I'm Dan. I write data-driven stories about sports and dig deeper into the underlying numbers behind why some athletes and teams perform better than others. I do all my analyses in R and strive to share as many of them as I can here on GitHub for the sake of clarity, reproducibility, and to help others learn how a lot of "fancy stats" are calculated. Here are a few of my favorite projects, which you can find the code for inside my GitHub repositories.
- An R package to scrape and store NHL play-by-play data
- Code
- An extreme gradient boosting model to predict goals in the NHL
- See it in action in the hockeyR package
- Code
- An automated Twitter bot that tweets about MLB home runs and the parks in which they wouldn't have made it out of
- Check it out 👇
- Code
- A companion app to @would_it_dong
- Created using R Shiny, allows users to overlay any hit on top of any field to see if it would have left the yard
- Check it out 👇
- Code
- An R Shiny app where users can compare and contrast NFL team draft pick success using Pro Football Reference's Approximate Value
- Check it out 👇
- Code
- Another hockey model attempting to quantify expected assists in the OHL
- Honroable mention in the 2021 Big Data Cup
- Includes this R Shiny app with which to explore the results
- Code