Simen Juklerød
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Simen Juklerød's performance-implied value at EUR 0.3M-0.7M, above the estimated acquisition range of EUR 0.1M-0.3M. Its 24-month market value projection is EUR 0.1M-0.3M. Confidence is low: 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.
Insufficient sample (< 900 league minutes)
| Performance | Below average | 24.3th pct among DEF peers (age-neutral) |
| Age | Unfavorable | 32.1 years |
| Acquisition cost | Very favorable | est. €104k vs market €300k |
| Expected appreciation | Very low | -31% over ~2 years (model) |
| Value gap | Very large | weak predictor on its own |
| Development | Low | |
| League translation | Moderate | league coefficient 0.65 |
| Tactical fit | Not evaluated | Requires event/role data not available from the current free source. |
| Risk | Very High | |
| Data confidence | Low |
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 1269 evaluated DEF players with 900+ minutes.
Performance (last season, league)
- Minutes
- 750 (28% of available)
- Goals + assists / 90
- 0.60
- Context-adjusted G+A / 90
- 0.32
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 24 (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
- 0.65 (rank 6)
- Team strength (Elo)
- 1401
- Opponent strength
- 1365
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Low
- Trajectory
- insufficient
- Breakout probability
- Age > 23
- Resale range (24m)
- €103k – €275k
Historical comparables (8): median 2-year value change -13% (IQR -30% to +16%).
Risk profile
Overall: Very High
- ▲Small sample: 750 league minutes last season.
- ▲Age 32: resale value typically declines.
- ⚠No continental-competition minutes last season.
- ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
- ⚠Played under 40% of available league minutes (injury data unavailable, cause unknown).
- ⓘ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
- 76 (DEF)
- Relative output kept
- 67%–160%
- Held a regular role (900+ min)
- 76%
- 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 | Sint-Truidense VV | Jupiler Pro League | LB | 16 | 750 | 28% | 1 | 4 | 0.60 | 0.32 | 1365 | 1401 | 0.65 |
| 2024/25 | Sint-Truidense VV | Jupiler Pro League | LB | 5 | 96 | 4% | 0 | 0 | 0.00 | 0.13 | 1337 | 1302 | 0.63 |
| 2021/22 | KRC Genk | Jupiler Pro League | LB | 9 | 790 | 26% | 0 | 0 | 0.00 | 0.07 | 1317 | 1356 | 0.49 |
| 2020/21 | Royal Antwerp FC | Jupiler Pro League | LM | 19 | 1104 | 36% | 3 | 3 | 0.49 | 0.42 | 1360 | 1436 | 0.55 |
| 2019/20 | Royal Antwerp FC | Jupiler Pro League | LB | 14 | 1009 | 39% | 0 | 1 | 0.09 | 0.09 | 1341 | 1437 | 0.63 |
| 2018/19 | Royal Antwerp FC | Jupiler Pro League | LB | 29 | 2591 | 96% | 1 | 6 | 0.24 | 0.20 | 1357 | 1385 | 0.65 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Jupiler Pro League Playoff I | Sint-Truidense VV | 6 | 104 | 0 | 1 | 1453 |
| 2021/22 | Volkswagen Supercup | KRC Genk | 1 | 90 | 0 | 0 | 1570 |
| 2021/22 | Uefa Europa League | KRC Genk | 1 | 21 | 0 | 0 | 1461 |
| 2020/21 | Uefa Europa League | Royal Antwerp FC | 6 | 431 | 0 | 1 | 1574 |
| 2019/20 | Uefa Europa League Qualifying | Royal Antwerp FC | 4 | 420 | 0 | 0 | 1502 |
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 |
|---|---|---|---|---|
| Cenk Ahmet Alkilic Super Lig · 2019 | 32 | €300k | €275k | flat |
| Laurent Jans Eredivisie · 2022 | 30 | €350k | €275k | fell |
| Aleksandr Denisov Premier Liga · 2020 | 31 | €350k | €175k | fell |
| Luca Antonelli Serie A · 2019 | 32 | €500k | €200k | fell |
| Mehdi Zeffane Ligue 1 · 2023 | 31 | €450k | €500k | flat |
| Gia Grigalava Premier Liga · 2018 | 29 | €450k | €2.0M | rose |
| Rodrigo Defendi Liga Portugal · 2015 | 29 | €300k | €400k | rose |
| Athanasios Papageorgiou Super League 1 · 2018 | 31 | €300k | €250k | flat |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 16 Jan 2025 | Vålerenga | Sint-Truiden | Unknown | €400k |
| 31 Aug 2022 | Genk | Vålerenga | Unknown | €1.5M |
| 1 Jul 2021 | Royal Antwerp | Genk | Free / loan | €2.5M |
| 17 Jul 2018 | Vålerenga | Royal Antwerp | Unknown | €300k |
| 27 Jan 2016 | Bærum | Vålerenga | Unknown | €100k |
| 1 Jul 2012 | Bærum SK Yth. | Bærum | 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.