Homie0609/2026SoccerNetChallenge-VQA

2026 Soccernet Challenge - VQA Overview

Task

Soccernet-VQA is a challenge focused on multimodal (text, image, video) multiple-choice question answering, covering 14 distinct soccer understanding tasks. These tasks include assessing background knowledge of players and teams, determining camera status, classifying actions, recognizing fouls, and many other complex scenarios.

More details could be found at:

• 📑 Paper Relevant Links: Paper ⋅ WebPage ⋅ Benchmark ⋅ Database
• 🏆 2026 SoccerNet Challenge - VQA: Eval (Test) ⋅ Eval (Challenge)

Data

Both the test phase and challenge phase are supported by 500 unique QA pairs, which span all 14 aforementioned tasks. You can download the test set and challenge set on our higgingface page or SoccerNet codebase (not yet).

Each QA pair contains three core components in its dictionary:

• Q: The question content.
• materials: Paths to relevant images or videos.
• Ox (e.g., O1, O2): The multiple-choice options.

An example of a QA pair is shown below:

  {
    "Q": "How many appearances did the midfielder who is replacing Antoine Griezmann in this video make for Atletico Madrid from 2002 to 2018?",
    "materials": [
      "materials/q12/SoccerReplay-1988/europe_champions-league_2023-2024/2023-11-07_atletico-de-madrid-celtic-fc-champions-league/2_19_01.mp4"
    ],
    "O1": "25 appearances",
    "O2": "7 appearances",
    "O3": "18 appearances",
    "O4": "13 appearances"
  }

Evaluation

As for this close-ended QA task, we directly use the accuracy as the evaluation metric:

$$\text{score}=\frac{\text{number of correct answers}}{500}\backslash text\{score\}\; =\; \backslash frac\{\backslash text\{number\; of\; correct\; answers\}\}\{500\}$$

Baseline

To facilitate benchmarking, we provide two frequently used models (Qwen2.5VL and GPT-4o) to infer directly as our baselines. Also, the SoccerAgent pipeline with multi-agent thoughts could be regarded as baseline as well, they can all be found in our Official Github Repo.

Prize

The Rank 1 submission of the challenge set can finally win the $1000 prize sponsored by KNQ Technology.