A bigger xG figure is not automatically a better one.
At full-time, FotMob shows 1.8 xG for a team while Understat shows 1.5. Neither figure is necessarily wrong: models can assign different probabilities to the same shots. Reliability depends on the question being asked, not which total is higher. FotMob works well for a quick read alongside live scores; Understat makes it easier to inspect the shots behind a total. For context on what the numbers measure, see how expected goals work.
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- Compare the shots shown by each service, not just the final xG sums. A missing or differently classified attempt can change the total.
If both include a shot, they may still assign it different xG values. Inspect the largest chances first; those differences are easier to spot than small variations across many shots.
A live figure and a later shot record may not reflect the same stage of processing. Recheck after the match before judging a discrepancy.
Confirm that both figures refer to the same fixture, team, and portion of play before comparing them.
Neither number becomes wrong simply because the other is different. The useful question is where the gap starts: the shots counted, their assigned values, or the point at which the figures were checked. For more context, see why xG models disagree on matches.
Best for live updates alongside football statistics.
FotMob is a scores and statistics platform where xG appears alongside the score, lineups and match events. It suits readers following a game as it unfolds or checking how the result compares with the chances created.
During play, its xG total is a snapshot rather than a settled number. For a comparison with Understat, the post-match figure is the better reference point.
Best for exploring shots and expected goals.
Understat is a football analytics site centered on expected goals. It suits readers who want to trace a surprising match total back to the chances behind it: the shot map shows each attempt, with an xG value for each one. Comparing those values with other websites for xG statistics can help pinpoint where two totals diverge.
| - Live match context FotMob Live Scores and Expected Goals Platform | VS | - Shot-level inspection Understat Expected Goals and Shot Map Analytics |
|---|---|---|
Following a match | Most useful for | Investigating xG gaps |
Live match statistics | Useful view | Shot map |
Live or final figure | Check before comparing | Same fixture and period |
| Open - | Open - |
Confirm the competition, date and teams, then check whether both figures cover the full match rather than a half or an in-progress game.
Look for a missing attempt or a chance recorded differently. If coverage is the issue, compare free and paid xG sources before treating the gap as a model disagreement.
Compare individual shot values where available. One high-value chance can explain much of the difference.
If the shots align but their values differ, the models may simply rate those chances differently; the larger total is not automatically more reliable.
For comparisons across matches, sticking with one source helps prevent differences between models from looking like changes in a team’s chances. For a puzzling single-match total, Understat’s shot map makes it easier to check which attempts contributed and how much each was worth. FotMob is useful for following xG as a match unfolds, but its live figure may change. An inspectable breakdown does not prove a model is right, either. Neither site supplies the definitive number for every question.
Expected goals estimates the quality of chances by assigning each shot a probability of becoming…
A shot’s probability is converted by the match into one of two outcomes: goal or…
