Estimating Situational Effects on OPS
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Philip A Yates
`What is the offensive value of Player A?´ Of all the metrics that sabermetricians have developed to attempt to answer that question, OPS (on base percentage plus slugging percentage) has been one of the first for the mainstream media to slowly embrace as an alternative to batting average. Looking at statistics for each team on ESPN.com, one sees that the batting statistics are sorted by OPS as the default sort. What if the question asked was `What is the offensive value of Player A in Situation B versus Situation C?´ In 1994, Jim Albert used the Gibbs sampler to estimate the effect different in-game situations had on batting average. One example of such a situation is a player's breakdown statistics in home and away games. By employing the Gibbs sampler on each component of OPS, one can compute the situational effect on a player's OPS. The data will consist of the hitting performance of major league regulars during the 2006 season who qualified for the batting title. Part of the appeal of OPS is that it is simpler to calculate than other more complicated metrics developed by sabermetricians; however, the raw value of OPS does have limitations such as not taking into consideration ballpark effects or the differences between the two leagues.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
- Conference Paper
- New England Symposium on Statistics in Sports
- Estimating Situational Effects on OPS
- Why On-Base Percentage is a Better Indicator of Future Performance than Batting Average: An Algebraic Proof
- Improving Major League Baseball Park Factor Estimates
- In Search of the "Last-Ups" Advantage in Baseball: A Game-Theoretic Approach
- The Role of Rest in the NBA Home-Court Advantage
- Racial Bias in the NBA: Implications in Betting Markets
- A Simple and Flexible Rating Method for Predicting Success in the NCAA Basketball Tournament: Updated Results from 2007
- The Passing Premium Puzzle Revisited
- Isolating the Effect of Individual Linemen on the Passing Game in the National Football League
- Probability and Statistical Models for Racing
- Improving Golf Instruction with the iClub Motion Capture Technology
- Composite Poisson Models for Goal Scoring
- Skill Evaluation in Women's Volleyball
- Probability Formulas and Statistical Analysis in Tennis
Articles in the same Issue
- Conference Paper
- New England Symposium on Statistics in Sports
- Estimating Situational Effects on OPS
- Why On-Base Percentage is a Better Indicator of Future Performance than Batting Average: An Algebraic Proof
- Improving Major League Baseball Park Factor Estimates
- In Search of the "Last-Ups" Advantage in Baseball: A Game-Theoretic Approach
- The Role of Rest in the NBA Home-Court Advantage
- Racial Bias in the NBA: Implications in Betting Markets
- A Simple and Flexible Rating Method for Predicting Success in the NCAA Basketball Tournament: Updated Results from 2007
- The Passing Premium Puzzle Revisited
- Isolating the Effect of Individual Linemen on the Passing Game in the National Football League
- Probability and Statistical Models for Racing
- Improving Golf Instruction with the iClub Motion Capture Technology
- Composite Poisson Models for Goal Scoring
- Skill Evaluation in Women's Volleyball
- Probability Formulas and Statistical Analysis in Tennis
