Beyond Expected Goals: A Probabilistic Framework for Shot Occurrences in Soccer

• URL: http://arxiv.org/abs/2512.00203v1
• Date: Fri, 28 Nov 2025 20:59:29 GMT
• Title: Beyond Expected Goals: A Probabilistic Framework for Shot Occurrences in Soccer
• Authors: Jonathan Pipping, Tianshu Feng, R. Paul Sabin,
• Abstract summary: Expected goals (xG) models estimate the probability that a shot results in a goal from its context, but they operate only on observed shots.<n>We propose xG+, a framework that first estimates the probability that a shot occurs within the next second and its corresponding xG if it were to occur.<n>We show that this improves predictive accuracy at the team level and produces a more persistent player skill signal than standard xG models.
• Score: 0.9940728137241215
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Expected goals (xG) models estimate the probability that a shot results in a goal from its context (e.g., location, pressure), but they operate only on observed shots. We propose xG+, a possession-level framework that first estimates the probability that a shot occurs within the next second and its corresponding xG if it were to occur. We also introduce ways to aggregate this joint probability estimate over the course of a possession. By jointly modeling shot-taking behavior and shot quality, xG+ remedies the conditioning-on-shots limitation of standard xG. We show that this improves predictive accuracy at the team level and produces a more persistent player skill signal than standard xG models.

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