When you are working with sports betting and data modeling, there is loads of data and information available on the internet. Now one of the problems with this wealth of information on professional sports is trying to harvest and collect this data.
Web scrapers have been around for some time and are extremely useful when trying to collect this large trove of information. Now a scraper can be written in VBA, Python, or many other languages, however I prefer python due to the error handling being better than VBA, as well as the ripping speed. What takes VBA several minutes to accomplish, a python script can accomplish in a few seconds.
In this video I am using Daniel Jones as the NFL Quarterback that I want to collect seasonal data on, however you can use this for MLB, Soccer, NBA, WNBA, college sports, or just about anything you want to scrap to get into your betting models.
One word of caution/help toward the sites you are going to scrape, please be aware that they will only allow so many pings to their site. If you create an oversized scrapper that tries to take all data from all pages, you can find yourself being blocked from hitting their site, as you are wiping out their connections, and hammering their servers too much. Remember when scraping from a free resource, be kind and don’t crush their servers, otherwise it won’t be free in the future.
If you have any questions about this walk through, please let me know. I am always willing to assist with data modeling and sports modeling where I can, even if it means assisting with a scraper.
Happy wagering!
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