Ally Blake - Generating New Data Through Simulating an NFL Game

For information on upcoming conferences, visit https://www.dataconf.ai. Generating New Data Through Simulating an NFL Game by Ally Blake Abstract: A play-level game simulation model can precisely quantify the impact and any intended and unintended consequences of potential rules changes. The goal of this project is to mimic a real NFL game, review the results of simulated games, compare to what one expects from a real game, and evaluate the results based on points per game and plays per game. Bio: Ally Blake got her undergraduate degree from the University of Tennessee with a major in Business Analytics. She interned in 2019 at the NBA League Office’s Basketball Strategy and Analytics team where she worked on various projects related to officiating. After college, she worked two years at IBM as an analytics consultant before moving to New York City in 2022 to work for the NFL on the Football Data & Analytics team. In her current role, she provides Officiating, Replay, and Football Operations reporting, while also using Next Gen Stats and other advanced data sets to improve the game. Ally has spent the last three years working at the NFL, while also finishing an MS degree from Georgia Tech. Presented at The New York Data Science & AI Conference Presented by Lander Analytics (August 26, 2025) Hosted by Lander Analytics (https://www.landeranalytics.com)