João Batxi
Value picture
Where the market, the likely price and the model estimates sit.
The model rates João Batxi's performance-implied value at EUR 2.9M-9.4M, below the estimated acquisition range of EUR 4.1M-9.7M. Its 24-month market value projection is EUR 3.5M-8.3M. Context-adjusted goal contributions are 0.67x the positional average in the league (2113 minutes, league coefficient 0.56). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 19
What drives the score. Not a black box: each component and its level.
| Performance | Above average | 65.8th pct among ATT peers (age-neutral) |
| Age | Unfavorable | 28.2 years |
| Acquisition cost | Neutral | est. €7.1M vs market €8.0M |
| Expected appreciation | Very low | -33% over ~2 years (model) |
| Value gap | Negative | weak predictor on its own |
| Development | Low | |
| League translation | Moderate | league coefficient 0.56 |
| 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
- 2113 (78% of available)
- Goals + assists / 90
- 0.43
- Context-adjusted G+A / 90
- 0.26
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 66 (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
- 0.56 (rank 10)
- Team strength (Elo)
- 1536
- Opponent strength
- 1339
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- declining
- Breakout probability
- Age > 23
- Resale range (24m)
- €3.5M – €8.3M
Trajectory drivers: relative output down 24% vs positional peers.
Historical comparables (8): median 2-year value change -44% (IQR -60% to -5%).
Risk profile
Overall: High
- ⚠League level coefficient 0.56 (1.00 = big-five average): output may not translate.
- ⚠No continental-competition minutes last season.
- ⚠League level estimated mainly from squad values (few matches vs other leagues).
- ⚠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
- 20 (ATT)
- Relative output kept
- 76%–104%
- Held a regular role (900+ min)
- 50%
- 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 | FK Krasnodar | Premier Liga | RW | 30 | 2113 | 78% | 2 | 8 | 0.43 | 0.26 | 1339 | 1536 | 0.56 |
| 2024/25 | FK Krasnodar | Premier Liga | RW | 30 | 2231 | 83% | 5 | 7 | 0.48 | 0.38 | 1295 | 1511 | 0.55 |
| 2023/24 | FK Krasnodar | Premier Liga | LW | 29 | 2088 | 77% | 1 | 4 | 0.22 | 0.26 | 1338 | 1405 | 0.49 |
| 2022/23 | FK Krasnodar | Premier Liga | LW | 14 | 740 | 27% | 3 | 2 | 0.61 | 0.41 | 1325 | 1405 | 0.53 |
| 2022/23 | GD Chaves | Liga Portugal | LM | 4 | 329 | 11% | 1 | 1 | 0.55 | 0.38 | 1395 | 1337 | 0.68 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Russian Cup | FK Krasnodar | 12 | 716 | 4 | 5 | — |
| 2025/26 | Russian Super Cup | FK Krasnodar | 1 | 66 | 0 | 0 | 1478 |
| 2024/25 | Russian Cup | FK Krasnodar | 5 | 255 | 0 | 0 | — |
| 2024/25 | Russian Super Cup | FK Krasnodar | 1 | 75 | 0 | 0 | 1491 |
| 2023/24 | Russian Cup | FK Krasnodar | 5 | 112 | 0 | 0 | — |
| 2022/23 | Russian Cup | FK Krasnodar | 5 | 311 | 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 |
|---|---|---|---|---|
| Nicolai Jörgensen Eredivisie · 2018 | 27 | €14.0M | €3.5M | fell |
| Scott Sinclair Scottish Premiership · 2018 | 29 | €4.5M | €2.4M | fell |
| Wanderson Premier Liga · 2020 | 26 | €9.0M | €8.0M | flat |
| Konstantinos Mitroglou Liga Portugal · 2017 | 29 | €12.0M | €7.0M | fell |
| Aleksandr Kokorin Premier Liga · 2018 | 27 | €11.0M | €5.2M | fell |
| Yacine Brahimi Liga Portugal · 2016 | 26 | €22.0M | €26.0M | flat |
| Luuk de Jong Eredivisie · 2018 | 28 | €8.0M | €9.5M | flat |
| Fernandão Super Lig · 2016 | 29 | €8.5M | €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 |
|---|---|---|---|---|
| 7 Sept 2022 | Chaves | Krasnodar | €1.5M | €575k |
| 1 Jul 2019 | Chaves B | Chaves | Unknown | Data unavailable |
| 1 Jul 2017 | Tondela U19 | Chaves B | Free / loan | Data unavailable |
| 1 Jul 2016 | Oriental U19 | Tondela U19 | Unknown | Data unavailable |
| 1 Jul 2015 | Real SC U17 | Oriental U19 | Unknown | Data unavailable |
| 1 Jul 2013 | Real SC U155 | Real SC U17 | Unknown | Data unavailable |
| 1 Jul 2011 | Benfica Yth | Real SC U155 | 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.