In forecasting competitions, the traditional mechanism scores the predictions of each contestant against the outcome of each event, and the contestant with the highest total score wins. While it is well-known that this traditional mechanism can suffer from incentive issues, it is folklore that contestants will still be roughly truthful as the number of events grows. Yet thus far the literature lacks a formal analysis of this traditional mechanism. This paper gives the first such analysis. We first demonstrate that the ''long-run truthfulness'' folklore is false: even for arbitrary numbers of events, the best forecaster can have an incentive to hedge, reporting more moderate beliefs to increase their win probability. On the positive side, however, we show that two contestants will be approximately truthful when they have sufficient uncertainty over the relative quality of their opponent and the outcomes of the events, a case which may arise in practice.

翻译：在预测竞赛中，传统机制通过将每位参赛者的预测结果与每个事件的实际结果进行比对来评分，总得分最高的参赛者获胜。尽管众所周知这种传统机制可能存在激励问题，但学界普遍认为随着事件数量的增加，参赛者仍会大致保持真实性。然而迄今为止，文献中仍缺乏对该传统机制的正式分析。本文首次对此进行了系统性分析。我们首先证明"长期真实性"的普遍认知是错误的：即使对于任意数量的事件，最优预测者仍可能具有对冲动机——通过报告更温和的信念来提高获胜概率。但积极的一面是，我们证明当两位参赛者对竞争对手的相对能力及事件结果具有足够不确定性时（实践中可能出现这种情况），他们将表现出近似真实性。