Leo Sauer
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Leo Sauer's performance-implied value at EUR 0.8M-8.1M, below the estimated acquisition range of EUR 5.9M-13.2M. Its 24-month market value projection is EUR 4.1M-15.9M. Context-adjusted goal contributions are 0.63x the positional average in the league (1419 minutes, league coefficient 0.43). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 41
What drives the score. Not a black box: each component and its level.
| Performance | Average | 36.1th pct among ATT peers (age-neutral) |
| Age | Very favorable | 20.5 years |
| Acquisition cost | Unfavorable | est. €8.9M vs market €7.0M |
| Expected appreciation | High | +18% over ~2 years (model) |
| Value gap | Very negative | weak predictor on its own |
| Development | High | breakout probability 32% |
| League translation | Uncertain | league coefficient 0.43 |
| 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 900 evaluated ATT players with 900+ minutes.
Performance (last season, league)
- Minutes
- 1419 (46% of available)
- Goals + assists / 90
- 0.32
- Context-adjusted G+A / 90
- 0.26
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 36 (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
- 0.43 (rank 15)
- Team strength (Elo)
- 1423
- Opponent strength
- 1313
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- High
- Trajectory
- declining
- Breakout probability
- 32%
- Resale range (24m)
- €4.1M – €15.9M
Trajectory drivers: minutes share down 35 pts; changed club; team strength up (+299 Elo); role change LM -> LW; relative output down 55% vs positional peers.
Historical comparables (8): median 2-year value change -37% (IQR -56% to +1%).
Risk profile
Overall: High
- ⚠Limited sample: 1419 league minutes last season.
- ⚠League level coefficient 0.43 (1.00 = big-five average): output may not translate.
- ⚠Projection range wider than for most evaluated players.
- ⚠Declining trajectory versus previous 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
- 82 (ATT)
- Relative output kept
- 73%–122%
- Held a regular role (900+ min)
- 61%
- 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 | Feyenoord Rotterdam | Eredivisie | LW | 20 | 1419 | 46% | 3 | 2 | 0.32 | 0.26 | 1313 | 1423 | 0.43 |
| 2024/25 | NAC Breda | Eredivisie | LM | 31 | 2498 | 82% | 7 | 2 | 0.32 | 0.31 | 1312 | 1125 | 0.50 |
| 2023/24 | Feyenoord Rotterdam | Eredivisie | LW | 13 | 275 | 9% | 2 | 4 | 1.96 | 0.38 | 1272 | 1593 | 0.48 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Uefa Europa League | Feyenoord Rotterdam | 6 | 253 | 1 | 0 | 1470 |
| 2025/26 | Uefa Champions League Qualifying | Feyenoord Rotterdam | 2 | 106 | 0 | 0 | 1498 |
| 2025/26 | Knvb Beker | Feyenoord Rotterdam | 1 | 45 | 0 | 0 | — |
| 2024/25 | Knvb Beker | NAC Breda | 1 | 90 | 0 | 0 | — |
| 2023/24 | Uefa Champions League | Feyenoord Rotterdam | 2 | 13 | 0 | 0 | 1693 |
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 |
|---|---|---|---|---|
| Jean-Paul Boëtius Eredivisie · 2015 | 21 | €4.5M | €2.2M | fell |
| Leandro Trossard Jupiler Pro League · 2017 | 23 | €4.0M | €16.0M | rose |
| Henry Onyekuru Super Lig · 2020 | 23 | €8.0M | €5.0M | fell |
| Andreas Cornelius Superliga · 2014 | 21 | €4.5M | €1.5M | fell |
| Frédéric Bulot Jupiler Pro League · 2014 | 24 | €2.5M | €2.0M | fell |
| Lincoln Super Lig · 2023 | 25 | €5.5M | €3.5M | fell |
| Mohamed Ihattaren Eredivisie · 2021 | 19 | €12.0M | €3.0M | fell |
| Fábio Silva Scottish Premiership · 2024 | 22 | €11.0M | €22.0M | 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 2025 | NAC Breda | Feyenoord | Free / loan | €5.0M |
| 12 Aug 2024 | Feyenoord | NAC Breda | Free / loan | €5.0M |
| 1 Sept 2023 | Feyenoord U21 | Feyenoord | Unknown | €75k |
| 1 Jul 2023 | MSK Zilina U19 | Feyenoord U21 | €235k | €75k |
| 30 Jun 2023 | Feyenoord U21 | MSK Zilina U19 | Free / loan | €75k |
| 21 Jul 2022 | MSK Zilina U19 | Feyenoord U21 | Free / loan | €75k |
| 1 Jan 2022 | MSK Zilina Yth | MSK Zilina U19 | Unknown | Data unavailable |
| 2 Aug 2018 | Slovan Yth. | MSK Zilina Yth | 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.