Dembo Sylla
Over the last 4 Ligue 1 games, Dembo Sylla has hit 1+ shot on target in 25% (1 of 4), 1+ total shot in 50%, 1+ foul committed in 0%, 1+ foul won in 0%, and been booked in 0% (0 of 4). These are raw hit rates from completed matches, not odds.
All markets last 4 games
Recent matches
The last 4 games Dembo Sylla featured in — minutes and the counts that settle these markets.
| Match | Min | SoT | Shots | Fouls | Won | Cards |
|---|---|---|---|---|---|---|
| Rodez AF12 May | 75 | 0 | 0 | 0 | 0 | 0 |
| @ Saint-Étienne24 May | 68 | 0 | 0 | 0 | 0 | 0 |
| Paris FC21 May | 68 | 1 | 4 | 0 | 0 | 0 |
| @ Le Havre3 Sep | 45 | 0 | 1 | 0 | 0 | 0 |
Frequently asked
How often does Dembo Sylla have a shot on target?
Over the last 4 Ligue 1 games, Dembo Sylla has hit 1+ shot on target in 25% (1 of 4). That's the raw hit rate from completed matches; SharpXI's model turns it into a true probability by adjusting for the opponent and expected minutes, then de-vigs the bookmaker's price.
How many shots on target does Dembo Sylla average?
Across the last 4 Ligue 1 games, Dembo Sylla is averaging 0.35 shots on target and 1.76 total shots per 90 minutes. SharpXI treats that as a starting rate, then adjusts for the opponent and expected minutes before pricing a 1+ or 2+ line.
How often does Dembo Sylla get booked?
Dembo Sylla is averaging 0.00 cards per 90 over the last 4 games. Bookings swing heavily on the referee, so the model multiplies a player's base rate by each official's card tendency — the biggest single lever in the to-be-carded market.
Does Dembo Sylla commit or win more fouls?
Over the last 4 games Dembo Sylla commits 0.00 fouls per 90 and wins 0.00 — an even split. Fouls committed and fouls won are separate markets, each modelled from the player's rate and the opponent faced.
Which player markets does SharpXI model for Dembo Sylla?
Shots on target, total shots, fouls committed, fouls won and to be carded — each as a true probability, de-vigged against the bookmaker's price. Dembo Sylla plays as a midfielder.
Rates shown are raw counts from public match data for context; the model adds shrinkage, opponent and referee factors, and de-vigging before flagging value. 18+ — please gamble responsibly.