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 |
|---|---|---|---|---|---|---|---|---|
| Rosengard W | UEFA Women's Champions League | 18 | 41 | — | 10.3 | 47% | 3.8 | 1.2 |
| Linkoping W | UEFA Women's Champions League | 4 | 11 | — | 4.5 | 50% | 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.
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| Hammarby W | UEFA Women's Champions League | 10 | 13 | — | 10.6 | 43% | 4.2 | 1.3 |
| Chelsea W | UEFA Women's Champions League | 41 | 98 | — | 15.8 | 56% | 5.5 | 0.9 |
| Manchester City W | UEFA Women's Champions League | 18 | 37 | — | 13.9 | 59% | 5.1 | 0.9 |
| Ajax W | UEFA Women's Champions League | 15 | 24 | — | 9 | 49% | 5.6 | 1.5 |
| FC Twente W | UEFA Women's Champions League | 28 | 76 | — | 16.6 | 52% | 5.7 | 0.8 |
| PSV W | UEFA Women's Champions League | 6 | 6 | — | 3 | 40% | 4.5 | 1.2 |
| Arsenal W | UEFA Women's Champions League | 36 | 87 | — | 14.8 | 57% | 6.3 | 1.2 |
| PAOK W | UEFA Women's Champions League | 6 | 14 | — | 10.8 | 44% | 4 | 2 |
| Zurich W | UEFA Women's Champions League | 7 | 5 | — | 1.7 | 44% | 2 | 1 |
| Klaksvik W | UEFA Women's Champions League | 6 | 1 | — | 1 | 17% | 0.5 | 0.5 |
| Apollon W | UEFA Women's Champions League | 11 | 25 | — | 10.8 | 45% | 3.9 | 1.2 |
| NSA Sofia W | UEFA Women's Champions League | 7 | 3 | — | 16.5 | 47% | 3.3 | 1.3 |
| Gintra W | UEFA Women's Champions League | 9 | 12 | — | 10.6 | 40% | 5.1 | 1.1 |
| Ol. Cluj W | UEFA Women's Champions League | 7 | 6 | — | 2.2 | 38% | 1 | 1.4 |
| Zhilstroy-2 2 W | UEFA Women's Champions League | 3 | 4 | — | — | — | 5 | 0.3 |
| SFK 2000 W | UEFA Women's Champions League | 9 | 15 | — | 5.8 | 43% | 5.4 | 1.7 |
| Vllaznia W | UEFA Women's Champions League | 10 | 9 | — | 5.4 | 42% | 3.9 | 1.8 |
| BIIK Kazygurt | UEFA Women's Champions League | 10 | 15 | — | 9.3 | 45% | 6 | 0.8 |
| Sporting W | UEFA Women's Champions League | 6 | 8 | — | 8 | 50% | 3.2 | 2.2 |
| Subotica W | UEFA Women's Champions League | 9 | 26 | — | 13.8 | 45% | 3.3 | 1.6 |
| Kiryat Gat W | UEFA Women's Champions League | 7 | 4 | — | 6 | 26% | 3.5 | 2.4 |
| Minsk FK W | UEFA Women's Champions League | 10 | 9 | — | 5.6 | 43% | 2.8 | 1.6 |
| Birkirkara W | UEFA Women's Champions League | 5 | 4 | — | 4 | 31% | 4 | 0.6 |
| Breznica W | UEFA Women's Champions League | 4 | 1 | — | 1 | 0% | 5.5 | 3.3 |
| Osijek W | UEFA Women's Champions League | 10 | 13 | — | 5.4 | 44% | 3.6 | 1.6 |
| Glasgow City W | UEFA Women's Champions League | 12 | 12 | — | 10.3 | 55% | 3.5 | 1.3 |
| OL Lyonnes W | UEFA Women's Champions League | 46 | 130 | — | 20.7 | 58% | 7.4 | 1.2 |
| Sparta Praha W | UEFA Women's Champions League | 11 | 8 | — | 6.2 | 43% | 3.5 | 1.6 |
| Slavia Praha W | UEFA Women's Champions League | 16 | 21 | — | 12.7 | 45% | 6.8 | 2.3 |
