This blog seeks to bring quantitative analysis to the combat sports world in a form that is approachable for non-technical audiences but still rigorous for those who are more quantitatively inclined.
I am a Data Scientist currently living in the Philadelphia, PA area. I’ve always been passionate about both data and sports. I was a collegiate soccer player at Dickinson College before earning an M.S. in Statistics from Carnegie Mellon University. Now I spend my free time combining my passions to conduct quantitative analysis primarily on combat sports, like mixed martial arts (MMA).
I’ve witnessed most major American sports go through some sort of analytics revolution, but I have not yet seen the same growth in MMA. Hence, I think there’s room to use publicly available MMA data in new ways that are beneficial to anyone interested in the sport, from fighters and coaches to MMA experts and sports bettors to even casual fans.
I invite feedback on all of my work. While all of my current plans for this blog involve quantitative MMA analysis, I am interested in branching out to other sports analytics or data science topics in the future. I’m always open to connecting with others to collaborate or just exchange ideas. The best way to connect with me is through Twitter, and my Linktree features some of my other work - to include my other websites, combat sports analytics resources I’ve created, etc.
For those wondering where the name LiteralFightNerd came from, I began sharing my early quantitative MMA analysis on Twitter and Reddit. In September 2020, I posted a long piece to Reddit on a machine learning algorithm I created that predicts judging decisions by round in the UFC. That post received over 100 comments. The very first comment, which came almost immediately, read “literal fight nerd” (proof). A couple months later this blog was born in honor of one of Reddit’s finest.
I literally am a fight nerd. Through this blog I hope to show that fight nerds can make substantive contributions to combat sports.
Enjoy!
-Nate