wolframko/pipes-lie-embargo-dominus

Betty Dota 2 Pro Matches Dataset

9,388 professional Dota 2 matches parsed from replay files with per-second game state snapshots and combat log events.

Dataset Structure

matches.parquet (9,388 rows)

One row per match. Contains metadata, STRATZ player statistics, and draft data.

Column	Type	Description
match_id	int64	Dota 2 match ID
league_name	string	Tournament name
league_tier	string	PROFESSIONAL, MAJOR, etc.
duration_sec	int64	Match duration in seconds
radiant_win	bool	True if Radiant won
radiant_team_id / dire_team_id	int64	Team IDs
p0..p9_hero_id	int64	Hero ID per player (STRATZ)
p0..p9_kills/deaths/assists	int64	Final KDA per player
p0..p9_gpm/xpm/networth	int64	Economy stats per player
p0..p9_gpm_per_min	list[int]	Gold per minute time-series
p0..p9_networth_per_min	list[int]	Net worth per minute
p0..p9_hero_damage_per_min	list[int]	Hero damage per minute
stratz_pb_hero_id	list[int]	STRATZ pick/ban hero IDs
replay_pb_hero_id	list[int]	Replay-parsed pick/ban hero IDs

ticks/ (189,120,930 rows)

One row per game-tick per hero. ~1,500 ticks per match x 10 heroes. Per-second snapshots of full game state.

Column	Type	Description
match_id	int64	Match ID
tick	int32	Raw tick number
game_time	float	Game time in seconds
slot	int8	Player slot (0-9)
hero	string	Hero internal name
x, y	float	Map position coordinates
hp, max_hp	int32	Current and max health
mana, max_mana	float	Current and max mana
gold	int32	Current gold
net_worth	int32	Total net worth
xp	int32	Total experience
kills, deaths, assists	int16	KDA at this moment
last_hits, denies	int16	CS at this moment
level	int8	Hero level
str, agi, int_	float	Attribute values
armor	float	Armor value
move_speed	int16	Movement speed
item_0..item_5	string	Items in 6 inventory slots

events/ (295,810,843 rows)

One row per combat log event. Damage, kills, gold gains, XP, healing, purchases.

Column	Type	Description
match_id	int64	Match ID
tick	int32	Raw tick number
game_time	float	Game time in seconds
timestamp	float	Exact event timestamp
event_type	string	DOTA_COMBATLOG_DAMAGE, _DEATH, _GOLD, _HEAL, _PURCHASE, _XP
source	string	Source entity (e.g. npc_dota_hero_invoker)
target	string	Target entity
value	int32	Damage/gold/xp amount
item	string	Item name (for PURCHASE events)

Statistics

• Matches: 9,388 professional games from 2025
• Ticks: 189,120,930 per-second hero state snapshots
• Events: 295,810,843 combat log entries
• Size: 5.97 GB compressed Parquet (from 103 GB JSON)
• Source: Valve replay files (.dem) parsed with manta + STRATZ API metadata

Usage

from datasets import load_dataset

# Load matches metadata
matches = load_dataset("wolframko/pipes-lie-embargo-dominus", data_files="matches.parquet", split="train")

# Load ticks (large - use streaming)
ticks = load_dataset("wolframko/pipes-lie-embargo-dominus", data_files="ticks/*.parquet", split="train", streaming=True)

# Load events
events = load_dataset("wolframko/pipes-lie-embargo-dominus", data_files="events/*.parquet", split="train", streaming=True)

import pandas as pd

# Quick analysis with pandas
matches_df = pd.read_parquet("hf://datasets/wolframko/pipes-lie-embargo-dominus/matches.parquet")
print(f"Matches: {len(matches_df)}, Radiant winrate: {matches_df.radiant_win.mean():.1%}")

Data Pipeline

1. Fetch: Match IDs from STRATZ GraphQL API (pro leagues 2025)
2. Download: Replay files (.dem.bz2) from Valve CDN
3. Parse: Per-second hero states + combat log via manta (Go)
4. Enrich: Player/team stats from STRATZ API
5. Convert: JSON to Parquet with full validation

License

MIT