| Barcelona W | UEFA Women's Champions League | 48 | 166 | — | 23.2 | 68% | 8.2 | 0.9 |
| LSK Kvinner W | UEFA Women's Champions League | 4 | 2 | — | 8 | 38% | 4 | 0 |
| Brondby W | UEFA Women's Champions League | 9 | 9 | — | 5.6 | 47% | 4.3 | 1.4 |
| Atletico Madrid W | UEFA Women's Champions League | 15 | 28 | — | 16.2 | 57% | 7.1 | 1.5 |
| Wolfsburg W | UEFA Women's Champions League | 38 | 90 | — | 16.5 | 53% | 5.5 | 1.3 |
| Bayern Munich W | UEFA Women's Champions League | 36 | 80 | — | 14.6 | 57% | 5.9 | 1 |
| Fortuna Hjorring W | UEFA Women's Champions League | 8 | 11 | — | 5.8 | 43% | 2.6 | 1.1 |
| St. Polten W | UEFA Women's Champions League | 34 | 52 | — | 9.2 | 41% | 3.3 | 1.2 |
| Fiorentina W | UEFA Women's Champions League | 8 | 5 | — | 7.7 | 48% | 4.3 | 1.8 |
| Paris SG W | UEFA Women's Champions League | 35 | 69 | — | 14.8 | 53% | 5.7 | 1.5 |
| Levante W | UEFA Women's Champions League | 6 | 13 | — | 13.2 | 51% | 5.7 | 1.7 |
| Slovácko W | UEFA Women's Champions League | 4 | 5 | — | 1 | 30% | 4.7 | 0.5 |
| GKS Katowice W | UEFA Women's Champions League | 6 | 5 | — | 14.3 | 46% | 5.2 | 1.5 |
| Anenii Noi W | UEFA Women's Champions League | 7 | 0 | — | 1.4 | 27% | 0.4 | 1.1 |
| RSC Anderlecht W | UEFA Women's Champions League | 8 | 15 | — | 11.2 | 43% | 6.3 | 1.5 |
| Mitrovica W | UEFA Women's Champions League | 4 | 4 | — | 6 | 45% | 2.3 | 1.5 |
| Manchester United W | UEFA Women's Champions League | 14 | 22 | — | 11.7 | 51% | 4.7 | 1.1 |
| Juventus W | UEFA Women's Champions League | 32 | 64 | — | 12.9 | 45% | 4.4 | 1.3 |
| Servette Chênois W | UEFA Women's Champions League | 16 | 11 | — | 7.5 | 44% | 3.1 | 1.5 |
| Roma W | UEFA Women's Champions League | 26 | 55 | — | 14.5 | 50% | 5.7 | 1 |
| OH Leuven W | UEFA Women's Champions League | 12 | 11 | — | 9.9 | 43% | 4.5 | 1.4 |
| Paris W | UEFA Women's Champions League | 23 | 35 | — | 11.9 | 47% | 4.4 | 1 |
| Bordeaux W | UEFA Women's Champions League | 4 | 8 | — | 10 | 53% | 6.8 | 2.3 |
| Farum BK W | UEFA Women's Champions League | 3 | 7 | — | 14.3 | 55% | 5 | 0.7 |
| CSKA Moscow W | UEFA Women's Champions League | 3 | 5 | — | — | 55% | 7.7 | 2.3 |
| Glentoran BU W | UEFA Women's Champions League | 4 | 5 | — | 9 | 55% | 9 | 0.8 |
| Cliftonville W | UEFA Women's Champions League | 3 | 6 | — | 7.5 | 43% | 3.3 | 2.3 |
| Hoffenheim W | UEFA Women's Champions League | 10 | 20 | — | 10.9 | 49% | 3 | 0.5 |
| Rosenborg W | UEFA Women's Champions League | 4 | 6 | — | 7.3 | 46% | 3.7 | 1.3 |
| Vålerenga W | UEFA Women's Champions League | 29 | 47 | — | 11.6 | 43% | 4.6 | 0.8 |
| Breidablik W | UEFA Women's Champions League | 14 | 28 | — | 9.8 | 41% | 5.9 | 1 |
| Nike | UEFA Women's Champions League | 3 | 1 | — | 0 | 16% | 1 | 0.3 |
