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Goals for/against per game, attack–defence differential, and market indicators for every club across Europe's top five leagues in 2026/27. Same season window as our predictions. No registration required.
All season rates are free to access. Read how we use attacking and defensive rates in the model.
| # | Club | MP | GF/g | GA/g | Diff | SoT | Poss | BTTS% | O2.5% | CS% |
|---|---|---|---|---|---|---|---|---|---|---|
| 3 | BRI Brighton |
7 | 3.29 | 0.71 | +2.58 | 9.1 | 62% | 82% | 85% | 47% |
| 1 | MCI Manchester City |
7 | 2.71 | 1.00 | +1.71 | 7.9 | 58% | 78% | 85% | 60% |
| 4 | CHE Chelsea |
7 | 2.43 | 1.86 | +0.57 | 7.3 | 55% | 83% | 85% | 39% |
| 6 | BRE Brentford |
7 | 1.86 | 1.14 | +0.72 | 6.1 | 53% | 69% | 82% | 24% |
| 2 | ARS Arsenal |
7 | 1.57 | 0.71 | +0.86 | 5.5 | 52% | 61% | 69% | 55% |
| 10 | IPS Ipswich |
7 | 1.57 | 2.14 | -0.57 | 5.5 | 49% | 75% | 85% | 32% |
| 11 | NEW Newcastle |
7 | 1.43 | 2.00 | -0.57 | 5.2 | 49% | 72% | 85% | 24% |
| 13 | MNU Manchester United |
7 | 1.43 | 1.43 | +0.00 | 5.2 | 50% | 66% | 79% | 16% |
| 5 | LIV Liverpool |
7 | 1.29 | 1.14 | +0.15 | 4.9 | 49% | 62% | 72% | 32% |
| 7 | LEE Leeds |
7 | 1.29 | 0.86 | +0.43 | 4.9 | 50% | 59% | 67% | 24% |
| 14 | CRY Crystal Palace |
7 | 1.29 | 2.43 | -1.14 | 4.9 | 47% | 75% | 85% | 24% |
| 15 | BOU Bournemouth |
7 | 1.29 | 1.86 | -0.57 | 4.9 | 48% | 69% | 85% | 16% |
| 8 | EVE Everton |
7 | 1.14 | 1.00 | +0.14 | 4.6 | 49% | 59% | 67% | 24% |
| 9 | HUL Hull City |
7 | 1.14 | 1.00 | +0.14 | 4.6 | 49% | 59% | 67% | 24% |
| 12 | AVL Aston Villa |
7 | 1.00 | 1.57 | -0.57 | 4.3 | 47% | 63% | 74% | 24% |
| 17 | FUL Fulham |
7 | 1.00 | 1.43 | -0.43 | 4.3 | 47% | 61% | 72% | 16% |
| 19 | SUN Sunderland |
7 | 0.86 | 2.00 | -1.14 | 4 | 45% | 65% | 79% | 16% |
| 16 | COV Coventry |
6 | 0.83 | 1.83 | -1.00 | 3.9 | 45% | 63% | 76% | 26% |
| 18 | NOT Nottingham Forest |
7 | 0.71 | 1.29 | -0.58 | 3.7 | 46% | 56% | 64% | 16% |
| 20 | TOT Tottenham |
6 | 0.50 | 1.50 | -1.00 | 3.3 | 44% | 56% | 64% | 8% |
| # | Club | MP | GF/g | GA/g | Diff | SoT | Poss | BTTS% | O2.5% | CS% |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | BAR Barcelona |
9 | 4.33 | 1.00 | +3.33 | 9.5 | 68% | 85% | 85% | 60% |
| 3 | RMA Real Madrid |
9 | 2.56 | 1.00 | +1.56 | 7.6 | 57% | 76% | 85% | 51% |
| 2 | ATM Atletico Madrid |
9 | 2.11 | 0.89 | +1.22 | 6.6 | 55% | 69% | 82% | 51% |
| 5 | RSO Real Sociedad |
9 | 1.89 | 1.89 | +0.00 | 6.2 | 52% | 77% | 85% | 39% |
| 4 | BET Real Betis |
9 | 1.78 | 1.56 | +0.22 | 5.9 | 52% | 72% | 85% | 45% |
| 14 | RAY Rayo Vallecano |
7 | 1.57 | 2.29 | -0.72 | 5.5 | 49% | 77% | 85% | 24% |
| 6 | SEV Sevilla |
9 | 1.56 | 1.78 | -0.22 | 5.5 | 50% | 72% | 85% | 32% |
| 17 | LEV Levante |
8 | 1.50 | 2.00 | -0.50 | 5.4 | 49% | 73% | 85% | 15% |
| 7 | ALA Alaves |
9 | 1.44 | 1.11 | +0.33 | 5.2 | 50% | 63% | 74% | 26% |
