Value of Plays Using Run Expectancy

Résumé fourni par la source

An important concept in sabermetrics research is the run expectancy matrix. As each base (first, second, and third) can be either empty or occupied by a runner, there are https://www.w3.org/1998/Math/MathML" display="inline"> 2 × 2 × 2 = 8 https://www.w3.org/1999/xlink" xlink:href=" https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781032668239/9724d500-130e-4e07-bd6f-d173665c5861/content/math5_1.tif "/> possible arrangements of runners on the three bases. The number of outs can be 0, 1, or 2 (three possibilities), and so there are a total of 8 × 3 = 24 possible arrangements of runners and outs. For each combination of runners on base and outs, we are interested in computing the average number of runs scored in the remainder of the inning. When these average runs are arranged as a table classified by runners and outs, the display is often called the run expectancy matrix.

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