Jordan Zemura
Full-back 65% of 17 recent starts WatfordPremier League 22/23
Also in: Serie AChampionship
What a window counts
Hit rates count the most recent completed games, newest first — reaching back into earlier seasons when the current one is short, and into games for a previous club, including in another league we cover.
All markets last 10 games
Compared with a Premier League full-back, 25/26, 1,736 appearances
Five selections from the player report, free in your inbox
Picked from 20 selections across 10 matches on this week’s slate, each with its record and the market price.
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Over the last 10 Premier League games, Jordan Zemura has hit 1+ shot on target in 10% (1 of 10), 1+ total shot in 20%, 1+ foul committed in 60%, 1+ foul won in 70%, and been booked in 0% (0 of 10). These are raw hit rates from completed matches, not odds.
Comparable wing-backs
Jordan Zemura has no Premier League record yet, so this profile is drawn from the Championship 26/27 season. These are the closest 5 Premier League wing-backs by standing within their own league — not by matching output, which does not carry across leagues. A reference for the rates above, not a forecast.
| Player | Apps | Shots/90 | Fouls/90 |
|---|---|---|---|
| Jordan ZemuraWatfordChampionship | 7 | 0.60 | 1.00 |
| Patrick DorguManchester United | 26 | 1.60 | 1.42 |
| Gabriel GudmundssonLeeds United | 32 | 0.61 | 1.06 |
| Noussair MazraouiManchester United | 20 | 0.44 | 1.06 |
| James JustinLeeds United | 29 | 1.13 | 0.61 |
| Hugo BuenoWolverhampton | 35 | 0.61 | 0.68 |
| These 5, combined | 0.85 | 0.93 |
No close match — the nearest profile sits well outside the usual range, so read these five as the closest available rather than as like-for-like.
Recent matches
The last 10 games Jordan Zemura featured in — minutes and the counts that settle these markets.
| Match | Min | SoT | Shots | Fouls | Won | Tck | Cards |
|---|---|---|---|---|---|---|---|
| @ Arsenal4 Mar | 64 | 0 | 0 | 0 | 0 | 6 | 0 |
| Man City25 Feb | 90 | 0 | 0 | 2 | 1 | 0 | 0 |
| @ Wolves18 Feb | 85 | 0 | 0 | 1 | 2 | 1 | 0 |
| Newcastle11 Feb | 90 | 0 | 0 | 1 | 0 | 1 | 0 |
| @ Brighton4 Feb | 90 | 0 | 2 | 0 | 1 | 4 | 0 |
| Nottingham Forest21 Jan | 90 | 1 | 2 | 0 | 2 | 2 | 0 |
| Crystal Palace31 Dec | 70 | 0 | 0 | 1 | 0 | 0 | 0 |
| @ Chelsea27 Dec | 90 | 0 | 0 | 1 | 1 | 4 | 0 |
| Everton12 Nov | 90 | 0 | 0 | 0 | 1 | 2 | 0 |
| Tottenham29 Oct | 90 | 0 | 0 | 2 | 1 | 1 | 0 |
Raw counts from every match on record, across 1 current Premier League official — the model applies each official's overall card tendency, not this split. All Premier League referees
Frequently asked
How often does Jordan Zemura have a shot on target?
Over the last 10 Premier League games, Jordan Zemura has hit 1+ shot on target in 10% (1 of 10). 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 compares it with the bookmaker's price as offered.
How many shots on target does Jordan Zemura average?
Across the last 10 Premier League games, Jordan Zemura is averaging 0.11 shots on target and 0.42 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 Jordan Zemura get booked?
Jordan Zemura is averaging 0.00 cards per 90 over the last 10 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 Jordan Zemura commit or win more fouls?
Over the last 10 games Jordan Zemura commits 0.85 fouls per 90 and wins 0.95 — winning more than committing. 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 Jordan Zemura?
Shots on target, total shots, fouls committed, fouls won and to be carded — each as a true probability, compared with the bookmaker's price as offered. Jordan Zemura plays as a defender.
Rates shown are raw counts from public match data for context; the model adds shrinkage, opponent and referee factors before flagging value, and compares against the bookmaker's price as offered — player markets are priced one side only, so that price still carries the bookmaker's margin. 18+ — please gamble responsibly.