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CS2 Hack Combat Intelligence

Advanced Counter-Strike 2 gameplay intelligence laboratory focused on aim consistency, spatial awareness, combat encounters, positioning, utility usage and competitive match analysis.

The project organizes gameplay observations into structured datasets and performance reports for studying patterns across matches.

🧠 Architecture

                    ┌─────────────────────┐
                    │     CS2 Match       │
                    │       Data          │
                    └──────────┬──────────┘
                               │
          ┌────────────────────┼────────────────────┐
          │                    │                    │
          ▼                    ▼                    ▼
    ┌───────────┐        ┌───────────┐        ┌───────────┐
    │    AIM    │        │  COMBAT   │        │   MAP     │
    │ ANALYSIS  │        │ ANALYSIS  │        │ ANALYSIS  │
    └─────┬─────┘        └─────┬─────┘        └─────┬─────┘
          │                    │                    │
          └────────────────────┼────────────────────┘
                               ▼
                    ┌─────────────────────┐
                    │  Intelligence Core  │
                    └──────────┬──────────┘
                               ▼
                    ┌─────────────────────┐
                    │ Performance Report  │
                    └─────────────────────┘

🎯 Core Objectives

• Analyze aim consistency
• Track combat encounters
• Study positioning
• Visualize player movement
• Analyze utility usage
• Compare rounds and matches
• Identify recurring mistakes
• Generate performance statistics

🔥 Aim Intelligence

The aim module converts recorded match statistics into measurable performance indicators.

{
  "match": "CS2-2026-184",
  "rounds": 24,
  "shots": 742,
  "hits": 418,
  "accuracy": 56.33,
  "reaction_score": 84.7,
  "tracking_score": 86.2,
  "target_switch_score": 79.8
}

Metrics

• Accuracy
• Hit consistency
• Reaction timing
• Target switching
• Engagement duration
• Crosshair placement
• First-shot performance

👁️ Spatial Intelligence

A radar-style visualization layer can represent recorded positions and important match events.

┌──────────────────────────────────┐
│                                  │
│        E                 E       │
│         \               /       │
│          \      A      /        │
│           \     │     /         │
│            \    ●    /          │
│                 │               │
│       U─────────┼─────────U     │
│                 │               │
│          R      │      R        │
│                                  │
└──────────────────────────────────┘

● Player
E Enemy Encounter
A Area Control
U Utility Event
R Rotation

The visualization is designed for reviewing recorded gameplay rather than interacting with the live game client.

⚔️ Combat Intelligence

Combat encounters can be classified by distance, duration, outcome and decision type.

Metric	Result
Encounters	21
Successful Engagements	15
Average Duration	4.8s
Accuracy	56.3%
First-Shot Success	68.7%
Positioning Score	89.4%

💣 Utility Analysis

Track the effectiveness of utility usage across rounds.

Utility
   │
   ├── Smoke
   │     ├── Site Entry
   │     └── Retake
   │
   ├── Flash
   │     ├── Entry
   │     └── Support
   │
   ├── HE
   │     └── Damage
   │
   └── Molotov
         ├── Denial
         └── Area Control

Example dataset:

{
  "smokes": 8,
  "flashes": 11,
  "he_grenades": 4,
  "molotovs": 3,
  "successful_utility_events": 19,
  "utility_efficiency": 82.6
}

🗺️ Round Intelligence

Every round can be represented as a sequence of decisions:

ROUND START
     │
     ▼
BUY PHASE
     │
     ▼
POSITIONING
     │
     ▼
UTILITY
     │
     ▼
FIRST CONTACT
     │
     ├──────► ADVANTAGE
     │
     ├──────► DISADVANTAGE
     │
     └──────► ROTATION
                │
                ▼
             ENDGAME

📊 Match Score

The intelligence engine combines multiple performance categories.

                 MATCH SCORE
                      │
       ┌──────────────┼──────────────┐
       │              │              │
       ▼              ▼              ▼
      AIM           COMBAT          MAP
       │              │              │
       └──────────────┼──────────────┘
                      │
                      ▼
                   UTILITY
                      │
                      ▼
                 DECISIONS
                      │
                      ▼
              FINAL PERFORMANCE

📈 Example Report

CS2 MATCH REPORT
────────────────────────────

Match:              #184
Rounds:             24

Aim Score:          84.7
Combat Score:       88.9
Map Score:          91.2
Utility Score:      82.6
Decision Score:     86.4

Overall Score:      86.8

Strongest Area:
Positioning

Improvement Area:
Utility timing during
mid-round rotations.

🔬 Analysis Pipeline

Recorded Match
      │
      ▼
Event Extraction
      │
      ├── Aim Events
      ├── Combat Events
      ├── Position Events
      ├── Utility Events
      └── Round Events
      │
      ▼
Normalization
      │
      ▼
Metric Calculation
      │
      ▼
Pattern Detection
      │
      ▼
Performance Scoring
      │
      ▼
Match Report

📁 Project Structure

cs2-hack-combat-intelligence/
│
├── analytics/
│   ├── aim/
│   ├── combat/
│   ├── positioning/
│   ├── utility/
│   └── rounds/
│
├── datasets/
│   ├── matches/
│   ├── rounds/
│   └── sessions/
│
├── visualization/
│   ├── radar/
│   ├── heatmaps/
│   └── dashboards/
│
├── reports/
│   ├── match-report.md
│   └── performance-report.md
│
├── models/
│   └── match-performance.json
│
└── README.md

🚀 Roadmap

• Match data model
• Aim analysis
• Combat analysis
• Positioning metrics
• Utility analysis
• Radar visualization
• Performance scoring
• Interactive round replay
• Advanced heatmaps
• Multi-match comparison
• Player progression dashboard
• Automated performance reports

📌 Research Focus

The project can be used to compare:

• Different maps
• Different weapon categories
• Different round types
• Attack and defense performance
• Entry versus support roles
• Utility-heavy versus aim-heavy rounds
• Individual versus team decisions

⚠️ Scope

This repository is intended for gameplay analysis, visualization and research. It does not implement operational aimbots, wallhacks, ESP overlays, injectors, game-memory manipulation, exploits, anti-cheat bypasses or automated online gameplay.

📜 License

MIT License.

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