Hockey Analysis in R: Public and Private Perspectives By Namita Nandakumar Abstract: There have been many catalysts for data-driven research in sports. Fans want to know if a certain player is secretly bad, if their team has a real shot at winning a championship, and if their front office is making good decisions. Teams want to know how to optimize in-game and player personnel decision-making throughout the year, from the regular season and playoffs to free agency and the amateur draft. We will explore and discuss both perspectives by analyzing publicly available NHL data in R to create a simple win probability model as well as identify team draft tendencies. Bio: Namita is currently a Quantitative Analyst for the Philadelphia Eagles. She graduated from Wharton in May 2018 with a BS in Economics and a concentration in Statistics. Namita has also written for The Athletic Philadelphia and Hockey Graphs, primarily on the topic of draft strategy and evaluation in the NHL. Twitter: @nnstats Presented at the 2019 New York R Conference (May 11th, 2019)