Betting Against Integrity: Identifying Match-Fixing Through In-Play Market Dynamics
Using betting data patterns to catch match-fixing in real time
Researchers analyzed live-betting data from Italian football matches to detect when betting markets behaved abnormally—a potential sign of match-fixing. They built a statistical model that predicts normal betting volumes based on match characteristics, then flagged deviations as suspicious. The approach successfully identified unusual betting periods that could warrant further investigation.
Match-fixing threatens the credibility of sports and costs leagues millions in lost revenue and fan trust. Football betting markets handle more money globally than any other sport, making them a prime target for manipulation. A tool that automatically flags suspicious betting patterns could help sports authorities catch cheating before it spreads, protecting the integrity of competitions that billions of fans rely on.