Player report
Idris Grimaldi
GK · Kelsford · Demo Premier League · 23 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
- Shot stopping0
- Defending0
- Chance creation31
- Availability0
Per 90, percentile ranked
Not enough minutes to rank against positional peers yet.
Well-rounded goalkeeper without a standout axis in this data — no category clears the 31th percentile among positional peers. Availability is the headline risk: 4% of available minutes played.
Season
Key strengths
- No standout axis in this dataNothing clears the 80th percentile among positional peers on the metrics we carry.
Key risks and limitations
- Shot stopping is a clear weakness0th percentile among GKs in this division
- Defending is a clear weakness0th percentile among GKs in this division
- Availability is the headline risk4% of available minutes; 23 matchweeks missed
- Too few minutes to rank against peers90 minutes, below the 270-minute floor. Rates are shown but carry no percentile.
- Low model confidence20% against a ceiling of 72%. The valuation range is correspondingly wide.
Valuation history
Comparable players
| Player | Similarity | Value | Age |
|---|---|---|---|
| Finn GrimaldiAshcombe | 0% | €2.05m | 35 |
| Omar ZielinskiAshcombe | 0% | €772k | 27 |
| Adam HaugenBrackenford | 0% | €12.1m | 22 |
| Viktor FarrowBrackenford | 0% | €1.69m | 26 |
| Finn GrimaldiCalderbrook | 0% | €9.03m | 27 |
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
- 20%of 72% ceiling
- Sample
- 90 min · 1 apps
- Last fixture
- 12 Dec
Percentiles are taken against GKs 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.