What it does

NBA Shot Focus analyzes shot data from the NBA 2016-2017 season Allstars. The analysis goal is to determine which NBA player is the best at making tough shots, most often and most consistently. The factors used in analyzing shot difficulty is: defenders distance while taking shot, time left on the shot clock, dribbles taken, and touch time.

How I built it

NBA Shot Focus scrapes stats.nba.com for NBA shot data for 2016-2017 season Allstars via python. Then the python sends the front-end JSON with required data for analysis. The JSON data is then parsed and converted through javascript to graphs that show each Players strengths and weaknesses for different factors in shot difficulty.

Challenges I ran into

Stats.nba.com does not provide an API for stats, so I had to write a python program for the backend that scrapes NBA for the data.

Accomplishments that I'm proud of

I'm proud to have completed this hackathon by myself, because this is my first time working with data analysis.

What I learned

I learned how to connect back-end to front-end through flask and also learned more about handling data and analyzing it. Also, based on my analysis I found out James Harden through my formula makes the most difficult shots. Before I started this project I predicted that the top would most likely be James Harden or Russell Westbook (ended up 3rd), so I think analysis is providing similar results to expectation.

What's next for NBA Shot Focus

I hope to add more analysis that moves beyond just making difficult shots, and also make it load every player in the NBA.

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