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Bundesliga 26/27
BA

Bakery Jatta

Wing-back 80% of 15 recent starts Hamburger SVBundesliga 26/27

Next match
Hamburger SV at TSG Hoffenheim›
Sat 10 OctReferee Harm Osmers

Shot map Foul map

Last games
max 20 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 Bundesliga wing-back, 25/26, 863 appearances

Bet line
Odds
Bookmaker
MarketHit rateModel
Shots on target0.37 per 90
20%
2 of 101.2×
3.50bet365Edge
Total shots1.11 per 90
40%
4 of 101.0×
1.67bet365Edge
Fouls won0.37 per 90
20%
2 of 100.4×
1.29bet365Edge
Fouls committed1.48 per 90
50%
5 of 101.0×
1.40bet365Edge
Tackles1.48 per 90
50%
5 of 100.8×
0%
0 of 10
Cards0.18 per 90
10%
1 of 100.7×
4.00bet365Edge
Goals0.18 per 90
10%
1 of 102.0×
form only
Assists0.18 per 90
10%
1 of 101.1×
form only
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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In 25/26, Bakery Jatta has hit 1+ shot on target in 27% of 15 Bundesliga appearances (4 of 15), 1+ total shot in 53%, 1+ foul committed in 60%, 1+ foul won in 33%, and been booked in 7% (1 of 15). These are raw hit rates from completed matches, not odds.

last 10

Comparable wing-backs

The closest 5 profiles to Bakery Jatta in Bundesliga, 25/26 — drawn from 34 wing-backs with 450 or more minutes. A reference for the rates above, not a forecast.

PlayerAppsShots/90Fouls/90
Bakery JattaHamburger SV 151.08 1.27
William MikelbrencisHamburger SV 260.77 1.15
Derrick Köhn1. FC Union Berlin 291.32 1.55
Louis OppieFC St. Pauli 230.84 0.84
ArthurSV Werder Bremen 200.80 1.51
Daniel SvenssonBorussia Dortmund 330.44 1.03
These 5, combined 0.81 1.19

Recent matches

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

MatchMinSoTShots FoulsWonTckCards
1. FC Köln19 Sep 13 0 0 0 0 0 0
@ RB Leipzig13 Sep 1 0 0 0 0 0 0
@ Borussia Dortmund29 Aug 82 0 0 2 1 1 0
SC Freiburg10 May 65 1 1 2 0 2 0
@ Eintracht Frankfurt2 May 68 0 1 0 0 2 0
TSG Hoffenheim25 Apr 75 1 3 0 0 0 0
@ SV Werder Bremen18 Apr 15 0 0 1 0 1 1
Bayer 04 Leverkusen4 Mar 29 0 0 0 0 0 0
@ 1. FSV Mainz 0520 Feb 65 0 0 2 1 0 0
1. FC Union Berlin14 Feb 74 0 1 1 0 2 0

Frequently asked

How often does Bakery Jatta have a shot on target?

In 25/26, Bakery Jatta has hit 1+ shot on target in 27% of 15 Bundesliga appearances (4 of 15). 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 Bakery Jatta average?

Across 15 Bundesliga appearances in 25/26, Bakery Jatta is averaging 0.39 shots on target and 1.08 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 Bakery Jatta get booked?

Bakery Jatta is averaging 0.10 cards per 90 this season. 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 Bakery Jatta commit or win more fouls?

This season Bakery Jatta commits 1.27 fouls per 90 and wins 0.49 — 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 Bakery Jatta?

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. Bakery Jatta plays as a midfielder.

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.