README.md

---
license: cc-by-4.0
task_categories:
  - tabular-classification
  - tabular-regression
  - other
language:
  - en
tags:
  - cs2
  - counter-strike
  - esports
  - sports-analytics
  - competitive-gaming
  - match-results
  - player-stats
  - team-stats
  - event-data
  - elo
  - hltv
  - liquipedia
size_categories:
  - 100K<n<1M
pretty_name: CounterQuant CS2 Silver
---

# CounterQuant CS2 Silver

**Normalized, canonical professional CS2 match data — every match result, map score, and player stat line from 2012 to present.**

> ⭐ If you use this dataset in research, a product, or any publication,
> please **cite the author** (see [Citation](#citation) below).

Sourced from **HLTV.org** and **Liquipedia**, normalized into clean relational tables, and exported as Parquet. This is the structured "source of truth" layer of the CounterQuant data stack — match records, per-map scores, player performance statistics, event metadata, roster history, and map veto sequences.

Curated and maintained by **[Eimantas Kulbe (KEDevO)](https://counterquant.com)** as part of the **CounterQuant** esports intelligence platform.

---

## The CounterQuant Data Stack

Silver sits in the middle of a four-tier architecture:

| Tier | Dataset | Contents | Status |
|------|---------|----------|--------|
| **Raw demos** | [CounterQuant CS2 Demos](https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Demos) | Raw `.dem` files, parse them yourself | Live |
| **Bronze** | [CounterQuant CS2 Bronze](https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Bronze) | Tick-level events: kills, damages, flashes, utility | Live, growing |
| **Silver** ← *this dataset* | — | Match results, map scores, player stats, rosters, events | Staging for export |
| **Gold Lite** | [CounterQuant CS2 GoldLite](https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-GoldLite) | ML-ready features: Elo, form, head-to-head, event context | Staging for export |

Silver does **not** require demo parsing — it covers all professional matches regardless of demo availability.

---

## Dataset at a Glance

| Metric | Value |
|--------|-------|
| **Total matches in DB** | 119,445 |
| **2024 matches (first public release)** | 9,248 |
| **Match maps in DB** | 190,446 |
| **Player-map stat rows** | 379,459 |
| **Events tracked** | 8,639 |
| **Teams tracked** | 11,223 |
| **Professional players tracked** | 1,272 |
| **Roster records** | 2,695 |
| **Veto sequences** | 108,777 |
| **Year range** | 2012 – present |
| **Tiers** | T1, T2, T3 professional |
| **Sources** | HLTV.org, Liquipedia |
| **Format** | Parquet (Snappy compression) |
| **License** | CC BY 4.0 |

---

## Current State & Release Schedule

> **Silver is not yet published to HuggingFace as Parquet files.**
> The underlying data exists in CounterQuant's PostgreSQL database.
> Export and upload is in progress, with 2024 as the first public batch.

| Release | Year Coverage | Target Date | Notes |
|---------|--------------|-------------|-------|
| **v1 — 2024** | Jan 2024 – Dec 2024 | Q3 2026 | T1/T2/T3 · ~9,248 matches · first public release |
| **Backfill — 2012–2023** | 2012 – 2023 | Q4 2026 | Historical backfill once 2024 is complete |
| **v2 — 2025** | Jan 2025 – Dec 2025 | 2027 | 2-year delay policy — released when 2025 is complete |
| **2026 and beyond** | 2026+ | 2028+ | 2-year delay · minimum 2-year embargo |

**Why a 2-year delay for recent data?**
The Silver dataset is the foundation for the CounterQuant prediction pipeline. Recent data
is used internally for model training and edge detection. It is released to the public on a
2-year rolling window to protect proprietary signal while still giving the research community
access to a large, high-quality historical dataset.

---

## What's in Silver

Silver contains **eight normalized tables** exported as per-year Parquet files:

| Table | Description | Current DB rows |
|-------|-------------|-----------------|
| `matches` | One row per match series | 119,445 |
| `maps` | One row per map played within a match | 190,446 |
| `player_stats` | Per-player per-map stats (kills, ADR, KAST, rating) | 379,459 |
| `events` | Tournament/event metadata | 8,639 |
| `players` | Professional player directory | 1,272 |
| `teams` | Team directory | 11,223 |
| `rosters` | Player–team assignment history | 2,695 |
| `vetoes` | Map veto sequences | 108,777 |

**What Silver does NOT contain** (see other tiers):
- Tick-level kill/damage/flash events → [CounterQuant CS2 Bronze](https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Bronze)
- Elo ratings / ML feature vectors → [CounterQuant CS2 GoldLite](https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-GoldLite)
- Polymarket odds / market intelligence → Private, never released
- Model predictions / proprietary embeddings → Private, never released

