Baseball fans are often passionate about statistics, but true numbers fanatics want to go beyond the 'baseball card' stats and make comparisons through other objective means. ""Sabermetrics"" uses algebra to expand on statistics and measure a player's value to his team and how he ranks among players of different eras. The mathematical models in this book, a follow-up to ""Understanding Sabermetrics"" (2008), define the measures, supply examples, and provide practice problems for readers.

Linear Algebra: Algorithms, Applications, and Techniques, Fourth Edition offers a modern and algorithmic approach to computation while providing clear and straightforward theoretical background information. The book guides readers through the major applications, with chapters on properties of real numbers, proof techniques, matrices, vector spaces, linear transformations, eigen values, and Euclidean inner products. Appendices on Jordan canonical forms and Markov chains are included for further study. This useful textbook presents broad and balanced views of theory, with key material highlighted and summarized in each chapter. To further support student practice, the book also includes ample exercises with answers and hints.

Interest in Sabermetrics has increased dramatically in recent years as the need to better compare baseball players has intensified among managers, agents and fans, and even other players. The authors explain how traditional measures-such as Earned Run Average, Slugging Percentage, and Fielding Percentage-along with new statistics-Wins Above Average, Fielding Independent Pitching, Wins Above Replacement, the Equivalence Coefficient and others-define the value of players. Actual player statistics are used in developing models, while examples and exercises are provided in each chapter. This book serves as a guide for both beginners and those who wish to be successful in fantasy leagues.

This book is concerned with the optimization problem of maximizing the number of spanning trees of a multigraph. Since a spanning tree is a minimally connected subgraph, graphs and multigraphs having more of these are, in some sense, immune to disconnection by edge failure. We employ a matrix-theoretic approach to the calculation of the number of spanning trees.The authors envision this as a research aid that is of particular interest to graduate students or advanced undergraduate students and researchers in the area of network reliability theory. This would encompass graph theorists of all stripes, including mathematicians, computer scientists, electrical and computer engineers, and operations researchers.