This is a walk through of my process on how I collect, scrub, prep, and model my data for any sport. Now I have used this process
for NBA, NFL, MLB, and Soccer. This is the reason it works so well is that the process is always consistent, and can just plug and chug
when it comes to the information you are pulling down.
In the process I will walk through how I collect data ID's that I will need to pull down more in depth information on players for the NFL
and how I will then prep another Python Scraper to fetch this more granular data.
In doing so, I can the scrub the data to prep it for use in a sports betting model within Python or excel.
Once I have the data scrubbed and prepped to use the points of information I need, I will then build the Python model I want to test or use.
Once I have collected the data, I do not need to refetch until I believe there is more updated information on more recent games. This is what makes the process
work so well, is then I can really focus on the model portion, and test my theories.
As always, this sprots betting model wont let your wagers beat a sports book, but it is a good start on foundational methods to help you become a more focused
and methodical sports bettor.
If you have any questions on the process or what I did, feel free to leave a comment and I can try to
0:00 - Intro
0:55 - Find the data you want to scrape and prepare Python for betting model
4:34 - Set Scrape down ID's for players using Python for betting model
7:44 - Clean up the HTML you scraped
14:20 - Prepare CSV file of records you want to scrape
15:50 - Build your player scraper
30:31 - Scrub the data you have scraped
44:20 - Create Simple Averages Model for Tight Tend TD's
Music by Joystock - www.joystock.org
2 авг 2024
