🔄Squad generation
Learn how to use the powerful auto-assignment tool to optimally distribute gymnasts across squads and flights while balancing level groupings and team affiliations.
Use the sophisticated auto-assignment tool to optimally distribute gymnasts across squads and flights, automatically solving the complex optimization problem of balancing skill levels and team affiliations.
Overview
The Squad Generation tool is a powerful automation feature that solves one of the most complex challenges in meet organization: optimally distributing gymnasts across squads and flights while respecting both skill level groupings and team affiliations. This tool handles the mathematical complexity of creating balanced, fair rotations that minimize conflicts and maximize organizational efficiency.
Accessing the Squad Generation Tool
Launching the Auto-Assignment Dialog
Open Squad List Page
Navigate to your session dashboard
Access the "Squad List" or "Squads & Rotations" tab
Initiate Auto-Assignment
Click the "Auto-Assign" button in the top header
This opens the squad generation configuration dialog
Configure Generation Settings
Adjust squad size, optimization priorities, and advanced options
Preview the expected distribution before generation
Understanding Optimal Assignment
The Optimization Challenge
Complex Problem Solving:
Multiple Variables: Each gymnast has a level and a club
Multiple Constraints: 4 apparatus rotations with squad size limitations
Competing Priorities: Balance level groupings vs team affiliations
Non-Trivial Solution: Manual assignment becomes exponentially complex with scale
What "Optimal" Means:
Level Balance: Gymnasts with similar skill levels grouped together when possible
Team Cohesion: Gymnasts from the same club kept together when beneficial
Equal Distribution: Avoids creating uneven squad sizes
Squad Size Configuration
Target Squad Size Setting
Squad Size Parameter:
Purpose: Define the ideal number of gymnasts per squad
Impact: Determines how total gymnasts are divided across apparatus
Example: 35 gymnasts with squad size of 9 = 3 squads of 9 + 1 squad of 8
Size Calculation Logic:
Distribution Priority: Fills squads as evenly as possible
Remainder Handling: Distributes extra gymnasts across squads fairly
Practical Size Examples
Example 1: 35 Gymnasts, Size 9
Squad A: 9 gymnasts
Squad B: 9 gymnasts
Squad C: 9 gymnasts
Squad D: 8 gymnasts
Example 2: 35 Gymnasts, Size 10
Squad A: 10 gymnasts
Squad B: 10 gymnasts
Squad C: 10 gymnasts
Squad D: 5 gymnasts
Optimization Priority Slider
Balancing Level vs Team Groupings
Priority Spectrum:
Left Extreme (Level Priority): Groups gymnasts only by skill level
Right Extreme (Team Priority): Groups gymnasts only by club affiliation
Middle Position: Balances both level and team considerations equally
Slider Functionality:
Continuous Scale: Any position between the two extremes
Real-time Preview: See how settings affect expected groupings
Fine-tuning: Adjust balance based on meet-specific requirements
Priority Decision Factors
When to Prioritize Levels:
Skill-Based Competition: Meets where level matching is critical
Technical Requirements: When apparatus difficulty varies significantly
Judge Expertise: When judges specialize in specific skill levels
When to Prioritize Teams:
Club Representation: Important for team scoring and morale
Travel Logistics: Clubs traveling together need to stay grouped
Coaching Coordination: Easier management when clubs are together
Advanced Generation Settings
Fixed Squad Size Option
Standard vs Fixed Mode:
Standard Mode: Tries smallest possible squad sizes first, then increases
Fixed Mode: Forces specific squad size across all squads
Fixed Size Behavior:
Example: 35 gymnasts, fixed size 10 = Squads of exactly 10, 10, 10, 5
Consistency: All squads (except remainder) have identical sizes
Predictability: Easier to plan apparatus utilization and timing
Pinned Athletes Feature
Selective Constraint System:
Purpose: Keep specific gymnasts in fixed positions during generation
Use Case: Honor pre-existing assignments or special requirements
Flexibility: Generate around pinned gymnasts while optimizing the rest
Implementation:
Pre-pin Athletes: Click the "Pin" button on the gymnast's tile in the squad list
Enable Pinning: Activate the "Pin Athletes" option in generation settings
Generate with Constraints: Tool optimizes around pinned gymnasts
Preserve Critical Assignments: Important placements remain unchanged
Flight Configuration
Subgroup Division Control:
Single Flight: All gymnasts in one group per squad
Dual Flights: Divide large squads into two subgroups
Minimum Flight Size:
Default: 10 gymnasts per flight
Automatic Division: Groups larger than minimum are split into two flights
Example: 12 gymnast squad → Flight 1: 6, Flight 2: 6 (if minimum is 10, stays as single flight)
Generation Algorithm
Scoring Factors:
Level Cohesion: How well gymnasts of similar levels are grouped
Team Integrity: How well gymnasts from same clubs stay together
Balance Achievement: How evenly priorities are met across all squads
Constraint Satisfaction: How well the solution meets size and structural requirements
Generation Performance
Efficiency Considerations:
Large Dataset Handling: Optimized for sessions with dozens of gymnasts
Real-time Results: Generation completes in seconds
Iterative Refinement: Can run multiple generations with different settings
No Manual Calculation: Eliminates need for complex manual organization
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