Player report
Mateo Vasquez
FWD · Ashcombe · Demo Premier League · 27 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 threat32
- Chance creation14
- Finishing56
- Defending98
- Availability94
Per 90, percentile ranked
- Goals0.15
- Assists0.00
- Shots2.7
- Shots on target0.6
- Key passes1.4
- Expected goals0.14
- Expected assists0.04
- Tackles0.9
- Interceptions0.6
- Clearances1.0
Elite defending forward (98th percentile), with above average finishing (56th). Chance creation is the clear gap at the 14th percentile.
Season
Key strengths
- Defending is a clear strength98th percentile among FWDs in this division
- Elite volume of tackles0.89 per 90, 96th percentile
Key risks and limitations
- Chance creation is a clear weakness14th percentile among FWDs in this division
Valuation history
Comparable players
| Player | Similarity | Value | Age |
|---|---|---|---|
| Diogo KovacBrackenford | 86% | €11.3m | 22 |
| Diogo KovacGranthorpe | 82% | €23.8m | 27 |
| Caleb FontaineHollinwell | 82% | €2.62m | 19 |
| Andre IbarraJarrowgate | 81% | €1.24m | 26 |
| Wilson ArdalDeepdale Vale | 79% | €4.98m | 32 |
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
- 72%of 72% ceiling
- Sample
- 1815 min · 22 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.