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@@ -31,7 +31,7 @@ This repository contains the **production-ready model artifacts** used by the pu
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- ## 🔍 What’s inside this repository
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  ### Model artifacts
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  - `home_goals_model.pkl`
@@ -50,7 +50,7 @@ This repository contains the **production-ready model artifacts** used by the pu
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  ---
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- ## 🧠 Modeling approach
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  ### Model type
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  - **Poisson Generalized Linear Models (GLM)**
@@ -65,13 +65,13 @@ This repository contains the **production-ready model artifacts** used by the pu
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  ### Outcome probabilities
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  Win / Draw / Loss probabilities are derived from the joint scoreline distribution:
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- \[
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  P(H=i, A=j) = \text{Poisson}(i|\lambda_H) \times \text{Poisson}(j|\lambda_A)
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- \]
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  ---
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- ## 📊 Features used (leakage-safe)
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  All features are **computed strictly from matches played before kickoff**.
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@@ -81,9 +81,9 @@ This design prevents **data leakage** and supports reliable backtesting.
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  ---
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- ## 🚀 Quickstart (Python)
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- ### 1️⃣ Install dependencies
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  ```bash
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  from huggingface_hub import hf_hub_download
 
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  ---
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+ ## What’s inside this repository
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  ### Model artifacts
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  - `home_goals_model.pkl`
 
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  ---
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+ ## Modeling approach
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  ### Model type
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  - **Poisson Generalized Linear Models (GLM)**
 
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  ### Outcome probabilities
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  Win / Draw / Loss probabilities are derived from the joint scoreline distribution:
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+ ```bash
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  P(H=i, A=j) = \text{Poisson}(i|\lambda_H) \times \text{Poisson}(j|\lambda_A)
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+
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  ---
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+ ## Features used (leakage-safe)
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  All features are **computed strictly from matches played before kickoff**.
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  ---
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+ ## Quickstart (Python)
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+ ### Install dependencies
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  ```bash
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  from huggingface_hub import hf_hub_download