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 |
|---|---|---|---|---|---|---|---|---|
| Dynamo Dresden | 2. Bundesliga | 67 | 84 | 0 | 12.7 | 50% | 5 | 2.2 |
| DSC Arminia Bielefeld | 2. Bundesliga | 35 | 49 | 0 | 14.1 | 48% | 5.5 | 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.
| Eintracht Braunschweig | 2. Bundesliga | 141 | 146 | 0 | 12 | 44% | 4.6 | 2.5 |
| Darmstadt 98 | 2. Bundesliga | 140 | 256 | — | 14.6 | 50% | 4.8 | 2.3 |
| Ingolstadt | 2. Bundesliga | 34 | 30 | — | 11.1 | 40% | 3.6 | 2.5 |
| Hansa Rostock | 2. Bundesliga | 68 | 71 | — | 12.7 | 45% | 4.5 | 2.5 |
| Ulm | 2. Bundesliga | 34 | 36 | — | 12.4 | 47% | 4.3 | 2.7 |
| Nürnberg | 2. Bundesliga | 177 | 255 | — | 12.8 | 48% | 5 | 2.4 |
| VfL Bochum 1848 | 2. Bundesliga | 71 | 103 | — | 13.2 | 52% | 5.4 | 2.4 |
| FC Union Berlin | 2. Bundesliga | 3 | 2 | — | 8 | 45% | 6 | 1.7 |
| Fortuna Düsseldorf | 2. Bundesliga | 182 | 269 | — | 13.3 | 50% | 5 | 2.4 |
| Kaiserslautern | 2. Bundesliga | 114 | 176 | — | 13.7 | 48% | 5.1 | 2.4 |
| Hannover 96 | 2. Bundesliga | 168 | 244 | — | 13.6 | 51% | 5.3 | 2.1 |
| Paderborn | 2. Bundesliga | 173 | 275 | — | 14.2 | 54% | 5.2 | 2.1 |
| Hamburger SV | 2. Bundesliga | 139 | 282 | — | 14.9 | 58% | 6 | 2.2 |
| Heidenheim | 2. Bundesliga | 68 | 92 | — | 13.6 | 48% | 5.9 | 1.7 |
| Osnabrück | 2. Bundesliga | 67 | 66 | — | 11.1 | 46% | 4.6 | 2.3 |
| Karlsruher SC | 2. Bundesliga | 178 | 288 | — | 13.3 | 50% | 5.2 | 2.3 |
| Hertha BSC | 2. Bundesliga | 95 | 157 | — | 13.2 | 50% | 5.2 | 2.4 |
| FC Köln | 2. Bundesliga | 36 | 54 | — | 16.5 | 52% | 6.3 | 2.3 |
| Erzgebirge Aue | 2. Bundesliga | 67 | 74 | — | 11.9 | 45% | 3.5 | 2 |
| Würzburger Kickers | 2. Bundesliga | 34 | 39 | — | 11.3 | 45% | 4 | 2 |
| SpVgg Greuther Fürth | 2. Bundesliga | 134 | 211 | — | 13.2 | 50% | 5.1 | 2.1 |
| Jahn Regensburg | 2. Bundesliga | 102 | 110 | — | 13.2 | 46% | 4.8 | 2.3 |
| Sandhausen | 2. Bundesliga | 65 | 81 | — | 10.7 | 42% | 4.8 | 2.7 |
| Wehen Wiesbaden | 2. Bundesliga | 34 | 36 | — | 12.5 | 45% | 4.4 | 2.4 |
| Magdeburg | 2. Bundesliga | 98 | 147 | — | 14.3 | 58% | 5.4 | 2.6 |
| Elversberg | 2. Bundesliga | 94 | 157 | — | 13.8 | 51% | 5.4 | 2.1 |
| Holstein Kiel | 2. Bundesliga | 142 | 219 | — | 13.4 | 54% | 5.1 | 2.2 |
| Schalke 04 | 2. Bundesliga | 128 | 214 | — | 14.8 | 50% | 5.3 | 2.3 |
| Preußen Münster | 2. Bundesliga | 60 | 70 | — | 12.3 | 48% | 4.2 | 3 |
| Werder Bremen | 2. Bundesliga | 34 | 65 | — | 17.3 | 56% | 6.4 | 2.1 |
| St. Pauli | 2. Bundesliga | 102 | 174 | — | 14.5 | 54% | 5.1 | 1.9 |