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Zeki Zielinski
Estimated market value
€604k
- Model range
- €286k – €922k
- Confidence
- 37%
- Season change
- −3.3%
Movement
- Last matchweek
- −1.5%
- Last 4 matchweeks
- −1.5%
- Season to date
- −3.3%
Reported in matchweeks, not days — football data arrives by fixture round.
Model estimate, uncalibrated. Values are model estimates on an uncalibrated scale. They are not predictions of a transfer fee and have not been validated against observed fees. Model 0.3.0-uncalibrated.
Valuation drivers
What moves this away from the €4.00m base value
- Performance−€1.54m
- Age−€357k
- League€0
- Position−€590k
- Availability−€909k
Not in this model
- ContractNo contract expiry data in the feed
- Market comparablesNo observed transfer fees in the feed
Availability
Read any valuation against this first
5 appearances, 5 starts, 19 matchweeks missed.
A player who is not on the pitch drifts down the index without his performance level falling with it, and availability is a direct discount on the valuation above. An unavailable player is not the same thing as a cheap one.
Scenarios
What the model would say under a different set of facts
- As measured€604kbenchmark
- Performance +10%€665k+€60k · +10.0%
- Performance +20%€725k+€121k · +20.0%
- Performance −10%€544k−€60k · −10.0%
- One year older€516k−€88k · −14.6%
- Fully available€1.00m+€398k · +65.9%
- Moves to a stronger divisionAlready in the strongest division we rate—
These are counterfactuals, not forecasts. Each row is the same model run with one input changed — it says nothing about whether that change is likely. The benchmark is this player’s measured estimate of €604k.
Player DNA
Percentile against GKs in the Demo Premier League
- Shot stopping76
- Defending89
- Chance creation79
- Availability21
Strong defending goalkeeper (89th percentile), with strong chance creation (79th). Availability is the headline risk: 21% of available minutes played.
Generated from the metrics above, not from scouting notes. Ball progression and pressing are absent because the feed carries no progressive passes, carries or pressures.
Valuation history
The performance index the valuation is built on, by matchweek
Profile
Per-90 percentiles against GKs
Percentiles as a table
| Metric | Zeki Zielinski |
|---|---|
| Saves | 1st |
| Goals conceded | 89th |
| Clearances | 89th |
| Key passes | 43rd |
| Assists | 43rd |
| Expected assists | 79th |
Per 90
Rate and percentile among GKs with 270+ minutes
- Goals0.00
- Assists0.00
- Shots0.0
- Shots on target0.0
- Key passes0.0
- Expected goals0.00
- Expected assists0.01
- Tackles0.0
- Interceptions0.0
- Clearances1.4
- Saves2.4
- Goals conceded0.6
Finishing
Goals against the quality of the chances they came from, running total
Scoring 0.01 goals fewer than his chances were worth — the chances are being created.
Comparable players
Closest percentile profiles among the same position
| Player | Similarity | Value | Age | Alike on |
|---|---|---|---|---|
| Kai BrennanNorthfleet | 94% | €579k | 19 | goals, assists |
| Viktor BarrosGranthorpe | 89% | €2.25m | 20 | goals, assists |
| Finn GrimaldiCalderbrook | 81% | €9.03m | 27 | goals, assists |
| Finn JokinenQuarrydale | 80% | €575k | 22 | goals, assists |
| Andre SalvatoreHollinwell | 78% | €1.80m | 29 | assists, shots |
| Rafael JokinenIlkeston Park | 76% | €15.6m | 20 | goals, assists |
Match log
5 appearances this season
| MW | Date | Opponent | Min | Sv | GC | Clr | KP | A | xA |
|---|---|---|---|---|---|---|---|---|---|
| 21 | 2 Jan | at EastmarshD 1–1 | 90 | 4.0 | 1.0 | 2.0 | 0.0 | 0 | 0.00 |
| 15 | 21 Nov | v LangmereD 0–0 | 90 | 0.0 | 0.0 | 2.0 | 0.0 | 0 | 0.01 |
| 14 | 14 Nov | v JarrowgateW 1–0 | 90 | 3.0 | 0.0 | 0.0 | 0.0 | 0 | 0.01 |
| 8 | 3 Oct | v QuarrydaleL 0–2 | 90 | 5.0 | 2.0 | 1.0 | 0.0 | 0 | 0.01 |
| 6 | 19 Sept | v Marsden CrossW 4–0 | 90 | 0.0 | 0.0 | 2.0 | 0.0 | 0 | 0.01 |
Data
- Last fixture
- 2 Jan
- Matchweeks covered
- 24
- Model
- 0.3.0-uncalibrated
Comparable transfers and contract situation are not shown, because the feed carries no transfer fees and no contract expiry dates. See methodology for what the model can and cannot see.