A general framework to quantify the event importance in multi-event contests

TL;DR

This paper introduces a statistical framework to measure the importance of individual events in multi-event contests, enhancing understanding of their influence on outcomes and public interest across different domains.

Contribution

It presents a novel general framework for quantifying event importance, applicable to diverse multi-event contests like elections and sports.

Findings

Schedule variations can reduce front-loading effects in elections.

Quantified event importance correlates with in-match performance.

Framework improves outcome prediction and public interest assessment.

Abstract

We propose a statistical framework for quantifying the importance of single events that do not provide intermediate rewards but offer implicit incentives through the reward structure at the end of a multi-event contest. Applying the framework to primary elections in the US, where earlier elections have greater importance and influence, we show that schedule variations can mitigate the problem of front-loading elections. When applied to European football, we demonstrate the utility and meaningfulness of quantified event importance in relation to the in-match performance of contestants, to improve outcome prediction and to provide an early indication of public interest.