Ratings4
Average rating3.5
"For decades, statistics such as batting average, saves recorded, and pitching won-lost records have been used to measure individual players' and teams' potential and success. But in the past fifteen years, a revolutionary new standard of measurement, sabermetrics, has been embraced by front offices in Major League Baseball and among fantasy baseball enthusiasts. But while sabermetrics is recognized as being smarter and more accurate, traditionalists, including journalists, fans, and managers, stubbornly believe that the 'old' waya combination of outdated numbers and 'gut' instinctis still the best way. Baseball, they argue, should be run by people, not by numbers. In this informative and provocative book, the ESPN analyst and senior baseball writer demolishes a century's worth of accepted wisdom, making the definitive case against the long-established view. Armed with concrete examples from different eras of baseball history, logic, a little math, and lively commentary, he shows how the allegiance to these numbers--dating back to the beginning of the professional game--is firmly rooted not in accuracy or success, but in baseball's irrational adherence to tradition. While Law gores sacred cows, from clutch performers to RBIs to the infamous save rule, he also demystifies sabermetrics, explaining what these 'new' numbers really are and why they're vital. He also considers the game's future and changes that will transform baseball and all of professional sports"--Amazon.com
Reviews with the most likes.
This isn't just a useful book for baseball or sports analytics. Law's approach to making sense of data in the applied field of baseball points out the many flaws and pitfalls of any analytical pursuit. Cases of “managing to the stat” or simply relying on counting stats to the exclusion of useful context are profoundly atavistic, but Law keeps pointing out how these lay approaches persevere and thrive despite more coherent methods.
I generally don't get much out of sports analytics books–they tend to be introductory primers to many of the concepts analytics nerds are already deeply familiar with. Where Smart Baseball excels is that Law does more just than show the advantage of a contextual number over a mere counting stat. Instead, he spends a great deal of a time exploring how the fallacies that went into creating myths like the relevancy of a Save or Pitcher Win were inculcated into fan and even subject matter expert's understanding of the game. It's this constant refrain about the emergence of error in commonsense stats that makes the book an extremely useful polemic against the use of shallow approaches to big data and broader analytics.