Player report
Caleb Ibarra
MID · Fallowfield · Demo Premier League · 29 years · Spain
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 threat39
- Chance creation84
- Finishing66
- Defending60
- Availability80
Per 90, percentile ranked
- Goals0.13
- Assists0.25
- Shots1.4
- Shots on target0.4
- Key passes1.1
- Expected goals0.12
- Expected assists0.18
- Tackles1.3
- Interceptions1.1
- Clearances1.8
Strong chance creation midfielder (84th percentile), with above average finishing (66th). Played 67% of available minutes.
Season
Key strengths
- Chance creation is a clear strength84th percentile among MIDs 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 |
|---|---|---|---|
| Goran SalvatoreRookwood | 86% | €10.2m | 28 |
| Yusuf GallagherCalderbrook | 85% | €15.2m | 32 |
| Viktor VasquezKelsford | 83% | €4.22m | 20 |
| Felix IbarraOakhurst | 83% | €8.93m | 32 |
| Emil CastileThorneside | 83% | €3.96m | 19 |
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
- 1438 min · 18 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.