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Jim Albert

Bowling Green State University



573 – Analysis of Baseball, Basketball, and Cricket Data

Beyond Runs Expectancy

Sponsor: Section on Statistics in Sports
Keywords: Baseball, Bayesian, Multilevel modeling, Sabermetrics

Jim Albert

Bowling Green State University

One important idea in sabermetrics is the runs expectancy matrix which gives the average number of runs in the remainder of the inning in 24 different runner/outs situations. However the basic runs expectancy matrix only describes the performance of an average offense against an average defense. We develop a reasonable sampling model for runs scored and illustrate efficient ways of simultaneously estimating run scoring distributions for all major league teams, and under different situations.

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