Player report
Hugo Castile
FWD · Pendlebury · Demo Premier League · 28 years · Croatia
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 threat40
- Chance creation45
- Finishing68
- Defending18
- Availability57
Per 90, percentile ranked
- Goals0.22
- Assists0.07
- Shots2.5
- Shots on target0.7
- Key passes1.6
- Expected goals0.19
- Expected assists0.10
- Tackles0.1
- Interceptions0.0
- Clearances0.1
Above average finishing forward (68th percentile). Defending is the clear gap at the 18th percentile. Played 56% of available minutes.
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
- Defending is a clear weakness18th percentile among FWDs in this division
Valuation history
Comparable players
| Player | Similarity | Value | Age |
|---|---|---|---|
| Pedro HalvorsenRookwood | 86% | €3.28m | 26 |
| Mateo GallagherGranthorpe | 82% | €2.45m | 19 |
| Goran ArdalBrackenford | 79% | €59.4m | 20 |
| Omar UgarteKelsford | 79% | €9.46m | 30 |
| Samir WhitlockDeepdale Vale | 78% | €3.65m | 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
- 69%of 72% ceiling
- Sample
- 1208 min · 15 apps
- Last fixture
- 23 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.