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 |
|---|---|---|---|---|---|---|---|---|
| Veles | FNL | 80 | 98 | 0 | 7.5 | 43% | 4.5 | 2.7 |
| SKA Khabarovsk | FNL | 173 | 200 | 0 | 6.1 | 47% | 4.6 | 2.3 |
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.
| Ural | FNL | 58 | 81 | — | 8.8 | 53% | 5.5 | 1.9 |
| Orenburg | FNL | 80 | 142 | — | 13.7 | 45% | 5.5 | 3 |
| Irtysh | FNL | 42 | 30 | — | 7.8 | 44% | 3.8 | 3.1 |
| Arsenal Tula | FNL | 94 | 96 | — | 5.1 | 54% | 4.7 | 1.7 |
| Krasnodar II | FNL | 79 | 91 | — | 9.1 | 43% | 4 | 2.5 |
| Sochi | FNL | 38 | 60 | — | 8.3 | 55% | 5.3 | 1.7 |
| Dolgie Prudy | FNL | 36 | 33 | — | 7.3 | 30% | 3.8 | 2.9 |
| Shinnik | FNL | 146 | 146 | — | 4.3 | 48% | 4.7 | 2 |
| Yenisey | FNL | 179 | 231 | — | 5.3 | 46% | 4.7 | 2.3 |
| Volgar Astrakhan | FNL | 111 | 102 | — | 4.1 | 44% | 4.4 | 2.6 |
| Baltika Kaliningrad | FNL | 112 | 147 | — | 10.2 | 48% | 6.2 | 2.7 |
| Rotor Volgograd | FNL | 96 | 96 | — | 8.1 | 42% | 4.2 | 2.3 |
| Alaniya Vladikavkaz | FNL | 147 | 213 | — | 6.2 | 50% | 5.4 | 2.5 |
| Chernomorets | FNL | 92 | 109 | — | 5 | 50% | 4.2 | 1.8 |
| Metallurg Lipetsk | FNL | 38 | 29 | — | 6.7 | 26% | 3.9 | 2.7 |
| Neftekhimik | FNL | 172 | 216 | — | 6 | 43% | 4.4 | 2 |
| Dinamo Bryansk | FNL | 41 | 25 | — | 6.8 | 43% | 4 | 2.3 |
| Tom' Tomsk | FNL | 77 | 77 | — | 7.5 | 38% | 4.3 | 3.1 |
| Khimki | FNL | 34 | 56 | — | 0.5 | 49% | 5.4 | 1.8 |
| Sokol Saratov | FNL | 90 | 65 | — | 3.6 | 46% | 4.1 | 1.9 |
| Tekstilshchik | FNL | 78 | 62 | — | 5.8 | 35% | 3.9 | 2.7 |
| Fakel | FNL | 105 | 152 | — | 9.3 | 45% | 4.9 | 2.6 |
| Torpedo Moskva | FNL | 171 | 236 | — | 6.7 | 49% | 5.1 | 2 |
| FK Nizjni Novgorod | FNL | 48 | 71 | — | 11 | 51% | 4.7 | 2.8 |
| Chayka | FNL | 98 | 93 | — | 6.5 | 48% | 4.4 | 2.3 |
| KAMAZ | FNL | 131 | 129 | — | 5.3 | 45% | 5.1 | 2.5 |
| Spartak Kostroma | FNL | 24 | 34 | — | 7.4 | 48% | 3.8 | 2.5 |
| Tyumen | FNL | 68 | 66 | — | 2.9 | 48% | 4.8 | 1.7 |
| Chelyabinsk | FNL | 24 | 33 | — | 6.6 | 51% | 3.8 | 1.7 |
| Volga Ulyanovsk | FNL | 26 | 28 | — | 7.7 | 52% | 5 | 2 |
| Chertanovo | FNL | 41 | 32 | — | 8.5 | 46% | 3.4 | 2.9 |
| Spartak Moskva II | FNL | 78 | 95 | — | 8.4 | 42% | 4.5 | 2.4 |
| Leningradets | FNL | 33 | 27 | — | 0.6 | 49% | 4.1 | 1.6 |
| Urozhay | FNL | 70 | 64 | — | 3.7 | 37% | 4.2 | 2.6 |
| Rodina Moskva | FNL | 96 | 134 | — | 5.8 | 53% | 5.5 | 1.8 |
| Akron | FNL | 112 | 127 | — | 4.3 | 46% | 4.4 | 2.5 |
| Ufa | FNL | 60 | 59 | — | 6.3 | 48% | 3.8 | 2.4 |
| Dynamo Makhachkala | FNL | 34 | 37 | — | 0.5 | 51% | 4.7 | 1.5 |
| Krylya Sovetov | FNL | 44 | 101 | — | 9.4 | 55% | 6.3 | 2.1 |