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 |
|---|---|---|---|---|---|---|---|---|
| Vitesse | Eerste Divisie | 40 | 69 | — | 15 | 47% | 5.2 | 2.2 |
| FC Eindhoven | Eerste Divisie | 41 | 56 | — | 13.9 | 44% | 4.8 | 1.8 |
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.
| Willem II | Eerste Divisie | 38 | 59 | — | 14.7 | 48% | 5.7 | 1.5 |
| RKC Waalwijk | Eerste Divisie | 38 | 71 | — | 14.8 | 51% | 4.8 | 1.5 |
| FC Dordrecht | Eerste Divisie | 40 | 52 | — | 14.9 | 48% | 6.2 | 2.4 |
| De Graafschap | Eerste Divisie | 41 | 81 | — | 17.8 | 56% | 6.6 | 1.4 |
| ADO Den Haag | Eerste Divisie | 40 | 100 | — | 19.3 | 60% | 7.3 | 1.5 |
| Almere City | Eerste Divisie | 38 | 78 | — | 16.4 | 48% | 6.9 | 1.6 |
| SC Cambuur | Eerste Divisie | 40 | 80 | — | 14.8 | 57% | 6.3 | 1.6 |
| MVV Maastricht | Eerste Divisie | 40 | 42 | — | 11.1 | 44% | 4.1 | 1.6 |
| Roda JC Kerkrade | Eerste Divisie | 40 | 61 | — | 14.1 | 52% | 5.2 | 1.4 |
| TOP Oss | Eerste Divisie | 40 | 56 | — | 11.8 | 43% | 4.7 | 2.2 |
| VVV-Venlo | Eerste Divisie | 41 | 56 | — | 13.5 | 49% | 5.1 | 1.9 |
| FC Den Bosch | Eerste Divisie | 41 | 67 | — | 13.3 | 47% | 5.4 | 1.8 |
| FC Volendam | Eerste Divisie | 3 | 7 | — | 17.7 | 57% | 7.3 | 0.7 |
| Helmond Sport | Eerste Divisie | 41 | 43 | — | 12 | 49% | 5.9 | 1.8 |
| FC Emmen | Eerste Divisie | 40 | 60 | — | 13.5 | 52% | 5.7 | 2.2 |
| Jong FC Utrecht | Eerste Divisie | 41 | 62 | — | 13.7 | 47% | 4.1 | 1.4 |
| Jong Ajax | Eerste Divisie | 41 | 51 | — | 12 | 52% | 4.3 | 1.8 |
| Jong PSV | Eerste Divisie | 41 | 69 | — | 14.3 | 52% | 5 | 1.6 |
| Jong AZ | Eerste Divisie | 41 | 67 | — | 14 | 54% | 5 | 1.5 |