Professional baseball teams have long used metrics to measure player performance. The Earned Run Average (ERA) has been at the cornerstone of baseball metrics, since its inception in 1912. Traditionalists have abhorred the use of new metrics conceived by Sabrematricians, however, to many they have proven quite valuable.
In a recent paper to be published and presented at the Northeast Decision Sciences Institute Conference in Providence, RI in March, the team from 5 Element Analytics scrutinized the ERA statistic to help formulate a better approach to identifying pitching performances that would be candidates for exclusion, otherwise known in the statistical world as outliers.
There is a great deal of insight in this research that exposes the impact of these hidden outliers, which can really create a true measure of a pitchers performance-
Tyler Levine, Pitcher for The Long Island Ducks Professional Baseball Club
The new approach discusses how outliers can be identified using statistical methods by comparing the change in variance of a set of observations by the removal of a single observation. In this way, a single bad game, or even an unusually good game are identified thus allowing for a true measure of performance. The data was initially tested on the top 10 pitchers in the National League, and identified fewer outliers than other methods, but found a better representation of a pitcher’s “True” ERA.
Since earned runs follow a count process, identifying outliers have benefits in a number of different areas. The approach could have significant implications for use in other areas such as healthcare, and transportation.
We would like to thank Tyler Levine and Long Island Baseball, in Bellmore, NY for their support during this research.
Click Here for a copy of the paper , “Outier Identification of Count Data Using Variance Difference”, being presented in Providence, RI, in April 2018 .
Should you like more information contact
Chief Operating Officer
5 Element Analytics
Phone: 516 945 0923