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GKDemo Premier LeaguePortugal26 years

Viktor Farrow

Brackenford · #2 · FARR

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Estimated market value

€1.69m

Model range
€911k – €2.46m
Confidence
49%
Season change
−2.2%

Movement

Last matchweek
−1.5%
Last 4 matchweeks
−5.4%
Season to date
−2.2%

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−€638k
  • Age+€304k
  • League€0
  • Position−€880k
  • Availability−€1.10m

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

Available minutes played29% · 630 of 2160

7 appearances, 7 starts, 17 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€1.69mbenchmark
  • Performance +10%€1.86m+€169k · +10.0%
  • Performance +20%€2.03m+€338k · +20.0%
  • Performance −10%€1.52m−€169k · −10.0%
  • One year older€1.51m−€181k · −10.7%
  • Fully available€2.54m+€854k · +50.6%
  • 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 €1.69m.

Player DNA

Percentile against GKs in the Demo Premier League

  • Shot stopping54
  • Defending56
  • Chance creation31
  • Availability30

Above average defending goalkeeper (56th percentile). Availability is the headline risk: 29% 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

Viktor Farrow index by matchweek

Profile

Per-90 percentiles against GKs

Percentiles as a table
MetricViktor Farrow
Saves79th
Goals conceded39th
Clearances56th
Key passes43rd
Assists43rd
Expected assists31st

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 assists0.00
  • Tackles0.0
  • Interceptions0.0
  • Clearances1.0
  • Saves4.3
  • Goals conceded1.3

Finishing

Goals against the quality of the chances they came from, running total

Viktor Farrow cumulative goals minus expected goals
−0.1−0.10.0+0.1+0.1Matchweek

Scoring 0.00 goals more than his chances were worth. Finishing runs like this historically revert.

Comparable players

Closest percentile profiles among the same position

Compare →
PlayerSimilarityValueAgeAlike on
Wilson MoreauMarsden Cross94%€19.1m24goals, assists
Viktor GrimaldiMarsden Cross94%€3.70m21goals, assists
Pedro ZielinskiKelsford93%€22.7m18goals, assists
Rafael FontaineGranthorpe92%€6.53m24goals, assists
Pedro IbarraJarrowgate92%€2.51m21goals, assists
Adam HaugenBrackenford91%€12.1m22goals, assists

Match log

7 appearances this season

Match-by-match statistics, most recent first
MWDateOpponentMinSvGCClrKPAxA
212 Janv AshcombeW 21903.01.01.00.000.00
1919 Decat QuarrydaleW 20904.00.01.00.000.00
1628 Novat KelsfordL 12905.02.01.00.000.00
1521 Novat Ilkeston ParkD 11904.01.01.00.000.00
1414 Novat GranthorpeW 10904.00.01.00.000.00
1231 Octat CalderbrookL 24905.04.01.00.000.00
45 Septat FallowfieldD 11905.01.01.00.000.00

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.