Michael Gregoritsch
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Michael Gregoritsch's performance-implied value at EUR 1.2M-3.6M, above the estimated acquisition range of EUR 0.5M-1.4M. Its 24-month market value projection is EUR 0.4M-1.2M. Context-adjusted goal contributions are 1.25x the positional average in the league (1287 minutes, league coefficient 0.94). 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: 55
What drives the score. Not a black box: each component and its level.
| Performance | Above average | 62.4th pct among ATT peers (age-neutral) |
| Age | Unfavorable | 32.2 years |
| Acquisition cost | Very favorable | est. €675k vs market €1.5M |
| Expected appreciation | Very low | -48% over ~2 years (model) |
| Value gap | Very large | weak predictor on its own |
| Development | Low | |
| League translation | Big-five league | league coefficient 0.94 |
| 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
- 1287 (42% of available)
- Goals + assists / 90
- 0.84
- Context-adjusted G+A / 90
- 0.67
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 62 (Above 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
- 0.94 (rank 3)
- Team strength (Elo)
- 1397
- Opponent strength
- 1434
- 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)
- €418k – €1.2M
Trajectory drivers: minutes share up 21 pts; changed club; team strength down (-108 Elo); league level down (-56 Elo); relative output up 65% vs positional peers.
Historical comparables (8): median 2-year value change -59% (IQR -73% to -47%).
Risk profile
Overall: High
- ▲Age 32: resale value typically declines.
- ⚠Limited sample: 1287 league minutes last season.
- ⚠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 | FC Augsburg | Bundesliga | ST | 17 | 917 | 30% | 6 | 3 | 0.88 | 0.67 | 1434 | 1421 | 0.94 |
| 2025/26 | Bröndby IF | Superliga | ST | 11 | 370 | 19% | 2 | 1 | 0.73 | 0.55 | 1303 | 1336 | 0.47 |
| 2024/25 | SC Freiburg | Bundesliga | ST | 20 | 631 | 21% | 2 | 1 | 0.43 | 0.40 | 1503 | 1505 | 0.94 |
| 2023/24 | SC Freiburg | Bundesliga | ST | 32 | 1682 | 55% | 7 | 5 | 0.64 | 0.49 | 1461 | 1481 | 1.01 |
| 2022/23 | SC Freiburg | Bundesliga | ST | 30 | 2175 | 71% | 10 | 5 | 0.62 | 0.51 | 1524 | 1561 | 1.04 |
| 2021/22 | FC Augsburg | Bundesliga | ST | 25 | 1390 | 45% | 9 | 0 | 0.58 | 0.63 | 1508 | 1425 | 1.05 |
| 2020/21 | FC Augsburg | Bundesliga | ST | 24 | 831 | 27% | 1 | 2 | 0.32 | 0.46 | 1521 | 1396 | 1.06 |
| 2019/20 | FC Schalke 04 | Bundesliga | ST | 14 | 831 | 27% | 1 | 1 | 0.22 | 0.33 | 1506 | 1415 | 1.06 |
| 2019/20 | FC Augsburg | Bundesliga | SS | 6 | 303 | 10% | 0 | 0 | 0.00 | 0.55 | 1538 | 1408 | 1.06 |
| 2018/19 | FC Augsburg | Bundesliga | SS | 32 | 2493 | 81% | 6 | 2 | 0.29 | 0.52 | 1528 | 1409 | 1.05 |
| 2017/18 | FC Augsburg | Bundesliga | SS | 32 | 2534 | 83% | 13 | 4 | 0.60 | 0.58 | 1523 | 1461 | 1.04 |
| 2016/17 | Hamburger SV | Bundesliga | ST | 30 | 1303 | 43% | 5 | 3 | 0.55 | 0.66 | 1535 | 1440 | 1.06 |
