within each column
The header row is critical - FUSE uses these headers as field names for expressions. Without a header row, FUSE cannot properly map the data.
Connecting External Data to FUSE
1. Open your graphic in the FUSE editor
2. Navigate to the External Data section
3. Connect your spreadsheet or API endpoint
4. FUSE reads the header row and creates named fields for each column
5. These fields become available to reference in expressions
Mapping External Data to Graphic Elements
Once your external data is connected, map the data columns to graphic elements:
1. Select the graphic element you want to populate with external data
2. Create an expression that references the corresponding column from the external data
3. Use the field name from the header row in your expression
4. Repeat for each element that should display external data
For example, if your spreadsheet has a column header "Round1_Team1", reference it in an expression to display that team name in your bracket graphic.
Combining LIGR Data and External Data
FUSE expressions can mix LIGR data (from the standard data hierarchy) with external data in the same graphic. This provides maximum flexibility when building graphics that need both match information and supplementary data.
For example, you can:
* Display live match scores from LIGR alongside tournament bracket positions from a spreadsheet
* Show team logos from LIGR Assets with custom statistics from an external database
* Combine player names from LIGR rosters with performance metrics from an external tracking system
Batch-Updating External Data Expressions
When building graphics with many external data fields (such as tournament brackets with multiple rounds), you can use batch editing to speed up the workflow:
1. Export your FUSE expressions as a text file
2. Use ChatGPT or a text editor to generate repetitive expressions based on a pattern
3. Provide ChatGPT with the pattern for one round and ask it to generate expressions for additional rounds
4. Import the modified expressions back into FUSE
This is particularly useful for tournament brackets where you have repetitive patterns across multiple rounds and positions.
Previewing External Data in FUSE
After mapping external data to your graphic elements:
1. Use the FUSE preview to verify all data displays correctly
2. Check that field names are mapped to the correct elements
3. Verify data positioning and formatting
4. Test with sample data before connecting live sources
Dynamic Updates
External data updates in the spreadsheet are reflected in the graphic without needing to re-publish. When you change values in your connected spreadsheet or API, the graphic automatically displays the updated information.
This makes external data sources ideal for information that changes frequently, such as tournament brackets that update after each round or statistics that refresh throughout a season.
Tips
* External data spreadsheets must have a header row - FUSE uses these headers as field names for expressions
* Use clear, descriptive header names that make sense in expressions (e.g., "HomeTeam" rather than "Col1")
* Test with sample data first before connecting live tournament or statistics data
* Use ChatGPT to batch-create expressions when you have repetitive patterns across multiple data fields
* Choose the external data format (Google Sheets, CSV, API) that best fits your workflow and update frequency
* External data can be combined with LIGR data in the same graphic for maximum flexibility