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https://github.com/elcaiseri/openfpl-scout-ai

An AI-powered Fantasy Premier League Scout that leverages machine learning models to predict player performances and optimize your FPL team selections. This project combines historical data, real-time match information, and advanced ML models including Linear Regression, XGBoost, and CatBoost to help you build the best possible team.
https://github.com/elcaiseri/openfpl-scout-ai

ai fantasy-premier-league football fpl machine-learning

Last synced: 3 months ago
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An AI-powered Fantasy Premier League Scout that leverages machine learning models to predict player performances and optimize your FPL team selections. This project combines historical data, real-time match information, and advanced ML models including Linear Regression, XGBoost, and CatBoost to help you build the best possible team.

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README 

          
# OpenFPL-Scout-AI



OpenFPL Scout AI



*Image credits: Generated with GPT-4o*



OpenFPL-Scout-AI is an AI-powered Fantasy Premier League Scout that uses ensemble machine learning (Linear Regression, XGBoost, CatBoost) to predict player points and optimize FPL team selection. It features a beautiful web interface for visualizing your optimal team in a football pitch layout.



## 🚀 Live Demo & API Access



**Web Interface:** **[https://openfpl-scout-ai-186049008266.europe-west1.run.app](https://openfpl-scout-ai-186049008266.europe-west1.run.app)**



**🔥 API Access via RapidAPI:** **[Subscribe on RapidAPI Marketplace](https://rapidapi.com/elcaiseri-elcaiseri-default/api/openfpl-api)** 

- Free tier: 10 requests/hour

- Professional support and documentation

- Easy integration with RapidAPI headers



## Features



- 🎯 **AI-Powered Predictions**: Ensemble ML models (Linear Regression, XGBoost, CatBoost)

- ⚽ **Interactive Web UI**: Beautiful pitch visualization with player cards

- 📊 **Real-time Data**: Live fixture and match data integration

- 🚀 **Fast Performance**: Async player predictions and caching

- 🏆 **Smart Team Selection**: Automated optimal team selection by position

- 👑 **Captain Assignment**: Intelligent captain/vice-captain selection

- 📱 **Mobile Responsive**: Works perfectly on all devices

- 📸 **Screenshot Feature**: Download your team lineup as PNG

- 🎨 **Professional Design**: FPL-themed UI with gradient backgrounds

- 🔌 **RapidAPI Integration**: Professional API marketplace access



## Installation



**Docker:**

```bash

docker build -t openfpl-scout-ai .

docker run -d -p 8000:8000 --name openfpl-api openfpl-scout-ai

```



## Usage



### Web Interface

Visit the [live demo](https://openfpl-scout-ai-186049008266.europe-west1.run.app) or [http://localhost:8000](http://localhost:8000) for local development:



- **Visual Team Display**: See your optimal team laid out on a football pitch

- **Player Cards**: Detailed cards showing player stats, fixtures, and expected points

- **Gameweek Selection**: Navigate between different gameweeks

- **Screenshot Export**: Download your team lineup as a high-quality image

- **Interactive Elements**: Click on player cards for detailed information



### API Access via RapidAPI



**🔥 Primary API Access:** [Subscribe on RapidAPI Marketplace](https://rapidapi.com/elcaiseri-elcaiseri-default/api/openfpl-api)



**Base URL:** `https://openfpl-api.p.rapidapi.com`



**Authentication:**

```http

X-RapidAPI-Key: YOUR_RAPIDAPI_KEY

X-RapidAPI-Host: openfpl-api.p.rapidapi.com

```



**Quick Example:**

```javascript

const options = {

    method: 'GET',

    headers: {

        'X-RapidAPI-Key': 'YOUR_RAPIDAPI_KEY',

        'X-RapidAPI-Host': 'openfpl-api.p.rapidapi.com'

    }

};



fetch('https://openfpl-api.p.rapidapi.com/api/gw/scout?gameweek=7', options)

    .then(response => response.json())

    .then(data => console.log(data));

```



### API Documentation

- **RapidAPI Docs:** [https://rapidapi.com/elcaiseri-elcaiseri-default/api/openfpl-api](https://rapidapi.com/elcaiseri-elcaiseri-default/api/openfpl-api)



