README.md

---
license: cc-by-4.0
task_categories:
- other
language:
- en
tags:
- cs2
- counter-strike
- esports
- demos
- sports-analytics
- game-theory
- esports-research
pretty_name: CounterQuant CS2 Demos
size_categories:
- n>1T
---

# CounterQuant CS2 Demos

**The largest open collection of professional CS2 demo files (.dem)**

Raw competitive Counter-Strike 2 demos collected from HLTV.org — focused on Tier 1 & Tier 2 matches.

Curated and maintained by **[Eimantas Kulbe (KEDevO)](https://cs2quant.kedevo.com)** as part of the **CounterQuant** esports analytics project.

---

## 📊 Dataset Overview

- **Total Size**: **3.74 TB+** (and continuously growing)
- **Time Period**: January 2024 – Present
- **Focus**: Tier 1 & Tier 2 professional matches
- **Update Frequency**: New demos added within 24–48 hours after matches
- **Last Updated**: May 20, 2026

---

## 🎯 Goal & Philosophy

To provide the global research, analytics, and esports community with **unrestricted access** to high-quality professional CS2 demo files.

**Philosophy**: Raw data only. No gatekeeping. Parse it, analyze it, and build whatever you want.

---

## 📁 File Structure

```bash
data/
├── 2024/
│   ├── tier1/
│   └── tier2/
├── 2025/
│   ├── tier1/
│   └── tier2/
└── 2026/
    ├── tier1/
    └── tier2/
```

**Example filepath**:
`data/2025/tier1/2401337/vitality-vs-g2-inferno.dem`

---

## 🚀 Quick Start

### Download specific year + tier (Recommended)

```python
from huggingface_hub import snapshot_download

# Example: Download all 2025 Tier 1 demos
snapshot_download(
    repo_id="KEDevO/CounterQuant-CS2-Demos",
    repo_type="dataset",
    allow_patterns="data/2025/tier1/**",
    local_dir="./cs2_demos",
    resume_download=True
)
```

### Parse a demo

```python
from demoparser2 import DemoParser

parser = DemoParser("data/2025/tier1/2401337/vitality-vs-g2-inferno.dem")

kills = parser.parse_event("player_death")
rounds = parser.parse_ticks(["total_rounds_played", "cash_spent_t", "cash_spent_ct"])
```

---

## What You Can Build

- Advanced win probability & clutch models
- Player chemistry & synergy analysis
- Utility usage and trade efficiency metrics
- New generation rating systems
- Tactical & game-theory research
- ML models for movement, positioning, and decision making

---

## Related Projects

- **[CounterQuant Bronze](https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Bronze)** — Structured & parsed version (Parquet/JSON)
- **[CounterQuant Platform](https://counterquant.com)** — Live analytics dashboard & API

---

## Citation

```bibtex
@dataset{kulbe2026counterquant,
  author       = {Eimantas Kulbe},
  title        = {CounterQuant CS2 Demos},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Demos},
  note         = {Continuously updated professional CS2 demo collection}
}
```

---

## License

This dataset is licensed under **CC BY 4.0** — you are free to use, modify, and build upon it with proper attribution.

---