Standard Article

Scoring Rules

  1. Robert L. Winkler1,
  2. Victor Richmond R. Jose2

Published Online: 15 JUN 2010

DOI: 10.1002/9780470400531.eorms0749

Wiley Encyclopedia of Operations Research and Management Science

Wiley Encyclopedia of Operations Research and Management Science

How to Cite

Winkler, R. L. and Jose, V. R. R. 2010. Scoring Rules. Wiley Encyclopedia of Operations Research and Management Science. .

Author Information

  1. 1

    Duke University, Fuqua School of Business, Durham, North Carolina

  2. 2

    Georgetown University, McDonough School of Business, Washington, D.C.

Publication History

  1. Published Online: 15 JUN 2010

Abstract

Probabilities are used to quantify uncertainty in operations research and management science modeling. Scoring rules provide a numerical measure (a score or reward) based on probabilities for an event or variable and on what actually occurs. As such, they are valuable in evaluating how “good” probabilities are in light of what happens, and they also provide incentives for careful elicitation of probabilities. We discuss basic properties of scoring rules, present families of scoring rules that are useful under various conditions, and discuss some related issues.

Keywords:

  • baseline distributions;
  • calibration;
  • decision analysis;
  • probability elicitation;
  • probability evaluation;
  • sensitivity to distance;
  • sharpness;
  • strictly proper scoring rules