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Decomposing Pythagoras by Edward H. Kaplan; Candler Rich is a Economics, Econometrics and Finance article available to read on EtoBox.

What is Decomposing Pythagoras about?

The Pythagorean win expectancy model developed by Bill James remains one of the most celebrated results in sports analytics. Many have extended the application of this model from its original use in baseball to other sports. Others have shown technical scoring conditions that imply the equivalence of win probability and the Pythagorean model. However, no explanation has been offered for why different sports yield different results beyond "that's what the data say." This article presents a theoretical analysis of the Pythagorean model by first deducing an exact within-team equation relating win percentage to seasonal scoring records, and then reconciling mathematically this result with the Pythagorean model which is cross-sectional across teams in a league. We derive a complete decomposition of the Pythagorean coefficient γ in terms of the exact model, and show that γ captures two key quantities -average points per game, and the average margins of victory and defeat -that together explain why different sports yield different results. We demonstrate this decomposition using the past decade of seasonal results from MLB baseball, NBA basketball, NFL football, and NHL hockey, and show t

Who reads Decomposing Pythagoras?

It is typically read by researchers, students, and practitioners in Economics, Econometrics and Finance.

Author
Edward H. Kaplan; Candler Rich
Publisher
Walter de Gruyter GmbH
Published
2017
Language
EN
Field
Economics, Econometrics and Finance (Social Sciences)

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