Bernd Leno
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Bernd Leno's performance-implied value at EUR 2.9M-7.4M, above the estimated acquisition range of EUR 2.3M-7.2M. Its 24-month market value projection is EUR 1.6M-3.5M. 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: not assigned
What drives the score. Not a black box: each component and its level.
Age above 33 (outside validated pool)
| Performance | Elite | 98.5th pct among GK peers (age-neutral) |
| Age | Unfavorable | 34.3 years |
| Acquisition cost | Very favorable | est. €3.1M vs market €6.0M |
| Expected appreciation | Very low | -65% over ~2 years (model) |
| Value gap | Very large | weak predictor on its own |
| Development | Low | |
| League translation | Big-five league | league coefficient 1.3 |
| 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 284 evaluated GK players with 900+ minutes.
Performance (last season, league)
- Minutes
- 3420 (100% of available)
- Goals + assists / 90
- 0.00
- Context-adjusted G+A / 90
- 0.00
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 99 (Elite)
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
- 1.30 (rank 1)
- Team strength (Elo)
- 1576
- Opponent strength
- 1597
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- stable
- Breakout probability
- Age > 23
- Resale range (24m)
- €1.6M – €3.5M
Historical comparables (8): median 2-year value change -63% (IQR -74% to -48%).
Risk profile
Overall: Moderate
- ▲Age 34: resale value typically declines.
- ⚠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 | Fulham FC | Premier League | GK | 38 | 3420 | 100% | 0 | 0 | 0.00 | 0.00 | 1597 | 1576 | 1.30 |
| 2024/25 | Fulham FC | Premier League | GK | 38 | 3420 | 100% | 0 | 1 | 0.03 | 0.01 | 1579 | 1555 | 1.23 |
| 2023/24 | Fulham FC | Premier League | GK | 38 | 3420 | 100% | 0 | 0 | 0.00 | 0.00 | 1581 | 1524 | 1.14 |
| 2022/23 | Fulham FC | Premier League | GK | 36 | 3240 | 95% | 0 | 0 | 0.00 | 0.00 | 1570 | 1495 | 1.23 |
| 2021/22 | Arsenal FC | Premier League | GK | 4 | 360 | 11% | 0 | 0 | 0.00 | 0.00 | 1631 | 1667 | 1.17 |
| 2020/21 | Arsenal FC | Premier League | GK | 35 | 3132 | 92% | 0 | 0 | 0.00 | 0.00 | 1567 | 1688 | 1.19 |
| 2019/20 | Arsenal FC | Premier League | GK | 30 | 2650 | 77% | 0 | 0 | 0.00 | 0.00 | 1584 | 1641 | 1.14 |
| 2018/19 | Arsenal FC | Premier League | GK | 32 | 2835 | 83% | 0 | 0 | 0.00 | 0.00 | 1535 | 1733 | 1.22 |
| 2017/18 | Bayer 04 Leverkusen | Bundesliga | GK | 33 | 2970 | 97% | 0 | 0 | 0.00 | 0.00 | 1504 | 1569 | 1.04 |
| 2016/17 | Bayer 04 Leverkusen | Bundesliga | GK | 34 | 3060 | 100% | 0 | 0 | 0.00 | 0.00 | 1526 | 1547 | 1.06 |
| 2015/16 | Bayer 04 Leverkusen | Bundesliga | GK | 33 | 2970 | 97% | 0 | 0 | 0.00 | 0.00 | 1515 | 1638 | 1.02 |
| 2014/15 | Bayer 04 Leverkusen | Bundesliga | GK | 34 | 3060 | 100% | 0 | 0 | 0.00 | 0.00 | 1528 | 1660 | 1.03 |
| 2013/14 | Bayer 04 Leverkusen | Bundesliga | GK | 34 | 3060 | 100% | 0 | 0 | 0.00 | 0.00 | 1547 | 1602 | 1.03 |
