
Marko Divković
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Marko Divković's performance-implied value at EUR 0.5M-1.4M, below the estimated acquisition range of EUR 0.9M-3.3M. Its 24-month market value projection is EUR 1.3M-3.3M. Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 73
What drives the score. Not a black box: each component and its level.
| Performance | Below average | 26.4th pct among DEF peers (age-neutral) |
| Age | Neutral | 27.1 years |
| Acquisition cost | Favorable | est. €1.7M vs market €2.7M |
| Expected appreciation | Low | -23% over ~2 years (model) |
| Value gap | Very negative | weak predictor on its own |
| Development | Low | |
| League translation | Uncertain | league coefficient 0.47 |
| 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 1268 evaluated DEF players with 900+ minutes.
Performance (last season, league)
- Minutes
- 1573 (79% of available)
- Goals + assists / 90
- 0.23
- Context-adjusted G+A / 90
- 0.15
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 26 (Below 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
- 0.47 (rank 12)
- Team strength (Elo)
- 1336
- Opponent strength
- 1269
- 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)
- €1.3M – €3.3M
Trajectory drivers: minutes share up 42 pts; league level up (+45 Elo).
Historical comparables (8): median 2-year value change -18% (IQR -45% to +11%).
Risk profile
Overall: Moderate
- ⚠Limited sample: 1573 league minutes last season.
- ⚠League level coefficient 0.47 (1.00 = big-five average): output may not translate.
- ⓘ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
- 24 (DEF)
- Relative output kept
- 60%–139%
- Held a regular role (900+ min)
- 71%
- 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 | Bröndby IF | Superliga | LB | 20 | 1573 | 79% | 3 | 1 | 0.23 | 0.15 | 1269 | 1336 | 0.47 |
| 2024/25 | Bröndby IF | Superliga | LB | 17 | 740 | 37% | 1 | 2 | 0.36 | 0.18 | 1287 | 1342 | 0.38 |
| 2023/24 | Bröndby IF | Superliga | LM | 19 | 1449 | 73% | 2 | 5 | 0.43 | 0.28 | 1283 | 1417 | 0.48 |
| 2022/23 | Bröndby IF | Superliga | ST | 11 | 448 | 23% | 0 | 3 | 0.60 | 0.47 | 1266 | 1329 | 0.47 |
| 2021/22 | Bröndby IF | Superliga | ST | 13 | 719 | 36% | 1 | 2 | 0.38 | 0.40 | 1231 | 1362 | 0.45 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Uefa Conference League Qualifying | Bröndby IF | 6 | 436 | 0 | 1 | 1388 |
| 2025/26 | Oddset Pokalen | Bröndby IF | 2 | 195 | 0 | 1 | — |
| 2024/25 | Oddset Pokalen | Bröndby IF | 5 | 352 | 2 | 1 | — |
| 2024/25 | Uefa Conference League Qualifying | Bröndby IF | 1 | 28 | 0 | 0 | 1475 |
| 2023/24 | Oddset Pokalen | Bröndby IF | 4 | 307 | 0 | 1 | — |
| 2022/23 | Uefa Conference League Qualifying | Bröndby IF | 4 | 201 | 2 | 0 | 1481 |
| 2022/23 | Oddset Pokalen | Bröndby IF | 1 | 90 | 0 | 0 | — |
| 2021/22 | Oddset Pokalen | Bröndby IF | 3 | 173 | 2 | 0 | — |
| 2021/22 | Uefa Conference League Qualifying | DAC Dunajska Streda | 2 | 155 | 0 | 0 | 1515 |
| 2021/22 | Uefa Europa League | Bröndby IF | 2 | 36 | 0 | 0 | 1529 |
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 |
|---|---|---|---|---|
| Kevin Tshiembe Superliga · 2023 | 26 | €2.0M | €800k | fell |
| Calvin Verdonk Eredivisie · 2024 | 27 | €2.5M | €2.5M | flat |
| Andreaw Gravillon Super Lig · 2024 | 26 | €3.7M | €1.0M | fell |
| Darko Todorovic Premier Liga · 2024 | 27 | €1.5M | €1.5M | flat |
| Marcelo Liga Portugal · 2016 | 27 | €1.7M | €3.0M | rose |
| Dídac Vilà Super League 1 · 2016 | 27 | €1.5M | €1.0M | fell |
| Joris Kramer Eredivisie · 2024 | 28 | €1.2M | €1.8M | rose |
| Fatih Aksoy Super Lig · 2022 | 25 | €3.8M | €2.3M | fell |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 1 Jul 2022 | Dunajska Streda | Bröndby IF | €1.0M | €700k |
| 30 Jun 2022 | Bröndby IF | Dunajska Streda | Free / loan | €700k |
| 31 Aug 2021 | Dunajska Streda | Bröndby IF | Free / loan | €750k |
| 1 Jul 2017 | Arsenal Academy | Dunajska Streda | Unknown | Data unavailable |
| 1 Jul 2013 | NK Otok | Arsenal Academy | 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.