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

arXiv: https://arxiv.org/abs/2512.00203 · HTML: https://mlsanity.com/paper/2512.00203/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 19 references that are in the map.
- First posted on arXiv 28 Nov 2025.

## Builds on (most cited first, 3 of 3)

- [A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions](https://mlsanity.com/paper/2011.09426/) (2020)
- [Measuring Football Players' On-the-ball Contributions From Passes During Games](https://mlsanity.com/paper/1810.02252/) (2018)
- [Biases in Expected Goals Models Confound Finishing Ability](https://mlsanity.com/paper/2401.09940/) (2024)

## Abstract (arXiv)

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.