CounterQuant CS2 Demos
The largest open collection of professional CS2 demo files (.dem)
Raw competitive Counter-Strike 2 demos collected from HLTV.org â focused on Tier 1 & Tier 2 matches.
Curated and maintained by Eimantas Kulbe (KEDevO) as part of the CounterQuant esports analytics project.
đ Dataset Overview
- Total Size: 3.74 TB+ (and continuously growing)
- Time Period: January 2024 â Present
- Focus: Tier 1 & Tier 2 professional matches
- Update Frequency: New demos added within 24â48 hours after matches
- Last Updated: May 20, 2026
đ¯ 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.
đ File Structure
bash
data/
âââ 2024/
â âââ tier1/
â âââ tier2/
âââ 2025/
â âââ tier1/
â âââ tier2/
âââ 2026/
âââ tier1/
âââ tier2/
Example filepath:
data/2025/tier1/2401337/vitality-vs-g2-inferno.dem
đ 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
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 â you are free to use, modify, and build upon it with proper attribution.