Card Statistics
Screen upcoming matches by both teams' booking records and the referee in charge, see the expected cards and the model's price, then check this week's strictest referees.
Card Screener
Every upcoming match with both teams' recent booking record against the line, the expected cards with the referee factored in, and a model price next to bet365 where the odds are in.
| Line | Odds | L15 | Last 10 · home / away | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Ref: not assigned yet | Over 4.5 Match cards | – | 59%1.70 | – | 5.2 | 60%6/10 | 60%12/20 | 67%20/30 | |
| Ref Wagner do Nascimento Magalhaes · 5.1 cards/match · ×1.15 | Over 4.5 Match cards | 1.83 55% | 58%1.72 | +7% | 5.7ref +0.7 | 70%7/10 | 60%12/20 | 57%17/30 | |
| Ref Edina Alves Batista · 5.7 cards/match · ×1.15 | Over 4.5 Match cards | 1.83 55% | 52%1.92 | -5% | 4.9ref +0.6 | 60%6/10 | 55%11/20 | 47%14/30 | |
| Ref Dámaso Arcediano Monescillo · 6.0 cards/match · ×1.15 | Over 5.5 Match cards | 1.90 53% | 49%2.04 | -7% | 5.6ref +0.7 | 60%6/10 | 55%11/20 | 45%13/29 | |
| Ref Álvaro Carranza · 4.4 cards/match · ×1.04 | Over 3.5 Match cards | 1.66 60% | 59%1.69 | -2% | 4.3ref +0.2 | 60%6/10 | 50%10/20 | 57%17/30 | |
| Ref Jacob Stausgaard Kobberrød · 3.2 cards/match · ×0.86 | Over 3.5 Match cards | – | 45%2.24 | – | 3.4ref −0.5 | 50%5/10 | 50%10/20 | 40%12/30 | |
| Ref: not assigned yet | Over 4.5 Match cards | – | 43%2.31 | – | 4.3 | 50%5/10 | 50%10/20 | 43%13/30 | |
| Ref Marius Lien · 3.3 cards/match · ×0.86 | Over 3.5 Match cards | – | 42%2.37 | – | 3.3ref −0.5 | 60%6/10 | 50%10/20 | 50%15/30 | |
| Ref: not assigned yet | Over 3.5 Match cards | – | 51%1.97 | – | 3.7 | 50%5/10 | 50%9/18 | 52%11/21 | |
| Ref Katia Itzel García · 5.4 cards/match · ×1.15 | Over 3.5 Match cards | 1.80 56% | 57%1.75 | +3% | 4.3ref +0.6 | 40%4/10 | 45%9/20 | 50%15/30 |
- ––Over 4.5 Match cardsExp 5.2 · Model 59%L560%6/10L1060%12/20L1567%20/30


- 1.83+7%Over 4.5 Match cardsExp 5.7 · Model 58%L570%7/10L1060%12/20L1557%17/30


- 1.83-5%Over 4.5 Match cardsExp 4.9 · Model 52%L560%6/10L1055%11/20L1547%14/30


Sabadell
Real Sociedad IIMon 20:30 · La Liga 2Ref Dámaso Arcediano Monescillo · 6.0 cards/match · ×1.151.90-7%Over 5.5 Match cardsExp 5.6 · Model 49%L560%6/10L1055%11/20L1545%13/29

Central Cordoba SdE
LanúsSun 23:30 · Liga Profesional de FútbolRef Álvaro Carranza · 4.4 cards/match · ×1.041.66-2%Over 3.5 Match cardsExp 4.3 · Model 59%L560%6/10L1050%10/20L1557%17/30

Hvidovre
Aarhus FremadMon 19:00 · First DivisionRef Jacob Stausgaard Kobberrød · 3.2 cards/match · ×0.86––Over 3.5 Match cardsExp 3.4 · Model 45%L550%5/10L1050%10/20L1540%12/30

- ––Over 4.5 Match cardsExp 4.3 · Model 43%L550%5/10L1050%10/20L1543%13/30


- ––Over 3.5 Match cardsExp 3.3 · Model 42%L560%6/10L1050%10/20L1550%15/30


- ––Over 3.5 Match cardsExp 3.7 · Model 51%L550%5/10L1050%9/18L1552%11/21


- 1.80+3%Over 3.5 Match cardsExp 4.3 · Model 57%L540%4/10L1045%9/20L1550%15/30


Hit rates pool both teams' recent matches (match cards): L10 is each team's last 10, so up to 20 games. Model: expected cards from each side's for/against averages, weighted toward recent games and shrunk to the average team, as a Poisson chance; where the bookmaker prices both sides it is blended half-and-half with the margin-free market price. Odds: bet365, where the feed has them. EV is model chance × odds − 1: the model’s view of the price, not a proven betting edge. Cards are yellows plus reds per side. The referee’s cards per match in our data, shrunk toward the average referee, scales the expected cards (×0.85 to ×1.15); before a referee is assigned the teams alone set it. Matches leave the list at kick-off. “Limited data” marks a team with fewer than 10 recent matches in our data, “new team” fewer than 5. A guide, not a forecast. Updated 8 Nov, 21:17.
Referees this week — strictest first
| Referee | Cards / match | Effect | Next match |
|---|---|---|---|
| Wagner do Nascimento Magalhaes | 5.1 | ×1.15 | |
| Edina Alves Batista | 5.7 | ×1.15 | |
| Katia Itzel García | 5.4 | ×1.15 | |
| Dámaso Arcediano Monescillo | 6.0 | ×1.15 | |
| Cláudio Filipe Ruivo Pereira | 5.5 | ×1.15 | |
| António Emanuel Carvalho Nobre | 4.9 | ×1.15 | |
| Guillermo Pacheco Larios | 4.5 | ×1.06 | |
| Braulio da Silva Machado | 4.4 | ×1.05 | |
| Álvaro Carranza | 4.4 | ×1.04 | |
| Javier Alberola Rojas | 4.0 | ×0.98 | |
| Oleg Kogut | 3.8 | ×0.95 | |
| Jacob Stausgaard Kobberrød | 3.2 | ×0.86 | |
| Marius Lien | 3.3 | ×0.86 |
How the Card Model Works
Cards are counted as yellows plus reds for each side. For every upcoming match the model takes each team's cards received and the cards its opponents picked up over its last 15 matches, weights recent games more, and shrinks the result toward the average team so a few wild games cannot dominate.
Then the referee comes in. Their cards per match across every game of theirs in our data is compared with the average match; the more games they have refereed, the more that rate counts. A strict referee scales the expected cards up (to at most ×1.4), a lenient one down (to ×0.7). Before a referee is appointed, the teams alone set the number.
Using Card Stats for Betting
Booking markets move on the referee more than most bettors realise: the same fixture can be a 3.5-card game with one official and a 5.5-card game with another. Use Strict referees to see the matches where the appointment pushes the line up, and Quiet games for unders.
Context matters too: derbies, relegation battles and cup ties tend to run hotter than the averages. Check the team stats for fouls and cards per game, and the player prop screener for individual booking lines.
Related stats
- Corner stats screenerCorner lines and hit rates by fixture
- Player prop screenerShots, fouls, tackles and cards by player
- Over/under goals screenerGoal-line hit rates for every upcoming match
- Mathematical football predictionsThis week's model probabilities for every match
- Football stats explainedWhat each number means and how to bet on it