Dynamic Expected Threat (DxT) Model: Addressing the Deficit of Realism in Football Action Evaluation

Abstract

Evaluating player actions in football is essential for understanding match dynamics and optimizing team strategies. Traditional models, such as the widely adopted Expected Threat (xT) model, assign static threat values to pitch zones without considering real-time player positioning, leading to a limited representation of the evolving tactical context. To address this limitation, we introduce the Dynamic Expected Threat (DxT) model, which adjusts threat values dynamically by integrating off-ball player positions. DxT refines the probability of shooting and ball movement using an Expected Goals (xG) model that incorporates off-ball player positioning. Built on event data from professional football matches, which encompasses over 335,000 actions, our results demonstrate that DxT significantly improves upon traditional xT models by offering a more accurate and dynamic evaluation of action threats. This framework enhances tactical analysis, providing valuable insights for coaches, analysts, and scouting professionals seeking a more realistic approach to performance evaluation.

Keywords

• football analytics
• expected goals
• expected threat
• decision-making evaluation
• tactical threat