About
Jim Albert is an Emeritus Distinguished University Professor in the Department of Mathematics and Statistics at Bowling Green State University, where he has taught since 1979. He is one of the leading figures at the intersection of Bayesian statistics, sports analytics, and statistics education.
His research spans Bayesian modeling, the application of statistical thinking in sports (particularly baseball), and innovations in how statistics is taught. He is co-author of several influential books, including Analyzing Baseball Data with R, now in its third edition, and author of the widely used LearnBayes R package.
Books
Analyzing Baseball Data with R (3rd ed.)
With Ben Baumer & Max Marchi · CRC Press · Updated with tidyverse and Statcast chapters
Probability and Bayesian Modeling
With Monika Hu · Chapman and Hall/CRC · Bookdown version available
Visualizing Baseball
CRC Press · Data visualization techniques applied to baseball statistics
Bayesian Computation with R (2nd ed.)
Springer Verlag · Introduction to Bayesian computation using R
Teaching Statistics Using Baseball (2nd ed.)
Mathematical Association of America · Statistics education through the lens of baseball
Curve Ball (2nd ed.)
Springer-Verlag · General introduction to statistical thinking in baseball
Blog
Baseball Research
Exploring Baseball with R
Ongoing blog posts applying statistical methods to baseball data — from Retrosheet to Statcast.
Patterns of Home Run Hitting in the Statcast Era
Analysis of home run trends across the Statcast era, exploring how launch angle and exit velocity relate to home run production.
Interactive Baseball Explorers
Collection of R Shiny apps for exploring baseball data interactively, including home run rates and zone visualizations.
A Course in Exploratory Data Analysis
Lecture notes for an EDA course at BGSU — covering Tukey's methods with modern R implementations.
R Packages
Functions for learning Bayesian inference. Available on CRAN.
Companion package for Probability and Bayesian Modeling. Includes visualizations for Bayesian inference.
Collect, manipulate, and visualize baseball pitch zone measurements from Statcast.
Markdown documents illustrating Bayesian computations with R.
Datasets and functions for performing exploratory data analysis methods taught in the EDA course.
Teaching Resources
Teaching Statistics Using Baseball
Supplementary materials, datasets, and R scripts for the MAA textbook on statistics education through baseball.
Bayesian Computation with R
Companion site with R scripts, datasets, and errata for the Springer text on Bayesian computation.
Probability and Bayesian Modeling
Full bookdown version of the Chapman & Hall text, freely available online with interactive R examples.
Teaching Datasets
All datasets from Teaching Statistics Using Baseball — organized by chapter, freely available.