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Chess is an intellectually demanding game played by millions of people around the world. Yet unlike tennis or other competitive sports there are few changes in the rankings of chess players. There have only been twelve world chess champions (see Table 1) since the official title was first established in 1886. Emmanuel Lasker held the title for 27 years (between 1894 and 1921), Aleksandr Alekhine for seventeen, and Mikhail Botvinnikfor thirteen. The last world champion, Anatoly Karpov, held the title for ten years between 1975 and 1985. In the 1985 the current champion, Gary Kasparov was the youngest player at the age of 22 to win the world chess title, which he has succesfully defended since. Below the world champion there are grandmasters, masters and many levels of chess experts in addition to the great numbers of common people playing chess. Yet grandmasters (including the world champion who is the top among the grandmsters) consistently win against all other chess players.

When combining forecasts, a simple average of the forecasts performs well, often better than more sophisticated methods. In a prescriptive spirit, we consider some other parsimonious, easy-to-use heuristics for combining interval forecasts and compare their performance with the benchmark provided by the simple average, using simulations from a model we develop and data sets with forecasts made by professionals in their domain of expertise. We find that the empirical results closely match the results from our model, thus providing some validation for the theoretical model. The relative performance of the heuristics is influenced by the degree of overconfidence in and dependence among the individual forecasts, and different heuristics come out on top under different circumstances. The results provide some good, easy-to-use alternatives to the simple average with an indication of the conditions under which each might be preferable, enabling us to conclude with some prescriptive advice.