Hi again! Pearson's correlation coefficients In part 2 of this series on what makes a good NBA player, I looked at which combine statistics like max vertical leap, lane agility, and bench press in combination with physical attributes like height, wingspan, hand size, etc. correlate most with rookie success in their first year, as evaluated by advanced metrics like offensive/defensive rating, assist %, rebound %, player impact estimate (PIE), etc. You can find a jupyter notebook with all of these Pearson's correlation coefficients at: github link . Feel free to play around with it to see if you can find any interesting correlations! Big takeaways: 1. Jumping ability =/= rebounding ability: Conventional wisdom suggests that good jumpers are probably good at getting rebounds. However, I found that max vertical leap has a significantly negative correlation with rebound % , for both offensive and defensive rebounds. In reality, it's the guards that have the best jum
Hi again! Today I will explore what physical attributes contribute to a successful NBA player. When we watch basketball, we sometimes hear the announcers and analysts talk about stats like wingspan, height, and hand size. How do these attributes contribute to a good player? Are there any that are particularly important? For this part one, I have scraped data from stats.nba.com to look at the distribution of physical attributes from the 2010-2017 NBA combine. To use my simple data scraper, check out my github: https://github.com/dzchen314, or email me for a tutorial (scraping data from stats.nba.com can be pretty tricky). First, I distill the data on these pages (https://stats.nba.com/draft/combine-anthro/#!?SeasonYear=2010-11) to the relevant features, such as by calculating a hand area feature in place of hand length and hand width (units are Imperial, pounds, inches, and inches^2). Now let's plot a notable correlation: Wingspan vs. height: both given in i