---

## Planned File Structure

```
data/
├── matches/
│   ├── matches_2012_2019.parquet        # Historical batch
│   ├── matches_2020_2023.parquet        # Recent historical batch
│   ├── matches_2024.parquet             # First public release
│   └── matches_2025.parquet            # Released 2027
├── maps/
│   ├── maps_2024.parquet
│   └── ...
├── player_stats/
│   ├── player_stats_2024.parquet
│   └── ...
├── events/
│   ├── events_2024.parquet
│   └── events_all.parquet               # Full event directory
├── players.parquet                      # Reference table, all time
├── teams.parquet                        # Reference table, all time
├── rosters/
│   ├── rosters_2024.parquet
│   └── ...
└── vetoes/
    ├── vetoes_2024.parquet
    └── ...
```

---

## Schema Reference

### `matches_YYYY.parquet`

One row per match series (bo1, bo2, bo3, bo5).

| Column | Type | Description |
|--------|------|-------------|
| `match_id` | int64 | HLTV match ID |
| `event_id` | int64 | Event this match belongs to |
| `event_name` | string | Event name (denormalized for convenience) |
| `team1_id` | int64 | HLTV team ID |
| `team1_name` | string | Team 1 name (denormalized) |
| `team2_id` | int64 | HLTV team ID |
| `team2_name` | string | Team 2 name (denormalized) |
| `winner_id` | int64 | HLTV team ID of the winner (null if not completed) |
| `winner_name` | string | Winner name (denormalized) |
| `format` | string | `bo1`, `bo2`, `bo3`, `bo5` |
| `team1_maps_won` | int16 | Maps won by team 1 |
| `team2_maps_won` | int16 | Maps won by team 2 |
| `date` | date | Match date (UTC) |
| `tier` | int16 | 1 = Major-level, 2 = Challenger, 3 = Regional |
| `is_lan` | bool | True if played on LAN |
| `event_stage` | string | Group stage, playoffs, grand final, etc. |

---

### `maps_YYYY.parquet`

One row per individual map within a match series.

| Column | Type | Description |
|--------|------|-------------|
| `map_id` | int64 | Internal map ID |
| `match_id` | int64 | Parent match ID |
| `map_number` | int16 | Map index within the series (1, 2, 3…) |
| `map_name` | string | CS2 map name (`de_mirage`, `de_dust2`, etc.) |
| `team1_id` | int64 | Team 1 HLTV ID |
| `team2_id` | int64 | Team 2 HLTV ID |
| `winner_id` | int64 | ID of the map winner |
| `team1_score` | int16 | Final score team 1 |
| `team2_score` | int16 | Final score team 2 |
| `team1_ct_score` | int16 | Team 1 rounds won on CT side |
| `team2_ct_score` | int16 | Team 2 rounds won on CT side |
| `team1_t_score` | int16 | Team 1 rounds won on T side |
| `team2_t_score` | int16 | Team 2 rounds won on T side |
| `went_overtime` | bool | True if map went to overtime |
| `pick_team_id` | int64 | Which team picked this map (null for decider) |
| `pick_type` | string | `pick`, `ban_remaining` (decider) |

---

### `player_stats_YYYY.parquet`

Per-player performance statistics for each map played.

| Column | Type | Description |
|--------|------|-------------|
| `stat_id` | int64 | Internal stat row ID |
| `match_id` | int64 | Match ID |
| `map_id` | int64 | Map ID |
| `map_name` | string | CS2 map name (denormalized) |
| `player_id` | int64 | Internal player ID |
| `player_ign` | string | In-game name at time of match |
| `steam64_id` | int64 | Steam 64-bit ID (null if unknown) |
| `team_id` | int64 | Team ID the player was on |
| `kills` | int16 | Total kills |
| `deaths` | int16 | Total deaths |
| `assists` | int16 | Total assists |
| `headshot_kills` | int16 | Headshot kills |
| `kast` | float32 | Kill/Assist/Survived/Traded percentage (0–1) |
| `adr` | float32 | Average damage per round |
| `rating_2` | float32 | HLTV Rating 2.0 |
| `opening_kills` | int16 | Opening duels won |
| `opening_deaths` | int16 | Opening duels lost |
| `clutches_won` | int16 | 1vX clutch rounds won |
| `clutches_attempted` | int16 | 1vX clutch rounds attempted |

---

### `events_YYYY.parquet`

| Column | Type | Description |
|--------|------|-------------|
| `event_id` | int64 | HLTV event ID |
| `name` | string | Full event name |
| `short_name` | string | Abbreviated name |
| `start_date` | date | Event start date |
| `end_date` | date | Event end date |
| `prize_pool_usd` | int32 | Prize pool in USD (null if unknown) |
| `location` | string | City, Country |
| `country_code` | string | ISO 3166-1 alpha-1 country code |
| `tier` | int16 | HLTV event tier |
| `organizer` | string | Organizing body (ESL, PGL, BLAST, etc.) |
| `is_lan` | bool | True if LAN event |
| `event_type` | string | `major`, `iem`, `epl`, `qualifier`, `regional`, etc. |

