Posts
Introducing xp_wOBA (Expected Pitch wOBA)
In this post, I created a new performance metric for both hitters and pitchers called xp_wOBA (Expected Pitch wOBA). It's a new metric to determine a single pitch's quality. It takes into account release speed, pitch location, hitter's count, pitch movement, etc. to determine the quality of a pitch.
Predicting Customer Tenure...with MLB Hitters
How long will a customer stay with our business or, in this case, how long will an MLB hitter stay in the MLB? In this post, I go through the value of knowing how long a customer will be with an organization, EDA of MLB data, how to clean and setup data for modeling, and how to fit a linear model and a gradient boosted tree model with xgBoost.
Customer Segmentation...with MLB players Pt. 1
Many businesses try to create customer segmentation to gain a greater understanding of their customer base. This post will show how this can be done from start to finish and how to interpret and validate the newly found segments. Throughout this example advice on how to do this with retail data is given.
Welcome to The Lob
Welcome to my new blog, The Lob. I plan on using this blog to to explain and practice various data science techniques using sports data.