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 |
|---|---|---|---|---|---|---|---|---|
| Galatasaray | Super Lig | 39 | 90 | — | 16.9 | 62% | 5.5 | 2.1 |
| Antalyaspor | Super Lig | 39 | 36 | — | 9.6 | 45% | 4 | 2.5 |
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.
| Fenerbahçe | Super Lig | 39 | 87 | — | 17.4 | 58% | 6.9 | 2.7 |
| Gençlerbirliği | Super Lig | 34 | 36 | — | 10.7 | 43% | 3.9 | 2.3 |
| Alanyaspor | Super Lig | 39 | 48 | — | 12.3 | 48% | 4.5 | 2.3 |
| Sivasspor | Super Lig | 4 | 1 | — | 8.3 | 41% | 3.8 | 2.3 |
| Beşiktaş | Super Lig | 39 | 70 | — | 16.8 | 55% | 5.5 | 2.3 |
| Kayserispor | Super Lig | 39 | 33 | — | 11.8 | 47% | 5.2 | 2.6 |
| Trabzonspor | Super Lig | 39 | 67 | — | 14.7 | 55% | 4.5 | 1.8 |
| Adana Demirspor | Super Lig | 5 | 7 | — | 12.4 | 41% | 3.8 | 3.4 |
| Rizespor | Super Lig | 39 | 62 | — | 13.3 | 50% | 4.5 | 2.4 |
| Kasımpaşa | Super Lig | 39 | 42 | — | 10.2 | 46% | 4.5 | 2.9 |
| Konyaspor | Super Lig | 38 | 47 | — | 12.9 | 51% | 4.9 | 2.7 |
| Samsunspor | Super Lig | 38 | 54 | — | 13.5 | 54% | 5.7 | 2.3 |
| Eyüpspor | Super Lig | 38 | 36 | — | 10.2 | 49% | 3.3 | 2.5 |
| İstanbul Başakşehir | Super Lig | 40 | 69 | — | 13.8 | 54% | 4.9 | 2.2 |
| Göztepe | Super Lig | 40 | 54 | — | 15.1 | 39% | 4.7 | 2.7 |
| Fatih Karagümrük | Super Lig | 34 | 31 | — | 10.4 | 45% | 3.6 | 1.8 |
| Gaziantep F.K. | Super Lig | 39 | 47 | — | 13.1 | 50% | 4.9 | 2.7 |
| Hatayspor | Super Lig | 5 | 14 | — | 11.8 | 49% | 4.8 | 2.2 |
| Kocaelispor | Super Lig | 34 | 26 | — | 10.2 | 50% | 4.2 | 2.4 |
| Bodrum FK | Super Lig | 4 | 2 | — | 12.3 | 39% | 5.8 | 1.8 |