The forecast of winners in sports brings valuable information for both organizers, media and audience, and this is particularly important in tennis, where the results of a round in a tournament determine which matches will occur in the next round. With that in mind, this work presents a study of the main factors influencing matches predictability and, from this analysis, a new hybrid approach is proposed to calculate the chances of victory of each of the competitors before the start of a match. A Fuzzy Inference System, with its ability to reproduce knowledge of an expert among mixed information, a Neural Network, with the capability of features extraction from examples, and a Strength Equation with optimized weighting factors are the techniques employed. These predictors have as inputs data from previous performances of the players, which in this case try to capture their short, medium and long-term performances, as well as their affinity for the different types of surfaces. Subsequently the results from these predictors are combined by a voting system. The results are encouraging, showing significant gains when comparing to the use of the ATP ranking.
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