AxeDB: Guitar Pricing Intelligence
New project for studying the used and vintage guitar markets
Data are.
Data scientist and armchair sabermetrician.
Latest posts
Multi-Armed Bandits in Python: Epsilon Greedy, UCB1, Bayesian UCB, and EXP3
This post explores four algorithms for solving the multi-armed bandit problem (Epsilon Greedy, EXP3, Bayesian UCB, and UCB1), with implementations in Python and discussion of experimental results using the Movielens-25m dataset.
Offline Evaluation of Multi-Armed Bandit Algorithms in Python using Replay
Multi-armed bandit algorithms are seeing renewed excitement, but evaluating their performance using a historic dataset is challenging. Here's how I go about implementing offline bandit evaluation techniques, with examples shown in Python.
Understanding the AdTech Auctions in Your Browser: an Analysis of 30,000 Prebid.js Auctions
An analysis of auction dynamics in client-side header bidding
Predicting The Shift: Boosting and Bagging for Strategic Infield Positioning
Using machine learning to predict strategic infield positioning using statcast data and contextual feature engineering.
Visualizing MLB Team Rankings with ggplot2 and Bump Charts
A quick tutorial on fetching MLB win-loss data with pybaseball and cleaning and visuzlizing it with the tidyverse (dplyr and ggplot).
On Draft Pick Value, the New Lottery, and Tanking
Tanking becomes a hot topic each season once it becomes apparent which of the NBA's worst teams will be missing the playoffs. In this post I address the value of a draft pick and of tanking in the league's end-of-season rankings, with applications to trade valuation and the impact of the league's recently proposed changes to the draft.
A Statcast Tribute to Baseball’s Strangest Pitch: the Eephus
I've been borderline obsessed with the eephus pitch for some time now. Every time I see a player pull this pitch out of their arsenal I become equal parts excited and bamboozled. Startlingly little research has been done to date on this uncommon pitch, and thus, this post is going to serve as an exploratory analysis of and tribute to the mythical eephus.
Leaving MLB: Lessons Learned in my First Data Science Role
For the past three months I have had the exciting opportunity to intern as a data scientist at Major League Baseball Advanced Media, the technology arm of MLB. This post gives an overview of what I've been working on and the advice I would give a fellow first-time data scientist on their first day on the job.
Introducing pybaseball: an Open Source Package for Baseball Data Analysis
Throughout my baseball-facing work at MLB Advanced Media, I came to realize that there was no reliable Python tool available for sabermetric research and advanced baseball statistics. As a response to this, I built pybaseball - a Python package for baseball data analysis.