A novel comparative study of NNAR approach with linear stochastic time series models in predicting tennis player's performance - Almarashi, A. M.; Daniyal, M.; Jamal, F. (BMC Sports Science, Medicine and Rehabilitation, 2024)
Background Prediction models have gained immense importance in various fields for decision-making purposes. In the context of tennis, relying solely on the probability of winning a single match may not be sufficient for predicting a player's future performance or ranking. The performance of a tennis player is influenced by the timing of their matches throughout the year, necessitating the incorporation of time as a crucial factor. This study aims to focus on prediction models for performance indicators that can assist both tennis players and sports analysts in forecasting player standings in future matches.