Player report
Dmitri Haugen
MID · Deepdale Vale · Demo Premier League · 34 years · Japan
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 threat80
- Chance creation10
- Finishing32
- Defending91
- Availability52
Per 90, percentile ranked
- Goals0.29
- Assists0.00
- Shots1.5
- Shots on target0.5
- Key passes0.6
- Expected goals0.29
- Expected assists0.02
- Tackles1.2
- Interceptions1.7
- Clearances2.6
Elite defending midfielder (91th percentile), with strong goal threat (80th). Chance creation is the clear gap at the 10th percentile. Availability is the headline risk: 44% of available minutes played.
Season
Key strengths
- Defending is a clear strength91th percentile among MIDs in this division
- Goal threat is a clear strength80th percentile among MIDs in this division
- Elite volume of interceptions1.72 per 90, 99th percentile
Key risks and limitations
- Chance creation is a clear weakness10th percentile among MIDs in this division
- Availability is the headline risk44% of available minutes; 12 matchweeks missed
Valuation history
Comparable players
| Player | Similarity | Value | Age |
|---|---|---|---|
| Viktor FontaineOakhurst | 86% | €27.1m | 18 |
| Rafael YilmazKelsford | 77% | €47.1m | 23 |
| Hugo OkaforThorneside | 75% | €7.56m | 31 |
| Wilson ChevalierLangmere | 74% | €13.7m | 23 |
| Pedro EriksenOakhurst | 73% | €10.8m | 28 |
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
- 56%of 72% ceiling
- Sample
- 941 min · 12 apps
- Last fixture
- 9 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.