Context

I wanted to learn how to scrape data from web pages into my R sessions to analyze things I otherwise wouldn't be able to analyze. I found an incredibly helpful tutorial on DataCamp.com, but I also decided that, in order to *really *learn it, I needed to pick my own dataset to work with. I am a huge hockey fan and I've wanted to play with some hockey data for a while, but I hadn't quite found what I was looking for here on Kaggle... so I decided to kill two birds with one stone and make this dataset.

Content

Within, there's year-by-year skater stats from 30 leagues across the most recent 38 seasons. There's also a "dim" table for each player where I scraped their height, weight, birthdate, birthplace, and draft position (if available).

Acknowledgements

All data was gathered from EliteProspects.com using the rvest package in R. Special thanks to EliteProspects for maintaining the most complete world ice hockey database that I've seen online, the creators of rvest, and to Arvid Kingl for the incredibly helpful rvest tutorial that helped me get up and going on this project.

Inspiration

I'm mostly excited to build some cool visuals and models with the data. I want to answer questions like: at what age do NHL players peak? Is it different depending on what round they're drafted in? How well do we expect a player to fare in X league based on how he did in Y league the preceding season?