Jim Albert is a distinguished professor of statistics whose research interests lie in Bayesian modeling and the application of statistical thinking in sports. His work delves into the principles of statistics and their practical applications. His publications explore the nuances of data modeling and the utilization of Bayesian methods for uncovering insights within data.
Focusing on the intersection of baseball and data analysis, this book introduces sabermetrics to fans and provides R programming skills for data exploration. It aims to motivate students to engage with large baseball datasets, enhancing their research capabilities. By learning R in the context of baseball, readers will gain practical insights that encourage independent exploration and analysis in the realm of sports statistics.
"Preface Baseball has always had a fascination with statistics. Schwarz (2005) documents the quantitative measurements of teams and players since the beginning of professional baseball history in the 19th century. Since the foundation of the Society of Baseball Research in 1971, an explosion of new measures have been developed for understanding offensive and defensive contributions of players. One can learn much about the current developments in sabermetrics by viewing articles at websites such as www.baseballprospectus.com, www.hardballtimes.com, and www.fangraphs.com. The quantity and detail of baseball data has exhibited remarkable growth since the birth of the Internet. First data was collected for players and teams for individual seasons { this type of data is what would be dis- played on the back side of a Topps baseball data. The volunteer-run Project Scoresheet organized the collection of play-by-play game data, and this type of data is currently freely available at the Retrosheet organization at www.retrosheet.org/. Since 2006, PITCHf/x data has been measuring the speeds and trajectories of every pitched ball, and newer types of data are collecting the speeds and locations of batted balls and the locations and movements of elders. The ready availability of these large baseball datasets has led to challenges for the baseball enthusiast interested in answering baseball questions with these data. It can be problematic to download and organize the data. Standard statistical software packages may be well-suited for working with small datasets of a specific format, but they are less helpful in merging datasets of different types or performing particular types of analyses, say contour graphs of pitch locations, that are helpful for PITCHf/x data"-- Provided by publisher
Focusing on Bayesian inferential methods, this book provides an introduction to Bayesian modeling through computational techniques using the R language. The new edition features updated R code illustrations, reflecting the dramatic growth in this field and enhancing the reader's practical understanding of Bayesian applications.
Introduction.- Simple Models.- Situational Effects.- How Do We Evaluate
Players.- Clutch Hitting.- Streakiness.- Does The Best Team Win?- Predicting
Results.- Wrap-Up. Introduction; Ch01: Simple Models from Tabletop Baseball
Games; Ch02: Exploring Baseball Data; Ch03: Introducing Probability; Ch04:
Situational Effects; Ch05: Streakiness (Or, The Hot Hand); Ch06: Measuring
Offensive Performance; Ch07: Average Runs per Play; Ch08: The Curvature of
Baseball; Ch09: Measuring Clutch Play; Ch10: Prediction; Ch11: Did the Best
Team Win?; Ch12: Post-Game Comments (A Brief Afterword); Appendix: Baseball
Games; Bibliography; Index.
Focusing on statistical modeling, this book explores the wealth of data generated in baseball, appealing to fans and media alike. It tackles key questions such as player ratings, game outcome predictions, and situational analysis, while also identifying the most valuable players in the World Series. Designed for a general audience, it is accessible without requiring extensive knowledge of probability or statistics, though familiarity with high school algebra is beneficial.
A valuable research tool in continuum mechanics for more that 50 years, this highly regarded engineering manual focuses on three important aspects of elasticity theory: finite elastic deformations, complex variable methods for two-dimensional problems for both isotropic and aeolotropic bodies, and shell theory. Additional topics include three-dimensional problems for isotropic and transversely isotropic bodies.
