
Lucas Gourna-Douath
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Lucas Gourna-Douath's performance-implied value at EUR 2.4M-8.5M, above the estimated acquisition range of EUR 2.5M-6.1M. Its 24-month market value projection is EUR 2.7M-9.3M. Context-adjusted goal contributions are 0.57x the positional average in the league (1276 minutes, league coefficient 0.88). 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: 90
What drives the score. Not a black box: each component and its level.
| Performance | Average | 52.8th pct among MID peers (age-neutral) |
| Age | Favorable | 22.9 years |
| Acquisition cost | Very favorable | est. €3.3M vs market €6.0M |
| Expected appreciation | Low | -11% over ~2 years (model) |
| Value gap | Large | weak predictor on its own |
| Development | Moderate | breakout probability 15% |
| 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 | Moderate | |
| 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
- 1276 (42% of available)
- Goals + assists / 90
- 0.00
- Context-adjusted G+A / 90
- 0.07
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 53 (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)
- 1361
- Opponent strength
- 1477
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Moderate
- Trajectory
- insufficient
- Breakout probability
- 15%
- Resale range (24m)
- €2.7M – €9.3M
Historical comparables (8): median 2-year value change -28% (IQR -48% to +109%).
Risk profile
Overall: Moderate
- ⚠Limited sample: 1276 league minutes last season.
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⚠Projection range wider than for most evaluated players.
- ⓘ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 | Le Havre AC | Ligue 1 | DM | 15 | 1276 | 42% | 0 | 0 | 0.00 | 0.07 | 1477 | 1361 | 0.88 |
| 2024/25 | Associazione Sportiva Roma | Serie A | CM | 6 | 227 | 7% | 0 | 0 | 0.00 | 0.12 | 1424 | 1668 | 0.99 |
| 2021/22 | AS Saint-Étienne | Ligue 1 | DM | 31 | 1806 | 53% | 1 | 0 | 0.05 | 0.09 | 1422 | 1321 | 0.86 |
| 2020/21 | AS Saint-Étienne | Ligue 1 | DM | 30 | 1316 | 38% | 0 | 0 | 0.00 | 0.06 | 1452 | 1371 | 0.75 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Uefa Europa League | Fußballclub Red Bull Salzburg | 1 | 1 | 0 | 0 | 1532 |
| 2024/25 | Uefa Champions League | Fußballclub Red Bull Salzburg | 6 | 301 | 0 | 0 | 1617 |
| 2024/25 | Uefa Champions League Qualifying | Fußballclub Red Bull Salzburg | 4 | 199 | 0 | 0 | 1480 |
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 |
|---|---|---|---|---|
| Oussama Targhalline Ligue 1 · 2024 | 22 | €2.5M | €16.0M | rose |
| Nicolás Domínguez Serie A · 2021 | 23 | €10.0M | €17.0M | rose |
| Máximo Perrone Laliga · 2024 | 21 | €9.0M | €35.0M | rose |
| Zaydou Youssouf Ligue 1 · 2020 | 21 | €7.2M | €4.0M | fell |
| Ronaldo Vieira Serie A · 2020 | 22 | €6.3M | €3.5M | fell |
| Festy Ebosele Serie A · 2024 | 22 | €6.0M | €2.5M | fell |
| Arne Maier Bundesliga · 2021 | 22 | €7.0M | €6.5M | flat |
| Manolo Portanova Serie A · 2022 | 22 | €2.5M | €400k | fell |
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 | Le Havre AC | Salzburg | Free / loan | €6.0M |
| 16 Jan 2026 | Salzburg | Le Havre AC | Free / loan | €4.0M |
| 30 Jun 2025 | Roma | Salzburg | Free / loan | €8.0M |
| 3 Feb 2025 | Salzburg | Roma | Free / loan | €8.0M |
| 13 Jul 2022 | Saint-Étienne | Salzburg | €13.0M | €10.0M |
| 1 Jul 2020 | Saint-Étienne B | Saint-Étienne | Unknown | Data unavailable |
| 1 Jan 2020 | St-Étienne U19 | Saint-Étienne B | Unknown | Data unavailable |
| 1 Jul 2019 | St-Étienne U17 | St-Étienne U19 | Unknown | Data unavailable |
| 6 Aug 2018 | US Torcy Yth. | St-Étienne U17 | Free / loan | Data unavailable |
| 1 Jul 2017 | US Sénart Jgd | US Torcy Yth. | Free / loan | Data unavailable |
| 1 Oct 2012 | Lieusaint Jgd. | US Sénart Jgd | 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.