Ignatius Ganago
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Ignatius Ganago's performance-implied value at EUR 1.3M-3.0M, above the estimated acquisition range of EUR 0.7M-2.0M. Its 24-month market value projection is EUR 0.8M-2.5M. Context-adjusted goal contributions are 1.25x the positional average in the league (842 minutes, league coefficient 0.88). Confidence is low: 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: not assigned
What drives the score. Not a black box: each component and its level.
Insufficient sample (< 900 league minutes)
| Performance | Average | 39.3th pct among ATT peers (age-neutral) |
| Age | Neutral | 27.4 years |
| Acquisition cost | Very favorable | est. €970k vs market €2.0M |
| Expected appreciation | Very low | -30% over ~2 years (model) |
| Value gap | Large | weak predictor on its own |
| Development | Low | |
| League translation | Big-five league | league coefficient 0.88 |
| Tactical fit | Not evaluated | Requires event/role data not available from the current free source. |
| Risk | Very High | |
| Data confidence | Low |
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 901 evaluated ATT players with 900+ minutes.
Performance (last season, league)
- Minutes
- 842 (28% of available)
- Goals + assists / 90
- 0.43
- Context-adjusted G+A / 90
- 0.63
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 39 (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
- 0.88 (rank 5)
- Team strength (Elo)
- 1304
- Opponent strength
- 1474
- 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)
- €767k – €2.5M
Historical comparables (8): median 2-year value change -18% (IQR -37% to +42%).
Risk profile
Overall: Very High
- ▲Small sample: 842 league minutes last season.
- ⚠No continental-competition minutes last season.
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⚠Projection range wider than for most evaluated players.
- ⚠Played under 40% of available league minutes (injury data unavailable, cause unknown).
- ⓘ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 | FC Nantes | Ligue 1 | ST | 13 | 842 | 28% | 3 | 1 | 0.43 | 0.63 | 1474 | 1304 | 0.88 |
| 2024/25 | FC Nantes | Ligue 1 | ST | 11 | 232 | 8% | 0 | 0 | 0.00 | 0.62 | 1540 | 1357 | 0.88 |
| 2023/24 | FC Nantes | Ligue 1 | ST | 6 | 182 | 6% | 0 | 0 | 0.00 | 0.51 | 1415 | 1309 | 0.87 |
| 2022/23 | FC Nantes | Ligue 1 | ST | 28 | 1519 | 44% | 5 | 3 | 0.47 | 0.51 | 1444 | 1349 | 0.82 |
| 2022/23 | RC Lens | Ligue 1 | ST | 4 | 55 | 2% | 0 | 0 | 0.00 | 0.45 | 1450 | 1626 | 0.82 |
| 2021/22 | RC Lens | Ligue 1 | ST | 28 | 1017 | 30% | 5 | 1 | 0.53 | 0.53 | 1403 | 1492 | 0.86 |
| 2020/21 | RC Lens | Ligue 1 | ST | 24 | 1308 | 38% | 7 | 3 | 0.69 | 0.78 | 1475 | 1371 | 0.75 |
| 2019/20 | OGC Nice | Ligue 1 | ST | 26 | 1231 | 49% | 3 | 1 | 0.29 | 0.39 | 1430 | 1456 | 0.82 |
| 2018/19 | OGC Nice | Ligue 1 | ST | 20 | 1033 | 30% | 2 | 0 | 0.17 | 0.35 | 1472 | 1453 | 0.82 |
| 2017/18 | OGC Nice | Ligue 1 | ST | 6 | 64 | 2% | 1 | 0 | 1.41 | 0.56 | 1494 | 1489 | 0.85 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2022/23 | Uefa Europa League | FC Nantes | 6 | 284 | 1 | 0 | 1483 |
| 2017/18 | Uefa Europa League | OGC Nice | 2 | 30 | 0 | 0 | 1393 |
| 2017/18 | Uefa Champions League Qualifying | OGC Nice | 1 | 13 | 0 | 0 | 1749 |
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 |
|---|---|---|---|---|
| Filip Djuricic Serie A · 2018 | 26 | €1.5M | €2.0M | rose |
| Joel Campbell Serie A · 2019 | 27 | €2.5M | €2.0M | fell |
| Royston Drenthe Premier Liga · 2013 | 26 | €1.8M | €1.5M | flat |
| Romain Del Castillo Ligue 1 · 2022 | 26 | €3.0M | €10.0M | rose |
| Nill De Pauw Ligue 1 · 2017 | 27 | €1.8M | €1.2M | fell |
| Pietro Iemmello Serie A · 2018 | 26 | €2.0M | €3.4M | rose |
| Levan Mchedlidze Serie A · 2017 | 27 | €800k | €400k | fell |
| Hyun-jun Suk Ligue 1 · 2018 | 27 | €3.5M | €1.6M | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 31 Dec 2025 | New England | FC Nantes | Free / loan | €2.0M |
| 31 Jan 2025 | FC Nantes | New England | Free / loan | €1.8M |
| 1 Sept 2022 | Lens | FC Nantes | €4.4M | €5.0M |
| 10 Jul 2020 | Nice | Lens | €6.0M | €3.6M |
| 1 Jul 2018 | OGC Nice B | Nice | Unknown | Data unavailable |
| 11 Jul 2017 | Brasseries | OGC Nice B | Free / loan | 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.