Player report
Bruno Okafor
GK · Rookwood · Demo Premier League · 18 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
- Shot stopping87
- Defending41
- Chance creation31
- Availability64
Per 90, percentile ranked
- Goals0.00
- Assists0.00
- Shots0.0
- Shots on target0.0
- Key passes0.0
- Expected goals0.00
- Expected assists0.00
- Tackles0.0
- Interceptions0.0
- Clearances0.9
- Saves3.3
- Goals conceded0.6
Strong shot stopping goalkeeper (87th percentile). Played 79% of available minutes.
Season
Key strengths
- Shot stopping is a clear strength87th percentile among GKs in this division
Key risks and limitations
- No statistical red flags in the data we holdThis is not the same as no risk: we hold no contract, injury, wage or transfer data, and nobody has watched the player.
Valuation history
Comparable players
| Player | Similarity | Value | Age |
|---|---|---|---|
| Jonas ChevalierQuarrydale | 92% | €18.4m | 19 |
| Tomas JokinenOakhurst | 91% | €346k | 35 |
| Rafael ToureenEastmarsh | 89% | €17.2m | 20 |
| Zeki RasmussenIlkeston Park | 87% | €834k | 23 |
| Kai ChevalierOakhurst | 87% | €6.97m | 33 |
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
- 63%of 72% ceiling
- Sample
- 1710 min · 19 apps
- Last fixture
- 23 Jan
Percentiles are taken against GKs 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.