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 |
|---|---|---|---|---|---|---|---|---|
| Guadalajara | Liga MX | 201 | 245 | — | 13.1 | 53% | 4.9 | 2.1 |
| Querétaro | Liga MX | 193 | 199 | — | 11.1 | 41% | 4.4 | 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.
| Tigres UANL | Liga MX | 234 | 348 | — | 14.1 | 56% | 5.3 | 2.2 |
| Atlas | Liga MX | 213 | 241 | — | 12.6 | 48% | 4.8 | 2.4 |
| Toluca | Liga MX | 217 | 360 | — | 13.6 | 52% | 4.8 | 2.3 |
| Cruz Azul | Liga MX | 229 | 336 | — | 14.2 | 54% | 5.4 | 2.1 |
| Monterrey | Liga MX | 230 | 344 | — | 14 | 52% | 5 | 2.1 |
| América | Liga MX | 219 | 342 | — | 13.7 | 54% | 5.2 | 1.7 |
| Santos Laguna | Liga MX | 220 | 272 | — | 13.2 | 48% | 5.3 | 2 |
| Pumas UNAM | Liga MX | 226 | 291 | — | 13.2 | 49% | 5 | 2.4 |
| Puebla | Liga MX | 217 | 238 | — | 12.5 | 46% | 4.5 | 2.4 |
| Necaxa | Liga MX | 202 | 247 | — | 13.2 | 45% | 4.5 | 2.2 |
| Juárez | Liga MX | 180 | 193 | — | 11.4 | 47% | 4.1 | 2.4 |
| Pachuca | Liga MX | 215 | 303 | — | 15.1 | 51% | 5.6 | 2.2 |
| León | Liga MX | 201 | 259 | — | 13.2 | 54% | 4.8 | 2.2 |
| Tijuana | Liga MX | 215 | 271 | — | 12.7 | 51% | 4.2 | 2.2 |
| Atlético San Luis | Liga MX | 186 | 250 | — | 11.8 | 49% | 4.4 | 2.2 |
| Mazatlán | Liga MX | 170 | 195 | — | 10.9 | 46% | 4 | 2.6 |