A Bayesian framework for analyzing alleged cheating in sports through hidden codes, with applications to bridge and baseball

TL;DR

This paper introduces a Bayesian statistical framework for detecting illegal signaling in sports, demonstrated through applications to bridge and baseball, offering a versatile forensic tool.

Contribution

It develops a novel Bayesian approach for analyzing cheating via hidden codes, applicable across different sports and scenarios.

Findings

Effective detection of illegal signaling demonstrated in bridge and baseball cases.

Bayesian method provides a flexible and general forensic analysis tool.

Framework enhances the ability to evaluate evidence of cheating in sports.

Abstract

We develop a statistical framework to evaluate evidence of alleged cheating involving illegal signaling in sports from a forensic perspective. We explain why, instead of a frequentist procedure, a Bayesian approach is called for. We apply this framework to cases of alleged cheating in professional bridge and professional baseball. The diversity of these applications illustrates the generality of the method.