Gross Productivity Average, or GPA, is a new baseball statistic that measures performance. Accounting for the effect that each plate appearance or baserunning play has on scoring opportunities, it is reported on a scale similar to that for batting average, making it easy for the average fan to understand. Beginning with a detailed explanation of the statistic and its derivation, the book identifies, in Part II, historical patterns in league-average GPA (even the steroids effect is quantified). Practical applications are then explored, as GPA is used in Part III to settle long-running arguments about strategy and in Part IV to reassess players and awards voting from 1952 to 2012.
David P. Gerard
Most Helpful Customer Reviews
This book is a great resource to determine which players really contribute and which don’t. I am a big San Francisco Giants fan and attend 10 or more games per year. It always bothered me that other teams walked Barry Bonds more than 100 times per year. I always questioned if that paid off in the end.
Baseball GPA provides the first careful and well reasoned look at this and many other topics. As I suspected, it did not make sense to walk Bonds so many times. I wish managers of that era had this type of knowledge so Bonds’ stats would have been even more amazing (although the Giants were better off with all those walks).
Baseball GPA describes a new statistic (GPA) that uses a single number to rate each batter and pitcher on a scale like a batting average. It uses computer analysis to assess 50 or more years of at-bat data and simulates games to help answer basic questions about baseball strategy.
The information is easy to understand,...
Baseball GPA is very different than any book I have read on sabermetrics. While most other books describe what has been done in the past in the field of baseball statistics with complex statistics that are difficult to follow, Baseball GPA presents and analyzes new information to create a new statistic, called GPA, allowing the reader to view the game in a new light.
A good example of this new information can be found in the chapters about base running, which I found especially interesting. A base running correction adjusts GPA for the contributions the player makes with steals, advancing on wild pitches, and being picked off bases. It was fascinating to look back at the data from some of Ricky Henderson's best seasons and see that when he was shooting for base stealing records, his contributions to his team were far less than when he stole far fewer bases. I had never seen data like this before.
Also, the adjustments to GPA for playing in various ball parks were...
Evidence Based Baseball!
David Gerard’s Baseball GPA brings Evidence Based Practice to Baseball. Baseball lore, common statistics and even Sabermetrics try to answer common baseball situational questions that fans and managers ponder routinely. Such examples include: when to bunt, when to steal, who should bat third and comparing the team value of homerun hitter that strikes out a lot vs. a ‘Punch and Judy’ hitter? The Baseball GPA statistic is a tool that measures outcome in a quantitative manner. Gerard compiled all 8.5 million MLB plate appearances since 1952 and digitized the data. This allows the computer to identify specific situations (outs, runners on base, the count, etc.) and predict the likelihood of various outcomes (runs scored, strikeout, double-play, etc.). The ability to produce these quantitative outcomes is new, refreshing and novel. It is truly Evidence Based Baseball and supplants all other common baseball statistics. Gerard...
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