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Expected Goals (xG) Explained
How shot-quality modelling replaced scoreline analysis in modern football
Where xG comes from
Why pundits hate it (and why they're wrong)
From xG to match prediction
Common xG mistakes
Frequently asked
How is xG different from 'shots on target'?
Shots on target counts each attempt equally - a tap-in and a hopeful 30-yard effort both register as 1. xG weights each shot by its probability of becoming a goal, so a tap-in might add 0.9 xG while the long shot adds 0.03 xG.
Can xG predict which team wins?
Not on its own, but feed two teams' rolling xG numbers into a Poisson goal model and you get a probability distribution over every scoreline - including 1X2 probabilities. That's exactly what BetsPlug's Poisson head does.
Which xG provider does BetsPlug use?
We source from the football-data.org feed, cross-checked against OpenLigaDB for leagues where both are available. Matches with large divergences get flagged for manual review.
Why do some matches have 'wrong' xG results?
Short-run variance. A team can have 2.5 xG and lose 0-1 because finishing is probabilistic. Over a full season (~38 matches) actual goals track xG closely, but any individual match can diverge substantially.
Does xG account for penalties?
Most providers do - a standard penalty is assigned 0.76 xG (the historical conversion rate). BetsPlug splits penalty xG from open-play xG internally so post-match xG totals reflect the real shot-quality picture.