Player report
Hugo Ekstrom
MID · Ilkeston Park · Demo Premier League · 21 years · Morocco
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 threat95
- Chance creation53
- Finishing70
- Defending9
- Availability89
Per 90, percentile ranked
- Goals0.34
- Assists0.06
- Shots2.1
- Shots on target0.7
- Key passes1.0
- Expected goals0.32
- Expected assists0.07
- Tackles0.9
- Interceptions0.6
- Clearances1.4
Elite goal threat midfielder (95th percentile), with above average finishing (70th). Defending is the clear gap at the 9th percentile. Played 73% of available minutes.
Season
Key strengths
- Goal threat is a clear strength95th percentile among MIDs in this division
- Elite volume of shots on target0.69 per 90, 94th percentile
Key risks and limitations
- Defending is a clear weakness9th percentile among MIDs in this division
Valuation history
Comparable players
| Player | Similarity | Value | Age |
|---|---|---|---|
| Hugo EkstromBrackenford | 85% | €15.3m | 24 |
| Rafael EkstromGranthorpe | 84% | €274k | 32 |
| Gabriel ArdalEastmarsh | 80% | €5.16m | 22 |
| Goran ArdalLangmere | 80% | €5.00m | 21 |
| Lucas OkaforBrackenford | 79% | €12.1m | 21 |
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
- 57%of 72% ceiling
- Sample
- 1574 min · 19 apps
- Last fixture
- 23 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.