⚽ SoccerNet

Soccer Video Understanding Benchmark Suite

Datasets · Benchmarks · Challenges · Research

🌐 Website · 🤗 Datasets · 💻 GitHub · 💬 Discord

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⚽ What is SoccerNet?

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:

• 550 complete broadcast games
• 12 single-camera games
• 300K+ temporal annotations
• 1M+ spatial annotations

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

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🤗 Datasets on Hugging Face

The official SoccerNet Hugging Face organization currently hosts the following datasets.

Core and research datasets

SoccerNet 2026

SoccerNet 2025

SoccerNet 2024

➡️ Browse all SoccerNet datasets

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🎯 Benchmark Tasks

SoccerNet covers tasks ranging from low-level field and player localization to high-level understanding of complete soccer games.

📺 Broadcast Video Understanding

• Action Spotting — localize actions in time
• Replay Grounding — retrieve a replayed action in a broadcast
• Camera Shot Segmentation — segment camera shots and localize their boundaries
• Ball Action Spotting — localize ball actions in time
• Dense Video Captioning — spot salient moments and generate commentaries
• Multi-View Foul Recognition — recognize fouls and their severity

🏟️ Field Understanding

• Field Localization — localize soccer pitch markings and goal posts
• Camera Calibration — estimate camera calibration
• Monocular Depth Estimation — estimate depth from a monocular camera

👤 Player Understanding

• Player Tracking — track multiple players through video sequences
• Player Re-Identification — re-identify players across views
• Jersey Number Recognition — identify player jersey numbers from tracklets

🧠 Game Understanding

• Game State Reconstruction — reconstruct the game state by tracking the ball and players in a top-view representation

➡️ Explore all SoccerNet tasks

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🏆 SoccerNet Challenges

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:

• Spiideo SoccerNet SynLoc
• Ball Action Anticipation
• Visual Question Answering
• Player-Centric Ball Action Spotting
• Novel View Synthesis
• FIFA Innovation Challenge — Skeletal Tracking Light (guest task)

Challenge resources are available through the SoccerNet website, Hugging Face datasets, GitHub development kits, and Codabench evaluation servers.

➡️ Explore the SoccerNet Challenges

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💻 Open-Source Code

Benchmark implementations, development kits, evaluation code, and research projects are maintained in the official SoccerNet GitHub organization.

Some of the main repositories include:

• sn-gamestate — Game State Reconstruction
• sn-calibration — Camera Calibration
• sn-tracking — Player Tracking
• sn-spotting — Action Spotting
• sn-reid — Player Re-Identification
• sn-mvfoul — Multi-View Foul Recognition
• sn-depth — Monocular Depth Estimation
• sn-echoes — SoccerNet-Echoes
• sn-jersey — Jersey Number Recognition
• sn-nvs — Novel View Synthesis

➡️ Browse the SoccerNet GitHub organization

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📚 Research

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

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🤝 Join the SoccerNet Community

SoccerNet is an open research community bringing together researchers and practitioners working on computer vision, video understanding, multimodal AI, sports analytics, and soccer.