Premier League xG Table 2025/26: Expected Goals Rankings
Live Premier League expected goals (xG) table for the 2025/26 season. See which teams are overperforming and underperforming based on xG data.
Editorial Team
Published 14 April 2026 · Updated 14 April 2026 · 4 min read
Premier League xG Table 2025/26
Expected goals (xG) measures the quality of chances created, not just the goals scored. A team’s xG tells you how many goals they should have scored based on the quality of their shooting opportunities — and comparing xG to actual goals reveals which teams are overperforming or underperforming.
This is one of the most important tools for football analysis and betting.
What Does the xG Table Tell Us?
Teams Scoring More Than Their xG (Overperforming)
These teams are converting chances at a rate above what the data expects. This could indicate:
- Elite finishing quality (sustainable for top strikers)
- Luck that will regress toward the mean
- A small sample of high-quality chances being taken well
Teams Scoring Less Than Their xG (Underperforming)
These teams are creating good chances but not converting them. This could indicate:
- Poor finishing that will improve as confidence grows
- Bad luck on tight margins (hitting the post, goalkeeper saves)
- Upcoming improvement in results as regression kicks in
How xG Is Calculated
Every shot in a football match is assigned an xG value between 0 and 1, based on factors including:
- Distance from goal — Closer = higher xG
- Angle to goal — Central = higher xG
- Body part — Headed shots typically have lower xG than feet
- Assist type — Through balls and crosses create different xG profiles
- Shot type — Open play, set piece, penalty
- Game state — Some models factor in whether the team is winning or losing
A penalty is typically valued at 0.76 xG. A shot from the halfway line might be 0.01 xG.
How to Use xG for Betting
1. Identify Regression Candidates
Teams with a big gap between actual goals and xG are likely to regress. Back the team that’s been “unlucky” (underperforming xG) and fade the team that’s been “lucky” (overperforming).
2. xG Difference for Match Betting
The difference between a team’s xG For and xG Against gives you a truer picture of quality than the league table.
3. BTTS and Goals Markets
Teams with high xG For AND high xG Against are ideal BTTS and Over 2.5 targets — they create chances but also concede them.
4. Season-Long Value
At the start of the season, xG data is noisy (small sample). By matchweek 10+, the data becomes more predictive than actual results.
Key Metrics Explained
| Metric | Meaning |
|---|---|
| xG (For) | Expected goals scored based on shot quality |
| xG (Against) | Expected goals conceded based on opponents’ shot quality |
| xG Difference | xG For minus xG Against — the truest measure of team quality |
| xG per Shot | Average quality of each shooting opportunity |
| Goals – xG | Actual goals minus expected goals — positive = overperforming |
| npxG | Non-penalty xG — removes penalties for a cleaner picture |
Data Sources
The best sources for Premier League xG data:
- FBref — Free, comprehensive xG data from StatsBomb
- Understat — Free xG data with visualisations
- The xG Philosophy (Twitter/X) — Post-match xG summaries
- Opta — Professional-grade data (used by clubs and bookmakers)
Important Caveats
- xG is not destiny — It measures chance quality, not outcomes. Some players genuinely finish above their xG over large samples.
- Small samples are unreliable — Don’t draw conclusions from 3-4 matches of xG data.
- Models differ — StatsBomb, Opta, and Understat each calculate xG slightly differently. Use one consistently.
- Context matters — A team defending a 3-0 lead will have different xG patterns than a team chasing the game.
This page is updated throughout the 2025/26 season. Bookmark it for regular xG analysis.
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