Matchmaking Engine

A high-performance, algorithm-driven matchmaking engine inspired by systems used in competitive games such as Valorant, Chess.com. Built entirely in Java, the engine focuses on data structures, algorithmic design, and fair match creation, with a responsive Swing UI to visualize the matchmaking process in real time.

This project is intentionally framework-free to highlight pure DSA + system logic without relying on databases or networking layers.

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Overview

The engine simulates a real-world matchmaking queue:

• Players join a pool with a rating and timestamp.
• The system identifies the longest-waiting player as the seed.
• A dynamic skill window expands over time to ensure fairness and avoid infinite waiting.
• The engine selects the closest candidates by rating.
• Once enough players are found, balanced teams are created using optimal or greedy algorithms.
• The UI displays active players, matches formed, and internal decisions.

This project demonstrates how competitive games build fair and scalable matchmaking systems using clean algorithmic logic.

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Features

• Dynamic skill-based matchmaking
• Search window expansion based on wait time
• Closest-K player selection using rating distance
• Advanced team balancing via:
  • Optimal bitmask partitioning (for small groups)
  • Greedy load-balancing heuristic (for large groups)
• Efficient player indexing using:
  • TreeMap for sorted skill ranges
  • PriorityQueue for longest-wait queries
  • HashMap for O(1) lookup
• Responsive Swing UI (non-blocking using SwingWorker)
• Real-time player queue visualization
• Match logs printed with team ratings and composition

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Data Structures Used

Purpose	Data Structure	Reason
Skill-based lookup	TreeMap	Efficient sorted rating ranges & submap queries
Longest-wait selection	PriorityQueue	Min-heap ordering by join time
Direct access	HashMap	O(1) existence checks & removals
Candidate selection	Sorting & lists	K-closest search and deterministic grouping
Team balancing	Bitmask enumeration	Optimal team splits for small N
Fallback balancing	Greedy heuristic	Fast balancing for large groups

This combination mirrors real matchmaking server internals.

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How It Works — Full Flow

1. Players join the matchmaking pool (rating + timestamp).
2. The engine picks the longest-waiting player as the seed.
3. A search window (minRating to maxRating) defines acceptable skill matches.
4. If the window yields too few players, it expands gradually.
5. A set of closest-K candidates is selected.
6. Players are removed from the pool.
7. Teams are balanced using either:
   • Exact optimal partitioning (bitmask search)
   • Greedy difference-minimizing allocation
8. The completed Match object is displayed in the UI.

This flow is highly extensible and mirrors real MMR-based games.

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User Interface (Swing)

The Swing UI provides:

• Player entry fields (ID + Rating)
• Adjustable:
  • Match Size
  • Window Expansion Amount
• Auto-match toggle
• Live queue visualization
• Scrollable match logs
• Background match processing for smooth responsiveness

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Project Structure

src/
└── skillmatch/
├── Player.java
├── PlayerPool.java
├── MatchMaker.java
├── TeamBalancer.java
├── Match.java
├── Team.java
└── Main.java

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Goal

The goal of this project is to showcase:

• Clean algorithmic thinking
• Strong understanding of data structures
• Real-world system design principles
• Efficient Java programming
• A fully functional matchmaking simulator without relying on external systems

A great project for resumes, system design interviews, and algorithms portfolios.

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Future Enhancements (Optional Ideas)

• Glicko/Elo rating updates after each match
• Persistent storage using JSON or files
• Graph-based skill clustering
• Live rating histogram visualization in Swing
• Simulation mode generating thousands of players

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Demo Preview

Below is a visual demonstration of the matchmaking engine in action, showing player queue input, real-time match formation, and team balancing inside the Swing UI.