gptilt/lol-esports-entities

GPTilt: League of Legends Esports Directory

This dataset is part of the GPTilt open-source initiative, aimed at democratizing access to high-quality LoL data for research and analysis, fostering public exploration, and advancing the community's understanding of League of Legends through data science and AI. It provides a clean, canonical reference for the people and organizations of competitive League of Legends.

By using this dataset, users accept full responsibility for any consequences arising from its use. GPTilt assumes no liability for any damages that may result. Users are strongly encouraged to review the ["Uses"](#uses) section—particularly the ["Out-of-Scope Use"](#out-of-scope-use) subsection—for guidance.

Getting Started

First, install Hugging Face's datasets package:

pip install datasets

Now, you can load the dataset!

from datasets import load_dataset

# Specify just the config_name / table
dataset = load_dataset("gptilt/lol-esports-entities", name="public_figures")

# Or include the split!
dataset = load_dataset("gptilt/lol-esports-entities", name="public_figures", split="train")

Dataset Summary

A periodically-refreshed directory of League of Legends esports public figures and teams, plus a unified entity alias index for resolving the many names each entity is known by. Built from Leaguepedia (lol.fandom.com) via its structured Cargo query API. It provides a clean, canonical reference for linking esports people and organizations across heterogeneous data sources, and for normalizing the many names each entity is known by.

Dataset Structure

The data is structured into 3 tables, each exposed as a separate config:

• —`public_figures`: One row per esports public figure (pro players, ex-pros, coaches, analysts, casters, owners). Identity is person_id, the canonical Leaguepedia page key. Includes canonical_name, display_name, role, region, retirement status, and the source wiki URL.

• —`teams`: One row per esports organization/team, keyed by team_id (the canonical Leaguepedia page key). Includes canonical_name, region, location, and a disbanded flag.

• —`entity_aliases`: A unified alias index. Every known surface name maps to a canonical entity via entity_id, with:
• —entity_type — person or team, distinguishing which directory the entity_id points at.
• —alias_type — where the name came from: ign (in-game name), real_name, romanization, other (wiki redirects/alt-names) for people; short (name/abbreviation) for teams.

All three tables share source and source_url columns linking each row back to its Leaguepedia page. To resolve a name to an entity, match on entity_aliases.alias, read entity_type/entity_id, then join to public_figures.person_id or teams.team_id accordingly.

Each table is a single, unpartitioned snapshot (one train split per config).

Dataset Creation

Curation Rationale

Esports data is scattered across match histories, broadcasts, and community sites, and the same person or team appears under many different names (in-game names, real names, romanizations, abbreviations, wiki redirects). This dataset was created to provide a stable, canonical directory of esports public figures and teams, together with a unified entity alias index that makes it possible to resolve those many names back to a single entity — a prerequisite for linking and normalizing esports data across sources.

Source Data

Data Collection and Processing

The source data originates from **Leaguepedia** (the League of Legends esports wiki), accessed through its structured **Cargo** query API.

1. 1.Extraction: The Players, PlayerRedirects, and Teams Cargo tables are queried in full on a weekly schedule.
2. 2.Raw Storage: Raw Cargo responses (JSON) are snapshotted to object storage, partitioned by week.
3. 3.Cleaning & Unification: Records are deduplicated on their canonical Leaguepedia page key; people (from Players) and teams (from Teams) become the public_figures and teams tables. All known names — in-game names, real names, romanizations, PlayerRedirects alt-names, and team abbreviations — are folded into a single entity_aliases index, where people and teams share one schema discriminated by entity_type. Boolean flags are normalized, and a source_url back to the originating wiki page is reconstructed for every entity. The clean layer is overwrite-only — each run reflects the latest snapshot of Leaguepedia, not historical state.
4. 4.Output: Each clean table is written to Parquet and published here as a separate config.

Who are the source data producers?

The underlying data is authored by the Leaguepedia community of volunteer editors, documenting the careers of competitive League of Legends players and the histories of esports organizations. The dataset curators are the contributors to the GPTilt project, who perform the automated collection, cleaning, and unification steps described above.

