Optimize Web scraping project

The objective of this project is to optimize an already functional web scraping program in python for the Betsson betting website, (IMPORTANT NOTE: it has to be betsson Spain), to extract odds from various Spain football competitions: La Liga, Copa del Rey, and the Champions League. The odds to be extracted include the Total Goals market and Both Teams Score, as shown in the attached screenshots. A functional Python program using Selenium is provided and can be executed to analyze the requeriments. The problem lies in excessive RAM consumption (~6GB once the webdrivers are created) and the initial time required for creating the webdrivers. I would consider acceptable a memory consumption of up to ~2GB. The less, the better. Once the webdrivers are created, it takes less than 1 second to retrieve the odds for the mentioned competitions (IMPORTANT: this time should be less than 1s). The program generates a thread for each game, and each thread has its own webdriver to monitor the odds. Selenium was chosen because no API calls were identified on the Betsson website, feel free to use another technology. The program is designed to obtain the odds every x seconds calling the function get_bets, more information in the source code. Important: The code can be adapted or rewritten from scratch, but it must respect the format in which bets are returned. In other words, a list of bets must be returned with the odds information, as seen in the BetOverUnder and BetYesNo classes. Who will get the job? No surprises here; it's whoever finds a better approach to reduce memory consumption by the program, or improves the existing one. Offers will be more highly regarded if, instead of stating 'I know X technologies and have X years of experience in X technology,' they have seen the code of the program, executed it, identified the issues, and believe they know how to address them. If you have any questions, feel free to ask.