---
license: cc-by-4.0
task_categories:
- other
language:
- en
tags:
- cs2
- counter-strike
- esports
- demos
- game-theory
- sports-analytics
pretty_name: CounterQuant CS2 Demos
size_categories:
- 10K<n<100K
---

# CounterQuant CS2 Demos

Raw CS2 (Counter-Strike 2) demo files (.dem) collected from HLTV — the authoritative competitive CS2 demo repository.

**Curated and maintained by [Eimantas Kulbe](https://github.com/redrum88) as part of the [CounterQuant](https://cs2quant.kedevo.com) esports analytics project.**

## Dataset Goal

Provide the CS2 research community with the largest open-access collection of raw professional demo files, covering all competitive tiers from CS:GO's origin through CS2's present day.

**The philosophy:** squeeze every available demo into one place so anyone can preprocess, parse, or derive features in any way they want — no gatekeeping, no preprocessing lock-in.

## Coverage

| Tier | Description | Years | Status |
|------|-------------|-------|--------|
| T1 | Major/S-tier events (top 20 world teams) | 2024–present | Active — daily updates |
| T2 | A-tier events (top 50 teams) | 2024–present | Active — daily updates |
| T3 | B-tier / regional events | 2024–present | In progress |
| Historical | CS:GO T1/T2 (pre-2024) | 2012–2023 | Planned |

## File Structure

```
data/
  {year}/
    tier{N}/
      {match_id}/
        {map_name}.dem
```

Example:
```
data/2024/tier1/2378549/astralis-vs-natus-vincere-mirage.dem
data/2025/tier2/2401337/team-vitality-vs-g2-inferno.dem
```

## Usage

### Parse with demoparser2 (Python)

```python
from demoparser2 import DemoParser

parser = DemoParser("data/2024/tier1/2378549/astralis-vs-natus-vincere.dem")

# Player kill events
kills = parser.parse_event("player_death", player=["name", "team_name"])

# Round-by-round economy
rounds = parser.parse_ticks(["total_rounds_played", "cash_spent_t", "cash_spent_ct"])
```

### Download via huggingface_hub

```python
from huggingface_hub import snapshot_download

# Download all 2024 T1 demos
path = snapshot_download(
    repo_id="KEDevO/CounterQuant-CS2-Demos",
    repo_type="dataset",
    allow_patterns="data/2024/tier1/**",
    local_dir="./demos",
)
```

### Stream individual files

```python
from huggingface_hub import hf_hub_download

dem = hf_hub_download(
    repo_id="KEDevO/CounterQuant-CS2-Demos",
    repo_type="dataset",
    filename="data/2024/tier1/2378549/match.dem",
)
```

## What You Can Do With These Demos

- **Feature engineering**: extract round economy, positioning, utility, player rating
- **Model training**: win-probability, player rating, team strength models
- **Research**: CS2 game theory, tactical analysis, team dynamics
- **Statistics**: compute your own KDA, HLTV Rating 2.0, ADR, Impact
- **No restrictions**: raw bytes, parse however you like

## Update Schedule

New demos are added within 24–48 hours of match completion. The pipeline runs continuously across dedicated VPS infrastructure.

## Data Source

Demos sourced from [HLTV.org](https://www.hltv.org) — the official repository for professional CS2 match data. HLTV is the authoritative source for all competitive CS2/CS:GO results and replays.

## Citation

If you use this dataset in research, please cite:

```bibtex
@dataset{kulbe2026counterquant,
  author    = {Eimantas Kulbe},
  title     = {CounterQuant CS2 Demos},
  year      = {2026},
  publisher = {HuggingFace},
  url       = {https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Demos},
  note      = {Continuously updated professional CS2 demo dataset, all tiers, T1/T2/T3}
}
```

## License

[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — use freely with attribution to Eimantas Kulbe / CounterQuant.

## Related Resources

- [CounterQuant Platform](https://cs2quant.kedevo.com) — live CS2 analytics dashboard
- [CounterQuant Bronze Dataset](https://huggingface.co/datasets/KEDevO/CounterQuant-Bronze) — structured match/player/team data (JSON/Parquet)