International Journal of Business, Humanities and Technology Vol. 2 No. 4; June 2012
67
Predicting Run Production and Run Prevention in Baseball: The Impact of
Sabermetrics
Philip Beneventano
Ernst & Young
200 Clarendon St.
Boston, MA 02116, USA.
Paul D. Berger
Bentley University
175 Forest St.
Waltham, MA 02452, USA.
Bruce D. Weinberg
Bentley University
175 Forest Street
Waltham, MA 02452, USA.
Introduction
The game of baseball is very popular in many countries, especially the United States, Japan, South Korea, China,
and a variety of Central American countries. As a result, the revolution in statistics that began a few decades ago,
and continues today, has spearheaded a revolution in the analysis of baseball data and its use in decision making
about which players a team should pursue and what value a player has to a baseball team.
The revolution started with Bill James, a man who, in the 1970s, worked as a security guard during the day and
had no professional baseball experience. He started composing his extremely popular Baseball Abstract books in
the late 1970s and coined the word “sabermetrics.†The word sabermetrics comes from an acronym of the Society
of American Baseball Research and represents an analysis of the game of baseball using detailed performance
data, rather than qualitative methods based on such numbers as a player’s height and weight, “look on his face,â€
and relatively simple statistics such as batting average (BA - number of hits divided by number of at-bats). While
more traditional professionals and fans might view popular statistics like batting average and strikeouts as
indicators of performance, current “sabermetricians†tend to use different, more detailed statistics, such on-base
percentage (OBP - ([hits plus walks plus hit by pitches] divided by [at-bats plus walks plus hit by pitches plus
sacrifice flies]) and frequently create their own measures to analyze which players (or te