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Ligue 1 25/26
BR

Bryan Okoh

Centre-back 100% of 12 recent starts AuxerreLigue 1 25/26

Next match
Auxerre at Stade Rennais›
Sun 11 OctReferee Willy Delajod

Shot map Foul map

Last games
max 13 on record
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 Ligue 1 centre-back, 25/26, 1,295 appearances

Bet line
MarketHit rateModel
Shots on target0.33 per 90
20%
2 of 101.8×
Total shots0.66 per 90
40%
4 of 101.3×
Fouls won0.55 per 90
30%
3 of 100.7×
Fouls committed1.43 per 90
60%
6 of 101.1×
Tackles1.10 per 90
60%
6 of 100.9×
10%
1 of 10
Cards0.22 per 90
20%
2 of 101.2×
Goals0.33 per 90
20%
2 of 107.4×
form only
Assists0.00 per 90
0%
0 of 10
form only
No bookmaker prices for this fixture yet. Player markets are usually priced closer to kickoff, and not every fixture carries every market. The hit rates and match-up above are complete either way.
Hit rate, per-90 and the market price are free. Switch the bet line above — each carries its own price where the bookmaker offers one. What’s paid is the model’s edge: whether that price is wrong. Rare tails the model can’t beat, like 3+ on target, stay hit-rate-only.

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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 Ligue 1 games, Bryan Okoh has hit 1+ shot on target in 20% (2 of 10), 1+ total shot in 40%, 1+ foul committed in 60%, 1+ foul won in 30%, and been booked in 20% (2 of 10). These are raw hit rates from completed matches, not odds.

last 10

Comparable centre-backs

The closest 5 profiles to Bryan Okoh in Ligue 1, 25/26 — drawn from 57 centre-backs with 450 or more minutes. A reference for the rates above, not a forecast.

PlayerAppsShots/90Fouls/90
Bryan OkohAuxerre 130.71 1.16
Chancel MbembaLille 130.66 0.94
Brendan ChardonnetStade Brestois 290.42 0.99
Francisco SierraltaAuxerre 100.73 0.84
DanteNice 130.77 1.06
Gautier LlorisStade Brestois 290.41 1.01
These 5, combined 0.53 0.98

Recent matches

The last 10 games Bryan Okoh featured in — minutes and the counts that settle these markets.

MatchMinSoTShots FoulsWonTckCards
Nice10 May 13 0 0 0 0 0 0
Angers3 May 90 0 0 1 0 2 1
@ Olympique Lyonnais25 Apr 90 1 1 1 2 0 0
@ AS Monaco19 Apr 90 0 1 1 2 0 0
Nantes11 Apr 90 0 0 3 0 2 0
@ Le Havre5 Apr 90 0 1 0 1 1 0
Stade Brestois21 Mar 90 2 3 0 0 0 0
@ Olympique de Marseille13 Mar 88 0 0 6 0 2 1
RC Strasbourg7 Mar 90 0 0 1 0 2 0
@ Lorient1 Mar 90 0 0 0 0 1 0

Frequently asked

How often does Bryan Okoh have a shot on target?

Over the last 10 Ligue 1 games, Bryan Okoh has hit 1+ shot on target in 20% (2 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 Bryan Okoh average?

Across the last 10 Ligue 1 games, Bryan Okoh is averaging 0.33 shots on target and 0.66 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 Bryan Okoh get booked?

Bryan Okoh is averaging 0.22 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 Bryan Okoh commit or win more fouls?

Over the last 10 games Bryan Okoh commits 1.43 fouls per 90 and wins 0.55 — committing more than winning. 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 Bryan Okoh?

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. Bryan Okoh 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.