| Pomurje W | UEFA Women's Champions League | 5 | 16 | — | — | 34% | 4 | 0.8 |
| Ferencvárosi W | UEFA Women's Champions League | 11 | 22 | — | 10.3 | 44% | 5.3 | 2.3 |
| Flora W | UEFA Women's Champions League | 7 | 9 | — | 3.2 | 41% | 4.6 | 0.9 |
| Valur W | UEFA Women's Champions League | 11 | 20 | — | 10.8 | 51% | 5.3 | 0.9 |
| KuPS W | UEFA Women's Champions League | 4 | 10 | — | 18.5 | 45% | 7.8 | 0.8 |
| SL Benfica W | UEFA Women's Champions League | 33 | 53 | — | 8.7 | 44% | 3.3 | 1.7 |
| Køge | UEFA Women's Champions League | 10 | 9 | — | 5 | 37% | 2.1 | 0.3 |
| Dinamo-BGU W | UEFA Women's Champions League | 8 | 17 | — | 6.5 | 59% | 7.4 | 1.5 |
| Eintracht Frankfurt W | UEFA Women's Champions League | 14 | 27 | — | 15.3 | 55% | 6 | 0.9 |
| LASK Crvena Zvezda W | UEFA Women's Champions League | 4 | 4 | — | 3.3 | 30% | 2.3 | 1.8 |
| Peamount United W | UEFA Women's Champions League | 3 | 5 | — | 4.5 | 44% | 4.5 | 0.7 |
| Athlone Town WFC W | UEFA Women's Champions League | 4 | 10 | — | 10 | 53% | 5.5 | 0.5 |
| Real Madrid W | UEFA Women's Champions League | 38 | 77 | — | 14.4 | 53% | 5.3 | 1.3 |
| Lanchkhuti | UEFA Women's Champions League | 7 | 4 | — | 4 | 38% | 2 | 1.1 |
| Häcken W | UEFA Women's Champions League | 22 | 22 | — | 9.1 | 43% | 3 | 1.5 |
| Racing W | UEFA Women's Champions League | 8 | 10 | — | 6.2 | 46% | 2.2 | 2 |
| Celtic W | UEFA Women's Champions League | 14 | 15 | — | 8 | 43% | 5.3 | 1.4 |
| Okzhetpes W | UEFA Women's Champions League | 4 | 0 | — | 1.5 | 17% | 0.7 | 1 |
| Galatasaray W | UEFA Women's Champions League | 10 | 14 | — | 5.1 | 41% | 1.5 | 1.6 |
| Brann W | UEFA Women's Champions League | 16 | 29 | — | 11.4 | 55% | 5.1 | 1.3 |
| SFK Rīga W | UEFA Women's Champions League | 3 | 1 | — | 0.7 | 26% | 1 | 0.3 |
| Spartak Myjava W | UEFA Women's Champions League | 8 | 11 | — | 8.9 | 49% | 3 | 1.4 |
| Fomget Gençlik W | UEFA Women's Champions League | 6 | 13 | — | 9.3 | 56% | 4.5 | 1.3 |
| Ljuboten W | UEFA Women's Champions League | 8 | 11 | — | 7.2 | 40% | 2.8 | 2.1 |
| Austria Wien W | UEFA Women's Champions League | 4 | 5 | — | 6.3 | 46% | 5.3 | 1 |
| Farul Constanţa W | UEFA Women's Champions League | 4 | 10 | — | 8 | 52% | 4.5 | 1.5 |
| Cardiff City W | UEFA Women's Champions League | 5 | 0 | — | 5.8 | 50% | 1.6 | 1.6 |
| ŽNK Mura W | UEFA Women's Champions League | 8 | 16 | — | 9.5 | 47% | 3.9 | 2 |
| Vorskla Poltava W | UEFA Women's Champions League | 12 | 29 | — | 11 | 51% | 6.4 | 2.1 |
| Metalist 1925 Kharkiv W | UEFA Women's Champions League | 12 | 17 | — | 6 | 46% | 4 | 1.4 |
| Neftçi Bakı W | UEFA Women's Champions League | 3 | 1 | — | 3.5 | 32% | 0.7 | 1.7 |
| Pyunik W | UEFA Women's Champions League | 4 | 1 | — | 8 | 56% | 5 | 1.8 |