Glloq/horse-racing-france
French Horse Racing Dataset Structured dataset of French horse racing covering 2014-01-01 → 2026-05-05, restricted to French meetings. This repository is provided "as is" under an other license. Overview Longitudinal collection of French race meetings with full race, runner, and payout records. The data is split into four normalized tables, each exposed as an independent Hub configuration. Configuration Description Rows reunions Race meetings (one row… See the full description on the dataset page: https://huggingface.co/datasets/Glloq/horse-racing-france.
French Horse Racing Dataset
Structured dataset of French horse racing covering 2014-01-01 → 2026-05-05, restricted to French meetings.
This repository is provided "as is" under an other license.Overview
Longitudinal collection of French race meetings with full race, runner, and payout records. The data is split into four normalized tables, each exposed as an independent Hub configuration.
Additional full-fidelity sources are archived under data/source.
Schema & Join Key
All tables share the `raceKey` join key, formatted as:
YYYY-MM-DD_R{numOfficielReunion}_C{numCourse}courses.ordreArriveeis the finishing-order target (result).- Join with
participantsonraceKey.
Note: reunions is defined at the meeting level and therefore has no raceKey; join it to courses via reunionKey.
Parquet Files (data/parquet)
Clean, flat, directly loadable tables. Each table is a separate configuration because the schemas differ:
from datasets import load_dataset
reunions = load_dataset("annaelmoussa/horse-racing-france", "reunions", split="train")
courses = load_dataset("annaelmoussa/horse-racing-france", "courses", split="train")
participants = load_dataset("annaelmoussa/horse-racing-france", "participants", split="train")
rapports = load_dataset("annaelmoussa/horse-racing-france", "rapports", split="train")Available configurations: reunions, courses, participants, rapports.
Each table is sharded into 5 Parquet files (suffix -0000 through -0004).
Full-Fidelity Sources (data/source)
The .tar.gz archives contain the unflattened data for full fidelity:
raw.tar.gz— raw JSON responses (source cache, kept so new columns can be derived later).normalized.tar.gz— normalized JSONL files, each with the nestedrawfield.
Validation Status
Final validation performed:
0duplicate race keys.0races without participants.0mismatches betweennombreDeclaresPartantsand participant rows.27finalized races without an arrival (2014/2015 only, source gap).4423races whose programme announces definitive payouts but returned no content (source gaps, mostly 2017/2018).
