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--- |
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title: NFL Receiving Yards Predictor |
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emoji: 📊 |
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colorFrom: purple |
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colorTo: red |
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sdk: gradio |
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sdk_version: 5.49.0 |
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app_file: app.py |
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pinned: false |
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license: mit |
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--- |
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# 🏈 NFL Receiving Yards Predictor |
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This interactive Gradio app predicts **NFL receiving yards** for any active wide receiver or tight end based on the quarterback, game week, stadium conditions, and real-time weather forecasts. |
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The model leverages **AutoGluon Tabular** for regression and integrates **player embeddings**, **team data**, and **environmental context** for enhanced accuracy. |
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--- |
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## 🚀 Demo |
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Try it live here: [Hugging Face Space](https://huggingface.co/spaces/SebastianAndreu/2025-24679-NFL-Yards-Predictor) |
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--- |
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## 🧠 Model Overview |
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* **Model Type:** Tabular Regression |
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* **Framework:** [AutoGluon Tabular](https://auto.gluon.ai/stable/tutorials/tabular_prediction/index.html) |
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* **Training Dataset:** Aggregated play-by-play and player stats from NFL seasons |
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* **Input Features Include:** |
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* Receiver & quarterback IDs (with learned embeddings) |
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* Team and opponent IDs |
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* Stadium type and surface |
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* Game spread and total line |
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* Weather conditions (temperature, humidity, wind, precipitation) |
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* Home/Away team indicators |
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--- |
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## ⚙️ How It Works |
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1. The app loads the pre-trained AutoGluon predictor and historical player embeddings from the Hugging Face model repo: |
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``` |
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SebastianAndreu/2025-24679-NFL-Yards-Predictor |
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``` |
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2. Users select: |
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* Receiver |
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* Quarterback |
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* Week |
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* Season |
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3. The app fetches: |
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* Game info (from local CSVs) |
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* Real-time weather forecast (via [Open-Meteo API](https://open-meteo.com/)) |
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4. The combined data is passed into the predictor for inference. |
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5. The model outputs the **expected receiving yards** for that matchup. |
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--- |
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## 📁 Repository Structure |
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``` |
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. |
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├── app.py # Main Gradio interface and logic |
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├── players.csv # Active player metadata |
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├── games.csv # Game schedule and context |
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├── hf_assets/ # Cached model assets from Hugging Face |
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├── nfl_model/ # Snapshot of downloaded model files |
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├── README.md # You are here |
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``` |
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--- |
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## 🧩 Key Functions |
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### `download_model_and_embeddings()` |
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Downloads and prepares the AutoGluon model and the player embedding dataset from Hugging Face. |
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### `get_game_info()` |
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Matches the selected receiver’s team, week, and season to the corresponding game, including opponent and stadium metadata. |
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### `get_weather_forecast()` |
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Fetches real-time forecast for the stadium using **Open-Meteo**, returning temperature, humidity, wind speed, and rain/snow conditions. |
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### `predict_yards()` |
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Prepares the full feature vector and runs inference using the AutoGluon predictor. If missing embeddings are detected, they’re replaced by mean values for stability. |
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--- |
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## 🧰 Requirements |
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To run locally: |
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```bash |
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pip install gradio autogluon tabular pandas requests huggingface_hub |
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``` |
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--- |
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## 🌤️ Weather API Integration |
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The app dynamically queries the [Open-Meteo](https://open-meteo.com/) API based on the selected stadium coordinates. |
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Example usage: |
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```python |
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https://api.open-meteo.com/v1/forecast?latitude=40.4468&longitude=-80.0158&hourly=temperature_2m,relative_humidity_2m,wind_speed_10m,weather_code |
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``` |
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--- |
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## 🏟️ Stadium Metadata |
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Each NFL stadium’s coordinates are stored in the `STADIUM_COORDS` dictionary to map weather forecasts accurately. |
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--- |
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## 🏈 Credits |
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* **Developer:** [Sebastian Andreu](https://huggingface.co/SebastianAndreu) |
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* **Model:** AutoGluon Tabular Regression trained on historical NFL data |
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* **APIs:** Open-Meteo (Weather), ESPN (Game Schedule) |
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* **Hosted on:** [Hugging Face Spaces](https://huggingface.co/spaces/SebastianAndreu/2025-24679-NFL-Yards-Predictor) |
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--- |
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## 🧾 License |
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MIT License © 2025 Sebastian Andreu |
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--- |
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## 💬 Feedback |
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If you find a bug or have a feature suggestion, please open an issue on the [model repository](https://huggingface.co/SebastianAndreu/2025-24679-NFL-Yards-Predictor). |
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
