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Large-scale geopolitical forecasting tournaments have emerged in recent years as effective testbeds for conducting research into novel forecasting tools and methods. A challenge of such tournaments involves the distribution of forecasting load across forecasters, since there are often more forecasting questions than an individual forecaster can answer. Intelligent load distribution, or triage, may therefore be helpful in ensuring that all questions have sufficient numbers of forecasts to benefit from crowd-based aggregation and that individual forecasters are matched to the questions for which they are best suited. A possible downside of triage, however, is that it restricts the choices of forecasters, potentially degrading motivation and accuracy. In two studies involving pools of novice forecasters recruited online, we examined the impact of limiting forecaster choice on forecasters’ accuracy and subjective experience, including motivation. In Study 1, we tested the impact of restricted choice by comparing the forecasting accuracy and subjective experience of users who perceived they did or did not have choice in the questions they forecasted. In Study 2, we further tested the impact of restricted choice by providing users with different menu sizes of questions from which to choose. In both studies, we found no evidence that limiting forecaster choice adversely affected forecasting accuracy or subjective experience. This suggests that in large-scale forecasting tournaments, it may be possible to implement choice-limiting triage strategies without sacrificing individual accuracy and motivation.