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 |
|---|---|---|---|---|---|---|---|---|
| Juventude | Serie B | 11 | 9 | — | 11.5 | 51% | 4.1 | 1.6 |
| Botafogo SP | Serie B | 45 | 40 | — | 12 | 49% | 5.3 | 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.
| Chapecoense | Serie B | 33 | 48 | — | 13.6 | 47% | 5 | 2.5 |
| Sport Recife | Serie B | 11 | 15 | — | 11.9 | 51% | 4 | 3.1 |
| Ferroviária | Serie B | 33 | 40 | — | 13.3 | 50% | 4.1 | 2.9 |
| Athletico PR | Serie B | 33 | 45 | — | 15.4 | 52% | 5.5 | 2.2 |
| Paysandu | Serie B | 33 | 34 | — | 13.9 | 45% | 5.1 | 2.7 |
| Fortaleza | Serie B | 11 | 14 | — | 13.4 | 47% | 4.7 | 3.2 |
| Ponte Preta | Serie B | 11 | 9 | — | 11.1 | 45% | 5.7 | 3.3 |
| Cuiabá | Serie B | 44 | 42 | — | 14.2 | 49% | 4.6 | 2.6 |
| Criciúma | Serie B | 44 | 52 | — | 13.4 | 50% | 5.7 | 2.8 |
| CRB | Serie B | 44 | 57 | — | 17.1 | 57% | 6.3 | 2.3 |
| São Bernardo | Serie B | 11 | 17 | — | 10.7 | 51% | 4.2 | 2.3 |
| Coritiba | Serie B | 33 | 34 | — | 12.3 | 52% | 4.9 | 3.3 |
| América Mineiro | Serie B | 44 | 42 | — | 13.2 | 53% | 5.5 | 2.5 |
| Novorizontino | Serie B | 44 | 52 | — | 14.2 | 50% | 5.3 | 2.7 |
| Avaí | Serie B | 44 | 52 | — | 13 | 48% | 4.7 | 2.9 |
| Atlético GO | Serie B | 44 | 42 | — | 13.5 | 50% | 4.8 | 2.9 |
| Londrina | Serie B | 11 | 12 | — | 11.5 | 46% | 5.6 | 3.2 |
| Goiás | Serie B | 45 | 49 | — | 13.2 | 49% | 5.1 | 2.5 |
| Remo | Serie B | 33 | 44 | — | 12.2 | 48% | 4.3 | 2.5 |
| Volta Redonda | Serie B | 33 | 25 | — | 15.8 | 53% | 5.5 | 2.6 |
| Vila Nova | Serie B | 44 | 51 | — | 12.3 | 48% | 4.5 | 3.4 |
| Náutico | Serie B | 11 | 16 | — | 14.6 | 58% | 6.5 | 3.1 |
| Ceará | Serie B | 11 | 12 | — | 13.6 | 50% | 5.4 | 3.3 |
| Operário PR | Serie B | 44 | 49 | — | 14.1 | 53% | 5.1 | 2.9 |
| Athletic Club | Serie B | 44 | 51 | — | 10.8 | 49% | 4.8 | 3 |
| Amazonas | Serie B | 33 | 36 | — | 12.5 | 46% | 4.4 | 3.2 |