Soccer DNA

What the company appears to be: Soccer DNA is a self-reported, AI-powered web application that presents users with a football (soccer) personality quiz. Based on their answers, it assigns them one of 30 original archetypes and generates a personalized report using GPT-5.6. The author states this is intended for both amateur players and casual fans.

What changed: This project was submitted as part of the OpenAI 2026 hackathon. It represents an early-stage prototype built over a short timeframe (likely a hackathon week), with no evidence of prior development or commercial traction.

Single most important open question: Is there any evidence that users are engaging with the quiz beyond its initial release, or that there is demand for a more developed version of this platform?

Note: All claims in this report are based on self-reported information from the author. No independent verification or third-party data has been used.

The description states that Soccer DNA is an AI-powered football personality quiz. It includes:

• A quiz with scenario-based questions
• Deterministic scoring logic to assign one of 30 archetypes
• GPT-5.6 integration for generating personalized reports and development plans
• A web application built using Next.js, React, Node.js, and OpenAI technologies

The author describes it as a tool that transforms user decisions into "football archetypes" rather than traditional personality labels.

Inference: The product appears to be a prototype or MVP built for a hackathon, not a commercial offering with ongoing user engagement or monetization.

The author positions Soccer DNA as:

• An alternative to traditional soccer player labeling (e.g., by position or stats)
• A way to understand how someone thinks and behaves on the pitch
• A tool for both casual fans and amateur players
• Designed around real game situations such as decision-making, communication, and risk-taking

It is described as aiming to make the experience enjoyable for general audiences while still offering tactical depth.

Claim: The author claims this is more than a novelty quiz — it combines archetypes, scoring logic, visual design, and AI guidance.

Inference: This positioning suggests an intent to evolve into a broader platform for player identity and development, but no evidence supports current adoption or traction.

The author states that the target audience includes:

• Amateur players
• Youth athletes
• School or community team members
• Casual fans of football (soccer)

They also note it should work for both experienced players and those who primarily watch soccer, suggesting a broad but not deeply segmented customer base.

Claim: The product is designed to be accessible to non-experts while still providing value to more knowledgeable users.

Inference: There is no evidence of specific buyer personas or segmentation beyond general categories; the ICP remains undefined in terms of behavior or usage patterns.

There is no mention of pricing, monetization, or business model in the description. The author does not describe any revenue streams or paid features.

Not evidenced: No evidence of a business model or pricing structure exists.

The project was built using:

• Technologies: JavaScript, Next.js, React, Node.js, OpenAI APIs (including GPT-5.6 and Codex)
• Framework: Responsive web application
• Architecture: Hybrid system combining deterministic scoring with generative AI for interpretation
• Features:
  • Scenario-based quiz
  • Structured archetype assignment
  • Personalized report generation via GPT-5.6
  • UI components designed for responsiveness

Claim: The author used Codex to refactor code, improve prompts, and manage edge cases.

Inference: The technical stack indicates a modern frontend/backend setup with AI integration, but no evidence of scalability or production deployment.

There is no evidence of user engagement, adoption metrics, or product maturity beyond the hackathon submission. The author notes that this is an early-stage prototype and that future features are planned, but no data on usage or retention exists.

Not evidenced: No traction signals such as active users, downloads, signups, or performance indicators.

The description does not mention competitors or similar products in the market. The author focuses on the uniqueness of their approach — using behavioral scenarios and archetypes instead of standard labels — but provides no context about existing tools or platforms in this space.

Not evidenced: No competitive landscape or comparison with other quiz or identity tools is provided.

• Unproven commercial viability: The project is described as a hackathon submission with no evidence of user traction or monetization.
• Unclear path to scale: While the author envisions future features like team dashboards and progress tracking, there’s no indication of how these would be developed or funded.
• AI dependency without clear value proposition: The use of GPT-5.6 is central, but it's unclear whether the added AI layer significantly improves outcomes over a purely deterministic system.
• No feedback loop or iteration mechanism: There is no evidence that user responses are collected or used to refine the archetypes or scoring logic.

Inference: Without any data on usage or customer feedback, there is no basis for assessing product-market fit or long-term sustainability.

1. What specific user behaviors or outcomes have you observed from people who completed the quiz?
2. How do you plan to validate that your archetypes are meaningful and distinct?
3. Are there any early adopters or pilot users beyond yourself?
4. What is your roadmap for monetization, if any?
5. Have you tested the AI-generated reports with real players or coaches?
6. How do you intend to grow beyond a single-person development effort?