---

### `players.parquet` (reference, all years)

| Column | Type | Description |
|--------|------|-------------|
| `player_id` | int64 | Internal player ID |
| `ign` | string | Current in-game name |
| `real_name` | string | Player's real name |
| `nationality` | string | Country code |
| `birth_year` | int16 | Year of birth |
| `hltv_id` | int64 | HLTV player profile ID |
| `steam64_id` | int64 | Steam 64-bit ID |
| `liquipedia_id` | string | Liquipedia profile slug |

---

### `teams.parquet` (reference, all years)

| Column | Type | Description |
|--------|------|-------------|
| `team_id` | int64 | Internal team ID |
| `name` | string | Team name |
| `hltv_id` | int64 | HLTV team ID |
| `region` | string | Region (EU, NA, CIS, Asia, SA, OCE) |

---

### `rosters_YYYY.parquet`

Player–team assignment history. One row per player–team stint.

| Column | Type | Description |
|--------|------|-------------|
| `player_id` | int64 | Player ID |
| `team_id` | int64 | Team ID |
| `joined_date` | date | Approximate roster join date (null if unknown) |
| `role` | string | `rifler`, `awper`, `igl`, `support`, `lurker` |

---

### `vetoes_YYYY.parquet`

Map veto sequences for bo3 and bo5 matches.

| Column | Type | Description |
|--------|------|-------------|
| `match_id` | int64 | Match ID |
| `veto_idx` | int16 | Step index (1, 2, 3…) |
| `team_id` | int64 | Team making the veto action |
| `action` | string | `ban`, `pick`, `left` (random remaining map) |
| `map_name` | string | CS2 map name |

---

## Quick Start (Preview)

Once 2024 data is published, loading will look like this:

```python
import polars as pl
from huggingface_hub import hf_hub_download

# Download 2024 match results
path = hf_hub_download(
    repo_id="KEDevO/CounterQuant-CS2-Silver",
    repo_type="dataset",
    filename="data/matches/matches_2024.parquet",
)
matches = pl.read_parquet(path)
print(f"2024 matches: {len(matches)}")

# Download 2024 player stats
stats_path = hf_hub_download(
    repo_id="KEDevO/CounterQuant-CS2-Silver",
    repo_type="dataset",
    filename="data/player_stats/player_stats_2024.parquet",
)
stats = pl.read_parquet(stats_path)
```

```python
import duckdb

# Top players by average rating across 2024 Tier 1 maps
conn = duckdb.connect()
result = conn.execute("""
    SELECT
        s.player_ign,
        COUNT(*) AS maps_played,
        ROUND(AVG(s.rating_2), 3) AS avg_rating,
        ROUND(AVG(s.adr), 1) AS avg_adr,
        ROUND(AVG(s.kast) * 100, 1) AS kast_pct
    FROM read_parquet('data/player_stats/player_stats_2024.parquet') s
    JOIN read_parquet('data/matches/matches_2024.parquet') m USING (match_id)
    WHERE m.tier = 1
    GROUP BY s.player_ign
    HAVING maps_played >= 20
    ORDER BY avg_rating DESC
    LIMIT 20
""").fetchdf()
print(result)
```

```python
# Map pool analysis — team win rates per map in 2024
result = conn.execute("""
    SELECT
        t.name AS team,
        s.map_name,
        COUNT(*) AS maps_played,
        SUM(CASE WHEN mp.winner_id = mp.team1_id THEN 1 ELSE 0 END) AS wins,
        ROUND(SUM(CASE WHEN mp.winner_id = mp.team1_id THEN 1.0 ELSE 0.0 END) / COUNT(*), 3) AS win_rate
    FROM read_parquet('data/maps/maps_2024.parquet') mp
    JOIN read_parquet('data/teams.parquet') t ON t.team_id = mp.team1_id
    GROUP BY t.name, mp.map_name
    HAVING maps_played >= 5
    ORDER BY win_rate DESC
""").fetchdf()
```

---

## Data Collection Methodology

### Sources
- **HLTV.org** — Primary source for match results, map scores, player statistics, events, and match metadata. Scraped via authenticated HTTP requests with proxy rotation. Match pages are scraped with Puppeteer to extract structured stat tables.
- **Liquipedia** — Supplementary source for player real names, nationalities, birth years, event metadata, and roster history. Used to fill gaps in HLTV data.