### Main Endpoints



- `GET /api/health` — Health check

- `GET /api/gameweeks` — Available gameweeks with saved data

- `GET /api/gw/scout` — Get optimal FPL team for specific gameweek

- `GET /api/gw/playerpoints` — Get filtered player point predictions

- `GET /api` — API information and metadata



**Sample `/api/gw/scout` response:**

```json

{

  "scout_team": [

    {

      "element_type": "Goalkeeper",

      "web_name": "Alisson",

      "team_name": "Liverpool",

      "expected_points": 5.2,

      "role": "",

      "now_cost": 55,

      "selected_by_percent": 15.5

    },

    {

      "element_type": "Defender",

      "web_name": "Alexander-Arnold",

      "team_name": "Liverpool",

      "expected_points": 8.1,

      "role": "captain",

      "now_cost": 70,

      "selected_by_percent": 45.2

    }

  ],

  "gameweek": 7,

  "version": "4.0.0",

  "credits": "OpenFPL-Scout AI - Team Predictions | Developed by Kassem @elcaiseri, 2025"

}

```



## Screenshots



The web interface provides a beautiful visualization of your optimal FPL team:



![Team Visualization](assets/FPL-Scout-Team-GW1-2025-08-07.png)



Features of the UI:

- **Football Pitch Layout**: Players arranged in realistic formation

- **Color-Coded Positions**: Goalkeepers (Orange), Defenders (Blue), Midfielders (Light Blue), Forwards (Green)

- **Captain Badges**: Golden 'C' for captain, Silver 'VC' for vice-captain

- **Fixture Information**: Opponent teams and home/away indicators

- **Expected Points**: AI-predicted points for each player

- **Team Statistics**: Total expected points and player count

- **Responsive Design**: Works on desktop, tablet, and mobile devices



## Model Overview



| Model             | Version | Description                    |

|-------------------|---------|--------------------------------|

| Linear Regression | v4.0    | Baseline linear model          |

| XGBoost           | v4.0    | Gradient boosting ensemble     |

| CatBoost          | v3.0    | Categorical boosting model     |



- Ensemble predictions for accuracy

- Feature importance analysis

- Optimized for FPL player performance



## API Integration



Integrates with Football Data API for:

- Live fixtures and matchups

- Home/away status

- Gameweek info



**For RapidAPI Users:** All data is pre-processed and cached for optimal performance.



## Code Structure



- `main.py`: FastAPI app and endpoints

- `src/scout.py`: FPLScout class (predictions, team selection)

- `src/models.py`: Pydantic response models

- `src/utils.py`: Config and helpers

- `src/logger.py`: Logging



## What's New



- **🔌 RapidAPI Marketplace**: Now available on RapidAPI with professional support

- **📈 Enhanced API**: New endpoints for gameweeks and player filtering

- **🌐 Live Deployment**: Available on Google Cloud Platform

- **🎨 Beautiful Web Interface**: Interactive team visualization with football pitch layout

- **📸 Screenshot Feature**: Export your team lineup as high-quality PNG images

- **📱 Mobile Responsive**: Perfect experience on all devices

- **2024/2025 Season**: Models updated with latest data

- **CatBoost Integration**: Improved ML pipeline ([Issue #1](https://github.com/elcaiseri/Fantasy-Premier-League-LTX/issues/1))

- **RESTful API**: FastAPI endpoints for team selection and predictions

- **Rebranding**: Now OpenFPL-Scout-AI

- **Refactored Code**: Improved modularity and maintainability

- **AI-Powered Predictions**: Advanced ensemble models

- **Async Processing**: Fast parallel predictions

- **Live Data**: Real-time match integration

- **Docker Support**: Easy deployment



## Contributing



Contributions welcome! Ideas for improvement:

- Enhanced algorithms and selection logic

- Additional UI features and visualizations

- Player injury/form tracking

- Better documentation

- Mobile app development



Fork, branch, and submit a pull request.



## License



MIT License — see [LICENSE](LICENSE) for details.



## API Support & Contact



**For API Support:**

- **RapidAPI Marketplace:** [https://rapidapi.com/elcaiseri-elcaiseri-default/api/openfpl-api](https://rapidapi.com/elcaiseri-elcaiseri-default/api/openfpl-api)

- **Email:** [support@openfpl.kassem.dev](mailto:iqasem4444@gmail.com)



**General Questions:**

- **Email:** [iqasem4444@gmail.com](mailto:iqasem4444@gmail.com)