The tool: nba-stats

This post introduces nba-stats, a Swift command line application that downloads Draft Combine Historical data into csv files. The goal is not so much to explain how the app was developed but to share the data. See below for some of the data that’s available:

Body fat %
Hand length/width
Height W O Shoes
Height W Shoes
Standing Reach
Weight Lbs
Wingspan
Pick Overall
Spot Up And Non Stationary Shooting Drill Data
Lane Agility Time Seconds
Shuttle Run Seconds
Three Quarter Sprint Seconds
Standing Vertical Leap Inches
Max Vertical Leap Inches
Max Bench Press Repetitions

I see this data, even though far from everything is exposed to the “public”, being valuable to answer questions about the following topics:

Physical trend through time. Have athletes gotten faster, stronger… through time?
School history. How many 1st round picks have come out of Kentucky vs…
How fast do I have to be to meet 1st round pick standards? Since the data can be mapped to the draft pick information, imagine knowing your goals before approaching training every single day.
For fun. Haven’t you wondered the difference between your hand length/width and the average NBA player?

Those are some of the topics that come to mind when I see this information but I’m sure many more can be discovered by the amazing open source community. I’ll also try to explore the datasets in the future to see what insights I can find. I’m already looking forward to it.

The Data

The app

Why Swift

First of all, here’s the code. Now, please don’t judge, the code is far from perfect since it’s my first interaction with Swift. I usually pick problems like these, where I’m comfortable with the workflow, to try to use new programming languages. In my experience, doing the same thing in a different way helps to develop technique and abstraction. The positive outcome of that exercise is very interesting.

The Repo has the instructions on how to use the app. You can check them out and reach out to me if you have any questions.