Tutorial: Machine Learning on Cy Young Voting
This post serves as a tutorial for building machine learning models in Python. The entire codebase for this tutorial can be found on
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python
Building an At-Bat Simulator
Simulation modeling is one of my favorite forms of analysis. Understanding how a process operates under certain conditions has always fascinated me. What
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OPS Projections with Machine Learning
As spring training approaches, the excitement for a new season becomes fresh. Fans and commentators alike discuss teams’ prospects, and multiple organizations release
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Using Machine Learning to Predict Baseball Hall of Famers
Being inducted into Major League Baseball’s Hall of Fame (HoF) is the highest honor a baseball player can receive. The achievement is rare;
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How Good (or Bad) Could the Royals Be?
I’ve always found simulation modeling to be highly informative. Given certain conditions and logic, what is likely to happen given repeated trials? What
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Factor Analysis on HoF Stats
Factor analysis is a methodology to reduce data complexity. Factors are latent variables that represent underlying constructs in data. An interesting baseball-related application
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Finding Similarities Among Pitchers
I’ve had several conversations recently about the nature of baseball stats compared to statistics in other sports, like football and basketball. Baseball, to
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Predicting Tomorrow’s Outcome
Predicting the outcome of future baseball games is notoriously difficult. Some common methodologies are slightly better than a coin flip. If you always
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Exploring 20 Years of Baseball Data (and Predicting Attendance)
Welcome back, readers! Are you ready for some more baseball data science fun? This blog has two main components: 1) exploring aggregated data
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