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. This book uses algebra to expand on statistics and measure a player's value to his team and how he ranks among players of different eras.

Sabermetrics, the specialized analysis of baseball through empirical evidence, provides an impartial perspective from which to explore the game. In this work, the third in a series, three mathematicians employ statistical science in an attempt to answer some of baseball's toughest questions. For instance, how good were the 1961 New York Yankees? How bad were the 1962 Mets? Which team was the best of the Deadball Era? They also strive to determine baseball's greatest player at various positions. Throughout, the objective evidence allows for debate devoid of emotion and personal biases,...

In this work, we consider the optimization problem of maximizing the number of spanning trees among graphs and multigraphs in the same class, i.e. having a fixed number of nodes and a fixed number of edges. 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. 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...

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 along with new statistics define the value of players. Actual player statistics are used in developing models, while examples and exercises are provided.