Model Driven Inputs to aid Athlete's Decision Making

Decision Making forms the basis of any successful athlete's career. The importance of making the right decision at crucial junctures during a game is eventually the difference between winning or losing a match. Team sports have an important characteristic in that they are usually a set of non-discrete events and a good decision by one athlete, doesn't necessarily lead to a reward. It is a sequence of good decisions that finally lead to the reward, which explains why goals are usually so rare in a game of Soccer. Through this paper, we explore Soccer and look at the number of possibilities that are available at any given time to a player and what is their best possible action. We propose a Model-driven Domain specific Sequential model that aims to predict the best possible action that can be taken by a Soccer Athlete (player), to maximize the probability of scoring a goal.