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Code-JL / repository
A Python-based web scraping toolkit that extracts and processes NFL kicking statistics from Pro-Football-Reference. This project automates the collection of comprehensive game data, with a particular focus on field goal attempts and environmental conditions.
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A Python-based web scraping toolkit that extracts and processes NFL kicking statistics from Pro-Football-Reference. This project automates the collection of comprehensive game data, with a particular focus on field goal attempts and environmental conditions.
The NFL Point Kicker Data Scraper systematically collects and processes data through a pipeline of specialized Python scripts, each handling a specific aspect of the data collection and formatting process. The result is a series of well-structured CSV files ready for analysis.
Comprehensive Data Collection
Intelligent Data Processing
Specialized Output Files
The system operates through a series of specialized scripts:
FootballInfoScraper.py - Initializes the scraping pipeline and collects game URLsFootballGameInfoScraper.py - Extracts detailed game dataGameUrlDateSeparator.py - Processes game datesDateToCSVFormat.py - Standardizes date formatsTotalDataFormatting.py - Creates the master datasetSplitDataFormatting.py - Generates specialized analysis files# Clone the repository
git clone https://github.com/Code-JL/NFL-Point-Kicker-Data-Scraper.git
# Navigate to project directory
cd NFL-Point-Kicker-Data-Scraper
# Install required packages
pip install -r requirements.txt
Execute the scripts in the following order:
python FootballInfoScraper.py
python FootballGameInfoScraper.py
python GameUrlDateSeparator.py
python DateToCSVFormat.py
python TotalDataFormatting.py
python SplitDataFormatting.py
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Note: FootballGameInfoScraper.py may take significant time to complete due to rate limiting.
The scraper generates several CSV files optimized for different analysis scenarios:
NFLKicksInfo2000-2022.csv - Complete datasetNFLKicksInfo2000-2022WeatherSplit.csv - Weather-specific analysisNFLKicksInfo2000-2022NonSplit.csv - General analysisNFLKicksInfo2000-2022NonSplitClosedDome.csv - Indoor game analysisNFLKicksInfo2000-2022WeatherSplitWindChill.csv - Wind chill impact analysisEach record includes:
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
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