FIFA_World_Cup_Games

<p align="left"> <a href="README_CN.md">中文</a>&nbsp;｜&nbsp;English </p> <br> # FIFA World Cup Full-Match Video Dataset <p align="center"> <img src="images/poster.jpeg" alt="FIFA World Cup Full-Match Video Dataset" width="900"/> </p> <p align="center"> <a href="https://github.com/choucisan/fwc_games"><img src="https://img.shields.io/badge/GitHub-World_Cup_Dataset-181717?style=for-the-badge&logo=github" alt="GitHub"></a> &nbsp; <a href="https://huggingface.co/datasets/choucsan/FIFA_World_Cup_Games"><img src="https://img.shields.io/badge/%F0%9F%A4%97_HuggingFace-Dataset-yellow?style=for-the-badge" alt="Hugging Face"></a> &nbsp; <a href="https://modelscope.cn/datasets/choucisan/FIFA_World_Cup_Games"><img src="https://img.shields.io/badge/ModelScope-Dataset-624aff?style=for-the-badge" alt="ModelScope"></a> &nbsp; <a href="https://choucisan.github.io/collections/fwc_games"><img src="https://img.shields.io/badge/Blog-Post-blue?style=for-the-badge" alt="Blog"></a> &nbsp; <a href="https://www.xiaohongshu.com/explore/6a28347e0000000016024961?xsec_token=ABKSEs1qbAzc4ocZhDx0e9CkuEQAXtCOPcoFbcRJaufac=&xsec_source=pc_user"><img src="https://img.shields.io/badge/RedNote-Post-red?style=for-the-badge" alt="RedNote"></a> &nbsp; <a href="https://choosealicense.com/licenses/mit"><img src="https://img.shields.io/badge/License-MIT-green?style=for-the-badge" alt="License"></a> </p> This dataset provides YouTube full-match references and structured match annotations for classic FIFA World Cup games. Instead of redistributing video files, it stores YouTube video IDs and URLs, then links each retained match to structured football data including match metadata, team statistics, lineups, formations, text event timelines, and pre-match prediction polls. --- ## Pipeline 1. **Playlist extraction**: Extracted video IDs, URLs, titles from the YouTube FIFA full-match playlist [`PLCGIzmTE4d0jq6wHT2TvSspZ_HLiIx4_y`](https://www.youtube.com/playlist?list=PLCGIzmTE4d0jq6wHT2TvSspZ_HLiIx4_y). 2. **Match normalization**: Parsed team names and World Cup editions from YouTube titles. 3. **External match linking**: Linked videos to Soccer365 match pages. 4. **Structured data crawling**: Crawled match metadata, stadium info, lineups, formations, team stats, event timelines, and prediction polls. --- ## Dataset Structure ``` FIFA_World_Cup_Games/ ├── images/ │ └── poster.jpeg ├── meta.jsonl # Match metadata ├── team_stats.jsonl # Team statistics ├── lineups.jsonl # Lineups and formations ├── events.jsonl # Text event timelines ├── polls.jsonl # Pre-match prediction polls └── pages/ # Individual match detail pages ``` ## Dataset Overview - **Total Matches**: 40 (verified full-match videos) - **Data Format**: JSONL | Field | Type | Description | |-------|------|-------------| | `video_id` | string | YouTube video ID | | `url` | string | YouTube video URL | | `title` | string | Match title | | `teams` | array | Two teams in the match | | `world_cup` | string | World Cup edition (e.g. "2022 Qatar") | | `match_info_url` | string | Soccer365 match page URL | ## Usage ```python from datasets import load_dataset dataset = load_dataset("choucsan/FIFA_World_Cup_Games") # or from ModelScope from modelscope import MsDataset dataset = MsDataset.load("choucisan/FIFA_World_Cup_Games") ``` ## License MIT License. ## Contact - 📧 **[e-mail]** - 🤗 [Hugging Face](https://huggingface.co/datasets/choucsan/FIFA_World_Cup_Games) - 🐱 [ModelScope](https://modelscope.cn/datasets/choucisan/FIFA_World_Cup_Games)