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 |
|---|---|---|---|---|---|---|---|---|
| Hapoel Be'er Sheva | Ligat ha'Al | 160 | 270 | — | 13.7 | 55% | 5.3 | 2.7 |
| Maccabi Haifa | Ligat ha'Al | 161 | 324 | — | 14 | 58% | 5.7 | 2.4 |
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.
| Beitar Jerusalem | Ligat ha'Al | 149 | 222 | — | 11.9 | 56% | 4.7 | 2.5 |
| Hapoel Kfar Saba | Ligat ha'Al | 28 | 24 | — | 6.9 | 48% | 4.1 | 2.6 |
| Hapoel Haifa | Ligat ha'Al | 149 | 183 | — | 10.4 | 47% | 4.2 | 2.4 |
| Maccabi Tel Aviv | Ligat ha'Al | 164 | 327 | — | 14.1 | 58% | 6.1 | 2.1 |
| Maccabi Petah Tikva | Ligat ha'Al | 126 | 135 | — | 9.9 | 48% | 3.9 | 2.6 |
| Hapoel Jerusalem | Ligat ha'Al | 113 | 124 | — | 10.3 | 45% | 3.8 | 2.1 |
| Maccabi Netanya | Ligat ha'Al | 146 | 193 | — | 12.9 | 52% | 4.7 | 2.9 |
| Ashdod | Ligat ha'Al | 140 | 168 | — | 10.6 | 48% | 4.1 | 2.4 |
| Hapoel Nof HaGalil | Ligat ha'Al | 23 | 14 | — | 8.7 | 46% | 4.3 | 2.3 |
| Bnei Yehuda | Ligat ha'Al | 28 | 22 | — | 5.8 | 46% | 3.8 | 2.4 |
| Ironi Tiberias | Ligat ha'Al | 57 | 58 | — | 10.5 | 43% | 3.6 | 2.7 |
| Hapoel Petah Tikva | Ligat ha'Al | 57 | 65 | — | 10.9 | 47% | 4.4 | 2.4 |
| Ironi Kiryat Shmona | Ligat ha'Al | 131 | 152 | — | 10 | 47% | 3.8 | 2.7 |
| Hapoel Tel Aviv | Ligat ha'Al | 114 | 134 | — | 9.8 | 49% | 4.7 | 2.7 |
| Bnei Sakhnin | Ligat ha'Al | 146 | 131 | — | 8.5 | 47% | 3.9 | 2.5 |
| Hapoel Hadera | Ligat ha'Al | 120 | 118 | — | 9 | 42% | 3.3 | 2.8 |
| Maccabi Bnei Raina | Ligat ha'Al | 96 | 96 | — | 10.1 | 47% | 3.8 | 2.7 |