
Rasmus Carstensen
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Rasmus Carstensen's performance-implied value at EUR 0.8M-3.2M, below the estimated acquisition range of EUR 0.8M-2.8M. Its 24-month market value projection is EUR 1.0M-4.0M. Context-adjusted goal contributions are 1.25x the positional average in the league (1225 minutes, league coefficient 0.47). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 77
What drives the score. Not a black box: each component and its level.
| Performance | Average | 37.7th pct among MID peers (age-neutral) |
| Age | Neutral | 25.6 years |
| Acquisition cost | Favorable | est. €1.5M vs market €2.0M |
| Expected appreciation | Neutral | +0% over ~2 years (model) |
| Value gap | Negative | weak predictor on its own |
| Development | Low | |
| League translation | Uncertain | league coefficient 0.47 |
| Tactical fit | Not evaluated | Requires event/role data not available from the current free source. |
| Risk | High | |
| Data confidence | Medium |
Bargain Index = percentile (among all evaluated players) of expected 2-year value relative to estimated cost. See methodology and backtests.
Market value history
Market value ≠ transfer fee ≠ acquisition cost.
Profile vs positional peers
Percentiles among 1163 evaluated MID players with 900+ minutes.
Performance (last season, league)
- Minutes
- 1225 (62% of available)
- Goals + assists / 90
- 0.51
- Context-adjusted G+A / 90
- 0.28
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 38 (Average)
Adjusted = shrunk toward positional baseline for small samples, corrected for team dominance over opponents, expressed relative to positional peers in the same league.
Context
- League strength
- 0.47 (rank 12)
- Team strength (Elo)
- 1441
- Opponent strength
- 1255
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- insufficient
- Breakout probability
- Age > 23
- Resale range (24m)
- €1.0M – €4.0M
Historical comparables (8): median 2-year value change -18% (IQR -50% to +3%).
Risk profile
Overall: High
- ▲Projection range among the widest 10% of evaluated players.
- ⚠Limited sample: 1225 league minutes last season.
- ⚠League level coefficient 0.47 (1.00 = big-five average): output may not translate.
- ⚠No continental-competition minutes last season.
- ⓘInjury history unavailable from current data source.
League translation
What happened to players who moved from this league to the big-five leagues (observed, not a forecast).
- Historical movers
- 23 (MID)
- Relative output kept
- 68%–122%
- Held a regular role (900+ min)
- 65%
- Confidence
- Medium
Output is relative to positional peers in each league. Movers are a selected group (clubs buy players who fit), so treat this as context, not a guarantee.
Season-by-season (domestic league)
Context-adjusted values are model outputs.
| Season | Club | League | Pos | Apps | Min | Min share | G | A | G+A/90 | Adj. G+A/90 | Opp. Elo | Team Elo | League str. |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2025/26 | Aarhus GF | Superliga | RM | 22 | 1225 | 62% | 5 | 2 | 0.51 | 0.28 | 1255 | 1441 | 0.47 |
| 2023/24 | 1.FC Köln | Bundesliga | RB | 23 | 1661 | 54% | 0 | 1 | 0.05 | 0.11 | 1563 | 1382 | 1.01 |
| 2022/23 | Silkeborg IF | Superliga | RB | 3 | 270 | 14% | 0 | 2 | 0.67 | 0.25 | 1315 | 1266 | 0.47 |
| 2022/23 | KRC Genk | Jupiler Pro League | RB | 4 | 47 | 2% | 0 | 1 | 1.91 | 0.13 | 1329 | 1495 | 0.58 |
| 2021/22 | Silkeborg IF | Superliga | RB | 22 | 1980 | 100% | 1 | 4 | 0.23 | 0.19 | 1279 | 1231 | 0.45 |
| 2019/20 | Silkeborg IF | Superliga | RB | 8 | 310 | 13% | 1 | 0 | 0.29 | 0.24 | 1281 | 1098 | 0.41 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Oddset Pokalen | Aarhus GF | 6 | 459 | 0 | 1 | — |
| 2024/25 | Dfb Pokal | 1.FC Köln | 1 | 37 | 0 | 0 | — |
| 2023/24 | Dfb Pokal | 1.FC Köln | 1 | 54 | 0 | 0 | — |
| 2021/22 | Oddset Pokalen | Silkeborg IF | 1 | 90 | 0 | 1 | — |
| 2019/20 | Oddset Pokalen | Silkeborg IF | 3 | 101 | 0 | 0 | — |
Small continental samples are shown for context only and are not over-weighted.
Historical comparables
Most similar profiles 2+ years ago (same position group) and what happened next. Chosen by similarity only — failures included.
| Player (then) | Age | Value then | ~2y later | Outcome |
|---|---|---|---|---|
| Ghayas Zahid Super League 1 · 2020 | 26 | €1.2M | €1.2M | flat |
| Núrio Fortuna Jupiler Pro League · 2022 | 27 | €3.0M | €1.5M | fell |
| Mihajlo Banjac Premier Liga · 2023 | 24 | €2.0M | €1.7M | flat |
| Víctor Vázquez Jupiler Pro League · 2013 | 26 | €3.5M | €4.0M | flat |
| Mees Hoedemakers Eredivisie · 2024 | 26 | €2.0M | €600k | fell |
| Ricardo Mangas Liga Portugal · 2024 | 26 | €4.0M | €2.0M | fell |
| Ilya Samoshnikov Premier Liga · 2024 | 27 | €2.5M | €2.0M | fell |
| Igor Kharatin Premier Liga · 2019 | 24 | €1.0M | €2.2M | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 30 Jun 2026 | Aarhus GF | 1.FC Köln | Free / loan | €2.0M |
| 7 Jul 2025 | 1.FC Köln | Aarhus GF | Free / loan | €2.0M |
| 30 Jun 2025 | Lech Poznan | 1.FC Köln | Free / loan | €2.0M |
| 23 Jan 2025 | 1.FC Köln | Lech Poznan | Free / loan | €1.0M |
| 1 Jul 2024 | Genk | 1.FC Köln | €1.5M | €2.0M |
| 30 Jun 2024 | 1.FC Köln | Genk | Free / loan | €2.0M |
| 4 Aug 2023 | Genk | 1.FC Köln | Free / loan | €1.5M |
| 9 Aug 2022 | Silkeborg IF | Genk | €3.0M | €1.5M |
| 1 Jul 2019 | Silkeborg U19 | Silkeborg IF | Unknown | Data unavailable |
| 1 Jul 2017 | Silkeborg Yth. | Silkeborg U19 | Unknown | Data unavailable |
MoneyballAI identifies statistical opportunities from available data. A player flagged as a potential bargain is not guaranteed to succeed, to transfer, to rise in value, or to generate resale profit. Market values, fees and contracts come from third-party sources; ranges are model estimates with stated confidence.