Team and match cards — booking totals and the referee
Match card totals and team card lines are, like player cards, driven heavily by the referee. SharpXI models the booking count for each team and the match.
How SharpXI models it
A team booking rate — recency-weighted — is multiplied by the referee's card tendency and an opponent factor, fed through a Negative Binomial for over/under card lines. Isotonic calibration corrected an over-confident tail on this market.
Go deeper: How we model cards → · Current referee card profiles →
Where the value tends to sit
Fiery fixtures under strict referees are where match-card overs pay; the referee assignment is the piece the market is slowest to fully reflect.
Premier League team leaders this season
In the 25/26 Premier League season, Tottenham led for cards a game at 2.74, ahead of Chelsea (2.68) and Bournemouth (2.37). That's against a Premier League team average of 1.95. Per-match rates from completed matches, not odds.
Per-match rates across the league (25/26 season, completed matches) — the teams whose underlying numbers drive this market.
| Team | Per match |
|---|---|
| Tottenham | 2.74 |
| Chelsea | 2.68 |
| Bournemouth | 2.37 |
| Brighton | 2.26 |
| Sunderland | 2.24 |
| Wolves | 2.13 |
| Crystal Palace | 2.03 |
| Everton | 2.03 |
Frequently asked
How are match card totals modelled?
By combining each team's booking rate with the referee's tendency and the opponent, then taking over/under probabilities from a Negative Binomial distribution.
Does the referee affect team cards as much as player cards?
Yes — at the match level the referee is still the dominant driver of the total number of cards, which is why SharpXI models it explicitly.
SharpXI is a statistical tool, not a betting operator, and no model guarantees a result. The honest scoreboard is closing-line value over a large sample. 18+ — please gamble responsibly.