Tennis Odds Extraction from Bet 365 with OCR and Google Sheets Integration

In this post, I’m excited to share a project that combines image processing, Optical Character Recognition (OCR), and Google Sheets to automate the extraction and management of tennis odds. This project can be incredibly useful for sports analysts, bettors, or anyone interested in gathering detailed tennis betting information without the manual effort.

The Problem

Collecting odds manually is not only time-consuming. but also tedious, error-prone and most important inefficient. Plus, bet sites like Bet365 makes scrapping odds a task almost impossible. So the idea of this project is collect screenshots of the desired odds. 

The Solution

Each screenshot contain various odds, and extracting this information accurately is crucial for any meaningful analysis or betting strategy. Our solution leverages the power of OCR to extract text from images, processes this text to clean and validate the data, and then uploads it to a Google Sheet for easy access and analysis. Here’s an overview of how it works:

Key Components

1. Image Processing:

   • Enhancement: The images are first enhanced to improve the accuracy of text recognition. This involves resizing, increasing contrast, and applying filters to make the text more readable for OCR.

2. Optical Character Recognition (OCR):

   • Text Extraction: Using Tesseract OCR, the script extracts text from the enhanced images. Tesseract is a powerful OCR engine that can recognize and read text in various languages and formats.

3. Data Validation:

   • Cleaning: The extracted text often contains noise and errors. The script cleans this data by removing unnecessary characters and correcting common OCR mistakes.
   • Validation: To ensure the extracted data is useful, the script validates the data against specific criteria. For instance, it checks if the data contains a certain number of odds and if these odds meet predefined conditions.

4. Google Sheets Integration:

   • Headers Setup: Before uploading any data, the script sets up headers in the Google Sheet to ensure the data is organized properly.
   • Data Upload: The validated data is then uploaded to a specified Google Sheet. This step uses the Google Sheets API to interact with the sheet, allowing for automated updates without any manual intervention.
   • Clearing Old Data: Before uploading new data, the script can clear old data from the sheet to avoid clutter and maintain accuracy.

The Workflow

1. Setup:

   • Folders: Create a folder named tennis on your desktop with a subfolder named screenshot. Place all the screenshots you want to process in the screenshot folder.
   • Credentials: Place your Google Sheets API credentials in the tennis folder.

2. Processing:

   • The script processes each screenshot in the screenshot folder. It enhances the image, extracts and cleans the text, and validates the data.

3. Uploading:

   • After validation, the data is uploaded to a Google Sheet. The sheet is set up with appropriate headers, and old data can be cleared before new data is added.

4. Analysis:

   • Once the data is in the Google Sheet, it can be easily analyzed and shared. The Google Sheet format allows for powerful data manipulation and visualization tools, making it ideal for sports betting analysis.

Benefits

• Automation: Automates the tedious process of data extraction, saving time and reducing errors.
• Accuracy: Enhanced images and validated data ensure high accuracy in the extracted odds.
• Integration: Seamless integration with Google Sheets makes it easy to access and analyze the data from anywhere.

Conclusion

This project showcases how combining OCR technology with cloud-based tools like Google Sheets can revolutionize data management in sports betting analysis. By automating the extraction and upload process, we can focus more on analyzing the data and less on the mundane task of data entry.