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 |
|---|---|---|---|---|---|---|---|---|
| Sporting CP | Liga Portugal | 37 | 94 | — | 17.2 | 61% | 6.8 | 2.2 |
| Gil Vicente | Liga Portugal | 37 | 50 | — | 13.4 | 49% | 5.5 | 2.4 |
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.
| Benfica | Liga Portugal | 37 | 78 | — | 16.6 | 58% | 7.1 | 2.2 |
| Porto | Liga Portugal | 37 | 74 | — | 14.4 | 56% | 5.6 | 2.5 |
| Vitória Guimarães | Liga Portugal | 37 | 42 | — | 13.1 | 52% | 4.6 | 2.5 |
| Sporting Braga | Liga Portugal | 37 | 67 | — | 12.2 | 62% | 5.4 | 2.3 |
| Boavista | Liga Portugal | 3 | 4 | — | 14.3 | 46% | 5.3 | 3 |
| Moreirense | Liga Portugal | 37 | 43 | — | 9.1 | 49% | 3.6 | 2.7 |
| Estoril | Liga Portugal | 38 | 64 | — | 11.4 | 53% | 4.4 | 2.5 |
| Santa Clara | Liga Portugal | 37 | 37 | — | 11.8 | 48% | 4.5 | 3.2 |
| Famalicão | Liga Portugal | 37 | 46 | — | 12.5 | 52% | 5.8 | 2.6 |
| Tondela | Liga Portugal | 34 | 27 | — | 10.6 | 44% | 4 | 2.7 |
| Arouca | Liga Portugal | 37 | 52 | — | 10.8 | 51% | 3.6 | 3.1 |
| Rio Ave | Liga Portugal | 37 | 41 | — | 10.6 | 47% | 4.4 | 2.8 |
| Nacional | Liga Portugal | 37 | 41 | — | 12.6 | 46% | 4.5 | 3.2 |
| Farense | Liga Portugal | 3 | 5 | — | 11 | 45% | 3.3 | 4.3 |
| Casa Pia | Liga Portugal | 38 | 35 | — | 8.5 | 41% | 3.9 | 3.1 |
| Estrela Amadora | Liga Portugal | 37 | 38 | — | 10.8 | 47% | 3.3 | 2.8 |
| Alverca | Liga Portugal | 34 | 35 | — | 9.7 | 45% | 4.4 | 2.3 |
| AVS | Liga Portugal | 37 | 29 | — | 11.2 | 40% | 3.7 | 2.6 |