| 2015/16 | Hamburger SV | Bundesliga | RW | 25 | 1434 | 47% | 5 | 2 | 0.44 | 0.50 | 1521 | 1433 | 1.02 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | World Cup | Austria | 2 | 130 | 0 | 1 | — |
| 2025/26 | Uefa Conference League Qualifying | Bröndby IF | 2 | 41 | 1 | 0 | 1511 |
| 2025/26 | Oddset Pokalen | Bröndby IF | 1 | 15 | 0 | 0 | — |
| 2024/25 | Dfb Pokal | SC Freiburg | 3 | 168 | 1 | 0 | — |
| 2023/24 | Uefa Europa League | SC Freiburg | 8 | 344 | 5 | 1 | 1507 |
| 2023/24 | Dfb Pokal | SC Freiburg | 2 | 145 | 0 | 0 | — |
| 2022/23 | Dfb Pokal | SC Freiburg | 5 | 411 | 2 | 0 | — |
| 2022/23 | Uefa Europa League | SC Freiburg | 7 | 274 | 3 | 0 | 1479 |
| 2021/22 | Dfb Pokal | FC Augsburg | 2 | 75 | 0 | 0 | — |
| 2020/21 | Dfb Pokal | FC Augsburg | 2 | 135 | 0 | 0 | — |
| 2019/20 | Dfb Pokal | FC Schalke 04 | 2 | 123 | 0 | 0 | — |
| 2019/20 | Dfb Pokal | FC Augsburg | 1 | 67 | 0 | 0 | — |
| 2018/19 | Dfb Pokal | FC Augsburg | 4 | 420 | 2 | 1 | — |
| 2017/18 | Dfb Pokal | FC Augsburg | 1 | 73 | 0 | 0 | — |
| 2016/17 | Dfb Pokal | Hamburger SV | 2 | 101 | 0 | 1 | — |
| 2015/16 | Dfb Pokal | Hamburger SV | 1 | 45 | 1 | 0 | — |
| 2013/14 | Dfb Pokal | FC St. Pauli | 1 | 15 | 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 |
|---|---|---|---|---|
| Djibril Cissé Ligue 1 · 2014 | 33 | €2.0M | €1.0M | fell |
| Semih Sentürk Super Lig · 2015 | 32 | €800k | €150k | fell |
| Marko Devic Premier Liga · 2016 | 33 | €2.0M | €425k | fell |
| Serdar Özbayraktar Super Lig · 2014 | 33 | €700k | €400k | fell |
| Nenê Serie A · 2014 | 31 | €1.2M | €350k | fell |
| Mattia Destro Serie A · 2021 | 30 | €2.5M | €1.3M | fell |
| Erdal Kilicaslan Super Lig · 2016 | 32 | €1.2M | €400k | fell |
| Antonio Floro Flores Serie A · 2014 | 31 | €2.5M | €1.5M | 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 | Augsburg | Bröndby IF | Free / loan | €1.5M |
| 7 Jan 2026 | Bröndby IF | Augsburg | Free / loan | €1.5M |
| 20 Aug 2025 | Freiburg | Bröndby IF | €1.5M | €3.0M |
| 8 Jul 2022 | Augsburg | Freiburg | €150k | €4.5M |
| 30 Jun 2020 | FC Schalke 04 | Augsburg | Free / loan | €5.5M |
| 1 Jan 2020 | Augsburg | FC Schalke 04 | Free / loan | €7.0M |
| 4 Jul 2017 | Hamburg | Augsburg | €5.5M | €3.5M |
| 23 Jul 2015 | VfL Bochum | Hamburg | €3.0M | €1.5M |
| 1 Jul 2015 | Hoffenheim | VfL Bochum | €500k | €1.5M |
| 30 Jun 2015 | VfL Bochum | Hoffenheim | Free / loan | €600k |
| 1 Jul 2014 | Hoffenheim | VfL Bochum | Free / loan | €450k |
| 30 Jun 2014 | St. Pauli | Hoffenheim | Free / loan | €450k |
| 1 Jul 2013 | Hoffenheim | St. Pauli | Free / loan | €200k |
| 30 Jun 2012 | SV Kapfenberg | Hoffenheim | Free / loan | €200k |
| 3 Jul 2011 | Hoffenheim | SV Kapfenberg | Free / loan | €250k |
| 1 Jul 2011 | SV Kapfenberg | Hoffenheim | €200k | €250k |
| 1 Jul 2010 | Kapfenberg II | SV Kapfenberg | Unknown | €100k |
| 1 Jul 2009 | AKA Kapfenberg | Kapfenberg II | Unknown | Data unavailable |
| 1 Jul 2008 | GAK Youth | AKA Kapfenberg | 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.