If you watch football in 2026, you cannot escape xG. Commentators mention it, analysts build entire arguments around it, and betting sites display it next to every match. But what does expected goals actually mean, and should you trust it? The short answer: xG is one of the most useful numbers in modern football, as long as you understand what it does and does not measure.

In simple terms, xG gives every shot a value between 0 and 1, representing how often a shot like it has been scored in the past. A penalty is worth about 0.79 xG because roughly 79 per cent of penalties are scored. A speculative shot from 30 yards might be worth 0.02. Add up all the shots in a match and you get a team's total xG: a measure of the quality of the chances it created.

How xG Is Calculated

xG models are built by data companies that analyse hundreds of thousands of historical shots. Opta's model, for example, learns from nearly a million shots and weighs more than 20 variables: distance from goal, angle, body part used, type of play, and how the chance was created. The model then estimates the probability that a new shot, with those characteristics, becomes a goal.

Different providers can assign slightly different xG values to the same shot, because their models weigh factors differently. That is normal: xG is an estimate from a model, not a fact about the match. The value lies in the pattern over many matches, not in a single decimal point.

What xG Tells You About Strikers

A striker's goal total matters, but xG separates two different skills: getting into good positions and finishing the chances. A player with high xG is consistently getting into dangerous areas, which is a repeatable skill. A player who scores far more than his xG is finishing brilliantly, but that finishing tends to cool down over time.

Non-penalty xG, written as npxG, removes penalties from the total, which is useful because penalties are awarded rather than created. And xG per 90 minutes adjusts for playing time, so you can fairly compare a player who plays every minute with one who comes off the bench.

xG for Teams: Reading a Match Properly

A team can win 1-0 while creating only 0.6 xG against an opponent's 2.5, and that tells you something important: the winning team was clinical or lucky, and the losing team created enough to win on another day. Over a season, those patterns matter. Teams that consistently out-create their opponents tend to climb the table; teams that rely on outscoring their xG tend to slide back.

That is why analysts use xG to spot teams whose league position flatters them. If a side sits fourth in the table but has a negative xG difference, expect a correction. If a side sits twelfth but creates more than it concedes, expect improvement.

What xG Does Not Measure

xG has clear limits. It does not credit a brilliant pass that ends without a shot, it does not measure defensive positioning that prevents a shot from happening, and it says nothing about a player's work rate or leadership. It also rates the chance, not the finish: a shot into the top corner and a shot straight at the keeper get the same xG if they come from the same spot.

That is why the best analysts pair xG with its cousin, xGOT, which re-scores the chance after the shot based on where it was placed. Together, they tell you who created more and who shot better. Used properly, xG is not a replacement for watching football. It is a tool that helps you see what your eyes might have missed.