Building an NBA Model using Advanced NBA Stats - Part 1

In this video, we begin building an NBA model by first scraping advanced NBA stats from a very popular website, basketball-reference.com. We then save the data in a CSV file and open it in an Excel spreadsheet. This is part 1 of a two part series describing how to build an NBA model to predict game outcomes.

[@waterbottle37]

Love the straight forward and detailed explanation of your python code, so helpful

[@KerrySportsAnalyst]

Hi Water! I'm glad you like the video. I try to explain code in the easiest way possible. Especially the tricky parts. Cheers!

[@BRflaNk]

You brought together two of the things I love most: Sports and coding. I'm about to do it for the NFL

[@KerrySportsAnalyst]

Hi BR! You speak my language. I love coding, sports, and analytics. Cheers!

[@mdelair93]

I was hoping you’d do something for NBA or MLB after watching your NFL videos. Thanks for sharing!

[@KerrySportsAnalyst]

Hey there MD! I had to do March Madness and NBA. Looking forward to upgrading my NFL analysis. Cheers!

[@Cobbtrades]

good stuff, you can also do the following
team_df = team_df.astype({'G': int, 'OPts': int, 'DPts': int, 'ORtg': float, 'DRtg': float, 'Pace': float})
intead of writing in line by line :-)

[@KerrySportsAnalyst]

Hi Cobb! Wow! That certainly makes sense and is much cleaner. Thanks for sharing! Btw, I'm still planning on posting a video on an NBA ML model. It will probably be posted in a couple weeks. Cheers!

[@Cobbtrades]

When is part 2 coming? Thanks