Combining vector forecasts to predict thoroughbred horse race outcomes

A large body of empirical studies has shown that a forecast developed by combining individual base forecasts performs surprisingly well. Previous work on the combination of forecasts has been confined to the area of time series forecasting. This work extends the combination of forecasts technique into the domain of forecasting one-time competitive events, specifically the scaled, relative finishing position of horses in thoroughbred sprint races. The present research develops a framework for the selection of the base forecasts and selects 12 base forecasts for analysis. The performance of the combination of the base forecasts is assessed on a sample of sprint races. Results of the analysis strongly suggest that the combination approach is both appropriate and effective. Some differences in results between this work and previous work in the time series domain suggest promising avenues for future research.