| 9 | DEP Deportivo La Coruna |
9 | 1.44 | 1.33 | +0.11 | 5.2 | 50% | 66% | 78% | 20% |
| 12 | VIL Villarreal |
9 | 1.44 | 1.44 | +0.00 | 5.2 | 50% | 67% | 80% | 20% |
| 16 | RAC Racing Santander |
9 | 1.44 | 2.78 | -1.34 | 5.2 | 47% | 80% | 85% | 20% |
| 13 | ESP Espanyol |
9 | 1.22 | 1.33 | -0.11 | 4.8 | 49% | 63% | 74% | 20% |
| 18 | ELC Elche |
9 | 1.22 | 1.89 | -0.67 | 4.8 | 48% | 69% | 84% | 14% |
| 8 | CEL Celta Vigo |
9 | 1.11 | 0.78 | +0.33 | 4.5 | 49% | 56% | 62% | 20% |
| 10 | OSA Osasuna |
9 | 1.11 | 2.00 | -0.89 | 4.5 | 47% | 68% | 84% | 26% |
| 11 | ATH Athletic Club |
7 | 1.00 | 0.86 | +0.14 | 4.3 | 48% | 56% | 61% | 24% |
| 19 | VAL Valencia |
9 | 0.67 | 1.67 | -1.00 | 3.6 | 45% | 60% | 70% | 14% |
| 20 | MAL Malaga |
9 | 0.67 | 2.00 | -1.33 | 3.6 | 44% | 63% | 76% | 8% |
| 15 | GET Getafe |
8 | 0.50 | 1.25 | -0.75 | 3.3 | 45% | 54% | 60% | 22% |
| # | Club | MP | GF/g | GA/g | Diff | SoT | Poss | BTTS% | O2.5% | CS% |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | INT Inter |
7 | 3.00 | 1.29 | +1.71 | 8.5 | 59% | 84% | 85% | 55% |
| 3 | ROM AS Roma |
7 | 2.29 | 0.43 | +1.86 | 7 | 57% | 67% | 77% | 47% |
| 2 | LAZ Lazio |
7 | 2.00 | 0.57 | +1.43 | 6.4 | 55% | 65% | 74% | 55% |
| 4 | MIL AC Milan |
7 | 2.00 | 1.00 | +1.00 | 6.4 | 54% | 69% | 82% | 39% |
| 6 | FRO Frosinone |
7 | 1.86 | 1.29 | +0.57 | 6.1 | 53% | 70% | 85% | 39% |
| 5 | COM Como |
7 | 1.71 | 1.00 | +0.71 | 5.8 | 52% | 66% | 77% | 39% |
| 12 | SAS Sassuolo |
7 | 1.71 | 2.00 | -0.29 | 5.8 | 50% | 76% | 85% | 24% |
| 15 | MON Monza |
6 | 1.50 | 2.50 | -1.00 | 5.4 | 48% | 78% | 85% | 17% |
| 9 | NAP Napoli |
7 | 1.43 | 1.00 | +0.43 | 5.2 | 51% | 62% | 72% | 32% |
| 10 | ATA Atalanta |
7 | 1.43 | 1.57 | -0.14 | 5.2 | 49% | 68% | 82% | 32% |
| 8 | JUV Juventus |
7 | 1.29 | 1.14 | +0.15 | 4.9 | 49% | 62% | 72% | 32% |
| 11 | LEC Lecce |
7 | 1.29 | 1.71 | -0.42 | 4.9 | 48% | 68% | 82% | 32% |
| 17 | UDI Udinese |
7 | 1.29 | 2.29 | -1.00 | 4.9 | 47% | 73% | 85% | 16% |
| 13 | TOR Torino |
6 | 1.17 | 1.50 | -0.33 | 4.7 | 48% | 64% | 76% | 26% |
| 19 | FIO Fiorentina |
7 | 1.14 | 2.43 | -1.29 | 4.6 | 46% | 73% | 85% | 16% |
| 7 | CAG Cagliari |
6 | 1.00 | 0.50 | +0.50 | 4.3 | 49% | 52% | 55% | 45% |
| 14 | BOL Bologna |
7 | 0.86 | 1.43 | -0.57 | 4 | 46% | 60% | 69% | 16% |
| 20 | VEN Venezia |
7 | 0.86 | 2.29 | -1.43 | 4 | 45% | 68% | 85% | 16% |
| 18 | GEN Genoa |
7 | 0.71 | 1.86 | -1.15 | 3.7 | 45% | 62% | 74% | 16% |
| 16 | PAR Parma |
6 | 0.67 | 1.67 | -1.00 | 3.6 | 45% | 60% | 70% | 17% |
| # | Club | MP | GF/g | GA/g | Diff | SoT | Poss | BTTS% | O2.5% | CS% |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | BAY Bayern München |
6 | 3.67 | 0.83 | +2.84 | 9.5 | 64% | 85% | 85% | 45% |
| 4 | LEV Bayer Leverkusen |
6 | 2.67 | 1.50 | +1.17 | 7.8 | 57% | 82% | 85% | 45% |
| 7 | RBL RB Leipzig |
6 | 2.67 | 1.83 | +0.84 | 7.8 | 56% | 85% | 85% | 36% |
| 10 | FCA FC Augsburg |
