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 |
|---|---|---|---|---|---|---|---|---|
| Peterborough United | League One | 182 | 302 | 0 | 12.9 | 56% | 5.3 | 1.8 |
| Fleetwood Town | League One | 156 | 179 | 0 | 11.5 | 48% | 5 | 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.
| Portsmouth | League One | 141 | 212 | 0 | 13.1 | 53% | 5.5 | 1.9 |
| Milton Keynes Dons | League One | 104 | 155 | 0 | 12.2 | 59% | 5.1 | 1.6 |
| Barnsley | League One | 136 | 221 | 0 | 12.8 | 53% | 5.4 | 2.1 |
| Ipswich Town | League One | 95 | 117 | 0 | 10.9 | 55% | 5 | 1.9 |
| Bradford City | League One | 41 | 54 | 0 | 12.6 | 49% | 5.2 | 2.1 |
| AFC Wimbledon | League One | 138 | 156 | 0 | 10.9 | 47% | 4.3 | 1.6 |
| Bristol Rovers | League One | 138 | 134 | 0 | 10.8 | 49% | 4.6 | 1.9 |
| Sheffield Wednesday | League One | 52 | 84 | — | 13.4 | 53% | 6.2 | 1.8 |
| Cardiff City | League One | 37 | 73 | — | 14.8 | 63% | 5.7 | 1.7 |
| Walsall | League One | 7 | 7 | — | 9.3 | 50% | 7 | 0.7 |
| Crewe Alexandra | League One | 92 | 93 | — | 10.4 | 52% | 4.6 | 1.5 |
| Plymouth Argyle | League One | 135 | 180 | — | 12.6 | 50% | 5.1 | 1.9 |
| Luton Town | League One | 41 | 57 | — | 12.2 | 57% | 6 | 1.6 |
| Rotherham United | League One | 129 | 165 | — | 13 | 47% | 5.8 | 1.7 |
| Burton Albion | League One | 223 | 244 | — | 11 | 44% | 4.7 | 2.1 |
| Shrewsbury Town | League One | 187 | 174 | — | 10.2 | 44% | 4.8 | 2 |
| Wycombe Wanderers | League One | 190 | 271 | — | 13 | 48% | 4.9 | 1.8 |
| Exeter City | League One | 134 | 142 | — | 10.5 | 52% | 5.2 | 2.2 |
| Crawley Town | League One | 46 | 57 | — | 11.4 | 56% | 4.1 | 2.4 |
| Northampton Town | League One | 178 | 181 | — | 9.9 | 45% | 4.1 | 1.8 |
| Mansfield Town | League One | 81 | 102 | — | 12 | 48% | 4.7 | 1.9 |
| Cambridge United | League One | 140 | 142 | — | 10.1 | 44% | 4.3 | 2 |
| Doncaster Rovers | League One | 139 | 159 | — | 11.3 | 49% | 4.3 | 1.6 |
| Rochdale | League One | 46 | 61 | — | 11.5 | 50% | 4.7 | 1.4 |
| Stockport County | League One | 82 | 121 | — | 12.7 | 53% | 4.8 | 2 |
| Huddersfield Town | League One | 83 | 114 | — | 12.8 | 53% | 6.4 | 1.9 |
| Wrexham | League One | 46 | 67 | — | 11.7 | 48% | 4.4 | 1.7 |
| Swindon Town | League One | 50 | 59 | — | 10.4 | 49% | 4.4 | 1.8 |
| Leyton Orient | League One | 132 | 178 | — | 11.7 | 52% | 5.2 | 2.3 |
| Oxford United | League One | 151 | 258 | — | 13.8 | 53% | 5.4 | 1.7 |
| Lincoln City | League One | 226 | 326 | — | 11.4 | 47% | 4.9 | 2.1 |
| Gillingham | League One | 104 | 117 | — | 10.8 | 41% | 4.6 | 1.9 |
| Carlisle United | League One | 46 | 41 | — | 11.1 | 46% | 4.8 | 1.8 |
| Port Vale | League One | 85 | 70 | — | 11.8 | 48% | 5 | 1.9 |
| Cheltenham Town | League One | 96 | 111 | — | 12.2 | 46% | 4.4 | 2.2 |
| Accrington Stanley | League One | 94 | 126 | — | 15.1 | 48% | 5.2 | 2 |
| Stevenage | League One | 128 | 139 | — | 11 | 46% | 5.1 | 2.1 |
| Sunderland | League One | 97 | 155 | — | 14 | 57% | 6 | 1.7 |
| Morecambe | League One | 46 | 57 | — | 11.9 | 44% | 4.4 | 1.5 |
| Charlton Athletic | League One | 193 | 265 | — | 12.1 | 50% | 5.2 | 2.3 |
| Birmingham City | League One | 46 | 84 | — | 13.2 | 67% | 5.8 | 1.7 |
| Bolton Wanderers | League One | 182 | 291 | — | 14.2 | 58% | 5.7 | 2 |
| Wigan Athletic | League One | 226 | 286 | — | 10.7 | 50% | 5.1 | 2.1 |
| Hull City | League One | 46 | 79 | — | 12.6 | 49% | 5.2 | 1.4 |
| Reading | League One | 129 | 191 | — | 11.9 | 52% | 4.4 | 1.9 |
| Derby County | League One | 48 | 78 | — | 12.5 | 51% | 6.4 | 1.7 |
| Blackpool | League One | 191 | 263 | — | 12.1 | 50% | 4.8 | 1.7 |