
Martin Frese
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Martin Frese's performance-implied value at EUR 1.7M-5.2M, above the estimated acquisition range of EUR 0.8M-2.0M. Its 24-month market value projection is EUR 1.1M-2.7M. Context-adjusted goal contributions are 0.90x the positional average in the league (2413 minutes, league coefficient 0.93). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Acquisition note: Final year of contract: selling club's leverage is reduced.
Bargain Index: 83
What drives the score. Not a black box: each component and its level.
| Performance | Average | 49.5th pct among MID peers (age-neutral) |
| Age | Unfavorable | 28.5 years |
| Acquisition cost | Very favorable | est. €1.0M vs market €2.5M |
| Expected appreciation | Very low | -30% over ~2 years (model) |
| Value gap | Very large | weak predictor on its own |
| Development | Low | |
| League translation | Big-five league | league coefficient 0.93 |
| Tactical fit | Not evaluated | Requires event/role data not available from the current free source. |
| Risk | Low | |
| 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
- 2413 (71% of available)
- Goals + assists / 90
- 0.07
- Context-adjusted G+A / 90
- 0.20
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 50 (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
- 0.93 (rank 4)
- Team strength (Elo)
- 1269
- Opponent strength
- 1518
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- improving
- Breakout probability
- Age > 23
- Resale range (24m)
- €1.1M – €2.7M
Trajectory drivers: minutes share up 55 pts; team strength down (-97 Elo); role change LB -> LM; relative output up 40% vs positional peers.
Historical comparables (8): median 2-year value change -28% (IQR -38% to +5%).
Risk profile
Overall: Low
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⓘ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).
Already playing in a big-five league.
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 | Hellas Verona | Serie A | LM | 31 | 2413 | 71% | 2 | 0 | 0.07 | 0.20 | 1518 | 1269 | 0.93 |
| 2024/25 | Hellas Verona | Serie A | LB | 11 | 544 | 16% | 0 | 0 | 0.00 | 0.09 | 1515 | 1366 | 0.99 |
| 2023/24 | FC Nordsjaelland | Superliga | LB | 21 | 1779 | 90% | 4 | 2 | 0.30 | 0.16 | 1279 | 1444 | 0.48 |
| 2022/23 | FC Nordsjaelland | Superliga | LB | 20 | 1682 | 85% | 0 | 2 | 0.11 | 0.10 | 1303 | 1352 | 0.47 |
| 2021/22 | FC Nordsjaelland | Superliga | LM | 21 | 1370 | 69% | 1 | 2 | 0.20 | 0.33 | 1267 | 1231 | 0.45 |
| 2020/21 | FC Nordsjaelland | Superliga | LB | 9 | 708 | 36% | 2 | 1 | 0.38 | 0.19 | 1291 | 1308 | 0.43 |
| 2019/20 | FC Nordsjaelland | Superliga | LB | 2 | 18 | 1% | 0 | 0 | 0.00 | 0.09 | 1228 | 1329 | 0.41 |
| 2018/19 | FC Nordsjaelland | Superliga | LB | 2 | 23 | 1% | 0 | 0 | 0.00 | 0.11 | 1404 | 1323 | 0.44 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Italy Cup | Hellas Verona | 1 | 90 | 0 | 0 | — |
| 2023/24 | Oddset Pokalen | FC Nordsjaelland | 5 | 412 | 1 | 0 | — |
| 2023/24 | Uefa Conference League Qualifying | FC Nordsjaelland | 4 | 360 | 1 | 0 | 1440 |
| 2022/23 | Oddset Pokalen | FC Nordsjaelland | 2 | 168 | 1 | 1 | — |
| 2021/22 | Oddset Pokalen | FC Nordsjaelland | 2 | 149 | 0 | 0 | — |
| 2018/19 | Oddset Pokalen | FC Nordsjaelland | 1 | 29 | 0 | 0 | — |
| 2018/19 | Uefa Europa League Qualifying | FC Nordsjaelland | 1 | 19 | 0 | 0 | 1259 |
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 |
|---|---|---|---|---|
| Dalbert Serie A · 2022 | 29 | €2.5M | €1.0M | fell |
| Darko Lazović Serie A · 2017 | 27 | €2.5M | €3.0M | rose |
| Gaël Kakuta Ligue 1 · 2020 | 29 | €2.8M | €7.0M | rose |
| Fabio Depaoli Serie A · 2023 | 26 | €3.0M | €3.0M | flat |
| Filip Djuricic Serie A · 2023 | 31 | €1.8M | €1.3M | fell |
| Alberto Grassi Serie A · 2022 | 27 | €2.5M | €1.8M | fell |
| Andrea Poli Serie A · 2018 | 29 | €4.0M | €2.4M | fell |
| Kike Pérez Laliga · 2023 | 26 | €4.5M | €2.8M | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 10 Jul 2024 | Nordsjaelland | Hellas Verona | Free / loan | €2.0M |
| 1 Jul 2017 | Nordsjaell. U19 | Nordsjaelland | Unknown | €100k |
| 1 Jul 2015 | FCN Youth | Nordsjaell. U19 | Unknown | Data unavailable |
| 1 Jul 2013 | BK Frem U19 | FCN Youth | 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.