### Normalization
All data is stored in a normalized PostgreSQL schema on CounterQuant's infrastructure before export to Parquet. Entity resolution (matching HLTV IDs with Liquipedia IDs, resolving player name changes, handling team rebrandings) is handled during ingestion.

### Player rating
The `rating_2` column uses HLTV's proprietary Rating 2.0 formula as scraped from match pages. CounterQuant does not independently compute Rating 2.0 — the value is the one HLTV publishes on their match statistics pages.

### Known limitations
- **Rating gaps**: Not all historical match pages have complete per-player rating data. Rows with missing rating have `rating_2 = null`.
- **Roster dating**: Roster join dates are approximate. Some early transfers have only month-level precision.
- **Overnight matches**: A small number of matches crossing midnight UTC may have off-by-one dates.
- **Team name changes**: Team names are recorded at time of match. Historical names (NaVi vs Natus Vincere, etc.) are normalized to current canonical names where possible.

---

## Match Coverage by Year

| Year | Matches | Maps | Tier 1 Fraction | Notes |
|------|---------|------|-----------------|-------|
| 2024 | ~9,248 | ~18,500 | ~20% | First public release — Q3 2026 |
| 2025 | ~10,336 | ~20,600 | ~20% | Released 2027 (2-year delay) |
| 2023 | ~10,200 | ~20,400 | ~20% | Backfill — included in 2012–2023 batch |
| 2020–2022 | ~25,000 | ~50,000 | ~15% | Backfill |
| 2015–2019 | ~30,000 | ~60,000 | ~10% | Backfill, CS:GO era |
| 2012–2014 | ~12,000 | ~24,000 | ~8% | Backfill, early CS:GO |

*Historical match counts are estimates based on current HLTV coverage. Exact counts will be published with each data release.*

---

## Related Datasets

| Dataset | Contents | Relationship |
|---------|----------|--------------|
| [CounterQuant CS2 Demos](https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Demos) | Raw `.dem` files | Source layer — parse yourself for custom event extraction |
| [CounterQuant CS2 Bronze](https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Bronze) | Tick-level kill/damage/flash/utility events | Event-level layer — join on `match_id` to enrich Silver stats |
| [CounterQuant CS2 GoldLite](https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-GoldLite) | Elo ratings, form, head-to-head, event context features | Derived from Silver — ML-ready feature tables |
| [CounterQuant Platform](https://counterquant.com) | Live dashboard, player ratings, predictions, API | Production platform built on the full data stack |
| [CounterQuant API](https://counterquant.com/api/docs/) | REST API for real-time and historical data access | API access to Silver and Gold data layers |

---

## Data Release Policy

| Layer | Public? | Timeline |
|-------|---------|----------|
| **Silver 2024** | ✅ CC BY 4.0 | Q3 2026 |
| **Silver 2012–2023** | ✅ CC BY 4.0 | Q4 2026 (backfill) |
| **Silver 2025** | ✅ CC BY 4.0 | 2027 (2-year delay) |
| **Silver 2026+** | ⏳ Delayed | 2028+ (2-year delay) |
| Elo / feature vectors | See GoldLite | Partial public, demo-derived features private |
| Market intelligence | ❌ Private | Never released |
| Model predictions | ❌ Private | Never released |
| Proprietary embeddings | ❌ Private | Never released |

---

## Citation

If you use this dataset in research, analytics products, or publications, please cite:

### BibTeX

```bibtex
@dataset{kulbe2026counterquantsilver,
  author       = {Eimantas Kulbe},
  title        = {CounterQuant CS2 Silver: Normalized Professional CS2 Match \& Player Statistics},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Silver},
  note         = {Canonical match results, per-map scores, player statistics,
                  event metadata, rosters, and veto sequences for professional
                  CS2 matches from 2012 to present. Sourced from HLTV and Liquipedia.}
}
```

### APA

Kulbe, E. (2026). *CounterQuant CS2 Silver: Normalized Professional CS2 Match & Player Statistics* [Dataset]. Hugging Face. https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Silver

### Acknowledgement (for papers/articles)

> Match results and player statistics sourced from *CounterQuant CS2 Silver* (Kulbe, 2026), available at https://huggingface.co/datasets/KEDevO/CounterQuant-CS2-Silver under CC BY 4.0.

---

## License

**Creative Commons Attribution 4.0 International (CC BY 4.0)**

You are free to:
- **Share** — copy and redistribute the material in any medium or format
- **Adapt** — remix, transform, and build upon the material for any purpose, including commercial

Under the condition that you **give appropriate credit** to **Eimantas Kulbe** and link back to this dataset.

Full license text: https://creativecommons.org/licenses/by/4.0/

---

*Dataset maintained by [Eimantas Kulbe](https://counterquant.com). For questions, issues, or collaboration: open a discussion on this dataset page or reach out via [CounterQuant](https://counterquant.com).*