Aggregated team performance data including expected goals, shots, possession, corners, and discipline stats.
| Team | League | MP | Goals | Avg xG | Shots/G | Poss% | Corners/G | Cards/G |
|---|---|---|---|---|---|---|---|---|
| West Ham United | Premier League | 239 | 318 | 0 | 11.7 | 43% | 4.7 | 1.7 |
| Sunderland | Premier League | 31 | 32 | 0 | 9.6 | 43% | 3.5 | 2 |
Expected Goals (xG) is the single most important advanced metric in modern football analytics. It measures the quality of scoring chances by assigning each shot a probability of being scored, based on factors like distance, angle, assist type, and whether it was a header. A penalty is worth about 0.76 xG, while a long-range shot might be just 0.03.
The Avg xG column shows how many goals a team is expected to score per match based on their shot quality. Teams with high xG but lower actual goals are likely due a positive regression — they are creating chances but not converting them yet. The reverse (low xG, high goals) suggests a team overperforming that may regress. Read our detailed xG explainer for a deeper dive.
Shots per game indicates offensive intent — teams averaging 15+ shots are creating volume. But shots alone do not tell you about quality, which is why xG is the more reliable predictor. A team with 10 shots and 1.8 xG is more dangerous than one with 16 shots and 1.2 xG.
Possession (highlighted green above 55%) reflects control but not necessarily dominance. Some of Europe's best counter-attacking teams thrive on low possession. For betting, possession is most useful in predicting corner counts (high-possession teams win more) and tempo (high-possession games tend to be lower scoring).
The Cards/G column tracks total cards per match per team. This is useful for the cards/bookings market, which some bookmakers offer as over/under on total cards or total booking points. Teams with aggressive pressing styles or those frequently defending deep tend to commit more fouls and receive more cards. Cross-reference with form — teams on losing streaks often accumulate more cards from frustrated tackles. Check our corner data alongside cards, as set-piece-heavy teams with high card counts create chaotic matches ideal for Over bets.
| Tottenham Hotspur | Premier League | 248 | 408 | 0 | 13 | 54% | 5.5 | 2 |
| Liverpool | Premier League | 240 | 497 | 0 | 17.2 | 61% | 6.7 | 1.5 |
| Manchester City | Premier League | 245 | 557 | 0 | 16.7 | 64% | 6.9 | 1.4 |
| Newcastle United | Premier League | 257 | 380 | 0 | 12.5 | 46% | 5.1 | 1.9 |
| Wolverhampton Wanderers | Premier League | 225 | 234 | 0 | 10.9 | 48% | 4.3 | 2.1 |
| Leicester City | Premier League | 154 | 217 | 0 | 11.1 | 50% | 4.4 | 1.7 |
| Crystal Palace | Premier League | 233 | 272 | 0 | 11.3 | 44% | 4.6 | 2 |
| AFC Bournemouth | Premier League | 152 | 201 | 0 | 13.2 | 46% | 5.4 | 2.2 |
| Nottingham Forest | Premier League | 144 | 173 | 0 | 11.6 | 41% | 4.2 | 2.1 |
| Southampton | Premier League | 166 | 166 | 0 | 11 | 49% | 4.8 | 1.8 |
| Leeds United | Premier League | 144 | 189 | 0 | 12.8 | 51% | 5.1 | 2.1 |
| Brighton & Hove Albion | Premier League | 226 | 322 | 0 | 13.9 | 55% | 5.4 | 2 |
| Brentford | Premier League | 182 | 274 | 0 | 11.4 | 46% | 4.5 | 1.9 |
| Fulham | Premier League | 191 | 238 | 0 | 12.4 | 51% | 4.9 | 2.1 |
| Everton | Premier League | 247 | 263 | 0 | 11.8 | 43% | 4.6 | 2 |
| Manchester United | Premier League | 243 | 373 | 0 | 14.4 | 54% | 5.3 | 2 |
| Aston Villa | Premier League | 229 | 334 | 0 | 12.5 | 50% | 5.4 | 2.1 |
| Chelsea | Premier League | 232 | 376 | 0 | 14.5 | 60% | 6 | 2.2 |
| Arsenal | Premier League | 242 | 448 | 0 | 14.8 | 56% | 6.1 | 1.6 |
| West Bromwich Albion | Premier League | 54 | 46 | — | 8.7 | 39% | 4.1 | 1.4 |
| Watford | Premier League | 44 | 37 | — | 10.6 | 42% | 4.5 | 1.9 |
| Stoke City | Premier League | 16 | 15 | — | 10.8 | 46% | 3.4 | 2.3 |
| Burnley | Premier League | 164 | 166 | — | 10.5 | 42% | 4.5 | 1.8 |
| Luton Town | Premier League | 38 | 52 | — | 11.4 | 42% | 5.3 | 1.9 |
| Swansea City | Premier League | 10 | 9 | — | 14.9 | 56% | 6.3 | 1.5 |
| Norwich City | Premier League | 40 | 24 | — | 10 | 43% | 4.5 | 1.5 |
| Ipswich Town | Premier League | 38 | 36 | — | 9.9 | 40% | 3.8 | 2.6 |
| Sheffield United | Premier League | 78 | 58 | — | 9.1 | 39% | 4.1 | 2.3 |
| Hull City | Premier League | 6 | 2 | — | 9 | 50% | 3.7 | 1.2 |