Datasets · Benchmarks · Challenges · Research
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SoccerNet is a large-scale benchmark suite for soccer video understanding.
Started in 2018 with action spotting in broadcast soccer games, SoccerNet has progressively expanded toward a broad range of problems in video understanding, field understanding, player understanding, and game understanding.
The data currently includes:
Beyond the datasets, SoccerNet organizes yearly international challenges where researchers and practitioners benchmark their methods on common tasks and evaluation protocols.
🌐 Website: soccer-net.org
The official SoccerNet Hugging Face organization currently hosts the following datasets.
| Dataset | Description |
|---|---|
| SoccerNet_raw_HQ | Gated repository for raw broadcast video (train/valid/test) — HQ, 720p, 224p, frames, and clips |
| SoccerNet_raw_HQ_Challenge | Gated repository for raw broadcast video, challenge split — HQ, 720p, 224p, LQ |
| SoccerNet-Tracking-RAW-Video | Gated repository for raw single-camera footage used in the tracking benchmark |
| SN-Features | Pre-extracted per-game features (frame embeddings, ResNET, player bounding boxes, field calibration), shared across editions |
| SN-Labels | Per-game labels (action spotting, dense captioning, camera shots), shared across editions |
| ActionAnticipation | Action anticipation dataset used for the SoccerNet 2026 Action Anticipation Challenge |
| SN-echoes | SoccerNet-Echoes audio commentary dataset |
| BannerReplacement | SoccerNet banner replacement dataset |
| Dataset | Task |
|---|---|
| SN-PCBAS-2026 | Player-Centric Ball Action Spotting |
| SN-NVS-2026 | Novel View Synthesis |
| SN-VQA-2026 | Visual Question Answering |
| Dataset | Task |
|---|---|
| SN-BAS-2025 | Ball Action Spotting |
| SN-Depth-2025 | Monocular Depth Estimation |
| SN-MVFouls-2025 | Multi-View Foul Recognition |
| SN-GSR-2025 | Game State Reconstruction |
| Dataset | Task |
|---|---|
| SN-BAS-2024 | Ball Action Spotting |
| SN-MVFouls-2024 | Multi-View Foul Recognition |
| SN-GSR-2024 | Game State Reconstruction |
| Dataset | Task |
|---|---|
| SN-Calibration-2023 | Camera Calibration |
| SN-ReID-2023 | Player Re-Identification |
| SN-Tracking-2023 | Player Tracking |
| SN-Jersey-2023 | Jersey Number Recognition |
| SN-BAS-2023 | Ball Action Spotting (gated) |
Action Spotting and Dense Video Captioning for the 2023–2024 editions are served from the shared SN-Features / SN-Labels repositories above rather than a per-edition repository.
| Dataset | Task |
|---|---|
| SN-Calibration | Camera Calibration |
| SN-Depth | Monocular Depth Estimation (football and basketball) |
➡️ Browse all SoccerNet datasets
SoccerNet covers tasks ranging from low-level field and player localization to high-level understanding of complete soccer games.
➡️ Explore all SoccerNet tasks
The SoccerNet Challenges have been organized yearly since 2021 and provide standardized datasets, development kits, evaluation protocols, and leaderboards for soccer understanding research.
The 2026 edition, the sixth SoccerNet Challenges edition, included:
Challenge resources are available through the SoccerNet website, Hugging Face datasets, GitHub development kits, and Codabench evaluation servers.
➡️ Explore the SoccerNet Challenges
Benchmark implementations, development kits, evaluation code, and research projects are maintained in the official SoccerNet GitHub organization.
Some of the main repositories include:
➡️ Browse the SoccerNet GitHub organization
SoccerNet research spans soccer video understanding, player and field analysis, multimodal understanding, and sports AI.
The project has grown from the original SoccerNet action spotting benchmark released in 2018 to a suite of datasets, tasks, benchmark methods, yearly challenges, and community contributions.
➡️ Browse SoccerNet publications
SoccerNet is an open research community bringing together researchers and practitioners working on computer vision, video understanding, multimodal AI, sports analytics, and soccer.