Rensselaer Polytechnic Institute Lally School of Management & Technology MGMT 6070 Statistical Methods for Reliability Engineering Term Project Presentation.

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Rensselaer Polytechnic Institute Lally School of Management & Technology MGMT 6070 Statistical Methods for Reliability Engineering Term Project Presentation Robert Ricker December 4 th, 2008

Summary Description Problem Statement The success of a Major League Baseball team relies heavily on the arm of the pitcher. In general, the pitching staff of a particular team must consistently provide a certain level of performance, efficiency, and reliability in order for the team to advance to the post season and eventually into the championship game. The objective of this project is to use pitcher characteristics to age the population of pitchers on a team to determine the most optimal pitching staff. Project Objective Expanded Roster 40 Man Pitching Staff Man 9 Innings/game x 162 games = 1458 Innings/Season Active Roster 25 Man Starting Rotation 5 Man System Overview The system consists of a 5 man rotation to cover 1458 innings / season.

Statistical data for inactive pitchers analyzed to determine the distribution function best representative of the reliability of an active pitcher in the league. The distribution function and the associated reliability functions were then used to determine the significant failure characteristics of a pitcher. A Monte Carlo simulation was then performed to simulate the failure times for a certain number of pitchers. The reliability of the current league pitching staff will be analyzed such that each pitcher must be fully operational in order for the team to be performing efficiently. Each pitcher will have the failure distribution calculated from the test data. Methodologies

Results/Discussion Data set consisted of 8164 inactive and active pitchers Data sorted according to innings pitched (from 0 to 7356) Top 2.5% inactive pitchers used for analysis Data suggests a Weibull distribution for inactive pitchers (i.e. failures) Overview plot for Top 2.5% inactive pitchers supports Weibull failure distribution

Results/Discussion Weibull distribution modeled in Maple Failure Probability Distribution Function & Reliability Function (Survival) Failure Probability Density Function Hazard / Failure Rate Function

Results/Discussion Monte Carlo simulation validated the Minitab and Maple Results T-test shows a gradual increase in ERA as active pitchers move into distribution

Conclusions Average failure rate for Inactive Major League Pitchers in the top 2.5% of Innings Pitched is Active Pitchers making it to the top 2.5% display a decline in key statistics such as ERA that suggests the efficiency is reduced. Teams should therefore draft additional pitchers to their staff to decrease the burden on the 5 starters and increase the efficiency throughout a career. Including all pitching data (both inactive and active) into analysis will help validate assumptions. Using a 3-Parameter Weibull Distribution will also add fidelity to analysis.