shantezhou/pokemon_data

Pokémon TCG Tournament Game Logs

Full game logs from an agent Pokémon TCG tournament ("Limited Card Battle"), 122,542 recorded games collected across 26 daily archives — an initial batch of 15 undated archives (top/, medium_high/) plus dated days 2026-07-21 → 2026-07-31 (days_0721_0731/). Both batches use the same per-day split rule and load together via the split config above.

Splits

Games in each daily archive were ranked by avg_score (per-agent average rating, ELO-like, ~1000–1230, higher = better):

Split	Games	Contents
top	18,200	the 700 highest-rated games from each archive (high-quality / eval set)
medium_high	104,342	every other game (pretraining set)

Episode IDs are globally unique across archives; the two splits are disjoint.

Columns

Column	Type	Description
episode_id	int64	unique game/episode id (original JSON filename)
agents	list<string>	the two agent names (info.TeamNames)
rewards	list<double>	final rewards per agent, e.g. [1, -1] (win/loss), [0, 0] (draw); may be null
json	string	the complete original game record, verbatim JSON

Each json value is one full game dump (~2–9 MB raw) with top-level keys: configuration, description, id, info, module_version, name, rewards, schema_version, specification, statuses, steps, title, version — including the complete step-by-step game trajectory under steps.

Usage

from datasets import load_dataset
import json

ds = load_dataset("shantezhou/pokemon_data", split="top", streaming=True)
for row in ds:
    game = json.loads(row["json"])
    print(row["episode_id"], row["agents"], row["rewards"])
    break

Parquet shards are zstd-compressed (~80x vs raw JSON); the full dataset is ~300 GB of raw JSON stored in a few GB of parquet.