Abstract:In many sports disciplines, the schedule of the competitions is undeniably an inherent yet crucial component. The present study modeled sports competitions schedules as networks and investigated the influence of network properties on the accuracy of predictive ratings and forecasting models in sports. Artificial networks were generated representing competition schedules with varying density, degree distribution and modularity and embedded in a full rating and forecasting process using ELO ratings and an ordere… Show more
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