Sports Analytics & Streaming Data Science on Twitch
In this video, I had the pleasure of speaking with Nick Wan. Nick streams data science content on Twitch but has also worked in sports […]
Classifying MLB Hit Outcomes
In 2015, MLB introduced Statcast to all 30 stadiums. This system monitors player and ball movement and has provided a wealth of new information, in the process […]
Data Science in Sports (Talk at Northwestern University)
This past weekend, I was honored to speak to almost 100 Kellogg MBA students about my work in sports analytics.
Jimmy Graham: A risk worth taking for the Chicago Bears?
Bears fans got a lesson in regression to the mean last season. It may have been wishful thinking, but Bears fans were convinced that Matt […]
Using ML to Understand Real Madrid’s Poor Last decade in La Liga
Using K-Means Clustering to analyze the types of teams Real Madrid and Barcelona drop points against in La Liga. This is a shorter version of […]
Using NCAA Stats to Predict NBA Draft Order
Intro & Lit Review Predicting the NBA draft is always difficult. Should you draft a player on college statistics, NCAA tournament performance, combine results, potential, […]
Beyond The Arch: A Closer Look at Post-Up Bigs
Beyond The Arch is a series of articles where I use K Means Clustering to better understand how players are used on offense in the […]
Did Cheating Really Help the Astros Win?
At this point, no one is denying that the Astros cheating in the 2017 season. I wanted to find out how much it actually helped them win.
Beyond The Arch: A Closer Look at Spot-Up Bigs
Beyond The Arch is a series of articles where I use K Means Clustering to better understand how players are used on offense in the […]
A Firsthand Account Interviewing at MLB Front Offices
Over the last few months, I’ve applied for several jobs in MLB front offices. I wanted to recount my experience so others could see what […]