What is "The Quant Edge Engine"?

It is a prompt listed on OpenRuna — A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. You can copy and adapt it for ChatGPT, Claude, Cursor, or other AI tools.

Is this prompt free to use?

Most OpenRuna resources are open or CC0-licensed. Check the license on this page before commercial use. Premium collections are clearly marked.

How do I get the best results?

Replace any template variables, add your project context, and ask the model to confirm assumptions. Iterate in 2–3 follow-up turns rather than expecting a perfect first response.

Can I use this with Claude and ChatGPT?

Yes. The prompt is model-agnostic text. Tips on this page cover Claude, ChatGPT, and Cursor specifically.

Where can I find related resources?

Scroll to Related resources on this page or browse the category hub on OpenRuna to find connected prompts, tools, and agents in the same topic area.

The Quant Edge Engine

TEXT

Prompt1463 chars · 189 words

You are a **quantitative sports betting analyst** tasked with evaluating whether a statistically defensible betting edge exists for a specified sport, league, and market. Using the provided data (historical outcomes, odds, team/player metrics, and timing information), conduct an end-to-end analysis that includes: (1) a data audit identifying leakage risks, bias, and temporal alignment issues; (2) feature engineering with clear rationale and exclusion of post-outcome or bookmaker-contaminated variables; (3) construction of interpretable baseline models (e.g., logistic regression, Elo-style ratings) followed—only if justified—by more advanced ML models with strict time-based validation; (4) comparison of model-implied probabilities to bookmaker implied probabilities with vig removed, including calibration assessment (Brier score, log loss, reliability analysis); (5) testing for persistence and statistical significance of any detected edge across time, segments, and market conditions; (6) simulation of betting strategies (flat stake, fractional Kelly, capped Kelly) with drawdown, variance, and ruin analysis; and (7) explicit failure-mode analysis identifying assumptions, adversarial market behavior, and early warning signals of model decay. Clearly state all assumptions, quantify uncertainty, avoid causal claims, distinguish verified results from inference, and conclude with conditions under which the model or strategy should not be deployed.

Overview

The Quant Edge Engine is a free prompt on OpenRuna. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor.

What this prompt does

"The Quant Edge Engine" is designed to help you get reliable results from AI assistants for real prompt tasks. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. It is catalogued in OpenRuna's resource graph so you can discover related prompts, tools, agents, and datasets in one place. Copy the content directly into ChatGPT, Claude, Gemini, or Cursor — or use it as a system prompt / skill instruction where applicable.

Use cases

Use "The Quant Edge Engine" when you need a repeatable prompt for professional workflows without writing instructions from scratch each time.
Adapt this prompt for team onboarding — paste into Claude or ChatGPT and iterate on the output with your project context.
Combine with related tools and prompts in the same OpenRuna category to build a full stack for your use case.
Reference during code review or planning sessions when you want consistent AI-assisted quality bars.

Example output

When you run this prompt, expect structured output similar to:

You are a **quantitative sports betting analyst** tasked with evaluating whether a statistically defensible betting edge exists for a specified sport, league, and market. Using the provided data (historical outcomes, odds, team/player metrics, and timing information), conduct an end-to-end analysis that includes: (1) a data audit identifying leakage risks, bias, and temporal alignment issues; (2) feature engineering with clear rationale and exclusion of post-outcome or bookmaker-contaminated variables; (3) construction of interpretable baseline models (e.g., logistic regression, Elo-style rati…

Outputs vary by model and temperature; treat the first response as a draft and refine with follow-up prompts.

Tips by platform

Claude

In Claude, paste the full prompt as the first user message or add it to Project instructions. Ask Claude to confirm assumptions before executing. For long prompts, use Claude's artifact panel to iterate on structured output.

ChatGPT

In ChatGPT, start a new chat and paste this prompt verbatim. Enable GPT-4o or your preferred model for coding tasks. Use follow-ups like "apply this to [your context]" for best results.

Cursor

In Cursor, add key instructions from this prompt to .cursorrules or a SKILL.md file. Reference it in Agent mode with @ mentions. Keep the original title in comments so teammates can find it on OpenRuna.

Frequently asked questions

What is "The Quant Edge Engine"?: It is a prompt listed on OpenRuna — A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. You can copy and adapt it for ChatGPT, Claude, Cursor, or other AI tools.
Is this prompt free to use?: Most OpenRuna resources are open or CC0-licensed. Check the license on this page before commercial use. Premium collections are clearly marked.
How do I get the best results?: Replace any template variables, add your project context, and ask the model to confirm assumptions. Iterate in 2–3 follow-up turns rather than expecting a perfect first response.
Can I use this with Claude and ChatGPT?: Yes. The prompt is model-agnostic text. Tips on this page cover Claude, ChatGPT, and Cursor specifically.
Where can I find related resources?: Scroll to Related resources on this page or browse the category hub on OpenRuna to find connected prompts, tools, and agents in the same topic area.