# Win-Draw-Loss Probability Engine AI Agent Connect > Win-Draw-Loss Probability Engine converts granular football scoreline data into primary match outcomes. Your AI client uses this MCP to calculate home, draw, and away win probabilities, derive fair decimal odds, and validate that your scoreline distributions are mathematically sound. ## Overview - **Category:** mathematics - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_NG6TJaUuvfJwPeqkjdQLKJVZeP9NCIPZTd3qMq8J/ai-agent-connect - **Tags:** football, probability, betting, statistics, sports-analytics ## Description If you work with football modeling, you know that raw scoreline matrices are hard to act on directly. This MCP bridges the gap between specific scoreline probabilities and the high-level outcomes you actually need for analysis. You can feed your agent a distribution of possible scores, and it will handle the heavy lifting of aggregating those into win, loss, or draw totals. It's built for precision. You can use it to check if your data is complete or if you're missing specific scoreline probabilities that would skew your model. Once you have a solid distribution, your agent can instantly calculate the fair decimal odds for every outcome. Instead of manually calculating these values, you just hand the matrix to your AI client and get the math done in seconds. It's a specialized tool for turning raw statistical distributions into clear, usable betting or analytical data. ## Tools ### aggregate_outcomes This tool converts a matrix of specific scorelines into primary match outcome probabilities. It sums up the probabilities for home wins, draws, and away wins based on the provided goal counts. ### calculate_fair_odds This tool determines the mathematically fair decimal odds for each primary match outcome. It uses the provided probabilities to output the exact odds for home, draw, and away results. ### get_outcome_summary This tool generates a text-based overview of match likelihoods. It provides a high-level summary of the probabilities and potential value found in the data. ### validate_matrix_completeness This tool checks if your scoreline distribution is mathematically complete. It verifies that the provided probabilities account for the full range of possible outcomes. ## Prompt Examples **Prompt:** ``` Aggregate these scorelines: [{"homeGoals": 1, "awayGoals": 0, "probability": 0.4}, {"homeGoals": 0, "awayGoals": 0, "probability": 0.6}] ``` **Response:** ``` Home Win: 0.4, Draw: 0.6, Away Win: 0.0. The total probability is conserved. ``` **Prompt:** ``` Calculate fair odds for a home win probability of 0.5, draw of 0.2, and away win of 0.3. ``` **Response:** ``` The fair decimal odds are: Home Win: 2.0, Draw: 5.0, Away Win: 3.33. ``` **Prompt:** ``` Is this matrix complete: [{"homeGoals": 1, "awayGoals": 0, "probability": 0.5}]? ``` **Response:** ``` No, the matrix is incomplete. The missing probability is 0.5. ``` ## Capabilities ### Outcome Aggregation Your agent uses this to turn individual scoreline data into win, draw, or loss totals. ### Fair Odds Calculation Your AI client calculates decimal odds based on the probability of each match outcome. ### Data Integrity Checks The agent verifies that a scoreline matrix represents a complete probability distribution. ### Probability Summarization Your agent generates text summaries of match likelihoods and potential value. ## Use Cases ### Model Validation Check if your football prediction model's scoreline matrix is missing any necessary probability data. ### Odds Comparison Calculate fair decimal odds to compare against market prices for home, draw, or away wins. ### Outcome Reporting Generate quick text summaries of match probabilities for stakeholders or team reports. ### Data Transformation Turn a complex list of specific scoreline probabilities into simple win/draw/loss percentages. ## Benefits - Converts granular scoreline data into primary match outcomes instantly. - Calculates mathematically fair decimal odds without manual formulas. - Identifies missing probabilities in incomplete scoreline matrices. - Provides text-based summaries of match likelihoods for faster reporting. ## How It Works Connect your AI client to the Vinkius-hosted MCP and start running math operations on your football data. 1. Connect your preferred MCP-compatible client to Vinkius. 2. Provide your scoreline matrix or probability data to your AI agent. 3. The agent calls the specific tool needed, such as aggregate_outcomes or calculate_fair_odds. 4. The MCP executes the mathematical operations and returns the results. 5. Your agent presents the final probabilities, odds, or summaries to you. ## Frequently Asked Questions **What does this MCP do?** It provides mathematical tools to transform football scoreline matrices into match outcome probabilities and fair decimal odds. **How do I use this with Claude or Cursor?** You connect your client to the Vinkius platform, which hosts and manages the MCP. Once connected, your AI client can call the tools directly. **Can it check if my probability data is missing values?** Yes, the validate_matrix_completeness tool checks if a provided scoreline matrix represents a complete probability distribution. **Does it calculate betting odds?** It calculates fair decimal odds for primary match outcomes using the calculate_fair_odds tool. **What kind of data does it need for scorelines?** For aggregation, each scoreline object needs homeGoals, awayGoals, and a probability value. **How do I convert scorelines to match outcomes?** You can use the `aggregate_outcomes` tool by providing a JSON array of scoreline objects containing home goals, away goals, and their respective probabilities. **Can I calculate betting odds with this server?** Yes, the `calculate_fair_odds` tool calculates the mathematically fair decimal odds for Home Win, Draw, and Away Win based on provided probabilities. **What happens if the probability sum is not 1.0?** The `validate_matrix_completeness` tool will detect if the sum is not 1.0 and will report the missing probability as a 'No-Result' state.