Book Review Moneyball

Michael Lewis’ Moneyball is a fascinating account of a recent revolution in baseball. The book tells the story of the Oakland A’s, who pioneered the use of advanced statistics in player evaluation to gain a competitive advantage. The A’s caught Lewis’ attention due to their ability to consistently field playoff calibre teams despite having a payroll less than a third the size of rivals such as the New York Yankees and the Boston Red Sox. Prior to the A’s run of success, player evaluation was largely the purview of scouts, who Lewis portrays as tobacco-chomping luddites who speak in baseball jargon that barely resembles English. The A’s General Manager, Billy Beane, turned tradition on its head by using Harvard-educated, laptop-wielding statisticians to identify and evaluate amateur talent. For these disciples of ‘Sabermetrics’ (the use of analysis to understand baseball performance), a scout’s assurance that a pitcher ‘has a cannon’ for an arm isn’t as important as the pitcher’s performance record. Although written in 2004, the book remains relevant today due to the rapid adoption of Sabermetrics throughout baseball over the last few years and the significant impact these techniques have had on the game. Indeed, the Boston Red Sox, winners of two of the last four World Series, employ Bill James, the father of the Sabermetrics movement, as a consultant. The book is also important in the business world because of the parallels between this baseball revolution and the analytics explosion in business. Moneyball can be a valuable asset to Pricing and Revenue Management practitioners who are challenging decisions made on gut feel and intuition and advocating a cultural shift to data-driven decision-making and performance measurement. The book is a quick, fun read, and presents a compelling case for using advanced analytics to inform decisions to result in a competitive edge. To supplement the judgement of scouts, Billy Beane and the A’s had hired a number of front-office personnel not for their baseball knowledge, but for their acumen and statistical expertise. This new approach resulted in changes across the organisation; changes in amateur scouting, player development, trade strategy and even in-game decisions. Just the way that new metrics such as Revenue Per Available Seat Mile and Revenue Per Available Room transformed decisionmaking in airlines and hospitality, new metrics from statistical analysis drove the A’s organisational changes. For example, batting average had long been considered the most relevant measure of player performance, but the A’s found that batting average was actually a poor predictor of future performance (due to a high variance based on the random results of balls batted into play). Metrics such as on-base percentage and slugging percentage are greater predictors of future performance because they reflect a player’s pitch selection and power, which are repeatable skills. The book explores how the A’s used these metrics as cornerstones of innovative player acquisition and player development strategies.