6 | 2.67 | 2.00 | +0.67 | 7.8 | 56% | 85% | 85% | 26% |
| 3 | SCF SC Freiburg |
6 | 2.50 | 1.00 | +1.50 | 7.5 | 57% | 75% | 85% | 45% |
| 5 | FSV FSV Mainz 05 |
6 | 2.33 | 1.67 | +0.66 | 7.1 | 55% | 80% | 85% | 36% |
| 6 | SVE SV Elversberg |
6 | 2.00 | 1.83 | +0.17 | 6.4 | 52% | 77% | 85% | 36% |
| 8 | WER Werder Bremen |
6 | 2.00 | 2.00 | +0.00 | 6.4 | 52% | 79% | 85% | 26% |
| 2 | DOR Borussia Dortmund |
6 | 1.83 | 0.67 | +1.16 | 6 | 54% | 64% | 73% | 45% |
| 14 | HOF 1899 Hoffenheim |
6 | 1.83 | 2.33 | -0.50 | 6 | 50% | 80% | 85% | 26% |
| 11 | FRA Eintracht Frankfurt |
6 | 1.67 | 2.67 | -1.00 | 5.7 | 49% | 82% | 85% | 26% |
| 12 | FCK 1. FC Köln |
6 | 1.33 | 1.83 | -0.50 | 5 | 48% | 69% | 85% | 26% |
| 13 | STU VfB Stuttgart |
6 | 1.33 | 1.67 | -0.34 | 5 | 49% | 68% | 82% | 26% |
| 18 | BOR Borussia Mönchengladbach |
6 | 1.33 | 3.33 | -2.00 | 5 | 45% | 84% | 85% | 8% |
| 9 | HAM Hamburger SV |
6 | 1.00 | 2.50 | -1.50 | 4.3 | 45% | 72% | 85% | 36% |
| 16 | SCP SC Paderborn 07 |
6 | 0.83 | 1.50 | -0.67 | 3.9 | 46% | 60% | 70% | 17% |
| 17 | UNI Union Berlin |
6 | 0.83 | 2.83 | -2.00 | 3.9 | 43% | 73% | 85% | 17% |
| 15 | FCS FC Schalke 04 |
6 | 0.67 | 1.17 | -0.50 | 3.6 | 46% | 55% | 61% | 17% |
| # | Club | MP | GF/g | GA/g | Diff | SoT | Poss | BTTS% | O2.5% | CS% |
|---|---|---|---|---|---|---|---|---|---|---|
| 6 | REN Rennes |
7 | 2.14 | 2.00 | +0.14 | 6.7 | 53% | 81% | 85% | 39% |
| 2 | PSG Paris Saint Germain |
7 | 2.00 | 1.29 | +0.71 | 6.4 | 53% | 72% | 85% | 39% |
| 8 | LEN Lens |
7 | 2.00 | 1.57 | +0.43 | 6.4 | 53% | 75% | 85% | 32% |
| 9 | MAR Marseille |
7 | 2.00 | 1.43 | +0.57 | 6.4 | 53% | 73% | 85% | 32% |
| 1 | LYO Lyon |
7 | 1.86 | 0.71 | +1.15 | 6.1 | 54% | 64% | 74% | 39% |
| 10 | STA Stade Brestois 29 |
7 | 1.86 | 1.43 | +0.43 | 6.1 | 52% | 72% | 85% | 24% |
| 3 | PAR Paris FC |
7 | 1.71 | 1.00 | +0.71 | 5.8 | 52% | 66% | 77% | 39% |
| 11 | TOU Toulouse |
7 | 1.71 | 1.57 | +0.14 | 5.8 | 51% | 71% | 85% | 24% |
| 14 | STR Strasbourg |
7 | 1.71 | 2.14 | -0.43 | 5.8 | 50% | 77% | 85% | 24% |
| 12 | AUX Auxerre |
7 | 1.57 | 2.43 | -0.86 | 5.5 | 49% | 78% | 85% | 32% |
| 4 | LIL Lille |
7 | 1.43 | 0.71 | +0.72 | 5.2 | 51% | 59% | 67% | 39% |
| 5 | MON Monaco |
7 | 1.43 | 0.86 | +0.57 | 5.2 | 51% | 61% | 69% | 39% |
| 16 | LEM Le Mans |
7 | 1.43 | 2.14 | -0.71 | 5.2 | 48% | 74% | 85% | 16% |
| 15 | ANG Angers |
7 | 1.29 | 2.14 | -0.85 | 4.9 | 47% | 72% | 85% | 24% |
| 7 | LOR Lorient |
7 | 1.00 | 0.86 | +0.14 | 4.3 | 48% | 56% | 61% | 32% |
| 13 | NIC Nice |
7 | 0.86 | 1.29 | -0.43 | 4 | 47% | 58% | 67% | 24% |
| 17 | EST Estac Troyes |
7 | 0.71 | 2.29 | -1.58 | 3.7 | 44% | 66% | 82% | 16% |
| 18 | LEH Le Havre |
7 | 0.71 | 1.57 | -0.86 | 3.7 | 45% | 59% | 69% | 8% |
