A study of tennis momentum based on a comprehensive evaluation model and a random forest model

When the situation of a tennis match changes, the player's performance and momentum on the court are always a topic of concern for the audience. How to correctly and intuitively show the player's current momentum and predict the player's future momentum change is always a great challenge. In this paper, the momentum evaluation model based on comprehensive evaluation and the momentum shift prediction model based on random forest are established to address the above two problems, respectively. Among them, the player momentum evaluation model can not only accurately calculate the real-time momentum of both players, but also intuitively show which player has an advantage and the degree of advantage at each moment. The Momentum Shift Prediction Model can predict the momentum changes of future players based on current and past match data. These two models can not only help tennis coaches to better arrange the match strategy but also help tennis players to correctly analyze the court situation and make correct judgments, which has certain practical value.