Conference Agenda

The Expected Threat model is a possession value model in football (soccer) with a Markov chain structure that allows for interpretation and visualization. To create a Markov chain, the pitch is discretized into different Markov states. However, selecting the right discretization of the pitch is still a challenging design choice. A model with more game states can better distinguish between different scenarios, but has less samples per state when estimating the Markov chain. This creates a trade-off between the model complexity in terms of the number of Markov states and the accuracy of the probability estimates. Theoretical analysis of the model gives error bounds, but interpretation of the results indicates that these might be on the conservative side. Simulations provide a more accurate characterization of the model’s error, which is indeed more optimistic than the theoretical bound. Finally, these insights are converted into a practical rule of thumb to help practitioners choose the right balance between the number of Markov states and accuracy of the probability estimates of the Expected Threat model.