Testing Hypotheses using Data Viz
As documented previously on this blog, I am a pretty big Royals fan. The month of July was, then, pretty exciting for me
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Predicting the Next Pitch: A Markov Chain Approach
I’ve written in the past about using machine learning to predict a pitcher’s next pitch, which is a particularly difficult problem. This blog
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A Text Analysis of Hall of Fame Speeches
Every summer, Major League Baseball inducts a small numbers of players into the Hall of Fame, with each inductee giving a speech. This
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Survival Analysis: How Long Do Careers Last?
Survival analysis inspects, well, how long an entity survives. In less morbid terms, it’s a methodology to understand time until event. This blog
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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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What’s Wrong with the Royals’ Offense?
As my friends know, I am a die-hard Kansas City Royals fan. When being realistic, I had modest hopes for the Royals this
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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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Which Teams are Most Similar Offensively?
This is a short post about finding similarities among the offenses of MLB teams. To accomplish this aim, I used two statistical methodologies
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Exploring 2016 Pitching Data
One of my favorite parts of baseball data is its depth. So many interesting nuances exist – we just have to look! That
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