Expected goals (xG) is a statistical measure that assigns a probability to each shot, representing the likelihood of it resulting in a goal based on shot quality rather than outcomes. A shot from six yards centrally might have an xG of 0.75. A long-range effort from outside the box might have an xG of 0.04. Summing all shots in a match gives each team's total xG — a measure of how many goals they deserved based on the chances they created.
Why is xG more useful than actual goals? Because goals contain random variance. An exceptional save, a shot hitting the post, a goalkeeper's positioning error — these are low-probability events that affect whether a goal is scored but carry no information about the quality of the chance itself. Over a season, teams tend to score roughly in line with their accumulated xG. Teams consistently outperforming their xG are likely finishing well above the sustainable rate and will regress. Teams underperforming are likely to improve.
xG (Expected Goals For) — how many goals per game a team is expected to score based on the quality of chances they create. The teams at the top of this column are the most dangerous attacking sides in the league. xGA (Expected Goals Against) — how many goals per game a team is expected to concede based on the quality of chances their opponents create against them. Lower is better. Diff (xG − xGA) — the net xG differential. A positive differential indicates a team creating significantly better chances than they allow. This is the most reliable single indicator of a team's true quality. BTTS% — the percentage of a team's matches in which both teams scored. High BTTS% teams make strong candidates for BTTS Yes markets. O2.5% — the percentage of matches in which over 2.5 goals were scored. High O2.5% teams are good candidates for over markets. CS% — clean sheet percentage, useful for BTTS No and under markets.
xG data is most useful when it reveals a gap between actual results and expected performance. A team sitting mid-table with the third-best xG differential in the league is likely underperforming and worth backing. A team in the top four with a negative xG differential has likely been scoring from poor chances or benefiting from opponents' poor finishing — a fragile position that may not hold. Cross-reference the xG table with the points standings and the value bet index to find markets where the bookmaker's price does not reflect the underlying statistical reality.
All xG figures are rolling 38-match averages, updated daily. For the full Poisson model output using these xG inputs, see the mathematical predictions page. For tips derived from the model, see today's predictions. Bet responsibly. 18+ only.
Full Poisson scoreline matrices and 1X2 probabilities for today's fixtures, built from the xG data on this page.
Full league standings with xG and xGA columns — see which teams are over or underperforming their expected results.
Markets where the model's probability exceeds the bookmaker's implied price. Built from the xG inputs above.