Player report
Viktor Ives
FWD · Ilkeston Park · Demo Premier League · 30 years · Senegal
Valuation
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.
Performance profile
Player DNA
- Goal threat1
- Chance creation55
- Finishing39
- Defending42
- Availability11
Per 90, percentile ranked
- Goals0.00
- Assists0.17
- Shots1.9
- Shots on target0.2
- Key passes1.4
- Expected goals0.02
- Expected assists0.17
- Tackles0.5
- Interceptions0.2
- Clearances0.5
Above average chance creation forward (55th percentile). Goal threat is the clear gap at the 1th percentile. Availability is the headline risk: 24% of available minutes played.
Season
Key strengths
- Elite volume of yellow cards0.00 per 90, 90th percentile
Key risks and limitations
- Goal threat is a clear weakness1th percentile among FWDs in this division
- Availability is the headline risk24% of available minutes; 16 matchweeks missed
- Small sample515 minutes across 8 appearances. Percentiles are published but thinly evidenced.
- Low model confidence41% against a ceiling of 72%. The valuation range is correspondingly wide.
Valuation history
Comparable players
| Player | Similarity | Value | Age |
|---|---|---|---|
| Jonas LindqvistMarsden Cross | 83% | €2.43m | 23 |
| Omar UgarteKelsford | 79% | €9.46m | 30 |
| Yusuf ChevalierJarrowgate | 77% | €5.38m | 18 |
| Elias AbbottQuarrydale | 76% | €12.0m | 33 |
| Bertrand CastileKelsford | 75% | €56.0m | 19 |
Comparable transfers
Not available. The feed carries no observed transfer fees and no contract expiry dates, so there is nothing to build a comparable-fee distribution from.
This section is left in rather than removed, because its absence is itself a finding: any fee inference in this report would be unsupported.
Data confidence
- Model confidence
- 41%of 72% ceiling
- Sample
- 515 min · 8 apps
- Last fixture
- 9 Jan
Percentiles are taken against FWDs in the Demo Premier League with 270 or more minutes. The model holds no contract, injury, wage or transfer data, and no progressive passing, carrying or pressing metrics.
Methodology
Weekly output is weighted by position, discounted by minutes as a credibility multiplier, and compared against an exponentially weighted average of the player’s own previous weeks — so the model moves on surprise rather than output. That becomes a percentile within the position group, then adjusted for age, league strength, position and availability.
An estimated value is not a transfer fee. Full methodology.