# Quantifying Football Shooting Precision: The Expected Shot Impact Timing (xSIT) Approach
## 1 Introduction  
The application of advanced data analytics in football has significantly enhanced the capacity to objectively evaluate player performance. Metrics such as expected goals (xG) and expected goals on target (xGOT) have become fundamental tools in the quantification of scoring opportunities and goalkeeper (GK) performance, respectively [1, 2]. While the xG metric measures the probability of a shot resulting in a goal based on pre-shot conditions, such as shooting location, shot type, and the preceding play [3, 4], the xGOT metric refines this estimate by incorporating post-shot information [5, 6]. Specifically, xGOT assesses the shot's actual placement and the degree of difficulty it presents to the GK. It considersfactors like the exact target area within the goal (e.g., top corner vs. central zone), the GK's positioning and response at the moment of the shot, and technical aspects of the strike, including power and ball trajectory, which influence the complexity of a potential save [7; 8]. By accounting for these post-shot variables, xGOT offers a more nuanced evaluation of shot quality and GK performance, thus enhancing our understanding of match dynamics and player impact.  
Despite these advancements, a critical limitation persists: current metrics did not sufficiently isolate and quantify the quality of the shooter's technical execution under match conditions [3; 4; 5; 6]. Specifically, there remains a need for a model capable of assessing the complexity and difficulty of the shooting action itself, independently of the final outcome (goal or no goal) or the GK's intervention.  
To address this gap, the present study introduces a novel metric: the Expected Shot Impact Timing (xSIT). This metric was designed to evaluate the shooting action by considering the spatial configuration of the shooter, the GK, and all outfield players, as well as incorporating dynamic variables such as ball velocity and player reaction time. Specifically, this metric analyzes the time interval between the execution of a shot and the onset of player movement, which is primarily governed by the reaction time of both GK and outfield players [9]. In doing so, xSIT captures the degree of difficulty and situational constraints faced by the shooter at the moment of execution, offering a more comprehensive analysis of technical performance.  
The xSIT model builds upon existing approaches to spatial modeling and dynamic analysis in football [10], introducing methodological innovations such as the construction of a shooting triangle, the integration of player reaction time (GK and outfield players), and the consideration of ball velocity. These enhancements enable a finer-grained evaluation of the post-shot context, situating xSIT conceptually between the existing xG and xGOT metrics.  
The main objective of this study was to develop and validate an innovative metric, termed Expected Shot Impact Timing (xSIT), designed to assess the shooting action in football under dynamic match conditions. The model's accuracy was evaluated through statistical analyses and further validated through consultations with professional match analysts who possess over 25 years of experience across various competition levels. Expert feedback was also integrated into the feature selection process and the interpretation of their influence on predictive outcomes. As a secondary objective, this study compared the performance and discriminative capacity of two existing post-shot expected goal metrics (xSIT and xGOT, expected goals on target) in evaluating the probability of scoring for shots on target after the moment of execution. Additionally, practical applications of the model were showcased using data from the 2023 Women's World Cup and the 2022 Men's World Cup, demonstrating its relevance to coaching staff and decision makers within the field of football analytics.