Personal and Sensitive Information

This dataset describes real, identifiable people — professional players, coaches, analysts, casters, and team staff — and includes real names, in-game names, nationalities/regions, and career status. All of this information is sourced from Leaguepedia, where it is already published about individuals in their public, professional capacity as competitors and public figures.

No private contact information (emails, addresses, phone numbers) is collected. Users must handle this data responsibly and in accordance with Leaguepedia's licensing and privacy terms and applicable data-protection law. This data must not be used to harass, dox, profile, or otherwise harm the individuals it describes. See the "Out-of-Scope Use" section.

Bias, Risks, and Limitations

• —Coverage Bias: Leaguepedia's depth varies by region and competitive tier. Major regions and tier-1 competition are documented far more completely than minor regions and lower tiers, so the directory is not an even sample of all esports participants.
• —Snapshot-Only: The clean layer is overwrite-only — it reflects the latest state of Leaguepedia at collection time, with no history retained. Fields like active_from/active_to are placeholders here and will be populated in a future curated (SCD Type 2) layer.
• —Editorial Lag: As a community wiki, Leaguepedia may lag behind real-world roster changes, retirements, or rebrands, and may contain occasional errors or gaps.
• —Name Ambiguity: A single surface name can map to more than one entity (e.g. a recycled in-game name). The entity_aliases index keeps every mapping and discriminates by entity_type, but consumers must expect one-to-many matches.

Recommendations

• —Treat the data as a best-effort snapshot of a community wiki, not an authoritative or complete registry.
• —When matching on entity_aliases, disambiguate using `entity_type` and handle multiple candidate entities for the same string.
• —Acknowledge the coverage bias toward major regions/tiers when reporting aggregate results.

Uses

Disclaimer

This dataset is derived from [Leaguepedia](https://lol.fandom.com/), a Fandom-hosted community wiki. GPTilt is not endorsed by Fandom, Leaguepedia, or Riot Games, and does not reflect their views or opinions. League of Legends and Riot Games are trademarks or registered trademarks of Riot Games, Inc. League of Legends © Riot Games, Inc.

License

This dataset is licensed under `cc-by-sa-3.0`. Because it is derived from Leaguepedia content, redistribution and derivative works must provide attribution to Leaguepedia and remain under compatible share-alike terms. Every row carries source and source_url columns linking back to the originating wiki page to support attribution.

Direct Use

This dataset is intended for non-commercial research, data analysis, and tooling aimed at understanding and organizing competitive League of Legends data. Suitable uses include:

• —Entity resolution — linking players and teams across match data, broadcasts, and other esports datasets.
• —Name normalization — resolving in-game names, real names, romanizations, and abbreviations to a canonical entity.
• —Descriptive analysis of the competitive landscape (regions, roles, organizations).
• —Educational purposes related to data science and esports analytics.

Out-of-Scope Use

This dataset must not be used to harass, dox, surveil, profile, or otherwise harm the individuals it describes, nor for any purpose that violates Leaguepedia's licensing and privacy terms or applicable data-protection law. It is a best-effort community snapshot and must not be relied upon as an authoritative record for decisions affecting individuals.

Changelist

Jun 2026

• —Initial release: public_figures, teams, and a unified entity_aliases index, sourced from Leaguepedia via its Cargo query API.
• —Change: include the entity's canonical id as a resolvable alias - this makes it so every entity now appears in entity_aliases, even if it does not have additional aliases.

Citation

If you wish to use this dataset in your work, we kindly ask that you cite it.

For most informal work, a simple mention of the GPTilt project and the League of Legends Esports Directory dataset will suffice. Please also attribute Leaguepedia as the upstream source.

BibTeX:

@misc{gptilt_league_of_legends_esports_directory,
  author    = { GPTilt Contributors },
  title     = { League of Legends Esports Directory },
  year      = { 2026 },
  publisher = { Hugging Face },
  journal   = { Hugging Face Hub },
  url       = { https://huggingface.co/datasets/gptilt/lol-esports-entities }
}