I recently came across a post (http://www.danielforsyth.me/exploring_nba_data_in_python/) demonstrating the ease of gathering data from NBA.com's API. I'm really excited about the way Andrew Wiggins has been playing this year, so I wanted to explore how his play has changed since the beginning of the year.

On Dec 23rd, the wolves played their first game against the Cavaliers. Wiggins had a huge game, putting up 27 points. Many journalists have depicted this game as a turning point in Wiggins' year.

Here, I plot shooting data from before and after Dec 22nd (so the games before Dec 23rd and the Dec 23rd and all following games). I'm not in love with splitting the data as before and after, as this depicts Wiggins' growth as occuring suddenly on Dec 23rd. I'm guessing Wiggins' growth is better modeled as continuous, gradual improvement, so maybe I'll do future posts that depict Wiggins' learning as continuous. For now, I'll stick with before/after as this is easier to graph.

I still have a lot to learn about NBA.com's API, so this post only uses shooting data. Any comments and suggestions would be greatly appreciated.