Tennis winner prediction based on time-series history with neural modeling

Abstract

Tennis is one of the most popular sports in the world. Many researchers have studied in tennis model to find out whose player will be the winner of the match by using the statistical data. This paper proposes a powerful technique to predict the winner of the tennis match. The proposed method provides more accurate prediction results by using both of the statistical data and environmental data and concerning experience of players based on Multi-Layer Perceptron (MLP) with back-propagation learning algorithm.