Player report
Tomas Delgado
MID · Northfleet · Demo Premier League · 21 years · France
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 threat76
- Chance creation88
- Finishing61
- Defending59
- Availability54
Per 90, percentile ranked
- Goals0.28
- Assists0.28
- Shots1.7
- Shots on target0.4
- Key passes1.0
- Expected goals0.28
- Expected assists0.20
- Tackles0.9
- Interceptions1.1
- Clearances2.5
Strong chance creation midfielder (88th percentile), with strong goal threat (76th). Availability is the headline risk: 45% of available minutes played.
Season
Key strengths
- Chance creation is a clear strength88th percentile among MIDs in this division
- Elite volume of clearances2.52 per 90, 96th percentile
Key risks and limitations
- Availability is the headline risk45% of available minutes; 12 matchweeks missed
Valuation history
Comparable players
| Player | Similarity | Value | Age |
|---|---|---|---|
| Wilson ChevalierRookwood | 83% | €941k | 23 |
| Zeki LindqvistIlkeston Park | 80% | €2.36m | 30 |
| Samir NakamuraBrackenford | 76% | €4.67m | 29 |
| Bertrand VasquezFallowfield | 75% | €505k | 25 |
| Finn OkaforThorneside | 75% | €16.6m | 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
- 53%of 72% ceiling
- Sample
- 963 min · 12 apps
- Last fixture
- 2 Jan
Percentiles are taken against MIDs 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.