| 2012/13 | Bayer 04 Leverkusen | Bundesliga | GK | 32 | 2880 | 94% | 0 | 1 | 0.03 | 0.01 | 1444 | 1641 | 1.11 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2024/25 | Fa Cup | Fulham FC | 2 | 210 | 0 | 0 | — |
| 2022/23 | Fa Cup | Fulham FC | 1 | 90 | 0 | 0 | — |
| 2021/22 | Fa Cup | Arsenal FC | 1 | 90 | 0 | 0 | — |
| 2020/21 | Uefa Europa League | Arsenal FC | 10 | 900 | 0 | 0 | 1571 |
| 2020/21 | Fa Cup | Arsenal FC | 2 | 210 | 0 | 0 | — |
| 2019/20 | Uefa Europa League | Arsenal FC | 2 | 210 | 0 | 0 | 1589 |
| 2018/19 | Uefa Europa League | Arsenal FC | 3 | 270 | 0 | 0 | 1481 |
| 2017/18 | Dfb Pokal | Bayer 04 Leverkusen | 5 | 510 | 0 | 0 | — |
| 2016/17 | Uefa Champions League | Bayer 04 Leverkusen | 7 | 630 | 0 | 0 | 1664 |
| 2016/17 | Dfb Pokal | Bayer 04 Leverkusen | 1 | 90 | 0 | 0 | — |
| 2015/16 | Uefa Champions League | Bayer 04 Leverkusen | 6 | 540 | 0 | 0 | 1627 |
| 2015/16 | Uefa Europa League | Bayer 04 Leverkusen | 4 | 360 | 0 | 0 | 1647 |
| 2015/16 | Dfb Pokal | Bayer 04 Leverkusen | 4 | 355 | 0 | 0 | — |
| 2015/16 | Uefa Champions League Qualifying | Bayer 04 Leverkusen | 2 | 180 | 0 | 0 | 1587 |
| 2014/15 | Uefa Champions League | Bayer 04 Leverkusen | 8 | 750 | 0 | 0 | 1696 |
| 2014/15 | Dfb Pokal | Bayer 04 Leverkusen | 4 | 450 | 0 | 0 | — |
| 2014/15 | Uefa Champions League Qualifying | Bayer 04 Leverkusen | 2 | 180 | 0 | 0 | 1478 |
| 2013/14 | Uefa Champions League | Bayer 04 Leverkusen | 8 | 720 | 0 | 0 | 1696 |
| 2013/14 | Dfb Pokal | Bayer 04 Leverkusen | 4 | 390 | 0 | 0 | — |
| 2012/13 | Uefa Europa League | Bayer 04 Leverkusen | 6 | 540 | 0 | 0 | 1538 |
| 2012/13 | Dfb Pokal | Bayer 04 Leverkusen | 2 | 180 | 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 |
|---|---|---|---|---|
| Lukasz Fabianski Premier League · 2019 | 34 | €5.0M | €1.5M | fell |
| Kasper Schmeichel Premier League · 2021 | 35 | €6.0M | €2.0M | fell |
| Willy Caballero Laliga · 2014 | 33 | €5.0M | €3.0M | fell |
| Rui Patrício Premier League · 2021 | 33 | €10.0M | €5.0M | fell |
| Hugo Lloris Premier League · 2022 | 36 | €7.0M | €1.2M | fell |
| Ben Foster Premier League · 2019 | 36 | €3.0M | €300k | fell |
| Carlos Kameni Laliga · 2015 | 31 | €5.0M | €2.0M | fell |
| Tim Howard Premier League · 2013 | 34 | €3.5M | €2.0M | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 2 Aug 2022 | Arsenal | Fulham | €3.6M | €9.0M |
| 1 Jul 2018 | Leverkusen | Arsenal | €25.0M | €20.0M |
| 1 Jan 2012 | Stuttgart | Leverkusen | €7.8M | €5.0M |
| 31 Dec 2011 | Leverkusen | Stuttgart | Free / loan | €5.0M |
| 10 Aug 2011 | Stuttgart | Leverkusen | Free / loan | €600k |
| 1 Jul 2011 | Stuttgart II | Stuttgart | Unknown | €600k |
| 1 Jul 2010 | Stuttgart U19 | Stuttgart II | Unknown | €150k |
| 1 Jul 2009 | Stuttgart U17 | Stuttgart U19 | Unknown | Data unavailable |
| 1 Jul 2007 | Stuttgart Yth. | Stuttgart U17 | Unknown | Data unavailable |
| 1 Jul 2003 | Bietigheim Yth. | Stuttgart Yth. | 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.